Research Handbook on Project Performance (Research Handbooks in Business and Management series) 1802207600, 9781802207606

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Research Handbook on Project Performance

Vittal S. Anantatmula and Chakradhar Iyyunni

RESEARCH HANDBOOK ON PROJECT PERFORMANCE

Research Handbook on Project Performance Edited by

Vittal S. Anantatmula Professor of Project Management, College of Business, Western Carolina University, Cullowhee, USA

Chakradhar Iyyunni Fellow, European School of Governance (EUSG), Berlin, Germany

Cheltenham, UK • Northampton, MA, USA

© Vittal S. Anantatmula and Chakradhar Iyyunni 2023

All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical or photocopying, recording, or otherwise without the prior permission of the publisher. Published by Edward Elgar Publishing Limited The Lypiatts 15 Lansdown Road Cheltenham Glos GL50 2JA UK Edward Elgar Publishing, Inc. William Pratt House 9 Dewey Court Northampton Massachusetts 01060 USA A catalogue record for this book is available from the British Library Library of Congress Control Number: 2023930291 This book is available electronically in the Business subject collection http://dx.doi.org/10.4337/9781802207613

ISBN 978 1 80220 760 6 (cased) ISBN 978 1 80220 761 3 (eBook)

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Contents

List of contributorsvii PART I

BACKDROP

1

Introduction to Research Handbook on Project Performance2 Vittal S. Anantatmula and Chakradhar Iyyunni

2

Project performance measures and metrics framework Riaz Ahmed

3

An alternative to traditional project management: using lean OKRs as a model for value creation for software product companies Bart den Haak

23

4

Modeling relationships of projects and operations: toward a dynamic framework of performance Pierre A. Daniel

39

PART II

11

TACTICS, STRATEGIES, AND RISKS

5

Construction and demolition waste recycling and reuse clause in standard form of contracts: impact on project performance Nurhaizan Mohd Zainudin, Ahmad Amir Hafiz Ahmad, Rahimi A. Rahman, and Fadzida Ismail

6

Project monitoring and data integrity James Marion and Tracey Richardson

7

Don’t ask what makes projects successful, but under what circumstances they work: recalibrating project success factors Lavagnon A. Ika and Jeffrey K. Pinto

8

Understanding the causes and effects of low-risk management: implementation in projects using the DEMATEL algorithm Chia-Kuang Lee, Wen-Nee Wong, Nurhaizan Mohd Zainudin and Ahmad Huzaimi Abd Jamil

9

Managing risk in Indian construction projects Chakradhar Iyyunni and Sunil Kumar

115

10

Risk analytics for project success Ruchita Gupta, Karuna Jain, and Charu Chandra Gupta

133

v

55

67

75

92

vi  Research handbook on project performance 11

Building capability for project success: examining the preparedness of emerging professionals using a university capstone project case study Michelle Turner and Guinevere Gilbert

12

Role of project management maturity in project performance Vittal S. Anantatmula

158 176

PART III NEXT PRACTICES 13

Addressing the performance gap with lean-led design Hafsa Chbaly and Maude Brunet

188

14

Fixed capacity and beyond budgeting: a symbiotic relationship within a scaled agile environment Yvan Petit and Carl Marnewick

197

15

Cross-cultural integration in the next practices of project management: a qualitative study Dhruv Pratap Singh and Mahesh S. Raisinghani

214

16

Project management lessons learned: essential safety features Kam Jugdev

231

17

Projects as vehicles of learning Arthur Shelley

240

18

Impact of Industry 4.0 on agile project management Vijaya Dixit and Upasna A. Agarwal

254

19

Performance management in public–private partnership projects: a perspective from the Indian road sector Dhruv Agarwal, Sagar Deshmukh, and Ganesh Devkar

265

Index286

Contributors

Dhruv Agarwal received his Master’s in construction engineering and management from the Faculty of Technology at the CEPT University, Ahmedabad, India. He completed his Bachelor’s in civil engineering at the R.V. College of Engineering, Bangalore, India. He has about three years’ work experience in infrastructure projects. He has researched in the area of public–private partnerships and lean construction. Upasna A. Agarwal is a professor in organization behavior and human resource management at the National Institute of Industrial Engineering. With an MBA and Master’s in labor law from Symbiosis, Pune, she also has a PhD from the Indian Institute of Technology, Mumbai. Upasna launched her academic career at the S.P. Jain Institute of Management and Research and has seven years of corporate experience prior to that. In 2017, she was recognized and awarded the Best Teacher Award by NITIE. In 2018, Upasna received the “AIMS International Outstanding Young Woman Management Researcher Award”, Association of Indian Management Scholars, and Best Faculty in Human Resources and Organization Behavior from the World HRD Congress. In 2019, Upasna was awarded the Higher Education Forum Best Young Teacher Award. Upasna was identified in the top 2% of scientists list released by Stanford University in 2021 and 2022. She has over 3,187 citations of her publications with an h-index of twenty-three. Ahmad Amir Hafiz Ahmad graduated with a BA in project management (Hons) in 2021 from Universiti Malaysia Pahang. During the final year of his study he began research on construction and project management under the supervision of Dr Nurhaizan Mohd Zainudin to complete his degree. Currently, he is working as a site inspector in an oil and gas company based in Kuala Terengganu. Riaz Ahmed (PhD, PMP) is professor and Director of Postgraduate Programs at Bahria University, Islamabad, Pakistan. He obtained his PhD from the University Technology Malaysia, with distinction, receiving the “Best Postgraduate Student Award”. He is a certified Project Management Professional from the Project Management Institute, USA. He has been working in higher education institutions for twenty years. He has published a number of scholarly articles in reputable journals, including Engineering, Construction and Architectural Management, Engineering Management Journal, Quality and Quantity, International Journal of Information Technology Management, International Journal of Modern Project Management, and International Journal of Productivity and Performance Management. Vittal S. Anantatmula is a professor in the College of Business, Western Carolina University, a campus at the University of North Carolina. He was the former director of graduate programs in project management and was a recipient of excellence in teaching and research awards at Western Carolina University including the University Scholar Award. Dr Anantatmula is also a global guest professor at Keio University, Yokohama, Japan and Skema Business School, France. He is a member of the Project Management Institute’s Academic Insight Team. Previously, he served as a director and board member of the Project Management Institute vii

viii  Research handbook on project performance Global Accreditation Center (PMI-GAC) from 2016 to 2021. He serves on the editorial board of several scholarly journals. In the past, Dr Anantatmula taught at the George Washington University. He has also worked in the petroleum and power industries for several years as an electrical engineer and project manager, and as a consultant for several international organizations including the World Bank. Dr Anantatmula has authored more than 100 publications including ten academic research books. He received his PhD from the George Washington University and he is a certified Project Management Professional. Maude Brunet is an assistant professor at HEC Montréal. Her research interests include governance and innovation of megaprojects, public infrastructure projects, and public–private partnerships. She is a member of the scientific committee of KHEOPS – the International Research Consortium on the Governance of Major Infrastructure Projects. She has been a certified Project Management Professional of the Project Management Institute since 2010. She has published in several project management and administrative science journals, and has been an associate editor for the International Journal of Project Management. She has fifteen years of experience in project management, including as a teacher, consultant, administrator at PMI Montréal, researcher, and speaker. Hafsa Chbaly is a postdoctoral researcher at HEC Montréal. She obtained her PhD at the ÉTS GRIDD Laboratory (Construction Department), and the BATir Laboratory at Université libre de Bruxelles, under a double-degree program. She obtained a Master’s degree in architectural engineering at Université de Liège and a Bachelor’s degree in building engineering at Universitat Politècnica de Catalunya. Her research focuses on the definition of value generation during complex projects through participatory approaches. She has seven years of experience in project management, including as a construction engineer, teacher, researcher, and speaker. Pierre A. Daniel is an associate professor in project studies at Skema Business School. He is the scientific director of the Specialized Master in Management of Projects and Programmes. He has focused his research activities on understanding how to manage complexity in megaprojects through the perspective of complex adaptive systems. His domains of expertise are strategic project management and uncertainty management. He developed a Development Modeling® Methodology to design and manage complexity in projects and programmes. Bart den Haak is the industry authority on objectives and key results (OKRs) in Europe. He is the author of the book Moving the Needle with Lean OKRs. As an international speaker, he inspires people to start using the OKR methodology that helped realize the transformational journeys of global giants such as Facebook and Google. He helps executive teams all over the world like Nike, ING, BinckBank (part of Saxo Bank), NN, Mural, Mambu, Backbase, and Bol.com to use OKRs to their advantage. He coaches both executive and operational teams in applying OKRs to their fullest potential. Bart holds a Bachelor’s degree in IT and organization management and a Master’s degree in software engineering. He has a strong background (twenty-plus years) in software engineering and agile product development, which makes him the ideal candidate for advising software as a service (SaaS) companies and their leaders on how to change the way in which they operate. Having advised and coached hundreds of leaders and their teams worldwide, Bart decided to use his wealth of knowledge and insight to write a book that goes beyond the basics of OKRs.

Contributors  ix Sagar Deshmukh is associate director of LEA-India [LASA], which is part of LEA Group Holdings Inc. Canada and deals in Infrastructure Consultancy services globally. He is an enthusiastic civil engineering professional working on infrastructure development. He spearheads the business operations in the Gujarat state of India. He has over two and half decades of professional experience in the field of traffic transportation and highways, strategic policies and planning, institutional development, road asset management, project management, and innovative designs. He spends quality time at academic and professional institutions as a member on Board of Studies, expert faculty, and as a jury panellist. Ganesh Devkar is an associate professor of construction management at CEPT University, Ahmedabad, India. He holds a doctorate in construction management from the Indian Institute of Technology Madras (IIT Madras). His doctoral work focuses on competencies in urban local bodies for implementing water, sanitation, and solid waste management in public–private partnership projects in India. Ganesh teaches construction quality and safety management, project appraisal, lean construction, and public–private partnerships. He has done research in the area of public–private partnerships, lean construction, and megaprojects. He has participated in four systematic reviews focusing on the delivery of infrastructure like water supply, sanitation, hygiene, telecom, electricity, and transport. Ganesh received the “Young Research Scholar Award” from the Project Management Institute, India in 2014. Vijaya Dixit is an associate professor at the Indian Institute of Management, Ranchi. She was also associated with the National Institute of Industrial Engineering, Mumbai for three years. She is a Fellow of Indian Institute of Management, Lucknow. She teaches courses on project management, operations management, operations strategy, procurement, and materials management. After completion of her Bachelor’s in marine engineering from the Marine Engineering and Research Institute, Kolkata, she had direct exposure to the shipbuilding industry as a design engineer. Her contemporary research interests lie in agile project management, Industry 4.0, project resilience, project risk management, project procurement, and contracts management. Her research has resulted in seventeen publications in international journals. In February 2015 she was conferred the “Young Research Scholar Award” by the Project Management Institute of India. Recently, she was awarded the AIMS-Jaipuria Outstanding Young Woman Management Researcher Award during the Eighteenth AIMS International Conference on Management on 5 March 2021. Guinevere Gilbert transitioned from a construction management career in the UK to higher education in 1995 when she arrived in Australia. She has lectured at RMIT University in Melbourne, in the fields of construction management and a range of project management courses, including post-disaster project management and project management careers. Guinevere’s research is in the field of organizational psychology in projects. Her PhD investigated graduate development programs in construction organizations. Her current research includes the development of a tool to measure volunteer commitment to a project; all things career-related for project management students and graduates; and project management maturity in local governments. Guinevere is a founding member of the volunteer group Project Management for Life, which delivers project management workshops to secondary school students around Melbourne, Australia. She finds her peace in rural Victoria among gum trees and kangaroos.

x  Research handbook on project performance Charu Chandra Gupta is a former deputy general manager of Hindustan Aeronautics Limited, Lucknow, India. He has a PhD in electrical engineering. He has an MSc (Engineering) and BSc (Engineering) from the Institute of Technology (BHU), India. He brings more than thirty-four years of high-tech aeronautical industrial experience and eleven years of teaching experience as professor and head of the department of aeronautical engineering in BBD National Institute of Technology and Management, Lucknow. He has wide experience across multiple domains such as R&D, design, manufacturing, maintenance, and quality assurance with expertise in development of prototypes, lab trials to flight trials, and commercialization of airborne electrical and avionics systems. He had been a member of the Board of Governors of the National Safety Council and authorized signatory of the Centre for Military Airworthiness and Certification (Ministry of Defense). Charu Chandra was recognized as an approved person for “Release Note Signatory” by the Directorate General of Aeronautical Quality Assurance (Ministry of Defense). He is the recipient of National Safety Awards for Organization (Green Tech Safety Award) and also the recipient of the Vikas Shiromani by the Institute of Economic Studies for his contribution to management. Ruchita Gupta is a technology, innovation, and project management professor at the National Institute of Industrial Engineering, currently serving as associate professor in the area of operations and supply chain. She has a PhD from IIT (Indian Institute of Technology), Bombay, with an MTech and BE as a gold medalist. She has twenty years of experience in industry in organizations like Hewlett-Packard and Financial Technologies. Her teaching and research interests include management of technology and innovation, technology acquisition and transfer, technology forecasting, and project risk management. She has published more than seventeen research papers in highly reputed A* journals such as Technology Forecasting and Social Change, Decision Sciences, Telecommunication Policy, and IEEE Transactions on Engineering Management. She is a recipient of the Award of Prominence in the Field of Technology and Innovation Management 2019 by the International Association of Management of Technology, USA. Ruchita has been involved in various consultancy and management development programs across industries. Lavagnon A. Ika is a project management professor and founding director of the Major Projects Observatory at the Telfer School of Management of the University of Ottawa (Canada). He sits on the prestigious academic boards of the US-based Project Management Institute and Europe-based International Project Management Association (IPMA), two of the leading project management associations in the world. He is also associate editor for the top project management journal, International Journal of Project Management. Professor Ika’s work earned him an Emerald Outstanding Paper in 2017, a Telfer Innovative Researcher Award in 2017, a Telfer Established Researcher Award in 2021, and an IPMA Global Research Award in 2017 and 2022. Fadzida Ismail received her MSc in construction management in 2005 from Universiti Teknologi Malaysia and Bachelor’s of quantity surveying in 2003 from Universiti Malaya. She is currently a lecturer in Universiti Malaysia Pahang. Her works revolve around construction project management and academic development. During her free time, she enjoys translation, editing, and proofreading.

Contributors  xi Chakradhar Iyyunni’s expertise is in risk management and decision-making, mentoring professionals and facilitating start-ups, group work and team building, project management and engineering R&D. He is a fellow, European School of Governance, associated with the East Side Institute, New York City and a former faculty at the Larsen & Toubro Institute of Project Management. He has a deep interest in human systems behavior in construction project performance. Dr Iyyunni’s multi-domain experience spans oil, gas, transportation, civil infrastructure, energy, and utilities, including renewable, nuclear, and conventional power plants, automotive, aerospace, pharmaceutical, life sciences, biomedical engineering and devices, and marine/ship structures. He has worked with project directors, cluster heads, senior project managers, and execution and construction managers with some of the project budgets exceeding billions of US dollars. Dr Iyyunni has published nine large case studies and seven research papers and has made a number of presentations and taught courses at reputable institutions, including in India IIM-Ahmedabad, NITIE, NMIMS-Shirpur, and HAL Academy. He supported six graduate students and a PhD student and served as examiner for two doctoral scholars. He actively reviews research paper submissions from international conferences and journals. Dr Iyyunni received his mechanical engineering degree from IIT Banaras, MS from Virginia Tech, and PhD from the University of Houston. Karuna Jain received her PhD degree in industrial engineering from the Indian Institute of Technology, Kharagpur, India in 1987. She was a postdoctoral fellow in operations management from the University of Calgary, AB, Canada in 1992. In 1995, she joined the Shailesh J. Mehta School of Management, Indian Institute of Technology, Bombay, where she was selected as the head in 2007 and served for two terms (2007–2012). She was a director with the National Institute of Industrial Engineering, Mumbai, India from 2013 to 2019. She has published extensively in national and international journals and participated in international conferences in the area of technology and operations management. Dr Jain was the recipient of the Distinguished Fellow Award in 2019 by the Project Management Institute, India in recognition of her inspired leadership and valuable contributions and the Distinguished Service Achievement Award in 2019 by the IAMOT Board for her exemplary service in the area of technology management. Ahmad Huzaimi Abd Jamil is a senior lecturer in the Faculty of Industrial Management, Universiti Malaysia Pahang. He obtained his PhD in project management from Universiti Teknologi Malaysia, 2020 and MBA in technology management at Universiti Utara Malaysia, 2013. His main research interests include investigating the various dimensions of building information modeling (BIM) legal and contractual challenges encountered by the various collaborators and contributors to the project procurement process. This also provides an immediate insight into contractual issues, which could influence the effectiveness of BIM implementation, usage, and collaboration within the project team. Kam Jugdev (PhD, PMP) joined Athabasca University in 2003 following a career as a project manager. She is currently working as a professor in project management and strategy at Athabasca University. Kam enjoys being able to relate theory to practice with students and through her collaborative research initiatives. Her research program spans project management as a source of competitive advantage using the resource-based view of the firm, project management lessons learned, project management tools and techniques, and project success/ failure.

xii  Research handbook on project performance Sunil Kumar is an experienced project management professional in the power industry. He has more than eighteen years of experience in leading large construction projects at macroand microlevel for green- and brownfield projects in India and Bhutan. Sunil is comfortable linking theory with practices. He is knowledgeable in construction strategy, productivity, resource-optimization, delay analysis, and lean construction. Sunil has published research papers and case studies and developed innovative games as part of experiential learning. He has taught at the Larsen & Toubro (L&T) Institute of Project Management since 2009. He delivers training programs and provides consulting services for L&T, the World Bank, Suzuki Motors, Aditya Birla, Hindustan Petroleum, and Tata Group. He holds a Bachelor’s of technology degree in mechanical engineering from GBPUAT, Pantnagar, and a graduate degree in business management from XIMB Bhubaneshwar. Sunil is a member of the Institution of Engineers (India) and the Royal Institute of Chartered Surveyors (UK), and is a doctoral student at XLRI School of Management, Jamshedpur, India. Chia-Kuang Lee is a senior lecturer and head of research in project management, with more than twelve years of experience in R&D works, specifically in construction management and project management. He has worked as the head of program for the Bachelor’s of project management with honors and Master’s in project management at Universiti Malaysia Pahang, and has been recognized with several teaching and research awards during his career, such as the Most Promising Academician Award 2018. James Marion is an associate professor with Embry–Riddle Aeronautical University Worldwide. He is currently the chair of the department of decision sciences. His experience includes leading large organizations in multiple product launches in the US, Europe, and Asia, as well as significant experience with Japanese companies including NEC and Panasonic. Dr Marion has a PhD in organization and management with a specialization in information technology management (Capella University). He holds an MS in engineering (University of Wisconsin-Platteville) and an MSc and MBA in strategic planning, as well as a postgraduate certificate in business research methods (Edinburgh Business School of Heriot-Watt University). Carl Marnewick is a professor at the University of Johannesburg, South Africa. The focus of his research is the overarching topic and special interest in the strategic alignment of IT projects with the vision of the organization. A natural outflow of this research is the realization of benefits to the organization through the implementation of IT/IS systems. His research to date has identified impediments in the realization of benefits, which is part of a complex system. He is currently the head of the information technology project management knowledge and wisdom research cluster. This research cluster focuses on research in IT project management and includes governance, auditing, assurance, complexity, IT project success, benefits management, sustainability, and agile project management. Yvan Petit has been a professor at the Business School of the University of Quebec at Montréal (ESG UQAM) since 2010. After being the program director for the postgraduate programs in project management, he was the associate dean for international relations at ESG UQAM between 2018 and 2021. He has taught in Canada, France, Algeria, Vietnam, and Sweden and in 2017 he received the Teaching Innovation Award at UQAM. His research interests are in portfolio management, agile approaches, and uncertainty management. He has over twenty-five years of experience in project management, primarily in software develop-

Contributors  xiii ment and R&D in the telecommunications industry. He has served as a member of the Project Management Institute Standards MAG (Member Advisory Group) and on the Canadian section for ISO standards on project management. Jeffrey K. Pinto is the Andrew Morrow and Elizabeth Lee Black Chair in Management Technology at the Black School of Business, Penn State–Erie, the Behrend College, Erie, PA, USA. He is the author or editor of more than twenty-five books on project management. Professor Pinto’s research has been published in Management Science, Research Policy, Journal of Management, Expert Systems with Applications, Sloan Management Review, Journal of Management Studies, Journal of Product Innovation Management, and IEEE Transactions on Engineering Management. One of the most frequently cited scholars in the field of project management, he has received career research awards from both the Project Management Institute and the International Project Management Association. Rahimi A. Rahman is a senior lecturer at Universiti Malaysia Pahang in the Faculty of Civil Engineering Technology. His research group explores a wide range of topics to realize sustainable development in the construction industry, including decision-making (e.g., decision support tools, assessments), green construction (e.g., waste management, green building), and construction technology (e.g., building information modeling (BIM), technology adoption). To achieve that goal, his team explores new and alternative approaches for enabling a more rigorous process in decision-making, identifying the “right” size and composition of project teams, and creating action plans for recruiting or developing individuals for the workforce. The team is currently exploring topics related to decision support tools for design and build projects, project managers’ decision-making processes toward environmental regulations, assessments for designing buildings, and tools for evaluating BIM capabilities. Mahesh S. Raisinghani is a lead professor of management information systems in the MBA (executive track) at Texas Woman’s University’s (TWU’s) College of Business, a senior fellow of the Higher Education Academy in the UK, and the director of strategic partnerships for the Association of Information Systems’ SIG-LEAD. Dr Raisinghani was awarded the Distinguished Research Award by the Association of Business Information Systems in 2022, ISACA’s Excellence in Education award in 2021, TWU’s 2017 Innovation in Academia Award, the 2015 Distinction in Distance Education Award, the 2008 Excellence in Research & Scholarship Award, and the 2007 G. Ann Uhlir Endowed Fellowship in Higher Education Administration. He was also awarded the 2017 National Engaged Leader Award by the National Society of Leadership and Success and the 2017 Volunteer Award at the Model United Nations Conference for his service to youth and government by the Model United Nations Committee. He has published over a hundred manuscripts in peer-reviewed journals, conferences, and book series; edited eight books; and consulted for a variety of public and private organizations on IT management and applications. Dr Raisinghani serves as the editor-in-chief of the International Journal of Web-Based Learning and Teaching Technologies; member of the Board of Directors of the Global IT Management Association; advisor for the National Society of Leadership and Success chapter at TWU; and an advisory board member of Enactus and X-Culture.org. He is included in the millennium edition of Who’s Who in the World, Who’s Who among Professionals, Who’s Who among America’s Teachers, and Who’s Who in Information Technology.

xiv  Research handbook on project performance Tracey Richardson is an associate professor of project management at Embry–Riddle Aeronautical University Worldwide. She has a doctorate of organizational leadership from Argosy University and is a certified Project Management Professional and a Project Management Institute Risk Management Professional. Tracey is a retired United States Air Force Aircraft Maintenance Officer. Arthur Shelley is a collaborative community builder, experienced international project manager, multi-awarded postgraduate learning facilitator, and creative education designer with over thirty years of professional experience across the international corporate, government, and tertiary education sectors. He is the author of four books, has worked in twelve countries, is a mentor in several international communities, and has supervised PhD candidates in five countries. His project-based learning programs have been facilitated in formal university programs (MBA, MPM) and in executive education in Australia, Thailand, Singapore, Russia, and Vietnam. Arthur is on the editorial board of the Journal of Applied Learning and Teaching, supports several other journals as a peer reviewer, and is the assessor on several international awards including the Most Innovative Knowledge Enterprise and Knowledge Ready Organisation. He has collaborated with organizations as diverse as NASA, Cirque du Soleil, local and national governments, universities, start-ups, SMEs, and multinational corporations. Dhruv Pratap Singh is a research analyst and the coaching program coordinator at X-Culture, USA. He graduated with a Master’s specializing in international project development from the NEOMA Business School, France. Under his leadership, his team won the “Best Team Award” among 1,047 global virtual teams participating in the international business consulting project. At the age of twenty, he cleared the examination to become PMI® Certified Associate in Project Management (CAPM)® and a month later earned the PRINCE2® Practitioner in Project Management certification by AXELOS®. Additionally, he has membership in the APM (Association for Project Management) and was a sponsored participant for the IPMA–YPMY 2020 (International Project Management Association – Young Project Manager of the Year 2020). Dhruv is the founder president of the American Society of Civil Engineers – UPES Chapter; he regularly mentors students and shares his experiences/advice on fundraising, event management, public speaking, leadership, and project management. Michelle Turner is an associate professor at RMIT University in Australia. Michelle teaches in the undergraduate and postgraduate project management programs and supervises research students. Alongside her teaching, Michelle conducts research on student employability, resilience, and well-being. Michelle’s work is published in project management, construction management, and education journals. In 2017, she developed a measure of student resilience that has been used internationally to develop and promote well-being across a range of higher education disciplines. Michelle’s research takes a systems perspective that recognizes the interaction between the university and the student in shaping employability, resilience, and well-being. Prior to entering academia, Michelle worked as a project manager in industry for more than fifteen years and led diverse projects in multiple industries. Wen-Nee Wong was a final-year student of the Faculty of Industrial Management at Universiti Malaysia Pahang. She graduated in 2020 with a Bachelor’s degree in project management (Hons) and obtained the “Best Paper Award” for her final-year thesis writing. Wen-Nee also earned her professional qualification as a Certified Associate in Project Management

Contributors  xv (CAPM)® from the Project Management Institute under the supervision of Dr Chia Kuang Lee in 2021. Nurhaizan Mohd Zainudin is a senior lecturer and the head of program for project management at the Faculty of Industrial Management, Universiti Malaysia Pahang. She practiced as a quantity surveyor and worked in the oil and gas industry prior to joining the university as a faculty member. She received her Master’s of project management from the Queensland University of Technology, Australia and her doctorate degree from the Iowa State University, USA. She has led and been involved in several research projects and closely participated and engaged in the development and accreditation of the project management degree program. Her research areas include workers’ safety, risk management, project management, and construction management. Her research team is currently working on topics related to decision-making processes by exploring tools such as Space Syntax in building design assessment.

PART I BACKDROP

1. Introduction to Research Handbook on Project Performance Vittal S. Anantatmula and Chakradhar Iyyunni

Without exception, an organization typically strives to create value for its shareholders by achieving its strategic objectives, thereby creating a healthy profit. More often than not, projects are the instruments by which an organization pursues accomplishment of its strategic objectives. While achieving strategic objectives or higher profit, projects are driven by project management principles of effective and efficient use of resources. This is where project performance assumes great importance. Project performance also aims to improve the success of a project and project management. Project success is seen from the perspectives of the project sponsor, the client, and the end user, whereas project management success is important for the project manager and the project team who focus on completing the project faster, better, and cheaper while accomplishing all the project objectives and goals. The successful efforts of the project team lead to project success in terms of project deliverables meeting clients’ expectations such as cost, time, quality, and value. Both project success and project management success depend on a variety of factors. In spite of recent advances in the project management profession – largely due to efforts led by professional associations such as the Association for Advancement of Cost Engineering International (AACEI), Project Management Institute (PMI), and International Project Management Association (IPMA) – research efforts suggest that many projects fail. One of the main reasons for this failure is the absence of a desired level of project performance. Effective project performance also underlines the important role of a project manager. Specifically, the project manager’s leadership role is of great importance in motivating people and creating an effective working environment for the project team to meet emerging challenges in today’s global economy. Further, sustainability has become undeniably important; along with ensuring profits, projects need to consider thought-leadership practices for both people management and minimizing the impact on our planet’s environment. This research handbook presents a number of chapters written by accomplished researchers and the topics vary widely. We organized them into three parts. The first part, “Backdrop,” includes this chapter as an introduction to the book and chapters that deal with project performance concepts and methods. The second part, “Tactics, Strategies, and Risks,” presents a series of chapters on the tactics, strategies, and risks associated with project performance. Finally, the third part, “Next Practices,” includes chapters that deal with next practices and new trends in project management that can have a major impact on project performance.

CHAPTER 2 Ahmed outlines the current understanding of project performance measures and metrics from a project management perspective. Project performance success criteria and its different 2

Introduction  3 dimensions have been defined for different phases and facets of projects. The author highlights the nonavailability of a performance standardized framework and proposes a comprehensive framework that can be adopted by various types of projects, organizations, and industries to enhance project performance success. Additionally, the chapter discusses different maturity levels for project performance and suggests a hierarchy or classification for prioritizing performance measures and metrics to increase the likelihood of project management success.

CHAPTER 3 Den Haak integrates lean thinking with ambitious goal setting of an objectives and key results (OKR) framework for improving project performance. This approach achieves a hyper-focus on one goal, fosters necessary behavioral changes, encourages experimentation, and builds devotion to continuous, long-term learning while eliminating inefficiencies; it is outcome (not output) driven. The author suggests including a value creation model (VCM) for company culture in the lean thinking plus OKR framework. Such an approach brings in the agility and flexibility required of the leadership to maintain the OKR cycle and keep it relevant and focused. This VCM is a necessity for digital product companies to stay relevant for their customers by aligning activities to measurable outcomes.

CHAPTER 4 Daniel presents a basic tension in the project performance literature that features two contrasting perspectives: output-orientation, which is focused on project efficiency such as meeting triple constraints, and outcome-orientation, with its focus on project success of realizing short- and long-term social benefits of project deliverables (outputs). The author highlights the need to go beyond the classical view of the project management life cycle (and output delivery) toward operationalizing outputs (outcomes) and obtaining benefits, which is the core intent and nature of projects; this view is indispensable for emerging topics of megaprojects and sustainable project management. The tenuous and dynamic interaction between project outputs and project outcomes is poorly understood and this resulting dynamic is crucial to understand project performance. The author introduces a multi-level framework of project performance based on projects, operations, and outputs feeding into outcomes. Project benefits and outcomes are realized as a value chain of operations. Each operation is a specific function. The value chain, therefore, highlights a new functional system or one whose functional performance is now improved, through the implementation of the project or program. The author exquisitely characterizes project delivery as a (value) chain of sociotechnical systems contributing to the strategic performance of the project, outcomes, and new resources necessary for efficient operations. The performance of these sociotechnical systems is steered by key performance indicators that measure the targeted outcomes (not outputs) and additionally by specifications that clarify the necessary qualities/features of the new resources required to achieve the outcomes.

4  Research handbook on project performance

CHAPTER 5 Zainudin et al. raise a very topical challenge to the construction industry of construction and demolition waste (CDW). Globally, many environmental problems have been associated with CDW. Therefore, CDW recycling is seen as necessary, given the rapidly growing amount of CDW over the years. The inclusion of a clause on CDW recycling in national Standard Form Contracts can encourage contractors to recycle CDW, hence improving construction waste management. The authors evaluate the contractor’s perception of the inclusion of CDW recycling as a mandatory clause in Standard Form Contracts. The results of a survey questionnaire responded to by contractors show that the inclusion of the CDW recycling clause in Standard Form Contracts would not benefit contractors and consequently hurt their project performance. Despite the fact that most contractors are aware of the environmental problems caused by CDW, the CDW recycling clause is seen as a constraint rather than an enabler but the inclusion of such clauses is necessary. It is indicated that the government could take a more strategic approach to CDW recycling (and probably research into construction methods for reducing the production of CDW itself).

CHAPTER 6 Richardson and Marion discuss the lack of predictability in project monitoring efforts. Organizations use the results of the project monitoring systems to provide information and help in making decisions such as allocating resources, budgets, and strategic selection of future projects. Despite being studied for decades, project monitoring is still more of an art than a science and, if left unchecked, the results can be a culmination of guesswork. This chapter illustrates the challenges in documenting project progress when progress is not visible. Status reporting is often left to those working on the project, but without the awareness of the significance of quality inputs, the impatience and incompetence of those giving inputs scupper the quality of monitoring. These data inputs may not be accurate. As they are foundations of the project monitoring system, they often would lead to erroneous project monitoring systems. The authors suggest that the data integrity problem could be adequately addressed by adding the role of “monitoring” to the project’s change control board.

CHAPTER 7 Ika and Pinto raise a hugely pertinent and paradigm-shifting challenge to understanding project success. While characterization of projects, its enablers and risks, has preoccupied the literature on success factors, “context is king” in projects. This contextual specificity arises from a number of factors such as project design, owners’ and contractors’ organizational design and risk tolerance, partnerships, PESTLE (Political, Economic, Social, Technological, Legal, and Environmental) conditions, site conditions, and contracts. With an extensive literature review, the authors underline the importance of understanding the conditions for success against a backdrop of complexity and uncertainty. Success conditions, “circumstances or pre-requisites that must exist or emerge for project success to occur,” are necessary elements to be in place before or during a project. For this purpose, they consider structural,

Introduction  5 institutional, and managerial categories along with meta-conditions such as multi-stakeholder commitment, collaboration, alignment, and adaptation.

CHAPTER 8 Lee et al. use the decision-making trial and evaluation laboratory (DEMATEL) for construction projects, which are generally exposed to a wide range of risks the majority of which have a direct impact on the organizations’ ability to accomplish project objectives. However, many organizations overlook the importance of incorporating risk management into their projects. The authors focus on the management of the interdependence of the factors influencing the implementation of risk management in projects such as resistance to change, lack of managerial support and communication, low-risk attitude, lack of resources, lack of knowledge in implementing risk management, and poor risk culture in organizations. To achieve project success and improve project performance, it is critical to identify the primary risk factors that must be carefully controlled to reduce the impact and alleviate the causes. To identify the essential causes and consequences, DEMATEL is employed to prioritize the elements and examine their interaction. The correlations between the causes and effects of low-risk management adoption are shown to be significant. The findings also revealed that resistance to change is the most important factor for a lack of risk management adoption. Consequently, management should pay more attention to this issue to improve risk management and project performance in construction projects.

CHAPTER 9 Iyyunni and Kumar explore the vicissitudes of the Indian context and contingent peculiarities of risk behavior in Indian projects using four case experiments. The authors illustrate stakeholder behavior at multiple levels – individual, interpersonal, team, organization, and societal levels – and identify methods to alleviate these risks. The authors derive a model for being “hopeful” that project managers have the appropriate risk attitude to initiate and stay in the virtuous cycle of delivering project success.

CHAPTER 10 Gupta, Jain, and Gupta believe that the current volatile, uncertain, complex, and ambiguous (VUCA) scenario in the global economy presents challenges to complete projects at a faster rate, on time or sooner, on budget or less, delivering value to the client. Addressing the VUCA requires innovation, collaboration, and change in mindset and these approaches add more risks to projects and project performance. A recent study by the PMI in 2018 indicated that 29% of project failure happens because of the absence of risk identification and its management. This study underlines the importance of effective risk management in improving project performance.

6  Research handbook on project performance This chapter presents a structured and predictive analytics approach of managing various risk management aspects such as risk identification, evaluation, assessment, and mitigation. The authors presented a few data-driven models for making quality decisions.

CHAPTER 11 Turner and Gilbert, with a concern that the failure rate of projects continues to be high, cite a PMI study (2021), which identifies a gap between the demand for project management skills and the availability of talent. Empowering a new generation of talent with the necessary project management skills and knowledge is critical in addressing the talent gap (and decreasing the rate of project failure). The authors describe a study undertaken to explore how a capstone project impacted on the perceived employability of final-year project management students. The survey measured collaboration, informed decision-making, commencement readiness, lifelong learning, professional practice and standards, and integration of theory and practice. There were seven key themes that emerged from the interviews: collaboration versus task allocation, working together – the impact of familiarity, group conflict, skills gap identification, confidence, application of course knowledge and skills, and the role of the mentor. This is enabled by the confidence and self-belief to apply the knowledge and skills learned at the university.

CHAPTER 12 Anantatmula, in a research effort using a survey questionnaire and case studies, explored relations among sets of three factors representing project performance, project success, and project management maturity of an organization. The chapter starts with the premise that in spite of great research efforts on projects by academic research, and professional associations, studies show that the number of successful projects has not changed significantly. The purpose of this chapter is to present relations among project success and project performance factors, and organizational project management maturity. The research results suggest that communication and top management support are important for improving project performance and project success. Further, the presence of project management maturity – consisting of portfolio management and formalized project management processes – improves project success and project performance.

CHAPTER 13 Chbaly and Brunet offer insight into managing performance in the face of complexity in projects via lean management. The “design performance gap” – a situation in which design fails to meet user needs – has been widely discussed in recent years. The problem stems from the fact that designers have insufficient information about user needs. To deal with this problem, many researchers highlighted the importance of involving users during the early stages of the project life cycle to identify and manage user requirements accurately, thereby generating value.

Introduction  7 This chapter describes the case study of a hospital megaproject that implemented a participative and inclusive approach, namely lean-led design. The lean-led design approach implemented by the clinical management of this hospital enables commitment as well as communication between architects and users like doctors and patients. Further, unlike with conventional practices, it begins with an in-depth questioning of current ways of doing things before moving on to architectural concerns, placing the patients at the center of the reflection. The aim is to create spatial configurations that facilitate the operations of healthcare services, making them safer and more efficient. The results and discussion of this chapter have brought forward important considerations regarding the role of early involvement of client stakeholders by illustrating how a lean-led approach contributed to project definition. The objective of this implementation was to ensure efficiency in the delivery of care services by aligning user needs with design solutions during the early stages. The chapter offers insights into the lean-led design approach for the project definition complexity of hospitals.

CHAPTER 14 Petit and Marnewick discuss a scaled agile framework wherein the influence of fixed capacity and its contingent impact on budgeting is discussed against the backdrop of software development for a financial institution. Scaling agilely within an organization has a direct influence on the way scheduling is done; this in turn has a direct influence on the budgeting process and the allocation of resources. This chapter investigates the notion of fixed capacity and its influence on the budgeting process. With fixed capacity, the aim is to visualize the workflow within a project and to prioritize the work-in-progress (WIP) in accordance with the capacity of the team. In the first phase, interviews were scheduled within a case that has adopted SAFe as a scaled agile framework. Among the realized benefits were: being closer to the business needs, delivering products in weeks rather than years, building more usable and simple software, and adopting new technologies faster. Analysis of the study indicates that the introduction of fixed capacity is not an easy process, but the benefits outweigh the difficulties. Fixed capacity introduces beyond budgeting with a focus on a fixed-capacity budget. As with fixed capacity, the benefits of beyond budgeting outweigh the agony associated with moving from a demand-based budget to a fixed-capacity budget.

CHAPTER 15 Singh and Raisinghani provide a comprehensive qualitative discussion on the role of cross-cultural integration as a next practice of project management. The chapter is at the intersection of research and practice with its focus on global projects and teams representing diverse cultures. It presents a structured, logical, and systematic organization of ideas on various facets of national and organization culture in project management, and their impact on project performance. The main objective of this study is to identify how best practices and cultural variables moderate or directly relate to the project outcomes. These cultural variables, such as level of informality, perceived deadlines, perceived productivity, perceived work ethics, cultural

8  Research handbook on project performance prejudice, language and accent barriers, and communication challenges, are iterated and augmented throughout this research effort using a qualitative research method to propose a theory that will help answer arguments related to the importance, relevance, and impact of culture on project success. This study considers the impact of cultural integration with the project management knowledge areas, project phases and processes, project teams, resources, scope, cost, time, quality assurance, conflicts, changes, and risk; all of them impact project performance.

CHAPTER 16 Jugdev, using the metaphor of a rearview mirror, likens the mirror to the lessons learned processes in project management. PMBOK® seems to focus on data and information, which is at the base of Rowley’s wisdom pyramid. PMBOK® also seems to ignore the relational aspects among project personnel and instead focuses on the structural elements of creating the knowledge edifice for the project. While journal abstracts viewed learning as a higher-order dynamical and relational activity, Jugdev notes the limitation of assessing only the abstracts instead of the full article, thereby losing theoretical components as well as relationships to success, benefits realization, or trust. The author concludes that the formal and informal learning processes (of sharing data, information, and understanding via knowledge and wisdom) conducted beyond and during project life cycles and within or beyond organizations by sharing knowledge and practices can only be supported by a diligent approach.

CHAPTER 17 Shelley has an expansive way of describing how the lens of project management could positively impact every walk of life, no matter the scale. Project performance then becomes an effective approach to enhancing competence and learning experiences. The consistent fluidity of the world means all professionals benefit from understanding change and adaptable to a change. Aspects that help achieve this are: understanding the role projects have in facilitating a successful change, being familiar with project management approaches, and being a member of project teams. More importantly, every professional benefits from the constant learning and new knowledge stimulated through project experience to remain relevant. Project performance is normally focused on delivery of scope with the desired quality and within the allocated time and budget. While it is important to measure the tangible project outcomes, organizational performance improves when projects are managed as strategic vehicles of capability development and acknowledge the longer-term, intangible outcomes they generate. This chapter proposes the optimal way to achieve sustained high performance – for individuals, teams, and organizations – by extending our perception of projects to include the intangibles they deliver. These include learning, relationships, trust, confidence, social connections, critical thinking, and understanding of complexity. It is time for the project management profession to acknowledge the value these projects bring to further team and organizational performance and to plan them as strategic outcomes of every project.

Introduction  9

CHAPTER 18 Dixit and Agarwal suggest the need for understanding Industry 4.0 technologies and their potential impact on project management. In considering their impact on agile project management, they are intertwining two of the unwieldy complex aspects of projects – technology and human systems. Industry 4.0 includes the Internet of Things, big data, autonomous robots, simulation, additive manufacturing, augmented reality, virtual reality, cloud computing, and so on, and some of these have found their way into traditional, brick-and-mortar project-based industry; that is, construction and infrastructure. For example, augmented/virtual reality is crucial in creating the behavioral shifts in awareness and compliance with safety. The authors indicate the impact to Project Management 4.0 as characterized by digitization, virtualization, transnationalization, professionalization, and agile methodologies. The micro- and meso-level impact on human resource management is discussed in relation to the individual’s Industry 4.0 specific technical competencies and further necessitates participative leadership and fostering psychological safety and trust in teams in addition to those stemming from agile project management practices. At the macro level, technology poses existential challenges to the role and behavior of leaders and organizations in a highly evolving technological landscape and concomitant emergent human behavior. Application of these technologies is likely to overcome the challenges of trade-off issues associated with cost, quality, schedule, and scope in the context of project management, thereby leading to enhanced project performance.

CHAPTER 19 Agarwal and Devkar argue that although public–private partnership (PPPs) have been adopted the world over for delivery of infrastructure projects, the failure of PPP projects in the recent past has brought the life cycle of these projects under increasing scrutiny. Often, the founding principles of PPP are considered to account for poor project performance. Contrary to this argument, this chapter presents arguments that the deviation from the founding principles is the real reason for the poor project performance. The arguments are based on analysis of the data collected from multiple case studies of road sector PPPs in India. Further, the literature review of this chapter presents best practice guidelines for PPP projects and connects these guidelines with the guiding principles of PPP projects. The analysis compares and contrasts the guiding principles and actual on-the-ground practice in the entire life cycle of PPP projects. This effort led to elaboration on gaps between theory and practice and reasons behind these gaps for improving the state of the art of PPP projects.

FINAL WORDS Organizations with formal project management processes are likely to use project performance planning tools and complete projects within cost and time. In other words, formal and proven project management processes and practices are likely to improve project performance. Further, the presence of portfolio management may likely promote formal project management practices and policies. Collaborative work culture, knowledge sharing, and efficient

10  Research handbook on project performance and transparent communication are important tenets of an effective team and, needless to say, project teams play a crucial role in enhancing project performance. Formal cost management practices, procurement processes, and protecting leakages via contractual and claims enforcement enhance project performance and success. Investing in individuals within project teams via training, mentoring, and coaching and organizing, and aligning people to project success and organizational values, will support project performance goals. Encouraging an attitude of excellence toward quality, risk, and HSE (health, safety, and the environment), and respect for workmen/project personnel, goes a long way toward building a “project culture” conducive to project performance.

2. Project performance measures and metrics framework Riaz Ahmed

1. INTRODUCTION A project is considered as a temporary effort in organizations that is structured to perform a set of activities for creating a unique result with a predetermined beginning and end defined by time-boundedness and limited resources. According to PMI (2017), “a project is a temporary endeavor undertaken to create a unique product or service”. Project performance denotes the extent to which project outputs and outcomes satisfy budget goals, schedule goals, operational and technical specifications, and, ultimately, the business needs of the client (Ali et al., 2018, p. 457). The traditional approach associated with the performance of a project includes the evaluation of scope, quality, and cost. Indeed, the process of measuring the action leads to quantifying project performance, which is considered as efficiency and effectiveness of action in the context of projects (Głodziński, 2019). To measure such actions, various metrics and measures of performance are required in projects that are different from each other. The performance measure is “a set of metrics that aids in assessing the efficiency and/ or efficacy of an action”, according to Neely et al. (1995). The performance measures allow project managers and other project stakeholders to assess project performance at the phase level, allowing proactive measures to be implemented based on current project reviews (Yun et al., 2016). According to Kaplan (1990), “no measures, no improvement”. For such manifestation, any given performance target that project or process participants wish to establish and track, one or more performance metrics can be identified. Identifying a vital variable that measures, reflects, or significantly influences a specific performance objective is a guiding principle in selecting a performance metric (O’Sullivan et al., 2004). More comparisons of metric results based on various project characteristics can be possible, which can be extremely valuable in evaluating and analyzing phase-level performance indicators (Yun et al., 2016). Project performance is considered as a trade-off between several measurements and dimensions specifically emphasizing what is done, such as scope and quality versus resources, including the time and cost to complete the project activities (Kabirifar & Mojtahedi, 2019; Zheng et al., 2019). The concept of project performance has been discussed in the literature as the extent or degree to which a project fulfills its intended purpose (Szatmari et al., 2021). Although project performance has been studied both academically and practically in the field of research, the key question is to decide “what will be measured” and more importantly to select a mechanism of performance indicators (Zheng et al., 2019). Indeed, the overall conceptualization of project performance includes schedule performance, quality performance, innovation performance, and benefit performance (Chen & Lin, 2018). On the other hand, project management practitioners emphasized that project performance is all about the success of projects, which must be in line with the organizational long-term goals. In other words, project management literature often defined project performance with the fundamental triple con11

12  Research handbook on project performance straints of time, cost, and quality (Barbosa et al., 2021; Younus & Younis, 2021). Nonetheless, different stakeholders have different stakes in the project, therefore various components and dimensions are also used to measure the project performance success, such as client satisfaction in addition to time, cost, and scope parameters (Zhu et al., 2021).

2.

PROJECT PERFORMANCE METRICS, MEASURES, AND DIMENSIONS

2.1

Metrics of Project Performance

A metric is a “method of calculating” a value (price, weight height, etc.), which is also a numerical measure used to track and evaluate the progress of an activity. Indeed, metrics are quantitative assessment measures that are routinely used to evaluate, compare, and track the performance of projects or production. A project metric represents how much a system, component, or process contains a specific attribute. Project metrics are essential indicators that can be used to track the progress of a project. Also, metrics support the implementation of corrective actions when the numbers do not match the expectations in projects. In addition to tracking the progress of a project, an effective project manager must keep track of the team’s progress and guide them toward the project’s objectives. In other words, a metric is a measurement that is used to gauge the performance of a project. To put it another way, it is a term that assesses how well something was done. For instance, project management metrics are used as a tool to assess the project’s success (or performance). Indeed, project management metrics enable project managers to analyze a project’s status, anticipate hazards, and assess the team’s productivity and quality of work, allowing them to determine the success of a project. In a project context, a performance metric can be in a tabular or figure format to provide an easily interpreted sign of performance. Rankin et al. (2008) defined cost, time, quality, safety, scope, innovation, and sustainability as performance indicators that could be applied to projects, in addition to capacity-based metrics, such as cost per unit and time per unit. Ling et al. (2009) identified essential project management strategies for different project measures that were found to have a significant impact on project performance, in terms of budget, schedule, quality, owner satisfaction, profitability, and public satisfaction. Similarly, Swarup et al. (2011) identified performance criteria influencing project goals in terms of schedule, cost, quality, and post-occupancy evaluation. Such performance metrics can be used by the practitioners to assess the outcomes of projects (Yun et al., 2016). Nevertheless, the improvement measures were developed using activity-based costing theory and controllability engineering theory, as well as monitoring metrics such as efficient project time, value-added, subcontracting percentage, number of invoices per day, invoice amount, disposal costs, tender reply percentage, and the number of changes in subcontract (Wegelius-Lehtonen, 2001). 2.2

Measures of Project Performance

A measure is a quantifiable indication of performance gathered when actions are being carried out. In contrast, a metric is a measurement or calculation that is linked to performance. Metrics are repeated measures that are used as benchmarks for comparing variation to a set of project

Project performance measures and metrics framework  13 goals that can be gathered by a variety of methods, such as tracking the number of days late or the number of flaws discovered. A metric is also called an indicator, or a key performance indicator (KPI) when it is utilized in a monitoring system to analyze a project through performance information. In projects, performance information is a piece of additional information needed to make sense of performance measures and indicators – such as the time of day, the outside temperature, and the size of a crowd. A metric is anything that can be measured and a criterion is a characteristic that is used to choose anything. Indeed, the criterion is a defined value of a measure for which a decision must be made based on, whether the parameter is above or below it. There are always several attributes that allow choosing anything that is a measurement, but there is no other connection between the two terms. Nevertheless, there are certain project success criteria used as measurable terms that describe what the project’s ultimate result should be that is acceptable to the end user, customer, and stakeholders. In other words, project success factors are actions or elements that must be present for the projects to be completed successfully. In the project management literature, one of the most common and frequently used measures of project performance is the “iron triangle”. The iron triangle refers to the cost, time, and quality that is believed to be the unique information among customers and project stakeholders (Maqsoom et al., 2020). These three elements of the “iron triangle” are considered part of the project throughout the project life cycle, commencing with the planning and design stages and concluding with the final closing stage (Kabirifar & Mojtahedi, 2019). Owing to this, it is considered important to monitor the progress of the projects beyond time, cost, and other areas according to their complications. Nonetheless, monitoring and control phases should not only consider the time and cost issues but also the other issues and behaviors that can be identified during the project execution phase in different knowledge areas such as project value, image, and reputation (Kabirifar & Mojtahedi, 2019). Several challenges are associated with the measures of the “iron triangle”. An increasing challenge to the “iron triangle” is that most of the project performances are measured with the performance criteria such as time, cost, and quality, which are identified and explained in most of the research studies as the critical success factors of the project. On the other hand, some research studies have explained other basic criteria to measure project performance, such as interpersonal skills or relationships among the project team members. Nonetheless, efforts have not been made to combine all such project performance measures into a comprehensive framework that can be used to quantify the overall project performance success (Shdid et al., 2019). To overcome this challenge, various measures and metrics used in the extant literature to determine project performance during different phases of the projects are synthesized in Figure 2.1. 2.3

Dimensions of Project Performance

In the project management context, various performance criteria and dimensions associated with projects at strategic, tactical, or operational levels are increasingly being used to measure performance that leads to project success. Such dimensions include: schedule performance, quality performance, innovation performance, benefit performance, project scope, time, cost, procurement management, associated risk, human resource, customer satisfaction, learning and innovation, senior management support and skills, integration of resources, safety, financial performance, stakeholder satisfaction, and effective communication (Szatmari et al.,

14  Research handbook on project performance

Figure 2.1

Synthesis of project performance measures and metrics used in the project lifecycle

2021; Maqsoom et al., 2020). Such performance dimensions have been explained in different contexts and ways. For instance, cost performance appraises whether a project is completed within the budget, schedule performance determines whether the project is finished within a given time frame; quality performance ensures that project deliverables meet the contractual requirements; innovation performance refers to whether the project generates useful ideas and new professional knowledge and techniques; and benefit performance measures the effectiveness of project outcomes in terms of promoting the organization competitiveness (Chen & Lin, 2018). Indeed, the importance of project performance is to keep project stakeholders informed about the status of the project because the progress of projects is measured by the project managers and the appropriate stakeholders. On the other hand, inadequate performance indicators provide incomplete information for decision-making that results in reduced project outcomes (Zheng et al., 2019). Moreover, project performance is also used for financial objectives and goals achieved at the end of the projects. Such financial gains are reported by the project leader who highlights the actual cost savings and revenue increased as a result of project outcome (Dasí et al., 2021). As a result, performance criteria and indicators are the critical aspects of project management, which highlight that measures of project performance need to be considered following the different phases of the project and significance of project types, in addition to the development and evaluation of important performance indicators that enable description of the characteristics affecting project outcome (Zheng et al., 2019). According to Sekar et al. (2018), dimensions of project performance include cost, time, quality, safety, and financial performance. However, the cost and financial performances are not the same. Indeed, project performance is a multidimensional construct and the “iron triangle” is most commonly used to measure project performance, which is made up of three important dimensions: cost, time, and quality. As such, cost and time performance are typi-

Project performance measures and metrics framework  15 Table 2.1

Literature review summary on dimensions of project performance

Dimensions/

Cost

authors

performance performance performance

(Głodziński,

Schedule

Quality

Scope Process

Stakeholder Time

performance influence

Financial

Safety

Future

performance performance performance potential

 

 

x

x

 

 

 

 

 

 

 

 

 

 

x

x

 

 

 

 

x

x

x

x

 

x

 

 

 

 

x

x

 

 

 

 

 

 

 

 

x

 

x

 

 

 

x

x

x

 

 

 

x

x

 

 

 

 

 

 

x

 

 

 

 

 

x

 

 

x

(Unterhitzenberger x

 

x

 

x

 

x

 

 

 

x

x

 

 

 

x

x

x

 

(Lee et al., 2020) x

x

x

x

 

 

x

 

x

 

(Salvador et al.,

 

 

 

 

 

 

x

 

 

 

x

x

 

 

 

 

x

 

 

 

(Adamtey, 2019) x

x

x

 

 

 

 

 

 

 

(Mossalam,

x

 

x

 

 

x

x

x

 

2019) (Wang et al., 2021) (Ahmed & Anantatmula, 2017) (Assaad et al., 2020) (Sekar et al., 2018) (Szatmari et al., 2021) (Gupta et al., 2019) & Bryde, 2018) (Aldhaheri et al., x 2018)

2021) (Mahmoudi et al., 2021) x

2020)

cally quantified as a percentage divergence from the initial plan, whereas quality performance is measured in terms of contractual agreements and technical standards compliance. Moreover, cost performance is concerned with the completion of the project within the allocated budgeted cost that includes both direct and indirect cost, whereas the financial performance of a project is related to return on investment, return on equity, return on assets, earning profits, and the overall contribution of the project in the organization’s financial success (Sekar et al., 2018). Such dimensions give useful and important information about project performance, especially in terms of task-related characteristics. Enumerating the customer’s requirement, or even expanding it to include the satisfaction of the stakeholder, is an additional significant factor. Such intangible criteria, which focus on perceptions and attitudes, are seen to be a useful addition to measuring project performance (Unterhitzenberger & Bryde, 2018). Therefore, various dimensions of project performance used in the extant literature are summarized in Table 2.1.

16  Research handbook on project performance

3.

ANALYZING THE CHALLENGES OF PROJECT PERFORMANCE

Although some measures, metrics, and dimensions have been used to measure project performance, there are yet several challenges associated with the performance of projects. Indeed, every project is always different or unique, and project success is judged in terms of the project’s completion, and project data can be used to examine and track project success or performance to build a knowledge base and improve the project management success (Ahmed & Anantatmula, 2017). On the other hand, project safety and quality can influence the performance of projects during the design and planning stages, where project management tools and procedures are used extensively (Sekar et al., 2018). Moreover, because of the evaluation bias, a project is more likely to be accepted and sustained within an organization regardless of its quality, increasing the likelihood that the organization will undertake low-quality initiatives that will perform poorly on the external market (Szatmari et al., 2021). However, similarities and variations in project monitoring and performance assessment methodologies under various scenarios (e.g., process improvement, R&D, etc.) have received less attention (Gupta et al., 2019). There are several issues and challenges in measuring project performances in different phases of the project. Sometimes the project during its development phase can lose the balance and deviate from its established initial objectives, which means there is a need for a correction plan. To avoid such corrections, there should be a mechanism to identify any deviation at the earlier stage. To deal with such divergence situations, performance indicators are established to discover and provide timely information to develop action plans and maintain the project balance (Pereira & Lima, 2018). Additionally, another similar challenge is that despite the efforts of project managers as well as employing different project management tools, most projects are still unable to achieve their targeted performance because of the inability of the organization to implement effective control mechanisms for the projects and manage the level of complexity in projects (Maqsoom et al., 2020). The most vital issues affecting the project performance success are poor project planning and control, which further results in poor performance. The development of effective standards and planning at the beginning of the project are the main critical factors of project success that should not be ignored. Likewise, the financial benefit is another concern in projects, which plays a significant role during the project initiation phase and is common among all project stakeholders. Project initiation without adequate design, estimation, and planning eventually leads to project failure (Kabirifar & Mojtahedi, 2019). Furthermore, another important factor that needs to be considered is flexibility in projects during the planning and implementation phases, which cannot only be accomplished by flexible decisions but also involve making adjustments in the entire planning system, departing from plans, changing them, or sidestepping them altogether (Sohi et al., 2020). Indeed, initial acceptance and moving forward with low-quality projects is a severe problem for businesses, because product-related decision-making is prone to decision traps, which can result in significant project failures (Szatmari et al., 2021). Given the global monetary worth of project work, underperformance is a major economic concern, and management approaches normally utilized in project management are required to increase the likelihood of project performance success. One of the main challenges for the project manager is to finish the project within the time frame determined by the project stakeholders. Indeed, project managers

Project performance measures and metrics framework  17 have always had difficulty in reducing project duration while taking into account the factors affecting the project’s implementation. Cost and time are considered important in project completion, whereas the quality is usually ignored in certain cases, which impacts the overall performance of the project (Mahmoudi & Feylizadeh, 2018). Furthermore, poor project performance can be caused by a lack of planning by the project management team, a lack of human resources, a lack of cost control, and scope modifications throughout the project (Sekar et al., 2018). Projects are implemented for the customers and customer satisfaction is one of the big challenges faced in measuring the project performance. The term “customer satisfaction” refers to how the customer sees the end product’s performance, which includes adherence to a set of pre-defined goals; if expectations were lower than actual performance, customer satisfaction would be achieved (Tam et al., 2020). Moreover, customer satisfaction is regarded as a reliable measure of project performance, which is positively associated with organizational success (Szatmari et al., 2021). Nevertheless, a project should meet the customer specification of the finished product in terms of quality and quantity (Aldhaheri et al., 2018). Indeed, the performance of a project cannot be fully appraised until it has been delivered and used by the customer (Ahmed & Anantatmula, 2017). For instance, complex projects have a complicated nature and project complexity may cause unintended consequences toward project performance. The complexity of the project adversely affects the cost performance that can negatively impact the project performance. Owing to difficult technical and organizational project complexity, complexity has a detrimental impact on project performance. Therefore, it is possible to improve project performance by using complexity and uncertainty reduction measures, in addition to developing a comprehensive project performance framework (Safapour et al., 2018).

4.

PROJECT PERFORMANCE FRAMEWORK

Many organizations have struggled to deliver high-quality projects, products, and services on time and at a low cost despite a lack of adequate performance measures and metrics, which include tangibles, intangibles, financial, and nonfinancial factors (Gunasekaran et al., 2015). In such situations, financial metrics have often been used as performance indicators. These measures gave current information about the organization’s performance but did not provide estimates for the future (Mishra et al., 2018). Although financial performance measurements were useful in the early years, according to Kaplan and Norton (1992), now organizations must consider them in projects to stay competitive. However, a few studies have proposed using a “balanced scorecard” to establish strategy alignment by balancing financial and nonfinancial measures (Kaplan & Norton, 1992). On the other hand, some researchers have proposed various frameworks to manage performance from the beginning to the end of the 1980s and early 1990s, including the performance measurement matrix (Keegan et al., 1989), performance pyramid (Lynch & Cross, 1991), results-determinants framework (Fitzgerald et al., 1991), balanced scorecard (Kaplan & Norton, 1992), Cambridge Performance Measurement Process (Neely et al., 1995), and performance prism (Neely et al., 2002). However, these performance frameworks are not adequate to comprehensively measure the performance of projects.

18  Research handbook on project performance According to Neely (1994), “a performance measurement system can be characterized as a set of metrics used to quantify both the efficiency and effectiveness of actions”. Performance measures are required in projects, due to which many research efforts have proceeded over the last many years to create acceptable measures for evaluating project performance. The majority of performance measures are used to analyze project performance outcomes at the project level; many performance studies have chosen KPIs from among frequently accepted performance measures (Yun et al., 2016). Following KPIs, Shohet (2006) defined phase-specific performance measures during the operations and maintenance activities, which are divided into four categories: (1) asset development metrics such as built area, asset occupancy, and asset age; (2) organization and management metrics such as the number of employees per built area, scope of facility management outsourcing, management span of control, and maintenance organizational structure; (3) performance management metrics such as a building performance indicator used to assess the overall state of building portfolio aligned with the performance of its systems and components; and (4) maintenance efficiency metrics such as annual maintenance expenditure, a maintenance efficiency indicator used to examine the investment associated with the performance of facilities. Performance frameworks of projects are still being developed to support better assessment procedures. Continuing efforts to compile a comprehensive compendium of performance models, such as the International Council for Building (CIB) Performance, are included in building and facility performance frameworks (O’Sullivan et al., 2004). The practice of quantifying the efficiency and effectiveness of action through different frameworks is known as performance measurement (Neely et al., 1995). All of the frameworks used in projects have performance objectives/criteria linked to efficiency; however, they generally lack quantifiable indicators related to priority and performance levels that can be used to specify and track project performance. Moreover, work on creating performance metrics that are meant to explicitly describe the performance objectives for “a project using quantitative criteria in a dynamic, organized style is also required in this area (O’Sullivan et al., 2004). Therefore, a comprehensive project performance framework emphasizing the level of performance as well as the level of performance priority in different types of projects is developed for adoption across the project life cycle in various environments and cultures to further improve project performance success (see Figure 2.2).

5. CONCLUSIONS A project is always unique and measuring the performance of each project is critical for project stakeholders. So, to monitor project performance, various measures and metrics have been discussed in the literature but still there is limited research on developing a comprehensive framework of project performance that can be adopted across the industries. Therefore, this chapter proposes a comprehensive framework encompassing different measures and metrics based on the extant literature that can help organizations to monitor and enhance the performance of different types of projects in various cultures and environments. The proposed framework places significant emphasis on project objectives, project value, project complexity, customer satisfaction, and stakeholders’ satisfaction, in addition to achieving cost, time, scope, and quality parameters while ensuring project performance success. Furthermore, the project performance dimensions, measures, and metrics highlighted in this

Project performance measures and metrics framework  19

Figure 2.2

Project performance framework

chapter enable the project managers and team members to remain focused on accomplishing strategic, tactical, or operational objectives and goals while measuring the project performance success more effectively and efficiently across the projects. Finally, the developed project performance framework can be adopted, tested, and used pragmatically across various cultures, industries, and sectors to enhance the likelihood of project management and project performance success.

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3. An alternative to traditional project management: using lean OKRs as a model for value creation for software product companies Bart den Haak

INTRODUCTION Project management is, in essence, a way to mitigate risk. It is the temporary endeavor we undertake to create a unique product, service, or result (PMI n.d.). For centuries in human history, this model has been used to achieve significant results, building roads, bridges, and houses, and producing goods like steel, cars, boats, and planes. It has served humanity greatly, and without projects and their management, we wouldn’t have built the world we live in today. Even today we cannot construct or engineer the things we love and need without project management. However, the world is changing rapidly. When we look at contemporary companies today, most don’t produce physical goods anymore. “Software is eating the world”, as Marc Andreessen wrote (Andreessen 2011). The modern world has experienced a digital transformation and, with it, the way that companies operate, advance, and mitigate risk is also changing. Many of the brick-and-mortar bank branches have been replaced by digital platforms and mobile apps. Factory floors have seen a massive change in manufacturing as robotic machinery driven by software has become commonplace. Most modern cars have a million lines of code written into them to autonomously drive on the highway. Airplanes can land automatically with the use of the software. Surgeons can perform surgery from a distance of hundreds of kilometers. Helpdesk support employees are increasingly replaced by advanced artificial intelligence (AI) chatbots. Most of the household appliances produced today contain software that can hook an oven or dishwasher up to Wi-Fi to receive commands from afar. And this is only the beginning. Despite the advancements, many software projects fail because of applying old project management techniques in a highly uncertain context like knowledge work (Hastie 2015). The traditional iron triangle of project management focuses on time, budget, and full scope. It is ignoring two critical factors: value and quality (and opportunity, if we consider agile). Yet hundreds of companies today still use traditional project management to deliver software. I argue that this is the reason why projects in software fail, because project management focuses on output, is solution based, and is resistant to uncertainty. This is an issue because often digital undertakings operate within what is unpredictable, volatile, and outside the parameters of what can be controlled. In my practice, I have worked with hundreds of companies, some with up to 35 teams. Based on my field research and observations, software development requires a different approach to project management. In this chapter, I will discuss the fallacy of traditional project management when applied to software companies, the difference between outcomes and output, how outcomes and products work hand in hand, distilling a value creation model 23

24  Research handbook on project performance (VCM) from a company’s vision, using the framework of lean objectives and key results (OKRs) as a foundation for software product companies to experiment, innovate, and learn using measurable outcomes. This latter component forms the alternate approach that software product companies can use as a road map to achieving their desired outcomes, and how they can deliver significant business value predictably while mitigating risk in highly uncertain environments. All of this without project management.

PROJECTS ARE TAYLORISM When you have an environment where most variables can be controlled, modern project management frameworks like PMBOK and PRINCE2 work really well (ignoring the fact that most projects are not using these frameworks, but just ad hoc or use custom frameworks). The market share of PMBOX is 27% and PRINCE2 is as low as 11% (PWC 2007). When we apply these frameworks to software development, the result is that most of these projects fail (Bagsall 2019). It is simply ineffective to apply a manufacturing process to software projects by breaking down the development of products and features into specialized repetitive tasks, which is also known as Taylorism. More importantly, it is ineffective to put highly educated software engineers into a production line setup and ask them to deliver their work within scope, time, and budget. As I will discuss in the next section, it is a model based on false beliefs. That is also why agile project management techniques emerged in the 1980s but did not get any traction at that time. They only gained attention after the Agile Software Development Manifesto was written in 2001. Agile is a set of values and guiding principles, but not a framework or method. There are very popular agile work management frameworks such as Scrum and Kanban but only a couple of real agile software development frameworks such as Extreme Programming (XP) or EVO. Many people believe that “doing Scrum” equals to “being agile”. As a result, you see a lot of success theater in companies that claim to be agile by merely implementing a work management system such as Scrum. None of the aforementioned agile frameworks are agile project frameworks. Dynamic Systems Development Method (DSDM) (Messenger 2014) is an agile method that focuses on the full project life cycle, which is one of the frameworks that has died in popularity. Today we see the rise of agile scaling frameworks such as LeSS, SAFe, DAD, Nexus, and more (Uludağ et al. 2021). These frameworks receive a lot of criticism from a variety of agile gurus in the field, who claim these aren’t real agile frameworks but just project management frameworks in disguise, inheriting all the problems described above. They try to help companies overcome the number one problem we face in this industry: uncertainty. However, this is impossible in software development. Therefore, many of these “large-scale agile frameworks” are drowning in governance to “control” risk. Let’s look at why project management is a big problem in software development.

THE FALSE BELIEFS OF TRADITIONAL PROJECT MANAGEMENT To define “false beliefs”, I refer to Project Myopia: “The belief that the project model is the only way of managing business change and development. Not seeing digital development

An alternative to traditional project management  25 as a continuing commitment to growing the business, but instead believing it will end and working towards that end” (Kelly 2020). Managers believe projects will help them answer the question “When will it be done?” Financial professionals like working with projects because it simplifies budgeting and forecasting. Project management is output based. However, what we have learned from decades of working with modern software companies is that their work is fundamentally ambiguous, unpredictable, and sometimes even chaotic. Projects often run past their due date, which makes stakeholders unhappy and creates a risk of running over budget. A project that was planned carefully months in advance can still result in disaster. The project model works great when building an airplane or a bridge, but with software development, on the other hand, it’s different. I offer three important reasons why the project model isn’t a perfect fit for software development. First of all, software development is never “done”. Once it serves users, it has produced value for them; for example, automation of repetitive tasks, producing search results, serving customized content, faster time to market, increasing customer base, improved customer satisfaction, and improved revenue. If a software system is up and running (also referred to as “in production”), a team of engineers needs to maintain it, otherwise it will degrade. They will also add new features to provide even more value to the users of that system. Software is only “done” when the company is out of business (Blockbuster, AltaVista, MySpace, Netscape). Secondly, software development is knowledge work. To use a hypothetical scenario, a company is two days into their project. Even at this early stage, knowledge is increasing and new insights about customer behavior are being generated. This can result in a small pivot of the initial plan. Two weeks later and priorities are already completely different. It is not as if planning skills are lacking; it’s simply that there is second-order ignorance of the problem in question that needs to be solved. In essence, we don’t know what we don’t know. Ask any software developer to name a large project and the total time it required their team to complete it. Then ask how long it will take them if they have to do it today. Likely the answer will be that the time they would need would be half the project size to one-tenth of the original project size. When we look at software projects, many managers believe that the speed of developing features is the constraint that needs to be managed. I argue that that’s not the point, and instead it is the speed of knowledge that is the constraint. If we apply Eli Goldratt’s theory of constraints (Goldratt 1984) to this problem, it becomes clear that one doesn’t need to manage projects; one needs to manage knowledge. Knowledge is the constraint of any IT endeavor and as a manager you want to find ways to elevate it. Knowledge will result in decisions that then are codified into source code and shipped to customers to solve their problems. Thirdly, the most important point is that developing software is not about results (the output). We don’t develop software for the sake of developing software features. However, most IT projects are only about “producing” outputs, as if working in a manufacturing plant. Half of the features (Bosch 2019, i) will not be used by customers and, even worse, most software systems will never be used at all. I’ve personally written software systems because people believed they were required, but in the end they never saw the light of day. And that is why software is never about the output, or the number of features one produces. Instead, it is about the outcomes. What do people do with it? The following questions could be posed to help gain a better understanding: Did the software actually save people time when booking an appointment with your system? Did it make their lives easier? Is the software being sold? These three questions outline why projects and their management are ineffective when developing software. So if projects are incompatible with software systems, then what is

26  Research handbook on project performance a suitable alternative that has the capacity to also measure performance? The first important distinction that needs to be made to resolve this issue is to discuss the difference between outcomes and output.

OUTCOMES OVER OUTPUT One of the problems with projects is that they decouple delivery from value. There is a tendency to fall back on what is known and predictable. For projects, that is to measure their outputs. The more output a team delivers within scope and budget with the given resources, the greater the perceived success of a software project to its company. An output is an amount of something produced by a person, team, machine, factory, country, and so on; for example, the number of product features delivered or the launch of an e-mail campaign. In his landmark book Outcomes over Output, author Joshua Seiden made it clear that the software industry shouldn’t focus on outputs, but rather on outcomes. He defines an outcome as “a change in human behavior that drives business results” (Seiden 2019). This definition can be applied to both internal and external stakeholders. For example, “Improved usability of complicated features” is an output, which may result in an outcome such as “Fewer people calling tech support”. In the end, the outcome could contribute to a reduction in costs (which we can also call the impact). Notice that I use the words “may” and “could” explicitly when describing the relationships between output, outcome, and impact because we are hypothesizing about the cause-and-effect relationship here. Maybe an improvement in usability won’t lead to a decrease in people calling the tech support desk, but it could have another effect elsewhere.

PRODUCTS AND OUTCOMES When products can be specified in the smallest details, project management indeed might be a good choice. Cause and effect are clear. When you build a house, you first need to build the foundation, then the walls, then the roof. It’s a highly predictable project, with clear milestones and deliverables. We can measure the progress and performance of building a house by simply counting how many milestones have been achieved before a given date. With digital products, it’s a different story. In digital environments, when the goal is to, say, improve the retention rate of a mobile app, the solution to the problem is unknown. Learning and acquiring the knowledge to understand the unique context, domain, and complex environment are required before developing products or features that could affect the retention rate of said mobile app to a noticeable degree. This is because of a complex adaptive system (CAS) whereby there is a presumption about the solution to a problem that is not necessarily based on facts but rather other external factors. In my experience, I have worked with a number of companies that have been struggling with disastrous projects in IT that were heavily biased. All of the eggs are put in one basket, so to speak, of a temporary project put in motion with the good intention of propelling a business forward. I have come to view projects as being high-risk even when output seems to be improving. Alas, output, and not outcomes.

An alternative to traditional project management  27 The speed of learning within a unique context determines the speed of delivery. It also happens to be the leading constraint of every product development endeavor undertaken. Learning is what prepares individuals for what to do and what not to do in the future. The conventional wisdom that the majority of large software companies has been practicing, reinforced by the use of project management methods, is to view complex, niche-knowledge work as if it is predictable. Unfortunately, optionality is thus inhibited and learning delayed to a point where there is the least time to respond and highest expenditure (Smart 2020). When operating under a project focused on output, products are rarely finished. They usually reach an endpoint when the company goes bankrupt or the product is no longer used. When developing products, the use of measurable outcomes describes the result of actions taken and behaviors. In product development, how customers use, speak about, or act with a product can be described by observing their behavior. What will people do with the product, what they say about it, and what problem it solves for them is the key paradigm shift for many modern product companies. What job needs to be done (Christensen et al. 2016) and how can the company solve that problem in the most effective way? This is lean thinking. For example, let’s presume a hypothetical situation where I find myself bored in the evenings and weekends. I want access to entertainment, in this case to a large volume of television series and movies. Netflix has solved that problem for me and has continually improved its content and services. They have even recently added games to the platform. The outcome for Netflix might be the number of engaged users who will watch four hours of content each week. If the company wants to make more money, it should increase the number of users on its platform, but therefore needs to provide appealing content. There is no project in the world that could generate this exact outcome, yet a VCM very much can. Often, our work is described in terms of detailed plans rather than outcomes; however, no matter how detailed a product development plan is, it can fail because of all the uncertainty and risk involved. Outcomes are inherently unpredictable, which is the biggest reason we cannot plan a project for them as influencing outcomes depends on human behavior, knowledge, and actions. These factors fall outside the parameters of project management. They are, however, components of a VCM. When working with software, we are building products. Product management is a different discipline than project management. A product is never finished. It doesn’t have a finite construct of fixed outputs and fixed time frames. So what can be used to measure and monitor its progress? How can leaders manage a company and its teams in such a way that they achieve (significant) results that matter to the company’s vision and strategy? The answer to this question is to look at the business outcomes of a company, starting at the highest level and long-term outcome, all the way down to product and operational teams.

FROM COMPANY VISION TO A VALUE-DRIVEN PORTFOLIO The alternative to projects is to align activities to measurable outcomes, starting from the company’s executive vision all the way through to concrete actions for product or engineering teams. Distilling a company’s vision into actions isn’t something novel. If the vision was to go to the moon and back, that vision would be broken down into the rockets, moon landers, and engines that would be required. Each of these would be isolated until the manufacturing of the

28  Research handbook on project performance specific nuts and bolts that would go into the engines would be considered and developed. We landed on the moon in 1969 as a result of this way of thinking. There are several strategy deployment frameworks that operate in a similar fashion. Hoshin Kanri (Marksberry 2011), Salesforces’ V2MOM framework (Benioff 2020), OSGM (Pepper 2007), and OKRs (den Haak 2021) are some popular examples. It is important to mention that none of these frameworks are project management models. There are a variety of articles (Cunha and Ribeiro 2022; Chen et al. 2022; Ferreira et al. 2017) that do indeed recommend using OKRs for performance management as well as running projects and I strongly discourage this. In my practice, although there are no firm and fast rules for how to use OKRs, they haven’t been an effective tool for individual performance management and project management. OKRs represent a goal-setting framework for teams and companies to define measurable goals and track their outcomes. In my work, I have developed an approach to OKRs that streamlines it and makes it a suitable candidate that can be used to execute an ambitious company vision without the need for project management. Lean OKRs are the evolved version of the OKR strategy execution tool that incorporates lean thinking into the mix. Lean thinking is lean because “it provides a way to do more and more with less and less – less human effort, less equipment, less time, and less space – while coming closer and closer to providing customer with exactly what they want” (Womack and Jones 2003, 15). As opposed to agile discussed above, where teams emphasize small batch sizes to deliver quickly, lean teams increase speed by managing flow (usually by limiting work-in-process). Lean meets the needed value requirements of customers with fewer resources and less waste. It’s a philosophy based on continuous experimentation to achieve optimal value with optimal efficiency. This, in combination with OKRs, it becomes a powerful tool to execute an ambitious company vision without the need for project management. When a company starts working with lean OKRs, the first important step is to distill the company’s vision into a single objective with a set of corresponding key results that are essentially measurable outcomes. Leaders in collaboration with their teams design an objective that will deliver on that single, overarching objective. This team-level objective will have its own set of key results, defined by the team. When working with lean OKRs, there is a strong emphasis on collaboration between leaders and teams to formulate their OKRs that will affect the company’s vision OKR in their own way. In my experience, this practice requires a shift in behavior from all levels within a company, one where trust, autonomy, experimentation, learning, and accountability are fostered and, over time, the norm. Software product companies are often already aligned to embrace uncertainty and the risky nature of product development. This is in large contrast to project management where the emphasis lies on completing the project within a specific time frame and budget, according to outlined specifications and a set schedule. In product development, proposed solutions and the customer’s responses are unknowns. With a project management model, managing and mitigating risk is often reactionary. The solution I propose is threefold: (1) Embrace uncertainty in an environment that favors learning (2) Unlearn traditional company structures and management practices (3) Distill the vision into a “value creation model” (using the lean OKRs framework as inspiration).

An alternative to traditional project management  29 First, acknowledging unknowns can be a scary thought for most people, and is exacerbated when there are unknown unknowns, referred to earlier as second-order ignorance. It is this blind spot that is the biggest problem in software product development. How can unknown unknowns be discovered in order to mitigate risk? Agile methods are a great way to mitigate risk in a highly uncertain environment. Much has been written (Vieira et al. 2020) about this topic but it is outside the scope of this book. If you would like to read more about this subject, then I highly recommend Doing Agile Right (Rigby et al. 2020). Secondly, unlearning traditional company structures is no small feat. Software companies that are structured by function (marketing, sales, engineering, quality assurance, user experience, research) or by a typical matrix (where teams report to multiple leaders, for example) should question if the current structure is the right model to deliver upon their corporate goals. Traditionally, departments or functions (marketing goals, sales goals, etc.) have set their own goal(s) in isolation from other departments, thus creating a silo effect. Modern product companies have generally organized themselves based on value creation or value streams and set goals accordingly (Skelton et al. 2019). For example, they might group people into product lines rather than having generic engineering or IT departments taking orders from random stakeholders. A bank might have teams working together on consumer mortgages, payments products, or customer loan products. Leaders can set team-based objectives that follow the company’s hierarchy. Calling traditional company structures into question will not only highlight inefficiencies or ineffectiveness but also allow management to allocate capacity to product outcomes, rather than allocating teams to projects and output. Thirdly, executive teams need to distill the company’s long-term vision into ideally one, but perhaps two or three, high-level company goals (see Figure 3.1), informed by the company’s corporate strategy, with a life span of about one to three years into the future. Less is more here. In my experience, it’s hard for leaders to create this level of focus because everything seems high priority. However, the stronger the strategy, the easier it is to define one or two really important goals that will propel the company forward; for example, “Customers choose us over competitor X” or “Grow five-day active customers exponentially”. Notice that these are strategic goals. I’ve excluded the basic overhead goals, the keep-the-lights-on activities, since they should be planned by teams themselves. Executive teams own the vision and a portfolio of company-level goals. Once the company-level goals are defined, a portfolio of “bets” per company goal can be created. The term “bet” is similar to the concept of a casino, where you will have losses and wins. Similar to the stock market where portfolios are diversified to reduce risk, the company goals need to be distilled into multiple bets to diversify. These bets are created by a special team called the “bet team” (Highsmith et al. 2019). This team consists of senior managers from multiple disciplines (for example, vice president of sales, vice president of products, vice president of engineering, vice president of support). Their responsibility is to define a small portfolio of bets in the form of outcome-based goals that will have a high probability of making an impact on the company goals (see Figure 3.3). The life span of these outcome-based bets is less than 12 months. All bets are then distilled into a portfolio of initiatives by an “initiative team” (Highsmith et al. 2019). These initiatives have a life span of three to four months, which makes them long term enough to achieve something significant with one or multiple teams, but small enough to not take on too much risk. Each initiative is assigned to one or multiple cross-functional

30  Research handbook on project performance product teams. The idea is that these product teams will (in)validate these hypotheses as soon as possible with a series of small experiments. To illustrate, the vision, company goals, bets, and initiatives form a model-like structure (see Figure 3.1), which I refer to as the VCM. Each node in the model illustrates a hypothesis, which needs to be proven by completing their underlying sub-nodes. Ideally, for each element in this model, the use of the lean OKR approach can help significantly to define radical focus on one or two company objectives. However, it has to be kept in mind that all models are only approximations, this one included. It is a simplified version of reality because cause and effect are now linearly defined, whereas in reality they are often interconnected and even circular. What I have come to learn through working with many software product companies is that while they have used this as their starting point, over time they have adjusted the model to suit their unique needs and requirements.

Figure 3.1

Vision is distilled into goals, bets, and initiatives in a value creation model (VCM)

Let’s zoom in on company goals, bets, and initiatives a bit closer, in order to understand how they can be managed and measured and achieve significant results. Company-Level Goal(s) (One to Three Years) Modern software product companies work differently because they are often already in tune to the fact that there is no perfect knowledge regarding their customers, external environment, geopolitical landscape, and possible disasters. If managers try to incorporate all these factors into their decision-making and define projects, this will be a slow, complicated, and cumbersome process. Instead, the leaders of modern product companies embrace uncertainty and distill their corporate vision into goals that are expressed in terms of desired outcomes.

An alternative to traditional project management  31 These goals do not describe solutions, but rather describe customer outcomes that will enable the company to achieve its vision. For example, “Boost the customer lifetime value (CLTV) of large and SME customers” or “Customers promote Acme Model X to their friends”. These goals, informed by the corporate business strategy, are stable for one to three years into the future. Each of these company-level goals has a description, potential challenges and opportunities, constraints, and clear measures of success, ideally focused on customer outcomes, rather than the traditional return on investment (ROI) metrics. Many companies have adopted lean OKRs to describe these outcome-based goals, which I will explore in the next section of this chapter. Bets (< 12 Months) As discussed earlier, when generating an impact on these outcome-based goals (objectives), modern companies develop a portfolio of bets. Each bet is a hypothesis that will have an effect on the company goal. To establish a mutually exclusive, collectively exhaustive (MECE) bet, they can be illustrated visually as aligning under each goal in the VCM. Visually representing the value creation of outcomes, with possible bets, acts as a communication tool to the rest of the company, which increases business value creation understanding throughout the company. With an overview of bets, leaders can now invest in these bets, decide to replace them, or extend investment in them. Instead of having managers for every function or department in a company, defining a goal team per company goal in the VCM who would be responsible for creating bets is a viable alternative (see Figure 3.2). These teams are chartered with engineering, operations, and product (optionally with sales and marketing) senior members. This is not intended to be a full-time role for any of the members. Initiatives (Three to Four Months) To prove that a bet works, there needs to be a portfolio of initiatives. The portfolio is created by the bet team. Each initiative consists of a series of smaller hypotheses that have a clear measure of success. Initiatives are not the same as projects. Initiatives have a running backlog of hypotheses that are continuously reprioritized. Completion is defined as achieving the desired outcomes, rather than by completing all the activities in the plan. Initiatives are often quarterly and you can only have one of them running per quarter, per product line to remain focused. A bet team is responsible for creating new initiatives in collaboration with product teams (see Figure 3.3). When a company is small, the bet layer of the VCM is removed and initiative teams are connected straight to company objectives, making the goal team responsible for the creation of initiative portfolios.

32  Research handbook on project performance

Figure 3.2

Goal team and their portfolio responsibilities

 

Portfolio Funnel The nodes inside the VCM are consistent over time. They probably won’t change much from week to week. However, that doesn’t mean everything is set in stone for eternity. If companies want to stay relevant, innovate, and respond to changing market conditions, they need to be flexible. Therefore, the nodes in the VCM will be evaluated on a regular basis. In the next section, we will explore the lightweight governance model of lean OKRs to adjust and achieve the outcomes we envision. To evolve the VCM, one can add new nodes to it. New company goals are removed and added by the executive team; new bets by the bet team, and new initiatives by the initiative team. Every team will have a backlog of candidate ideas, which make up a portfolio funnel. In Figure 3.3, you will see a backlog from a bet team. If the bet team wants to modify the VCM, they need to align that with the executive team. They then review it and finally add or replace an existing bet. Bets can then be allocated with new capacity and/or budget. This process is similar to initiatives.

An alternative to traditional project management  33

Figure 3.3  

Bet portfolio backlog as an idea bank to add to a slot in the VCM

LEAN OKRS

One of the most popular tools for digital companies is the use of OKRs. As described earlier, every node in the VCM (Figure 3.1) should be described in terms of outcomes. A VCM lends itself very well to OKRs because objectives are inherently ambitious goals and key results are inherently measurable outcomes. OKRs have been around for about 20 years. An objective is a memorable, short, qualitative, and aspirational description of what you want to achieve. It should not describe the business-as-usual activities that are required to keep the business afloat. In fact, a well-written objective should be based on the company’s vision for the future, thus is ambitious and challenging. Key results are the measurable outcomes that indicate whether an objective has been achieved. Rather than describing what needs to be done, they describe the indicators of success in a way that is quantitative. Lean OKRs are a response to an unfortunate global trend to create an excess inventory of OKRs throughout a company whereby numerous goals are rewritten as objectives and the inspirational nature of OKRs is watered down. Lean OKRs are about setting fewer but more meaningful goals. It is based on a single OKR at the company level based on the company’s vision and strategy, and where the other levels within a company work in an aligned fashion with their own OKRs to generate an impact on the company’s objective. This focus means making tough choices but brings the transformative potential of OKRs to full fruition by boosting transparency, experimentation, and alignment in a company. Setting lean OKRs should be a collaborative process between teams and their leaders. They require leaders to describe desired outcomes and then pass the complex problems that arise to be solved by equipped and engaged teams. Leaders should provide challenges for teams to solve, rather than dictate which solutions to implement or what features to build. OKRs can

34  Research handbook on project performance only be effective if leadership is dedicated to empowering their skilled and knowledgeable employees. OKRs drive change in human behavior. That behavior change could perhaps be reflected in customers but also stakeholders, suppliers, board members, managers, and employees. In his book Outcomes over Output, Seiden (2019) defined an outcome as a change in human behavior that drives business results; for example, customers that promote your product to others because you have automated their boring manual tasks. Another example would be higher product quality because software engineers started to use automated tests to prevent product defects. To see this change in human behavior, observing and measuring current habits and behavior is necessary. When working toward an objective, teams will find that they have to run small, targeted experiments to change employee or customer behavior. For those teams, it is of the utmost importance that there is an environment of experimentation, learning, and autonomy. In my extensive experience as a corporate consultant, I have found that integrating OKRs with effective leadership strategies based on Lean principles is the most powerful approach for achieving goals. Lean OKRs are designed as a comprehensive method that is spear-pointed toward company-wide alignment on a single, overarching objective that is easy to understand and aspirational in nature, often referred to as a stretch goal or moonshot. The following is an example of an OKR template and also an example of a well-formulated objective with corresponding key results. OKRs are written in a simple format: Objective: [What you want to achieve] KRs: • Key result 1 • Key result 2   An example of a good OKR: Objective: Customers choose us over [competitor] KRs: • Increase the percentage of customers that prefer our product to the competitor’s in a blind test from 30 to 75 percent. • Increase the average order rating from 3.1 to 5.0. The three key ingredients of lean OKRs are a single, ambitious objective, key results, and the OKR cycle. This last one isn’t as obvious, but without it OKRs are a worthless tool, as systematically checking in on the OKRs set is a practice that creates the behavioral habit, accountability, and responsibility required to see continuous change and improvement over time. The lean OKR cycle, when applied to a VCM, can ensure that the goals, bets, and initiatives that have been set are not cast aside and abandoned, but rather are revisited quarterly, monthly, and weekly.

An alternative to traditional project management  35

LEAN OKR CYCLE: A LIGHTWEIGHT GOVERNANCE MODEL Implementing a lightweight governance model to periodically review outcomes is vital. In the lean OKR model, we call this the OKR cycle. To reduce risk, it helps to receive fast feedback, so leaders are able to evaluate and correct the course before it is too late. To apply the lean OKR cycle to VCM, every node in the VCM has different review cycles, but in general company goals are reviewed quarterly, bets monthly, and initiatives weekly. Check-ins, therefore, must be regular and predictable so that goals will not be set and forgotten, but rather reviewed and adjusted on a recurring basis. The OKR cycle (Figure 3.4) is the system for achieving your OKRs, and while there are variants available, in its basic form it looks like Deming’s circle: the Plan–Do–Check–Adjust (PDCA) cycle (Tague 2005). The notable variations range from as few as three steps to as many as eight. The PDCA cycle, however, is a form of scientific problem-solving and an important tool in lean that is often used to implement change or improvement initiatives. It is also the version of the cycle I’ve found the most useful for companies to start out with. The OKR cycle is the starting point for many companies but it is important to note that a company can absolutely adjust the cycle to suit its needs and culture; for example, by combining the setting and alignment phases, extending or truncating the monthly cycles, or adding a pre-aligning or planning step before the goal-setting workshop.

Figure 3.4 The lean OKR cycle that can also be applied to the VCM The cycle has five phases that repeat every 90 days for quarterly goals: (1) Setting phase: where you develop new OKRs (in a VCM, these would be goals with corresponding bets and initiatives) during a goal-setting workshop

36  Research handbook on project performance (2) Alignment phase: during the alignment workshops, goals are aligned with other teams, managers, and leadership (3) Kick-off phase: announcing and making goals, bets, and initiatives transparent to the rest of the company (4) Execution phase: performing weekly check-ins, tracking status, and making commitments. It is in this phase that leaders and teams continuously discover, learn, and experiment with what actions to take that affect behavior and generate the desired outcomes (5) Review phase: reflecting on the goals and the process as a whole to define actions for improvement The rhythm for other nodes in the model (company goals and bets) can be reviewed monthly, quarterly, trimester, or semesterly. Which rhythm is best depends on the size of the company, the company culture, and the business domain. For initiatives, the advice is to start with 90 days and adjust if necessary.

VCM AMBASSADOR TEAM When working with the VCM, teams are cross-disciplinary and grouped from different departments or functions to work together in creating desired outcomes for a specific initiative. Implementing an additional team, the VCM ambassador team, which would replace the Project or Portfolio Management Office (PMO), is a new concept that I propose for this model as it could significantly assist with the change management demands placed on employees with this undertaking. The team is usually small and consists of coaches, business analysts, and facilitators. They are key to the success of digital transformations and especially the transformation of this new and modern approach of working as a software product company. They oversee the transformation, creation, and adjustment of the VCM and support the company by offering to coach and mentor on demand. They are consultative and facilitative. This team focuses on the delivery of value within the company. They can help with investment allocation on bets and initiatives, as well as the implementation of the cycle.

CONCLUSION In this chapter, I have proposed a VCM that uses the lean OKR cycle as a viable alternative to traditional project management. This unique combination caters specifically to the natural strengths of a software product company of being already aligned to the unpredictability of outcomes, an environment that embraces experimentation and learning, and the flexibility to pivot based on customer and employee behavior feedback. The temporary nature of project management is instead replaced with the longevity of continuously evolving products with cross-disciplinary product teams. The introduction of goals, bets, and initiatives sets a software company up to be able to work toward a clearly defined goal that is in line with the company vision and being open to the results of outcomes rather than being bound by the rigidity of the project management model that favors output delivered on time and on budget. The future of software product companies will surely evolve faster than the speed of light in the coming years. Those companies require a model that allows them to build on their knowl-

An alternative to traditional project management  37 edge, testing hypotheses and rolling out features that deliver value to their customers, likely anticipating customer wants and needs. In this version of the future, project management is better suited to other facets of life such as city infrastructure or manufacturing. Using the lean OKR framework to support the VCM means that efficiency and providing consistent value for customers goes hand in hand for the long haul.

REFERENCES Andreessen, Marc. 2011. Why Software Is Eating the World. https://​a16z​.com/​2011/​08/​20/​why​-software​ -is​-eating​-the​-world. Accessed April 30, 2022. Basgall, Joel. 2019. Doomed from the Start. Geneca. January 25, 2017. https://​www​.geneca​.com/​ download​-the​-doomed​-report. Accessed April 30, 2022. Benioff, Marc. 2020. Create Strategic Company Alignment with a V2MOM. Salesforce.com. https://​ www​.salesforce​.com/​blog/​how​-to​-create​-alignment​-within​-your​-company. Accessed April 30, 2022. Bosch, Jan. 2019. Using Data to Build Better Products: A Hands-On Guide to Working with Data in R&D – The Basics. CreateSpace Independent Publishing Platform. Chen, Deyu, Chen, Jiaying and Ning, Minjuan, 2022, April. Research on Enterprise Performance Management from the Perspective of OKR. In 2022 International Conference on County Economic Development, Rural Revitalization and Social Sciences (ICCRS 2022) (pp. 91–95). Atlantis Press. Christensen, C.M., Hall, T., Dillon, K., and Dunca, D.S. 2016. Know Your Customers’ “Jobs to Be Done.” Harvard Business Review Press. Cunha, Pedro and Pedro, Ribeiro. 2022. Definition of a Technique for Characterizing the Expected Benefits of a Project. Procedia Computer Science, 196 (2022), 1007–1012. Den Haak, Bart. 2021. Moving the Needle with Lean OKRs. Business Expert Press. Ferreira, Luis Gustavo Araujo, Viegas, Priscila Bibiana, and Trento, Dagoberto, 2017, September. An Agile Approach Applied in Enterprise Project Management Office. In Brazilian Workshop on Agile Methods (pp. 95–102). Springer. Goldratt, Eliyahu M. 1984. The Goal: A Process of Ongoing. North River Press, 3rd edition (June 1, 2012). Hastie, Shane. 2015. Standish Group 2015 Chaos Report – Q&A with Jennifer Lynch. InfoQ. October 4, 2015. https://​www​.infoq​.com/​articles/​standish​-chaos​-2015. Accessed April 30, 2022. Highsmith, Jim, Luu, Linda, and Robinson, David. 2019. EDGE: Value-Driven Digital Transformation. Addison-Wesley Professional, 1st edition (September 26, 2019). Kelly, Allan. 2020. Project Myopia. LeanPub. Marksberry, Phillip W. 2011. The Theory behind Hoshin: A Quantitative Investigation of Toyota’s Strategic Planning Process. International Journal of Business Innovation and Research, 5(3), 347–370. Messenger, Steve. 2014. Agile Business. https://​www​.agilebusiness​.org/​page/​TheDSDMA​gileProjec​ tFramework. Accessed April 30, 2022. Pepper, John. 2007. What Really Matters: Service, Leadership, People and Values. Yale University Press. PWC. 2007. Insights and Trends: Current Programme and Project Management Practices. PricewaterhouseCoopers. https://​www​.pwc​.com/​cl/​es/​publicaciones/​assets/​insighttrends​.pdf. Accessed April 30, 2022. Rigby, Darrell, Elk, Sarah, and Berez, Steven H. 2020. Doing Agile Right. Harvard Business Review Press. Seiden, Joshua. 2019. Outcomes over Output: Why Customer Behavior Is the Key Metric for Business Success. Independently published. Skelton, Matthew, Pais, Manuel, and Malan, Ruth. 2019. Team Topologies: Organizing Business and Technology Teams for Fast Flow. IT Revolution Press. Smart, Johnathan. 2020. Sooner Safer Happier: Antipatterns and Patterns for Business Agility. IT Revolution Press. 

38  Research handbook on project performance Tague, Natasha R. 2005. Plan–Do–Study–Act Cycle. The Quality Toolbox. ASQ Quality Press, 2nd edition. Uludağ, Ömer, Putta, Abheeshta, Paasivaara, Maria, and Matthes, Florian. 2021. Evolution of the Agile Scaling Frameworks. In: Gregory, P., Lassenius, C., Wang, X., and Kruchten, P. (eds) Agile Processes in Software Engineering and Extreme Programming. XP 2021. Lecture Notes in Business Information Processing, vol. 419. Springer. https://​doi​.org/​10​.1007/​978–3​-030–78098–2​_8 Vieira, Marcel, Hauck, Jean Carlo Rossa, and Matalonga, Santiago. 2020. How Explicit Risk Management Is Being Integrated into Agile Methods: Results from a Systematic Literature Mapping. 19th Brazilian Symposium on Software Quality. “What Is Project Management?” PMI. n.d. https://​www​.pmi​.org/​about/​learn​-about​-pmi/​what​-is​-project​ -management. Accessed April 30, 2022. Womack, James P. and Jones, Daniel T. 2003. Lean Thinking: Banish Waste and Create Wealth in Your Corporation. Simon and Schuster.

4. Modeling relationships of projects and operations: toward a dynamic framework of performance Pierre A. Daniel

1.

FROM PROJECT OUTPUTS TO OPERATIONAL OUTCOMES

The projectification of society (Jensen et al., 2016; Lundin et al., 2015; Schoper et al., 2018) or of organizations (Midler, 2019)—that is, the diffusion of projects as a form of organizing—requires the project management domain to adopt new theoretical and practical scopes. Projectification amplifies the negative impacts of projects that fail because of their lack of alignment with strategic objectives (Apm, 2015; KPMG, 2010; Project Management Institute, 2014; The Standish Group International, 2015). Debates surrounding sustainable development topics also challenge the fundamental practices and theoretical foundations of project management (Huemann and Silvius, 2017; Keeys and Huemann, 2017; Kivilä et al., 2017; Moehler et al., 2018; Sabini et al., 2019). In particular, reconsiderations of the scope of project management suggest the need to extend the time horizon beyond traditional activities associated with the development phase that lead to outputs (buildings, engineering structures, information systems) and into operational phases, which produce value and contribute to the achievement of outcomes and benefits. Similar theoretical shifts appear in the field of megaprojects (Alderman et al., 2014). The debates about project performance, or its lack, as well as effective measurements (Prakash Prabhakar, 2008; Yu et al., 2005), tend to revolve around two complementary but contradictory perspectives: one centered on the ability to deliver outputs while respecting a triple constraint (cost, time, and quality) and another that prioritizes the benefits to which outputs contribute (Cooke-Davies, 2002; Ika, 2009; Serra and Kunc, 2015; Serrador and Turner, 2015). Classic performance models include project outputs and cost, time, and quality criteria, but they neglect more subjective criteria such as long-term goals or societal impacts (Haass and Guzman, 2020; Ika et al., 2012; Ngacho and Das, 2014). Performance models based in the project benefits stream of research generally link outputs, outcomes, benefits, and visions (Breese, 2012), but the underlying theory ignores the mechanisms by which these relationships operate. Nor are the dynamics that govern interactions across key notions of performance and the transformation of outputs into outcomes well understood (Zwikael and Smyrk, 2012). We leverage the theory of complex systems to propose a theoretical model of the operational dynamics between outputs and outcomes. Concepts of complexity and uncertainty are central to this aspect of systems theory, as applied to projects (Daniel and Daniel, 2018; Geraldi et al., 2011; Padalkar and Gopinath, 2016; Williams, 1999), so we use them to lay the foundations for a systemic project theory that can clarify central concepts for managers. We define operational development as the dynamics of projects interacting with operations to 39

40  Research handbook on project performance develop new operational value chains. We illustrate this approach using the case of a Covid-19 vaccination campaign implemented in December 2020 in France. This case represents the types of complex programs to which our framework aims to make theoretical and practical contributions: (1) it is a megaproject, with impacts on millions of people and costs in excess of 1 billion euros and (2) it entails new functional operations and new strategic outcomes. According to benefits management frameworks, piloting a project using operational outcomes is effective only if the outcomes and benefits are not distant from the project (Williams et al., 2020), as is the case for the vaccination program, which aims for operational and strategic objectives that can be measured at very short deadlines.

2.

A MULTI-LEVEL FRAMEWORK OF PROJECT PERFORMANCE BASED ON PROJECTS, OPERATIONS, AND OUTCOMES

2.1

Project Outcomes Are Results of Value Chain Operations

The field of operational strategy establishes a direct relationship between an organization’s projects and the strategic objectives that it seeks for its future. Projects can be described as strategic initiatives, aligned with short- and medium-term goals according to a balanced scorecard (Kaplan and Norton, 2008). For the strategic management of organizations, projects and their strategic objectives must be set in advance, in the preliminary phases, to ensure the organization can achieve them (Shenhar et al., 2001a). Techniques for analyzing the financial profitability of projects, such as the net present value, reflect the status of strategic objectives as benefits drawn from an operational phase of the project (return on investment [ROI] phase), which occurs after a development phase (investment phase). Some studies recommend that project performance management should be based as much on financial ROI (operational exploitation phase) as on the costs of the investment (development phase) (Gardiner and Stewart, 2000). Logical framework analysis techniques go even further in assigning importance to operational and strategic phases, resulting from project execution. They describe projects or programs as multiple operational systems, each with measurable objectives, such that they are organized according to a hierarchy of objectives, which make it possible to determine the intended success of the project product in its operational phase (Baccarini, 1999). Array projects reinforce the idea that large projects (or programs) should be described as “super systems” because they are agglomerations (Shenhar et al., 2001b). Notable examples (e.g., New York City Transit Authority, English Channel Tunnel, the U.S. Strategic Defense Initiative “Star Wars”) actually are organizations that comprise different operational functions, represented as systems. Megaproject research thus delves into array projects and proposes that at high levels of complexity, megaprojects combine dispersed arrays of systems, each with a specific goal but also all sharing a common goal (Davies and Mackenzie, 2014). Figure 4.1 shows that the benefits of the French vaccination campaign are driven by operational systems that are part of the operation phase of the project, a routine phase, which aims to be repeated for at least eight months according to the announcements of government authorities. The vaccination campaign was introduced by the president of the French Republic, who announced a goal of vaccinating all adults who wish to be vaccinated before the end of summer 2021. Each operational system has a specific function (produce, deliver, store, reg-

Modeling relationships of projects and operations  41 ister, vaccinate), related to its target outcome (number of vaccine doses produced, delivered, stored, and injected). Together the operational systems constitute an operational value chain, in which each operation has its own objective (project outcomes), but they all aim at the common objective established by governmental authorities (project benefit).

Figure 4.1

Project benefit and outcomes as value chain of operations

Proposition 1. The outcomes of a project or program, which constitute its operational benefits, can be represented as a value chain of operations, each with a specific function. The value chain highlights new functional systems or those whose functional performance is improved through the implementation of the project or program. 2.2

Operations as Sociotechnical Systems

Ackoff (1971) describes the characteristics of organizations as systems, so an organization is a “purposeful system” that contains at least two “purposeful” elements with a common goal. Each system has a function that causes it to produce an “outcome,” as well as inputs, or the resources it uses to produce the output. Similarly, Emery and Trist (1960) represent operational activities as sociotechnical systems, with functions and objectives, whose functioning can be measured and controlled. Operational management theories with a sociotechnical approach feature the widely used input–process–output (IPO) model, which provides a basis for operational descriptions of different transformation functions in organizations (Chase et al., 2006; Slack et al., 2013). These transformation processes occur in all organizations (private, public, nongovernmental) and in fields as varied as manufacturing, transportation, retailing, warehousing, healthcare, and telecommunications. To function, they use resources (machines, documents, human resources, facilities), which make it possible to convert inputs into desired outputs. These inputs can be raw materials, individuals (customers, patients, consumers), or finished products from another system.

42  Research handbook on project performance Figure 4.2 outlines one operation of the value chain, presented previously as sociotechnical systems. The resources identified are necessary for the functional transformation of each system. Not all resources are described; this representation is limited to those that did not exist at the start of the project and that thus must be developed and delivered. Each operational system’s mission is to achieve a target level of operational performance, as the outcome of the system. This outcome is defined and then assessed regularly during the management cycle, on the basis of the outputs produced by each operation and their performance measurement, using key performance indicators (KPIs). System resources are often described with specifications that indicate operational quality and functionality levels of the resources that ensure the intended outcome is achievable.

Figure 4.2

A sociotechnical systems approach of the operational value chain

Proposition 2. The value chain, made up of operations, is a chain of sociotechnical systems, each with its own operational function, contribution to the strategic performance of the project, outcomes, and new resources necessary for efficient operations. The performance of sociotechnical systems is described and steered by key performance indicators that measure the targeted outcomes and by specifications that clarify the necessary qualities of the new resources required to achieve the outcomes. 2.3

Operational Resources Required for Operations Are Delivered by Projects

Classical operational management theories highlight the fundamental role of project management as an organizational and methodological means to produce new operations that an organization wishes to create, adapt, or improve (Chase et al., 2006). The logical relationship between “temporary” projects and “routine” operations is evident in new product development literature, which explains that experiments are necessary to design new operations and implement them (Thomke, 2001; Thomke and Reinertsen, 1998). In discussing adaptability, Thomke (2001) goes even further, highlighting the importance of modularizing new

Modeling relationships of projects and operations  43 product development to clarify the interdependencies among different product functions. This approach favors a modular architecture for developing complex products, and it entails dividing the product development into a program of experimental subprojects. Some modules are known in advance; others are more innovative and give rise to various adaptations during the development phases. Theories of uncertainty management in projects (management of unknown unknowns) also suggest modularizing complex projects into subprojects, to make it possible to define levels of uncertainty specific to each subproject and therefore management methods adapted to each one (Lenfle, 2011; Lenfle and Loch, 2010). Modular approaches have long been practiced for project management, as promoted by work breakdown structures, product breakdown structures, or even logical framework analysis, in which the architecture of projects reflects a hierarchy of operational objectives. However, the new challenges of modular approaches, especially for complex projects and megaprojects, reflect the need to adapt managerial practices to each project. The many changes that emerge during the development phase of projects demand the most dynamic and scalable management methods possible, within a strategic program of projects (Davies and Mackenzie, 2014). The challenge is to enable the strategic architecture to facilitate coordination among various interests and priorities of stakeholders, across interrelated projects (Maylor et al., 2006; Pellegrinelli, 2011). Figure 4.3 highlights both the systemic relationship between projects in the development phase and operations in the operational phase and the systemic relationship between operational value chain and project benefits and outcomes. The resources in each operational system do not exist in reality as long as the project remains in its early phases. They typically constitute what project management theory would call project outputs (or deliverables). That is, the resources of each operational system correspond with the outputs that the projects must deliver. The model deepens the IPO approach by presenting a systemic, functional relationship that managers and decision makers can describe in operational terms. It also enables the visualization of a project management perspective (PMI, 2013), which consists of delivering project outputs, and a benefits management perspective (Chih and Zwikael, 2015), according to which the project contributes to achieving future operational objectives (outcomes and benefits). Proposition 3. Systemic resources needed for the proper functioning of operational systems result from project development activities. The architecture of the portfolio of projects thus derives from operations in which different strategic and operational issues and interests are represented within functional systems.

44  Research handbook on project performance

Figure 4.3

New operational resources result from development projects

3.

A MODEL OF EMERGENT PERFORMANCE BASED ON PROJECTS AND OPERATIONS INTERACTIONS

3.1

Innovation in Projects Creates Instability in Operations

 

Project management literature acknowledges the dynamics at play during the development phase of projects; projects are contingent and subject to varying levels of uncertainty and complexity (Loch et al., 2006; Sauser et al., 2009; Shenhar and Dvir, 1996). Different management dynamics emerge, according to the levels of uncertainty and complexity (Lenfle and Loch,

Modeling relationships of projects and operations  45 2010; Pich et al., 2002; Sommer and Loch, 2004). At one extreme, project dynamics can be stable, predictable, and controllable because they are well known; at the other, they are unpredictable, subject to many changes, back-and-forth decision-making, and modified outputs and outcomes. Studies of the management of uncertainty highlight two main modes: management of routine or management of innovation. The first version, involving routine planning and control, implies a stable, predictable project phase and an operational process under control. The second, involving uncertainty management, instead requires innovation management mechanisms (Thomke, 2003, 1998). Such classifications of the degrees of uncertainty are well established (Pich et al., 2002), though descriptions of innovation dynamics within systems are insufficient and require better theoretical grounding (Sommer et al., 2009). The operational systems that are the raison d’être of a project are based on resources. The resources are the subject of project development cycles, as well as the outputs of a development phase of the project. Each resource gives rise to a project, the dynamics of which are subject to varying degrees of uncertainty too (Lenfle and Loch, 2010; Loch et al., 2008). In projects that suffer unforeseeable uncertainty, the resources have an emerging nature and are not predictable. Their results may impose a real impact on the construction of the operational system to which they contribute. Thus, the development dynamic of system resources can considerably affect the operational start-up dynamic of the target system. Figure 4.4 highlights the cause-and-effect relationship that may exist between a development phase project and one or more systems in the operational phase. In our illustrative example, the project to develop a new Covid-19 vaccine is subject to extreme uncertainty and innovation efforts. Several hundred vaccine candidates are in development. When the first vaccine (by Pfizer) proved its effectiveness, the detailed specifications associated with this messenger ribonucleic acid (mRNA) technology vaccine created even more uncertainty in two operational systems as they were being designed: the storage system for future vaccine doses and the vaccination system for the French population. In both systems, several resources are constrained by new specifications that place decision makers in charge of the design and implementation of the new operations in a state of extreme instability, which takes the form of functional uncertainty in the system design.

Figure 4.4

Project execution dynamic and the impacts on operational design instability

46  Research handbook on project performance Proposition 4. Development phase projects can be subject to a high level of uncertainty that may cause modifications to the specifications of the operational resources. In such circumstances, the resources might create uncertainty in the design process of operational systems, modifying previously identified specifications and creating functional and operational instability within the systems. 3.2

Instability in Operations Design Creates Uncertainty in Projects

Recent research on megaprojects emphasizes the importance of integration management to stabilize the different components that constitute resources within functioning systems (Davies and Mackenzie, 2014). Thus, the proper functioning of sociotechnical systems, including effective integration of the various resources, remains a key consideration for ensuring the operational performance pursued with megaprojects. The question of how to control unstable operational systems represents an important axis for operational management, concerned with operational systems that create innovation and instability (Ackoff, 1979). Decision theories therefore highlight different levels of stability within operational systems, depending on their nature (Littauer, 1965; Littauer and Ehrenfeld, 1964; Rubinstein, 1975). In stable and controlled operational systems, the resources and their specifications are known. Decision makers, on the basis of experience data, can test the capacity of resources to produce the targeted outcomes. In unstable operational systems, resources necessary for the production of the targeted outcomes are not clearly known, their specifications must be established, and they may need to be modified. New product development literature indicates that product specifications are unstable. Less than 5% of development projects achieve fully detailed specifications before product design begins (Thomke and Reinertsen, 1998). Therefore, product development practices go through several stages (planning, concept development, system-level design, detail design, testing and refinement, production ramp-up), all of which aim for stabilization of operational systems (Chase et al., 2006). The design process is described as a “design funnel,” which attempts to reduce possibilities by going from uncertainties to certainty (Slack et al., 2013, p. 112). Figure 4.5 depicts the possible uncertainties, as a source of unstable dynamics in the developing system. The uncertainties arising from the instability of an operating system in turn can create uncertainties within the development phase, by changing the resources and specifications within them. For example, France’s president proclaimed that the “Vaccinate” operational system was too slow, just two weeks after the start of the vaccination campaign. As a result, the Ministry of Health began modifying the specifications of the “vaccination plan” resource by integrating “health workers” into the priority population. This modification will have impacts on at least two other resources: the “vaccination facilities” that require vaccination centers in various regions of France for emergencies and the “registration system” that demands a national, online, accessible system that remains functional in an emergency. These design changes, beyond even the modification of resource specifications, increase uncertainty within the projects. They also put government agencies and public sector actors into very innovative project conditions. Proposition 5. The design dynamics of operational systems are subject to an uncertainty management process, which can lead to modifications of the uncertainty conditions of projects. In such circumstances, descriptions of operational resources and their specifications can

Modeling relationships of projects and operations  47

Figure 4.5

Instability in operations design and impacts on the project level of uncertainty

provoke innovation during ongoing projects, which modifies uncertainty levels and management practices. 3.3

Systemic Interactions of Projects and Operations Create Dynamics of Coevolution and Emergence

Interactions between projects and operations are common to innovation management. The stage gate approach explains that interactions of product/business case definitions and project implementations are frequent in the front-end phase (Cooper, 2008). The development of new products also requires managerial flexibility (Thomke and Reinertsen, 1998), to deal with the many changes that take place during new product development processes. Flexibility implies a decision-making capacity to modify the product according to evolutions within projects, because the specifications change with the development of the project. Studies of array systems (Shenhar et al., 2001b) and the management of system integration in complex megaprojects (Davies and Mackenzie, 2014) also acknowledge that the interactions among systems (projects) and systems of systems (operational platforms) require decision-making both back and forth, as well as a capacity to adapt across levels of governance (program level) and execution (project level). Furthermore, research in the field of strategy confirms that the development management cycle of new strategic processes entails emerging processes. For example, the strategic management cycle of operations is part of the interaction between decision makers who define strategic objectives and operational managers who develop new operational systems (Kaplan and Norton, 2008). Operations strategy theories further suggest that mechanisms of emergence should be observed, measured, and managed. Thus, both the theoretical and professional literature appears to concur that interactions exist, function as sources of uncertainty, and require managerial practices based on flexibility and adaptability. However, few studies perform analysis or modeling of emerging organizational dynamics,

48  Research handbook on project performance which are a source of change for managers and evolution in systems (Daniel and Daniel, 2018). The operational dynamics across projects and operations in development demand more in-depth theoretical and practical investigations. For our illustrative case, we consider two systemic dynamics that intertwine and contribute to the establishment of an operational system, the project dynamic that contributes to the production of resources, which are conditions for future business, and the operational dynamic that contributes to the discovery of the conditions required to achieve the outcomes and benefits. Figure 4.6 shows that uncertainty about the Covid-19 vaccine development project initially was resolved with the success of the Pfizer vaccine, followed by announcements of the delay of the Sanofi vaccine. It caused instability in the “produce” and “deliver” systems, because the contracts no longer allowed for the production and delivery of the required doses. In response, the French government entered into discussions with Sanofi to switch some of its factories to RNA vaccine production processes. These new specifications increase the level of innovation within the development subsystems of production plants and their capabilities. For Sanofi, contributing to RNA vaccine production is not a routine project.

Figure 4.6

Design dynamics and the impacts on project execution innovation

Modeling relationships of projects and operations  49 Proposition 6. An emergence dynamic between operations and projects feeds on instability (in operations) and innovation (in projects). It is based on systemic feedforward and feedback mechanisms; over the course of the project, it causes changes in the areas of uncertainty within subprojects and operational systems. This dynamic clarifies how operational performance within operations evolves under the effect of the decisions and actions implemented.

4.

GOVERNING PROJECTS AS OPERATIONS UNDER DEVELOPMENT

4.1

Revisiting Agency Theory and Project Governance

The lack of focus on operational systems (i.e., their innovation, instability, and uncertainty) in prior analyses of projects and programs might be explained partly by agency relationships, in which responsibilities for outputs (project manager) and for outcomes (project funder) are separated (Eisenhardt, 1989; Turner and Müller, 2003). Descriptions of the output to be delivered tend to provide the basis for the specification, which constitutes the central element of a contract between the project developer and the project client. Such a contractual relationship makes it complicated, if not impossible, to adapt the specifications that describe the outputs to be delivered. An agency contractual relationship seemingly has forced project management to focus on the management of contractual commitments rather than seeking to contribute to new operational performance. The principles of organizational agility and management of agile projects, though they cannot address all the questions we raise, show that the agency relationship should be reconsidered, especially with regard to risk management and uncertainties in commercial contracts. Our representation of projects assumes that project managers and project clients acquire techniques that allow them to communicate their priorities. The principal–agent relationship instead anticipates a division of responsibilities, between the development and operational phases of the project. It can support legitimate governance, provided that all actors understand the effects of one phase of the project on other phases. According to our theorizing, a complete separation of responsibilities, priorities, and analyses is questionable, because for some projects, the interactions between phases of the project are unstable and evoke new uncertainties and changes. Thus, in projects subject to instability, the principal and agent must share management techniques and models to facilitate communication and managerial decisions. 4.2

Revisiting Performance Models and Frameworks

Operational management has given rise to a science of stable operational activities, which must be controlled and optimized (Littauer and Ehrenfeld, 1964; Shewhart, 1931; Weaver, 1948). Yet it requires a better view of unstable, innovative activities as they are developing (Ackoff, 1979). The systemic approach that we propose highlights that complex dynamics constantly operate among systems of the development phase and systems of the operating phase of the project, thereby generating emerging performance. Certain principles of historical project management are sometimes called into question; descriptions of the final outputs of the project are not stable or definitive, especially if the operational system to which it contributes

50  Research handbook on project performance is not known or experienced. We thus raise three questions about risk and uncertainty management practices and their statistical and operational bases. First, the operational systems targeted need to be described more clearly, particularly in terms of operational value chain, outcomes, and benefits, to be effectively evaluated, debated, negotiated, and studied. Traditional project analysis practices do not establish a connection between project outputs and their contributions to future operational systems. Second, analyses of risks and uncertainties, which partially determine the success or failure of a project, cannot mix the uncertainties of the development phase with those of the operational phase, so they always leave some performance hidden. Third, governance organizational practices tend to split the development of outputs (governed by the project management team) from the achievement of outcomes (debated by strategic committees). This principle of agency and organization offers coherence but also amplifies the gap between populations that do not use common decision models to choose or act on the projects and operations that result from them. 4.3

Revisiting the Scope of Project Performance

Models for evaluating performance and analyzing risks and uncertainties in projects mainly focus on the scheduling phase (Hazır and Ulusoy, 2020). The systems approach that we propose offers a theoretical framework that would allow us to define a new model for analyzing project uncertainty and complexity, based on a broad representation of project performance. One of the most engaging aspects pertains to the theory of projects, in that our proposed model seeks to broaden the definition of a project, especially its meaning for operations management, which tends to limit the notion of a project to the development phase. The systemic approach we propose also derives from both the theory of sociotechnical systems, with its rich history in operational management, and the theory of complex adaptive systems, which has a growing influence in organizational science. The challenge is to understand the dynamics of change, emergence, and adaptation that result from feedback mechanisms in complex organizations. The theoretical and methodological apparatus we present could allow both practitioners and project management theorists to build operational project models and analyses, including longitudinal assessments of project and operational systems (development systems). Such a theoretical and practical apparatus has not been available or applied previously to understand projects and programs as they are now widely accepted to exist in theory, namely as new operational systems under development. Such a perspective offers the project management field a new position within the science of management and organizations, between operational management and strategy.

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PART II TACTICS, STRATEGIES, AND RISKS

5. Construction and demolition waste recycling and reuse clause in standard form of contracts: impact on project performance Nurhaizan Mohd Zainudin, Ahmad Amir Hafiz Ahmad, Rahimi A. Rahman, and Fadzida Ismail

INTRODUCTION In recent years, the generation of construction and demolition waste (CDW) has increased tremendously and posed multiple threats to the economy, environment, and sustainability. The alarming rise of CDW generation can be attributed to urbanization and extensive infrastructure and reconstruction projects (Jain, 2021). Relatively in the European Union, CDW comprises the largest waste stream with stable amounts produced over time (EEA, 2020). If not treated, CDW could negatively affect the environment, leading to severe air pollution and increased concentrations of particulate matter and aerosols (Swarna, Tezeswi, & Siva Kumar, 2022). Malaysian waste management is in a dire state of improvement. Besides open dumping and illegal dumping, Malaysian landfills suffer from minimal efforts toward source separation for recycling despite the dominance of recyclable materials in the waste composition, CDW inclusive (Moh & Abd Manaf, 2017). In addition to the shortage of dumping sites and scarce resources for building materials, the critically lacking mentality toward cleanliness and sense of responsibility toward properly managing waste create the need to incorporate reduce, reuse, and recycle policy in CDW management in the construction industry. In line with policymakers’ effort to promote sustainable solid waste management, policymakers such as Solid Waste Management and Public Cleansing Corporation (SWCorp) and the Construction Industry Development Board (CIDB) are actively conducting awareness campaigns and 3R workshops and offering advice to contractors, consultants, and customers to reduce CDW (Nadarason et al., 2018). Policymakers are fully aware that the reduction of CDW greatly benefits from the recycling and reuse of waste in the construction industry. As such, the incorporation of a mandatory clause for recycling and reuse of CDW in the standard form of contracts for construction projects is essential. With the implementation of the recycle and reuse CDW mandatory clause, contractors will most likely be affected by the mandatory requirements. It is interesting yet significant to know the contractors’ perspective on the recycling and reuse of CDW as a mandatory clause in the standard form of contracts. Therefore, the objectives of this chapter are: (1) To examine contractors’ perception of recycling and reusing CDW in the construction industry (2) To examine contractors’ opinions on the inclusion of recycling and reuse CDW in the standard form of contracts.

55

56  Research handbook on project performance

LITERATURE REVIEW Construction and Demolition Waste Management Previous literature has provided widespread definitions of CDW. One generally accepted definition provided by Tchobanogious, Eliassen, and Theisen (1977) emphasized construction waste as waste from construction, renovation, and repairing of premises, while demolition waste is defined as waste accumulated from razed structures. The growth of buildings and commercial housing in Malaysia makes up a significant amount of building waste generated by the construction sector (Umar, Shafiq, & Ahmad, 2021). Lai, Yeh, Chen, Sung, and Lee (2016) proposed that the CDW generated from the life cycle of buildings was aggregated, as shown in Figure 5.1. The demand for implementing major infrastructure projects in Malaysia also impacts increasing the production of building waste. As a result of cumulative and increased volumes of CDW, pollution becomes more detrimental to health and natural ecosystems (Udawatta et al., 2015). CDW management is, therefore, an important area of concern within the Malaysian construction industry. The Malaysian construction industry seeks to create a better standard operation procedure (SOP) and mechanism to increase the efficiency of CDW management (Umar, Shafiq, & Ahmad, 2021). While several mechanisms have been implemented in the construction industry, certain enforcement will assure proper CDW management among the project stakeholders. Regardless, the abundant generation of CDW presents multiple challenges to sustainable development, not only in Malaysia but also across many countries in the world. Therefore, as the implementer of construction activities, the contractor plays an important role in CDW management and CDW minimization (Wu, Yu, & Shen, 2017).

Source: Lai et al., 2016.

Figure 5.1

The type of CDW generated throughout the life cycle of buildings

Construction and demolition waste recycling and reuse clause in standard form  57 Construction and Demolition Waste Recycling CDW management includes processes of identification, collection, storage, and recycling (Iodice et al., 2021). Over the years, prior works have been conducted by both researchers and practitioners to find effective ways to prevent and minimize CDW in projects by utilizing the resources (Elizar, Wibowo, & Koestalam, 2015). Recycling is one of the efforts implemented in many areas and industries to reduce waste. The need for the reuse and recycling of CDW has increased over the years, primarily to promote environmental protection and sustainable construction materials (Lai et al., 2016). Recycling is the reprocessing and converting of recycled materials into a new item or use (Bao & Lu, 2021). Recycling or reusing waste from development or demolition depends on the market for each waste. Prior works suggested incineration as a CDW management strategy. However, it is somehow proven ineffective and not well accepted because of its limited applicability (Kabirifar et al., 2020). Recycling and reuse, on the other hand, has been the area of interest for many prior works and researchers from various perspectives: environmental impacts, economic impacts, and social impacts, as well as the effect of the recycle and reuse strategy on project life cycle, stakeholders’ decision, and tools and technologies. Nevertheless, the literature is flawed when it comes to the implementation of such a strategy in the CDW management of the construction industry as a mandatory clause in the standard form of contracts. It is generally acknowledged that major progress has been made in recycling over the years and it is safe to expect that more building and demolition waste will be recycled in the future (Kabirifar et al., 2020). Environmental issues, rising costs for CDW disposal, and demolition of waste dumps have led to this. Therefore, implementing recycling and reuse strategies as a mandatory clause in the standard form of contracts is considered necessary for the CDW management. It is even more vital to understand the perspective of contractors as the implementer of such strategies on having the mandatory clause to recycle and reuse CDW in building projects. Construction and Demolition Waste Management Performance Every year, building projects have been promoted and urban renewal plans have caused the demolition of existing buildings (Lai et al., 2016). Building and demolition operations produce large quantities of solid waste such as concrete blocks, steel, wood, and glass. Such waste was listed as resources that can be utilized for renewable resources, thus the need to recycle and reuse CDW. Although recycling and reuse options have their respective strengths and weaknesses when considering the size, time, cost, market, and government policy, the options are still worth implementation in managing CDW. According to Elizar, Wibowo, and Koestalam (2015), for effective and improved CDW management performance, some variables must be controlled and monitored. The variables are assets, human resources, knowledge, technology, and policy. The effort to include the recycle and reuse clause in the standard form of contracts benefits the environment, social, and economic situations of a country and contributes to the overall CDW management performance of the construction industry.

58  Research handbook on project performance

RESEARCH FRAMEWORK A conceptual model was developed to represent the expected relationship of the study variables visually. As depicted in Figure 5.2, the first to understand in the study is the environmental issue regarding CDW and CDW management. By imposing a mandatory clause for recycling and reuse of CDW in the standard form of contracts, the contractors’ perspective toward the mandatory clause of recycling and reusing CDW is another variable to explore in the study.

Figure 5.2

Research framework

METHODOLOGY This study adopted a quantitative research approach for its data collection and analysis. A set questionnaire was developed and utilized to collect data and answer the study objectives developed for the study. The quantitative research design was chosen for the study to achieve rational, objective, and impartial results and findings (Sekaran & Bougie, 2010). Questionnaire Survey A questionnaire was developed to gather primary data for the study. The main data focus on the inclusion of a mandatory clause to recycle and reuse in the standard form of contracts for construction projects in Malaysia and contractors’ perception if the clause is implemented. The questions in the survey were designed and developed based on a literature review conducted in the study. The final version of the questionnaire involved closed-ended questions and was divided into three sections: section (1) general information, section (2) environmental issues and recycling CDW, and section (3) contractors’ opinion toward mandatory clause for recycling and reuse of CDW. A five-point Likert scale was used for the closed-ended questions from 1 – Strongly Disagree to 5 – Strongly Agree, considering that a five-point Likert scale is more common in many research areas and convenient for respondents (Taherdoost, 2019). Two academics with industry backgrounds in construction management and expertise in CDW management

Construction and demolition waste recycling and reuse clause in standard form  59 reviewed the questionnaire to improve its structure, content, language, and capability to empirically test the conceptual framework of the study (Babbie, 2015). Questionnaires were distributed online to construction companies in Kuala Terengganu, Malaysia. The simple random sampling method was implemented where samples were randomly selected from a list of construction companies in Kuala Terengganu. The samples were obtained from the CIDB directory of companies. The construction companies are registered with the CIDB ranging from Grade 7 (G7) to Grade 5 (G5) categories. The wide range of backgrounds allowed the researchers to produce a more comprehensive result. The data collection process spanned two months and data were compiled electronically since it is easy, cost-efficient, and provides the participants with some anonymity. Online data collection also helps reach target respondents that are difficult to access and contact. The online questionnaires were accompanied by a formal covering letter mentioning the study title, its objectives, and a declaration of anonymity/confidentiality. A reminder email was sent to the companies at seven-day intervals. Statistical Analysis The statistical analysis was conducted using Microsoft Excel. The results were analyzed descriptively using the mean value in order to achieve the study objectives. Since the questions included in the questionnaire used a five-point Likert scale, a reliability test of data is required. Using the Statistical Package for the Social Science (SPSS), the Cronbach’s coefficient alpha test was done to verify the reliability and consistency of data collected using the questionnaire. Sekaran and Bougie (2010) stated that the range of alpha values is from 0 to 1, where higher values will indicate higher data reliability.

RESULTS AND DISCUSSION Reliability of Data After the recording of data, the Cronbach’s coefficient alpha test is applied to check the reliability of the collected data. The purpose of applying Cronbach’s alpha is to measure the internal consistency to identify the closeness of the relation of a set of items in a group (Dornyei & Taguchi, 2009). The Cronbach’s alpha is a coefficient of reliability (or consistency) and any Cronbach’s alpha that equals to or is greater than 0.7000 is often regarded as satisfactory. The collected data were computed using the SPSS software on environmental issues, CDW recycling, and contractors’ perspective toward recycling CDW as mandatory. The results of the Cronbach’s coefficient alpha are shown in Table 5.1. All elements – environmental issues, recycling CDW, and contractors’ opinion on the inclusion of a mandatory reuse and recycling clause – presented a Cronbach’s alpha value of more than 0.70, where each element scored 0.872, 0.909, and 0.944, respectively. These values signify that the data collected are interrelated and that the scales used are reliable.

60  Research handbook on project performance Table 5.1 Element

Cronbach’s coefficient alpha test Item

Environmental issues The development needs to move in line with

AVE

CR

Cronbach’s alpha

0.609

0.903

0.872

0.662

0.931

0.909

0.752

0.955

0.944

environmental sustainability I am aware that the environment is now deteriorating due to waste from construction and demolition Inefficiencies in CDW management and demolition waste among contractors lead to environmental pollution I realize that many contractors are not aware of the environmental problems facing the country now I realize that many contractors take the easy way out of their CDW by dumping it in the wrong place I am willing to help the environment by recycling my CDW materials Recycling CDW

I know that recycling building materials waste and demolition waste will help to reduce the environmental problems we face now Recycling is easy to apply in the construction industry I always recycle my CDW Recycling CDW is profitable to contractors Recycling CDW makes work easier Recycling CDW will not affect the construction time of new buildings Using building materials from recycled products will not affect the life span of a building

Contractors’ opinion

Recycling CDW should be included as one of the clauses in a contract document There should be a penalty imposed on contractors failing to recycle CDW Recycling CDW should be made mandatory for all projects Inclusion of recycling CDW in the clause will benefit the contractors Recycling CDW enshrined in the clause will not be to the detriment of the contractor I am willing to receive a penalty for violating the rules of recycling CDW contained in the clause I am willing to report environmental pollution by other contractors to the responsible party

Results of Section 1 Only 146 responses were recorded within two months after the questionnaires were distributed online to all samples. Table 5.2 summarizes the breakdown of the respondents, including positions and percentages. As mentioned earlier, section 1 of the questionnaire focused on the respondents’ general information, including the types of projects their companies carried out, academic qualifications, years of involvement in the construction industry, and their current position in the company. A range of positions responded to the questions. However, the major-

Construction and demolition waste recycling and reuse clause in standard form  61 Table 5.2

Summary of demographic scales of respondents

Profile

Description

Count

Types of projects carried out

Building construction

52

35.62%

Civil construction

86

58.90%

Other

8

5.48%

Gender Academic qualification

Years of involvement in the construction industry

Position in current company

Total

Percentage

Female

42

28.77%

Male

104

71.23%

SPM

34

23.29%

Diploma

54

36.99%

Degree

50

34.25%

Master

8

5.48%

Less than 3 years

60

41.10%

3 to 5 years

40

27.40%

6 to 10 years

42

28.77%

11 to 15 years

4

2.74%

Contractor

64

43.84%

Designer

6

4.11%

Engineer

40

27.40%

Executive

2

1.37%

Nonexecutive

2

1.37%

Project manager

24

16.44%

Quantity surveyor

4

2.74%

Safety and health officer

2

1.37%

Site supervisor

2

1.37%

 

146

100%

ity were at the operational level: 44% were engineers and 27% were contractors. Accordingly, the majority of the respondents had been involved in the construction industry for less than three years. Only 3% of the respondents had vast construction industry working experience, between 11 and 15 years in the construction industry. Results of Section 2 Respondents’ concerns about environmental issues Table 5.3 summarizes the respondents’ concerns about the environmental issues in relation to CDW management in the construction industry. Respondents strongly agreed that any development and construction projects must progress and move toward sustainability (mean score of 4.73) to maintain a healthy and safe environment for the community. Construction projects produce various waste that might harm the environment and humans. Therefore, the need to properly manage the waste is significantly important. Additionally, the respondents strongly agreed that the environment is deteriorating because of the poor management of CDW in

62  Research handbook on project performance Table 5.3

Respondents’ concerns about environmental issues

Item The development needs to move in line with

Min

Max

Mean

Standard

Excess

deviation

kurtosis

Skewness

3

5

4.73

0.51

1.89

-1.65

3

5

4.49

0.55

-0.86

-0.47

3

5

4.48

0.55

-0.91

-0.41

3

5

4.45

0.62

1.70

-1.03

3

5

4.40

0.57

-0.79

-0.27

2

5

4.18

0.73

-0.26

-0.51

environmental sustainability I am aware that the environment is now deteriorating due to waste from construction and demolition Inefficiencies in CDW management and demolition waste among contractors lead to environmental pollution I realize that many contractors are not aware of the environmental problems facing the country now I realize that many contractors take the easy way out of their CDW by dumping it in the wrong place I am willing to help the environment by recycling my CDW materials

the construction industry (mean score of 4.49) and that the inefficiencies in managing CDW among contractors are leading to poor environmental conditions (mean score of 4.48). With a mean score of 4.18, the respondents were slightly willing to help improve the management of CDW in the construction industry and indirectly improve the environmental condition by recycling CDW in their projects. This result shows that this concept is still new, and contractors are still embracing the idea of having to recycle and reuse their CDW on-site. Respondents’ perceptions of recycling CDW The respondents were asked to explore the feasibility and suitability of adopting the recycle and reuse principles in the management of CDW on construction sites. Seven questions were asked and the respondents were required to give an opinion on the impact of having to recycle and reuse CDW at different stages of the construction period – the recycle and reuse principles could be implemented during the construction work by using recycled materials, or during the initial stage by integrating the reimagine and redesign elements. Table 5.4 summarizes the respondents’ perceptions of recycling CDW on construction sites. The majority of the respondents slightly agree (mean score of 4.25) that recycling CDW in construction projects will help reduce the environmental problems in many countries, including Malaysia. However, some respondents are still contemplating whether the recycling and reuse principles are the best solutions to improve the poor state of Malaysia’s pollution level. Besides that, the respondents were generally neutral, with slight agreement toward recycling and reusing CDW at construction sites. On average, the respondents agreed (mean values ranging from 3.30 to 3.56) on the idea of recycling CDW and that implementing the recycling and reuse principles in CDW management will not affect the overall progress of construction activities. Therefore, it is obvious that the suitability of waste minimization through recycling and reuse needs more exposure among the key players of the construction industry, particularly in the Malaysian construction industry.

Construction and demolition waste recycling and reuse clause in standard form  63 Table 5.4

Respondents’ perceptions of recycling CDW

Item

Min

Max

Mean

Standard

Excess

deviation

kurtosis

Skewness

3

5

4.25

0.62

-0.57

-0.21

Recycling is easy to apply in the construction 2

5

3.56

0.80

-0.53

0.25

I know that recycling building materials waste and demolition waste will help to reduce the environmental problems we currently face industry I always recycle my CDW

2

5

3.30

0.83

-0.37

0.28

Recycling CDW is profitable to contractors

2

5

3.48

0.80

-0.44

-0.10

Recycling CDW makes work easier

2

5

3.41

0.79

-0.46

-0.04

Recycling CDW will not affect the

2

5

3.49

0.76

-0.34

-0.17

2

5

3.53

0.73

-0.22

-0.12

construction time of new buildings Using building materials from recycled products will not affect the life span of a building

Results of Section 3 Respondent opinions on the inclusion of recycling CDW clause in the standard form of contracts Table 5.5 summarizes the respondents’ opinion on the inclusion of recycling and reuse as a mandatory clause in the standard form of contracts for construction projects. Seven questions were asked to respondents about including a mandatory clause to recycle and reuse CDW in construction projects, and the majority of the respondents neither agreed nor disagreed with the idea. The highest mean value was 3.81, where respondents thought it is quite fair if other contractors or the public log a report to the local authorities if a violation of the environmental act causing pollution occurred on construction sites during the construction period. When asked if the recycle and reuse clause should be made mandatory and included in the standard form of contracts for all construction projects, the respondents neither opposed nor supported the effort. The mean value scored at 3.33, and the respondents had a slight tendency toward agreeing to have the mandatory clause included in the standard form of contracts. However, the respondents argued that they were not willing to be penalized should the recycle and reuse clause be made mandatory for all construction projects. With the mean value of 2.99, the respondent did not agree with having a penalty for breaching the contract clause, indicating that the respondents did not agree with the inclusion of the recycling and reuse clause in the standard form of contracts. Accordingly, when asked whether or not the recycling and reuse initiative should be included as a mandatory clause in the standard form of contracts, the respondents remained neutral with only a slight agreement (mean value of 3.32). The result shows that the key players in the Malaysian construction industry do not fully acknowledge the importance of protecting the environment and minimizing the production of CDW on construction sites. Therefore, policymakers should take further actions toward implementing the recycling and reuse principles in all construction projects.

64  Research handbook on project performance Table 5.5

Respondents’ opinions on the inclusion of recycling CDW as a mandatory clause in the standard form of contracts

Item

Min

Max

Recycling CDW should be included as one of 1

Mean

Standard

Excess

deviation

kurtosis

Skewness

5

3.32

0.86

0.16

-0.40

1

5

3.36

0.88

0.40

-0.77

1

5

3.33

0.85

0.30

-0.41

1

5

3.30

0.81

-0.24

-0.46

1

5

3.25

0.88

-0.19

-0.38

1

5

2.99

0.89

-0.08

-0.21

2

5

3.81

0.81

-0.63

-0.11

the clauses in a contract document There should be a penalty imposed on contractors failing to recycle CDW Recycling CDW should be made mandatory for all projects Inclusion of recycling CDW in the clause will benefit the contractors Recycling CDW enshrined in the clause will not be to the detriment of the contractor I am willing to be penalized for violating the rules of recycling CDW contained in the clause I am willing to be reported for environmental pollution by other contractors to the responsible authorities

Table 5.6

Overall element statistics

Element

Min

Max

Mean

Std. deviation

Kurtosis

Skewness

Environmental issues

2

5

4.45

0.613

0.226

-0.779

Recycling CDW

2

5

3.88

0.812

-0.498

-0.053

Contractors’ opinion

1

5

3.33

0.880

0.009

-0.378

 

Finally, Table 5.6 summarizes the overall mean value of each section included in the questionnaire. As discussed earlier, the respondents were in agreement that the construction activities contributed to the production of CDW, resulting in the poor environmental condition in Malaysia with an overall mean value of 4.45. However, the respondents neither disagreed nor approved the inclusion of the recycle and reuse as a mandatory clause in a standard form of contracts (overall mean values of 3.88 and 3.33). Although there is a slight tendency that respondents think recycling is a solution toward improved CDW management and hence a better environment for the country, the results indicate that the key players were not ready for the enforcement of such initiatives and that policymakers should make more effort to demonstrate the importance of having a mandatory recycle and reuse clause in the standard form of contracts.

CONCLUSION For this study, the focal point is to gauge the perception of the key players in the construction industry, specifically those working in the construction companies in Kuala Terengganu, Malaysia. The findings were analyzed descriptively using the mean values to rank the variables included in the questionnaire. The questionnaires were distributed online to the constructing companies registered and located in Kuala Terengganu, Malaysia. The companies

Construction and demolition waste recycling and reuse clause in standard form  65 were registered with the CIDB, ranging from Grade 7 to Grade 5. The respondents for the questionnaire have verified the following: (a) Players in the construction industry, particularly those who are registered and located in Kuala Terengganu, Malaysia, are aware of the environmental impacts of the CDW production and that a better CDW management is required to improve the pollution level of the country. (b) Although it is generally acknowledged that reuse and recycle is imperative at each stage of the construction cycle, the key players in Kuala Terengganu were not affected by the initiative to recycle and reuse to minimize the CDW production, thus reducing the pollution level caused by the CDW. (c) Players in the construction industry, with reference to those in Kuala Terengganu, Malaysia, are not ready for the inclusion of a recycling and reuse initiative as a mandatory clause in the standard form of contracts. Despite the players’ acknowledgment that the CDW generated from the construction activities is a contributing factor to the high level of pollution in the country, they are not ready to embrace recycling and reusing waste as a mandatory clause for all construction projects. Finally, the study findings are only an initial step to understanding the perception of the key players in the construction industry toward implementing recycling and reuse initiatives in CDW management. Although the findings do not favor the inclusion of a mandatory recycle and reuse clause in the standard form of contracts, the results should be taken as a trigger for the need to make the key players aware of the importance of the recycle and reuse initiatives. Particularly for the contractor who will be the implementer of such initiatives, it is of utmost importance that the contractor can support and be ready to work in line with policymakers’ intention to minimize CDW generation and reduce the pollution level of the country.

REFERENCES Babbie, E.R. (2015). The Basics of Social Research. Boston: Nelson Education. Bao, Z. & Lu, W. (2021). A decision-support framework for planning construction waste recycling: A case study of Shenzhen, China. Journal of Cleaner Production, 309(2021), 127449. doi: 10.1016/j. jclepro.2021.127449 Dornyei, Z. & Taguchi, T. (2009). Questionnaires in Second Language Research: Construction, Administration, and Processing. Second edition. New York: Routledge. Elizar, E. Wibowo, M.A., & Koestalam, P. (2015). Identification and analyze of influence level on waste construction management of performance. Orocedia Engineering, 125, 46–52. doi: 10.1016/j. proeng.2015.11.008 Esa, M.R., Halog, A., & Rigamonti, L. (2016). Developing strategies for managing construction and demolition wastes in Malaysia based on the concept of circular economy. Journal of Material Cycles and Waste Management, 19(3), 1144–1154. doi: 10.1007/s10163–016–0516-x Esa, M.R, Halog, A., & Rigamonti, L. (2020). Strategies for minimizing construction and demolition wastes in Malaysia. Resources, Conservation and Recycling, 120, 219–229. European Environment Agency (EEA). (2020). Construction and demolition waste: Challenges and opportunities in a circular economy. ETC/WMGE Report, 1/2020. Retrieved at https://​www​.eionet​ .europa​.eu/​etcs/​etc​-wmge/​products/​etc​-wmge​-reports/​construction​-and​-demolition​-waste​-challenges​ -and​-opportunities​-in​-a​-circular​-economy.

66  Research handbook on project performance Iodice, S., Garbarino, E., Cerreta, M., & Tonini, T. (2021). Sustainability assessment of construction and demolition waste management applied to an Italian case. Waste Management, 1(128), 83–98. doi: 10.1016/j.wasman.2021.04.031 Jain, M.S. (2021). A mini review on generation, handling, and initiatives to tackle construction and demolition in India. Environmental Technology & Innovation, 22, 101490. Kabirifar, K., Mojtahedi, M., Wang, C.C., & Tam, V.W.Y. (2020). A conceptual foundation for effective construction and demolition waste management. Cleaner Engineering and Technology, 1(2020), 100019. doi: 10.1016/j.clet.2020.100019 Lai, Y., Yeh, L., Chen, P., Sung, P., & Lee, Y. (2016). Management and recycling of construction waste in Taiwan. Procedia Environmental Sciences, 35, 723–730. doi: 10.1016/j.proenv.2016.07.077 Moh, Y.C. & Abd Manaf, L. (2017). Solid waste management transformation and future challenges of source separation and recycling practice in Malaysia. Resource, Conservation and Recycling, 116, 1–14. https://​doi​.org/​10​.1016/​j​.resconrec​.2016​.09​.012 Nadarason, K.S., Nagapan, S., Abdullah, A.H., Yunus, R., Abas, N.H., Hasmori, M.F., & Vejayakumaran, K. (2018). Recycling practices of construction and demolition (C&D) waste in construction industry. Journal of Advanced Research in Dynamical and Control System, 10(6), 281–289. Sekaran, U. & Bougie, R. (2010). Research Methods for Business: A Skill-Building Approach. Fifth edition. London: Wiley. Swarna, S.K., Tezeswi, T.P., & Siva Kumar, M.V.N. (2022). Implementing construction waste management in India: An extended theory of planned behaviour approach. Environment Technology & Innovation, 27, 102401. Taherdoost. H. (2019). What is the best scale for survey and questionnaire design: Review of different lengths of rating scale/attitude scale/Likert scale. International Journal of Academic Research in Management (IJARM). Helvetic Editions, 8. Tchobanogious, G., Eliassen, R., & Theisen, R. (1977). Solid Waste: Engineering Principles and Management Issues. New York: McGraw Hill. Udawatta, N., Zuoa, J., Chiveralls, K., & Zillante, G. (2015). Improving waste management in construction projects: An Australian study. Resources, Conservation and Recycling, 101, 73–83. Umar, U.A., Shafiq, N., & Ahmad, F.A. (2021). A case study on the effective implementation of the reuse and recycling of construction and demolition waste management practices in Malaysia. Ain Shams Engineering Journal, 12(2021), 283–291. Wu, Z., Yu, A.T.W., & Shen, L. (2017). Investigating the determinants of contractor’s construction and demolition waste management behavior in Mainland China. Waste Management, 60, 290–300. https://​ doi​.org/​10​.1016/​j​.wasman​.2016​.09​.001

6. Project monitoring and data integrity James Marion and Tracey Richardson

PROJECT MONITORING AND DATA INTEGRITY Project monitoring and controlling has been studied for decades. Left to its own devices, a project would likely never arrive at the finish line with the required deliverables—much less within the specified budget and schedule. It is project management that keeps projects on target, and it does so by collecting status information and using that information to drive corrective action. While this process may appear straightforward, there are many challenges associated with monitoring projects. To begin with, projects are temporary and unique. They often break new ground. When many unknowns are involved, the progress toward a novel goal is often difficult to measure. Adding to this is the often-chaotic experience of the project team members who carry out the work of the project. Monitoring a project requires the collection of status information from team members who, when under schedule and budget pressure, may choose to focus on doing work rather than providing timely reports. When team members do report status, they may at times be doing little more than guessing, creating data integrity problems. This is particularly the case in complex software-intensive projects. Given that software is invisible and has an infinite number of moving parts, the exact status of code is difficult to gauge. These factors suggest that to enhance the likelihood of success, project managers need to be well versed in effective project monitoring practices. An examination of the literature associated with project monitoring provides a starting point.

THE BASELINE The progress of any project is determined by comparing the current state with the original plan. The original project plan detailing a complete picture of the scope, the schedule, and the budget is the baseline (Kim, Wells, & Duffey 2003; Larson & Gray, 2018; Kloppenborg, Anantatmula, & Wells, 2018). The baseline is the plan that is “cast in stone” so that any change to the plan must be proposed through the integrated change control process (Shafiq, Zhang, et al., 2018). Changes that are accepted are documented and implemented and are incorporated into a new baseline (Bhatti et al., 2010). What is essential in the context of project monitoring is that the absence of a clear-cut project baseline eliminates the ability for the project manager to report progress. There is no “progress to plan” without a plan—regardless of if the information collected from project monitoring is accurate or not. While the baseline is the basis for reporting progress, the baseline is not a tool for monitoring or collecting project performance data. It is in effect the paper upon which the progress of the project is recorded and measured against. The challenge for project managers is that while the baseline is well known and understood, the progress against the baseline plan is not (Bhatti et al., 2010).

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68  Research handbook on project performance

EARNED VALUE AS PROJECT MONITORING Earned value is an important tool for removing some of the ambiguity of progress reporting, as it measures the work accomplishment and budget consumption (Willems & Vanhoucke, 2015). For example, when the project reports that it is under budget—with no other information except for the original budget plan and current date of the project—the reason for the apparent “under budget” state is unclear. For example, is the project truly under budget? Or has the project spent less than planned because it is behind schedule? The answer to this question becomes clearer when the monetary value of the completed work is reported (EV) along with the original budget (planned value: PV) and the actual spending (actual cost: AC). The benefit of EV is only attainable if the project team can measure the “monetary value of the completed work”, which is also defined as percent complete × budget. Determining the budget (PV) and AC values are normally trivial exercises. However, the central problem is determining the percent complete and its associated value. In the case of a tangible project such as clearing a piece of land or building a backyard deck, EV determination is straightforward consumption (Willems & Vanhoucke, 2015). But what about the case of a complex software-intensive system development that requires the development of use cases, architecture, system design, and development and integration of modules (Varajão, Fernandes, & Silva, 2020)? When determining EV within a project becomes guesswork, the reported status of the project may be misleading and may not reflect reality. One approach designed to address such concerns is to employ EV at the level of the work package. The granular nature of monitoring at the work package level offers the possibility for greater accuracy. Once again, however, the accuracy of the reporting depends upon the nature of the work characterized by the work package, often constrained by resources (Song, Martens, & Vanhoucke, 2022). Another possibility for improving the accuracy of EV monitoring is to use it at key intervals within the project (Kerzner, 2017). An example of this is to use EV only at key business decision points within the project. Carrying out EV at discrete intervals where tangible milestones have been achieved provides advantages over attempting to monitor using EV on a continuous basis (Acebes, Pajares, Galan, & Lopez-Paredes, 2014). A decision point or gate milestone is typically associated with clear targets or milestones for accomplishment of key project deliverables. When this approach is applied, the completion (or lack of it) for key deliverables comes into clearer focus. One challenge is that progress associated with individual deliverables may not say much about the progress of the overall project (Kerzner, 2017). As an example, consider a project where three important software modules are to be completed at a specific milestone. If the milestone is achieved, then the progress on the modules could be said to be excellent—if not complete. But what will be the progress at the next milestone when the multiple modules are integrated into the complete system? Integration is typically where hidden defects are brought to the surface. Prior to an integration milestone, then, the project may be on target. After an integration milestone, the project may find itself well behind schedule because of the sudden appearance of a tsunami of integration-related defects.

THE REARVIEW MIRROR While EV indexes can be used to make projections about the future (Caron, Ruggeri, & Merli, 2013), progress monitoring is fundamentally about looking back at what was accomplished—

Project monitoring and data integrity  69 as well as what was not. Another way to employ EV is to look ahead at the project and denote what “should” be completed at specific milestones and create EV-based control charts that anticipate outcomes (Rodrigo, Linda, & Fernando, 2020). This “ex-ante” approach has been cited as a means for improving accuracy in EV monitoring and making the scheme more forward-looking and anticipatory in nature (Mortaji, Noori, Noorossana, & Bagherpour, 2018). This approach foreshadows other methods of looking ahead using metrics. Progress reporting communicates what has been completed—so it is natural to think of EV, as well as any progress-reporting methodology, as a rearview mirror approach. The challenge is the time span between what happened in the project and when it was reported. In projects, objects in the rearview mirror may be further away than they appear, thereby making the information obsolete by the time it is reported.

CRITICAL SUCCESS FACTORS AND KEY PERFORMANCE INDICATORS AS PROJECT MONITORING Critical success factors (CSFs) are those outcomes that must be in place for a project to be considered successful (Kerzner, 2017). Progress toward the achievement of CSFs is measured using key performance indicators (KPIs). The benefit of CSFs is that project goals are explicitly stated and the measured achievement against the stated goals is captured in KPI measures and plotted. On the other hand, the project deliverables also constitute project goals and the measurement of such progress also requires the collection of timely and accurate data that may or may not be available. If accurate data on progress to plan is difficult to come by when measuring overall project progress, the challenge will exist in equal measure for CSF and KPI progress measurement. The benefit of the CSF methodology is successful for project monitoring purposes only if the progress captured from the project team members is accurate and of high quality. It may not be. Control Charts Modern quality management systems focus on the principle of “manage the process and the quality of the deliverables will take care of itself”. In project management, the process being managed for the purpose of project quality is the project life cycle. The life cycle, whether expressed in phases, sprints, or a monolithic end-to-end schedule, is primarily measured using methods such as EV. For example, performance indexes may be plotted on a control chart in the same way that control charts are developed within the context of construction or manufacturing (Votto, Lee Ho, & Berssaneti, 2021). The challenge in project management is that measuring progress of complex intangible work such as system development is not as straightforward as testing tangible products on an assembly line (Aliverdi, Moslemi Naeni, & Salehipour, 2013; Galante, La Fata, & Passannanti, 2019). While it is a simple matter to plot the measurement of specifications of products in manufacturing (Leu & Lin, 2008), measuring the percent complete of code development depends upon many factors—some of which requires estimation on the part of the developer. For example, progress could be measured in terms of number of modules completed versus the plan, lines of code written, or the completion of a complete system, to name but a few. However, while such

70  Research handbook on project performance metrics may be captured, they may often be incomplete because of many unknown factors. For example, questions that could be asked include: (1) While code (and/or system design) is said to be complete, does it work? (2) Has the completed work been tested? (3) Does the completed work require integration into other systems? (If so, what is the confidence level that defects will not emerge en masse once integration is attempted?) (4) Are there any changes in requirements, standards, or assumptions that changed while the code and/or system was being developed? (5) How long ago was the work completed (and if time has passed, does the progress report remain valid)? While the control chart remains an important means for visualizing progress, it is only as useful as its accuracy (Bauch & Chung, 2001).

HOW DO ORGANIZATIONS COLLECT PROJECT PROGRESS DATA? What is not well documented in the literature is the process to ensure the data collected for reporting is accurate and consistent across the project. Organizations may adopt a “rule of thumb” for reporting an activity’s progress, described as the percent complete, or the 0% rule, 50% rule, and the 100% rule (Larson & Gray, 2018). The 0% rule states that if an activity is started but not yet complete, the activity will be reported as zero progress until completion, at which time it will be documented as 100% complete. The 50% rule states that if an activity is started but not yet complete, the activity will be reported as 50% progress until completion, at which time it will be documented as 100% complete. The 100% rule states that if an activity is started but not yet complete, the activity will be reported as 100% complete as soon as it begins. Each of these rules of thumb has pros and cons associated with their use, but the bottom line is that they are not an accurate representation of progress. The lack of data integrity could be impacting project progress reporting and organizational decision making, as it is fundamentally flawed (Anbari, 2003). When looking for ways to improve its project progress reporting, an organization may seek a solution to data integrity question by filling the gap with a part of the organization that exists to control projects: the Change Control Board (CCB).

TRADITIONAL ROLE OF THE CHANGE CONTROL BOARD (CCB) In its traditional role, the CCB oversees the formal change control progress for all projects (Hinojosa, 2008). Its purpose is to review all requested project changes, evaluate the changes’ impact to all aspects of the project, and, if the change is approved, issue responses by sending out change orders to the project team. The CCB is generally considered a committee with a committee chair and committee membership includes subject matter domain experts, a system engineer (they help balance trade-offs across domains), those who oversee shared resources, and other organizational representatives as needed. The change control process (see Figure 6.1) begins when a stakeholder identifies that something in the project plan needs to be changed. The change might be additions to the scope,

Project monitoring and data integrity  71 requirements to meet regulatory guidance, or missing details from the original project plan, to name a few reasons. In this case, we will refer to the person who submits the change request as the originator. The originator, in collaboration with the project manager, will document the request, including changes to requirements, cost, and additions to the schedule, and submit the details to the CCB.

Figure 6.1

The change control process

The CCB will evaluate the merits of the change request and consider its impact on the scope, schedule, and budget of the project. But this evaluation’s scope does not stop at the impact of the project. Because the CCB has oversight of the organization’s project portfolio, it can also consider the impact on other projects, as shared resources can be a critical asset. If the CCB deems the change acceptable, the change control process will identify the affected work packages and send out work order changes. Those change orders are issued to the project’s stakeholders and the work packages will be updated to reflect scope, schedule, and budget updates.

ADDING THE ROLE OF ‘MONITORING’ TO THE CCB The CCB, by virtue of its oversight role of the project baseline, is uniquely positioned to provide insights on project progress information arising from Work Package Team Leads. In addition to taking on the responsibility for capturing accurate progress information, the CCB would continue its function to approve project changes (see Figure 6.2). Whether due to specialized training or unique experience working on the CCB, the CCB members have a better understanding of an organization’s risk tolerance. Additionally, those who serve on the CCB have a unique perspective and likely have relationships with project managers and work package leads. Finally, the membership of the CCB involves project team members who

72  Research handbook on project performance possess significant domain expertise. Such expert judgment puts team members in a position where they can ask the right questions about reported progress, aid in backfilling what is missing, and cast a skeptical eye over overly optimistic progress reports. In this scenario, the CCB members—in the same way as project core team members—are assigned oversight of work package leads associated with their specific domain expertise. Once progress reports are vetted by CCB members, the reports are combined to assemble the formal status of the project along with EV metrics. In cases where cross-domain issues or discrepancies arise among the different reports submitted by CCB members, a designated arbiter of the issues will evaluate. Typically, this individual will be the Chief Technical Officer of the organization or project, or a team member assigned to system engineering responsibilities. While this data integrity role increases the scope of the CCB, it has the potential to increase the data accuracy making project status much more valid. Since the CCB maintains the integrity of the baseline considering change and updating the baseline (or PV) as necessary, this additional obligation in effect makes the CCB responsible for the project progress or EV line. The CCB therefore owns not only PV but also EV integrity.

Figure 6.2

Adding the role of ‘monitoring’ to the Change Control Board

IMPLEMENTATION CONSIDERATIONS The decision to add the monitoring function of EV in addition to PV oversight and data integrity requires more than the determination to implement it. The implementation of the methodology requires answering the following questions: (1) Who are the Work Package Leaders and what is their specific area of responsibility (i.e. project domain expertise)? (2) Which Work Package Leaders are assigned to which CCB members? (3) How specifically will CCB members collect data from Work Package Leaders?

Project monitoring and data integrity  73 (4) How often will progress data be collected? (5) How will the progress reports be evaluated and vetted? These questions relate to the specific strategy of “plan progress measurement” processes thought through in advance of the project. The first two questions to be answered are ones associated with project stakeholder identification and assessment. It is recommended that the Work Package Leader and CCB member mapping could take place in the initiating of the project during stakeholder analysis. The next two questions incorporate communication and stakeholder engagement planning. Finally, the fifth question relates specifically to project integration as monitor and control project work planning. Establishing a clear strategy to plan progress management formalizes the process, which can be studied for effectiveness, efficiency, and success.

CONCLUSION Organizations continue to struggle with project monitoring efficacy and at its foundation is questionable data integrity. It is especially problematic with complex projects where tangible progress cannot be seen. A solution may already exist with specialized knowledge of the organization: the CCB. While the example in this chapter was illustrated using software development, the CCB is a solution to any organization struggling with project monitoring challenges because of questionable data integrity, regardless of industry, sector, or project complexity.

REFERENCES Acebes, F., Pajares, J., Galan, J. M., & Lopez-Paredes, A. (2014). A new approach for project control under uncertainty. Going back to the basics. Elsevier Science. 10.1016/j.ijproman.2013.08.003 Aliverdi, R., Moslemi Naeni, L., & Salehipour, A. (2013). Monitoring project duration and cost in a construction project by applying statistical quality control charts. International Journal of Project Management, 31, 411–423. Anbari, F. T. (2003). Earned value project management method and extensions. Project Management Journal, 34(4), 12–23. Bauch, G. T., & Chung, C. A. (2001). A statistical project control tool for engineering managers. Project Management Journal, 32, 37–44. Bhatti, M. W., Hayat, F., Ehsan, N., Ishaque, A., Ahmed, S., & Mirza, E. (2010, October). A methodology to manage the changing requirements of a software project. In 2010 International Conference on Computer Information Systems and Industrial Management Applications (CISIM) (pp. 319–322). IEEE. Caron, F., Ruggeri, F., & Merli, A. (2013). A Bayesian approach to improve estimate at completion in earned value management. Project Management Journal, 44(1), 3–16. Galante, G. M., La Fata, C. M., & Passannanti, G. (2019). Project monitoring by dynamic statistical control charts.  Journal of Modern Project Management, 7(3). Hinojosa, E. U. (2008). Process Mining Applied to the Change Control Board Process (doctoral dissertation, Master’s thesis, Eindhoven University of Technology, Eindhoven). Kerzner, H. (2017). Project Management Metrics, KPIs, and Dashboards: A Guide to Measuring and Monitoring Project Performance. Wiley. Kim, E., Wells Jr, W. G., & Duffey, M. R. (2003). A model for effective implementation of Earned Value Management methodology. International Journal of Project Management, 21(5), 375–382.

74  Research handbook on project performance Kloppenborg, T., Anantatmula, V., & Wells, K. (2018). Contemporary Project Management. 4th ed. Cengage. Larson, E. W., & Gray, C. F. (2018). Project Management: The Managerial Process. McGraw Hill. Leu, S., & Lin, Y. (2008). Project performance evaluation based on statistical process control techniques. Journal of Construction Engineering and Management, 134(10), 813–819. Mortaji, S. T. H., Noori, S., Noorossana, R., & Bagherpour, M. (2018). An ex-ante control chart for project monitoring using earned duration management observations. Journal of Industrial Engineering International, 14(4), 793–806. 10.1007/s40092–017–0251–5 Rodrigo, V., Linda, L. H., & Fernando, B. (2020). Applying and assessing performance of earned duration management control charts for EPC project duration monitoring. Journal of Construction Engineering and Management, 146(3), 04020001. 10.1061/(ASCE)CO.1943–7862.0001765 Shafiq, M., Zhang, Q., Akbar, M. A., Khan, A. A., Hussain, S., Amin, F. E., … & Soofi, A. A. (2018). Effect of project management in requirements engineering and requirements change management processes for global software development. IEEE Access, 6, 25747–25763. Song, J., Martens, A., & Vanhoucke, M. (2022). Using earned value management and schedule risk analysis with resource constraints for project control. European Journal of Operational Research, 297(2), 451–466. Varajão, J., Fernandes, G., & Silva, H. (2020). Most used project management tools and techniques in information systems projects. Journal of Systems and Information Technology. doi: 10.1108/ JSIT-08-2017-0070 Votto, R., Lee Ho, L., & Berssaneti, F. (2021). Earned duration management control charts: Role of control limit width definition for construction project duration monitoring. Journal of Construction Engineering and Management, 147(9). https://​doi​.org/​10​.1061/​(ASCE)CO​.1943​-7862​.0002135 Willems, L. L., & Vanhoucke, M. (2015). Classification of articles and journals on project control and earned value management. International Journal of Project Management, 33(7), 1610–1634.

7. Don’t ask what makes projects successful, but under what circumstances they work: recalibrating project success factors Lavagnon A. Ika and Jeffrey K. Pinto

INTRODUCTION: TROUBLE IN PARADISE The islands of Hawai’i are among the most idyllic settings in the United States, offering beautiful beaches, temperate climates, and stunning and varied scenery. As a booming tourist destination for millions of travellers each year, government and tourism officials have worked to balance the needs of the local populations with the expectations of the islands’ many guests. One area that represents a particular sore point for residents of the most heavily populated island of O’ahu is the lack of sufficient infrastructure to support the congestion around the capital city of Honolulu. Commutes along the main highway from the airport and western environs into the city centre can take hours and are a constant source of frustration for travellers and locals alike. With a goal of easing traffic congestion, the state and federal officials embarked on a series of studies from 2005 to 2008 to identify the best means for developing an infrastructural solution to urban and suburban congestion. In 2008, voters approved a proposal to fund the building of a 20-mile elevated rail system. The timing of the project was unfortunate, as it coincided with the “great recession,” which effectively tabled all major infrastructure projects for over 18 months. However, after a careful study was undertaken by planners and state regulators, the City and County of Honolulu signed an agreement in 2012 with the Federal Transit Administration to build the project for $5.122 billion. The funding for the rail system would cover development of the 20-mile, 21-stations project, as well as paying for 80 rail cars. Performance to date has been disappointing, to put it mildly. In fact, the rail project has been the subject of multiple state and city audits that identified a consistent record of fiscal waste and poor management, plus lawsuits, calls for a forensic audit to investigate whether criminal activity occurred, and U.S. Department of Justice subpoenas (Frosch & Overberg, 2019). Among the litany of mistakes made to date are: (1) the development and subsequent abandonment of a public–private partnership when bids came in much higher than expected, (2) poor planning, and (3) a continuing opaque and confusing funding process that clouds the effective costs of the project (Fujii-Oride, 2021). Technical challenges with transport car design, inability to locate underground utilities, and infighting among stakeholders have also slowed development to a crawl (Nakaso, 2021). The project has not been helped by the continuous stream of upbeat projections and public assurances that it has turned the corner, a state audit determined: “We found that, from the beginning, unrealistic deadlines and revenue projections resulted from a desire to demonstrate that the project was progressing satisfactorily and to minimize public criticism, which could have eroded support for the project.”

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76  Research handbook on project performance Concerns about the project’s mismanagement have caused the federal government to withhold $744 million since 2015. As of the end of 2021, the project is estimated to be only 63% completed, with 15 miles of the 20-mile guideway in place, 68 of the 80 cars delivered, and a current budget shortfall of $3.5 billion deficit – the difference between the latest estimate of the final overall cost and revenue expected by 2030, when the tax increases that are funding most of the construction expire (Fujii-Oride, 2021). Cost overruns have been attributed notably to limited supply of labour, superficial or inadequate initial planning, and increases in the cost of materials. The current expected budget at completion for the project is estimated at about $12 billion – 136% more than when the full funding grant agreement was signed in 2012. With a budget that has more than doubled and a new completion estimate that is 11 years past the original plan, the Honolulu rail project offers a large set of “How not to” lessons for megaproject organizations and urban planners alike. In project management theory and practice, these lessons are what have been called critical success factors (CSFs), the levers that project funders and managers may use to bolster a project’s chances of success, those few elements “where things must go right” if project funders and managers are to create “an environment where projects are managed consistently with excellence” (Kerzner, 1987, p. 32) or, put simply, those “conditions, events, and circumstances that contribute” to positive project outcomes (Ika, 2009, p. 8).

CRITICAL SUCCESS FACTORS The idea of CSFs connects with the notions of project success – the achievement of the goal towards which project management efforts are directed – and project performance – the degree to which, during project execution or after project completion, success is likely to be reached – that remain complex and elusive in theory and practice (Pinto, Davis, Ika, Jugdev, & Zwikael, 2021; Ika & Pinto, 2022). Projects have increasingly become a means for organizations, both public and private, to achieve strategic, medium- or long-term, business case objectives and deliver value for multiple stakeholders with differing if not conflicting expectations. Further, at the time when the imperative of sustainability – that is, the triple bottom line of economic, social, and environmental considerations (Elkington, 1997) or the UN Sustainable Development Goals (UN, 2015) – is gaining momentum in the project management literature (Huemann & Silvius, 2017), project funders and managers seek to reach the targets of efficiency, without sacrificing the goals of effectiveness and sustainability (Carvalho & Rabechini, 2017; Ika & Pinto, 2022). The increased interest in understanding project success and the factors that can lead to improved performance offers an interesting irony; namely that at a time when the use of project-based work is at an all-time high, as the demand for new and enhanced infrastructure, emergency development of vaccines and other pharmaceuticals, efforts supporting green technologies and net-zero initiatives continue to capture the public’s attention and earn significant public and private funding, the success rates of projects in many settings languish. Most recent Chaos Reports (Standish Group, 2020), for example, cite a success rate of only 31% for new software projects. Moreover, these disappointing numbers reflect the steady state of substandard performance that has occurred for some 20 years. As our opening example illustrates, worldwide, megaprojects offer little reason for optimism, as they collectively continue to overrun their initial budgets and schedules to the tune of billions (USD) (Flyvbjerg, 2014).

Don’t ask what makes projects successful, but under what circumstances they work  77 Therefore, despite decades of work, the question “what makes projects successful?” continues to garner attention from both practitioners and researchers alike. In particular, since the 1960s, research has continued apace on CSFs both inside and outside project management journals (Rubin & Seeling, 1967; Murphy, Baker, & Fisher, 1974; Morris & Hough, 1987; Pinto & Slevin, 1988; Cooke-Davies, 2002; Jugdev & Müller, 2005; Ika, 2009; Rodríguez-Segura, Ortiz-Marcos, Romero, & Tafur-Segura, 2016; Unterhitzenberger & Bryde, 2019; Wang, Xu, He, & Chan, 2022). Our goal in this chapter is to critically examine the current state of theory and research on project CSFs, both in terms of reinforcing what we, as a scholarly profession, know as well as highlighting areas that continue to pose challenges for scholars and practitioners alike. Although the topic of CSFs is one that has been addressed in the project management literature for some time now, with probably the earliest papers on the topic appearing in the 1960s (e.g., Rubin & Seeling, 1967), we still face a paradox in our knowledge of the topic. Specifically, as we learn more about the complex nature of project behaviour (Ika, Love, & Pinto, 2022), we find that CSFs become increasingly complex and generalizations previously made about them more open to qualification and even contradiction. Further, CSF research offers an interesting juxtaposition with an equally active research stream on the nature of project success. That is, project scholars continue to identify complications in the previously “well-recognized” relationship between CSFs and subsequent effect (project outcomes). As our knowledge of what it means to be “successful” has been progressively challenged and/or modified in the literature (Zwikael & Meredith, 2021; Ika & Pinto, 2022), it is important to re-examine CSFs. This chapter first updates the most significant literature on project CSFs and, building on key existing frameworks, highlights the importance of more modern perspectives, citing additional CSFs. In an attempt to further “complexify” CSF research, the chapter then reveals five gaps in the CSF literature. We conclude with a call for practitioners and scholars to switch from a narrow and unproductive focus on success factors to a broader and more promising focus on success conditions in the face of complexity and uncertainty. The chapter also ends with an agenda highlighting future research to move our understanding of CSFs forward.

FROM OLD FRAMEWORKS TO A NEW FRAMEWORK OF CRITICAL SUCCESS FACTORS? The lessons from the longitudinal and historic reviews of project success (Jugdev & Müller, 2005; Ika, 2009; Wang et al., 2022) are clear: there has been a gradual broadening in our understanding of CSFs since the 1960s. Table 7.1 lists some of the key frameworks of CSFs in the project management literature. It is important to note that for some scholars the focus was jointly on factors that promote project success or failure (e.g., Rubin & Seeling, 1967; Belassi & Tukel, 1996; Unterhitzenberger & Bryde, 2019); that is, “[t]he body of literature on project success also encompasses project failures” (Jugdev & Müller, 2005, p. 26). Although not intended to be exhaustive, Table 7.1 offers a fair treatment of various studies of success and failure, while also providing a glimpse into the manner in which these models have both maintained continuity and modification through some 50+ years of work on the topic. As we have learned from contingency theory, while it is virtually impossible to develop an exhaustive list of CSFs that would work for all projects, the idea of a universal grouping of CSFs seemed to be garnering attention until recently (Ika, 2009). However, research on

78  Research handbook on project performance Table 7.1

Seven key frameworks of project critical success factors

Murphy et al. Project manager (1974)

(commitment to project goals; authority and influence; task orientation; administrative skill; human skill; technical skill; early and continued involvement; participation in goal setting and criteria specification) Project team (capabilities; commitment to goals; participation in goal setting, setting budgets and schedules, major decision-making, problem solving; early and continued involvement; “sense of mission”; structural flexibility) Parent organization (coordinative efforts; structural flexibility; effective strategic planning; rapport maintenance; adaptability to change; past experience; external buffering; prompt and accurate communications; enthusiasm; project contributes to parent capabilities) Client organization (coordinative efforts; rapport maintenance; establishment of reasonable and specific goals and criteria; change procedures; prompt and accurate communication; commitment; lack of red-tape; prompt decision-making; influence and authority of contact) Managerial techniques (judicious and adequate but not excessive, use of planning, con­trol, and communication systems) Preconditions (clearly established specifications and design; realistic schedules; realistic cost estimates; avoidance of buy-ins; avoidance of over-optimism; favourable interface with legal-political environment; conceptual clarity)

Baker et al.

Clear goals

(1983)

Goal commitment of project team On-site project manager Adequate funding to completion Adequate project team capability Accurate initial cost estimates Minimum start-up difficulties Planning and control techniques Task (vs social orientation) Absence of bureaucracy

Morris &

Project objectives and viability

Hough

Technical uncertainty innovation

(1987)

Politics Community involvement Schedule duration urgency Financial, legal, and contractual matters Project implementation

Pinto &

10 CSFs under project team control:

Slevin (1987) Project mission Top management support Project schedule/plan Client consultation Personnel Technical tasks

Don’t ask what makes projects successful, but under what circumstances they work  79 Pinto &

Client acceptance

Slevin (1987) Monitoring and feedback (continued)

Communication Troubleshooting 4 CSFs outside project team control: Characteristics of the project team leader Power and politics Environment events Urgency

Cooke-

Adequacy of company-wide education of risk management

Davies

Organizational maturity for risk ownership assignment

(2002)

Adequacy of risk register maintaining Adequacy of up-to-date risk management plan Adequacy of documentation of organizational responsibilities Keep project (or project stage duration) as far below 3 years as possible (1 year is better) Allow changes to scope only through a mature process Maintain integrity of performance measurement baseline Effective benefits delivery and management process that involves mutual co-operation of PM and management line functions Portfolio and programme management practices that allow strategic alignment of projects A suite of project, programme, portfolio metrics for aligning decisions Effective means of “learning from experience”

Hyväri

Project

(2006)

(size and value; having a clear boundary; urgency; uniqueness of the project activities; density of the project network; project life cycle end-user commitment; adequate funds/resources; realistic schedule; clear goals/objectives) PM/leadership (ability to delegate; authority; ability to trade off; ability to coordinate; perception of his or her role and responsibilities; effective leadership; effective conflict resolution; having relevant past experience; management of changes; contract management; situational management; competence; commitment; trust; other communication) Project team members (technical background; communication; troubleshooting; effective monitoring and feedback; commitment; other scope known by members also) Organization (steering committee; clear organization/job descriptions; top management support; project organization structure; functional manager’s support; project champion) Environment (competitors; political; economic; social technological; nature; client; subcontractors)

Khang &

Clear understanding of project environment by funding and implementing agencies and consultants

Moe (2008)

Competencies of project designers, planners, managers, PM team Effective consultations with stakeholders Compatibility of development priorities of the key stakeholders Adequate resources and competencies available to support the project plan Compatible rules and procedures for PM Continuing support of stakeholders Commitment to project goals and objectives Adequate provisions for project closing in the project plan Donors and recipient government have clear policies to sustain project’s activities and results Adequate local capacities are available There is strong local ownership of the project

80  Research handbook on project performance comprehensive, often execution-focused, CSF lists and frameworks has dwindled while work has continued significantly at the individual project CSF level, most especially as a function of classic contingency theory (Morris, 1994). One notable but recent exception is the work of Wang et al. (2022) whose 36-CSF framework on infrastructure construction megaprojects includes CSFs related to the project (e.g., clear goals), organization (e.g., project manager’s competency), stakeholders (e.g., public support or acceptance), management (e.g., scope management), and external environment (e.g., economic, technical, and political stability). Hoegl and Gemünden (2001) emphasized teamwork quality as a CSF for innovative projects, which they connected with team performance (efficiency and effectiveness) and personal success (satisfaction and learning). Gemünden et al. (2005) outlined the contribution of project autonomy as a CSF. Drawing on the classic contingency theory and noting that different projects show different CSFs (Dvir, Lipovetsky, Shenhar, & Tishler, 1998), Shenhar and Dvir (2007) devised the Novelty, Technology, Complexity, and Pace or NTCP diamond model, which is akin to a CSF model. As our understanding of project success evolves, we have discovered that project sponsorship – also known as project supervision or the “management of project management,” as the British Association for Project Management (APM) calls it – is a CSF (e.g., Bryde, 2008). Likewise, along with the (organizational) project management, leadership, and governance approach itself (e.g., Müller, Drouin, & Sankaran, 2019), project management maturity (e.g., Ibbs & Kwak, 2000), procurement method and contract management (e.g., Hyväri, 2006), ownership (e.g., Zwikael & Meredith, 2021), (external) stakeholder engagement (e.g., Lehtinen & Aaltonen, 2020), and even organizational justice (e.g., Unterhitzenberger & Bryde, 2019) have all been identified as project CSFs. Moreover, learning from institutional theories, additional CSFs such as familiarity and compliance with and efficiency of the public procurement regulatory framework and professionalism of staff have been identified (Mwelu, Davis, Ke, Watundu, & Marcus, 2021). Still, despite these burgeoning lists, a brief glance at professional and scholarly journals suggests that most of the CSF research tends to focus on short-term, objective, project management success, rather than medium-term, business case success, not to mention subjective stakeholder success or long-term, green success, or societal success (Shenhar & Dvir, 2007; Ika, Meredith, & Zwikael, 2021). For example, while behavioural CSFs such as de-biasing project estimates (e.g., the application of “optimism bias uplifts”) have come to the fore, as a result of the contribution of the Planning Fallacy principle – that is, the tendency to over-promise and under-deliver in projects (Flyvbjerg, 2014) – they have largely focused on minimizing cost overruns, thus espousing a narrower and more short-term view of project success (Ika et al., 2022). In light of a much-needed reconceptualization of project success to encapsulate other issues such as the delivery of benefits and value, issues of timing, and sustainability considerations (Ika & Pinto, 2022), new CSFs continue to come to the fore. Examples include but are not limited to: applying benefits realization practices and having a sound business case from the outset (Zwikael & Meredith, 2021); agency on the part of funders and managers as they grapple with shifting internal and external environment and resort to changing leadership, strategy, governance, plans, and scope (Ika et al., 2021); agility/flexibility in the project management approach (Winch, Dongpin, Maytorena-Sanchez, Pinto, Sergeeva, & Zhang, 2021) to cope with complexity and uncertainty and increase their projects’ odds of success; project resilience, defined as the ability to adapt to and recover from pressure, adversity, distress, or disturbances with minimal effects on the project’s performance (Williams, Gruber, Sutcliffe,

Don’t ask what makes projects successful, but under what circumstances they work  81 Shepherd, & Zhao, 2017); temporal ambidexterity on their part as they deal with short-term and long-term tensions in the project (Slawinski & Bansal, 2015; Ika et al., 2021); and “sustainability by the project” (i.e., managing the project in a socially, economically, ethically, and/or environmentally viable fashion) (Huemann & Silvius, 2017). Our review shows that the majority of existing frameworks of CSFs offers a mixed bag, incorporating generic items that are relevant for all projects (e.g., clear goals, top management support, project manager competence) or broad items that are difficult to operationalize in practical or measurable terms (e.g., adaptability to change, leadership, governance), and they also include project or industry-specific items such as private vs public sector. As Hyväri (2006) notes: “the success factors are usually listed in either very general terms, or very specific terms affecting only particular projects” (Hyväri, 2006, p. 31).

CRITICAL SUCCESS FACTOR RESEARCH: FIVE GAPS CSFs confront both practitioners and scholars with a few important challenges. The chapter singles out five gaps in CSF theory and practice that warrant significant attention. Gap #1: The Underperformance Gap Practice reveals that, all too often, projects (sometimes entire classes like infrastructure or IT/ software) underperform not only in terms of their time, cost, and scope but also in terms of their target benefits and stakeholder expectations (Flyvbjerg, 2014; Denicol, Davies, & Krystallis, 2020). Whether the causes of such problems are behavioural (e.g., human bias in estimation), technical (R&D and other “discovery projects” rarely lend themselves to accurate forecasts), institutional (the result of a lack of adequate training of project staff), intra-organization cultural (the existence of a variety of toxic workplace behaviours; cf. Pinto, 2014), abusive leadership (Gallagher, Mazur, & Ashkanasy, 2015), or some other systemic pathologies, there is strong evidence that our approach to CSFs requires continuous modification and reanalysis, as we acknowledge that steps taken to adequately address this topic still struggle to keep up with the practical realities of modern project management practices. Consider one simple but important example: software project management operated with the so-called “waterfall” model of system development and implementation, featuring a structured and rigorously planned set of steps from features development to system introduction. Unfortunately, researchers and practitioners alike came to realize that this focus on project efficiency at the expense of user satisfaction was rendering project after project under-utilized or outright cancelled. At the turn of the century, an alternative project development model, agile, was introduced into many organizations with the implicit goal of shortening planning cycles and focusing on system acceptance and use over development efficiency. Success rates began to improve as professionals realized that they had been focusing their energies towards promoting the wrong set of goals (Serrador & Pinto, 2015). Gap #2: The Temporal Conflation Gap As emerging strategy theories suggest, our understanding of the factors that can improve the likelihood of project success is often muddled by a variety of external forces, impacts, and

82  Research handbook on project performance events that may be outside the direct control of project managers and organizations. That is, time plays a big role and may turn projects into success-failure or failure-success paradoxes, as we learn from time theories (Ika et al., 2021, 2022). For example, some projects that were initially deemed as failures at their completion, such as the Sydney Opera House, became resounding business successes over time, while others, like the second generation of Ford Taurus and the Los Angeles Red Line Metro, which were considered successes at their completion, were ultimately business failures. There is a tendency, especially with high-profile projects such as public works or infrastructure, to focus too quickly on assessments of their value, which, history and experience tend to strongly argue, typically occur too early or before adequate time has elapsed to offer a reasonable assessment. Gap #3: The Context Gap As we learn from contingency and institutional theories, some classes of projects may be highly successful in a given setting and then fail, either partially or completely, in another setting, making context particularly important in understanding what makes projects successful (Ika & Donnelly, 2017; Chipulu & Vahidi, 2020; Pinto et al., 2021). Indeed, Engwall’s (2003) point that “No project is an island” is especially important in that it militates against a “one and done” attitude, where organizations assume that having accomplished a particular challenge once implies that the steps can simply be replicated in other settings. For example, China’s massive, multi-trillion (USD) “Belt-and-Road” infrastructure initiative has had a mixed success rate in achieving the goals of cultural and economic integration because of the resistance of ethnic minorities in some parts of the country (Li, Liu, & Qian, 2019). Gap #4: The “Complexification” Gap The idea of success factors assumes a probabilistic nature of what constitutes project success and downplays the complexity and uncertainty associated with the delivery of many projects. Success factor research implicitly conjectures that all the relevant alternatives, probabilities, and consequences when we make decisions can be known. In other words, if we can learn from past projects and work on their best-practice success factors, we can repeat success in our current projects. Yet, this assumption may fall short for the more complex projects, for which many decision variables are unknown or unknowable (Love, Ika, Matthews, & Fang, 2022). We should realize that “success is, in fact, a dangerous guide to follow too closely” (Petroski, 2013, p. 23). Thus, it is important to understand that it might be virtually impossible to replicate the CSFs that prevail “in advance of the project” or “in the wake of the project” (Hirschman, 1967, p. 146). To put this argument in a slightly different way, if we go into a project assuming a priori that there is a clear and defined set of CSFs to which we must pay heed in order for the project to succeed, we ignore context and contingency, a point we raised in our third argument. For us to depend too heavily on formulaic approaches to the application of CSFs is to remove critical reasoning and the recognition of special circumstances or contexts within which we are managing projects.

Don’t ask what makes projects successful, but under what circumstances they work  83 Gap #5: The External Environmental Impact Gap Recent CSF literature reviews suggest we may have reached a point in time where CSFs are more strategy-, organization-, and stakeholder-related (Jugdev & Müller, 2006; Ika, 2009; Wang et al., 2022). For example, Pinto and Slevin (1988) note that while CSFs such as project mission and top management support are more or less under the control of the project manager and team, others may be outside their control: characteristics of the project team leader, power and politics, environmental events, and urgency. Yet, project management research has not fully examined the CSFs associated with the external environment. This latter gap is an important issue that we will address in more detail below. For now, consider the implications of our changing understanding of project success, from its earlier conceptualization as the simple “iron triangle” of time, cost, and quality to one that has evolved to recognize an increasing complexity: not only to the customer and the project organization, but to the larger environment, as well as society as a whole (Pinto et al., 2021; Ika & Pinto, 2022). Research on CSFs, however, has not proceeded in the same evolutionary manner, with much of the recent work still locked into an emphasis on project execution efficiency, and categorizing a relatively limited set of factors (Fortune & White, 2006). Thus, the clear question emerges: can we be confident in our sets of CSFs if we no longer understand what “success” actually means?

MOVING FROM SUCCESS FACTORS TO SUCCESS CONDITIONS CSF researchpresents us with a paradox: we seem to know why project management or business cases fail or how projects can be successful, yet they still fail; a lot. This paradox suggests that CSF research continues to fall short of its ambitions. Indeed, in light of the above five gaps in CSF research, it is not surprising that there still prevails (Fortune & White, 2006; Ram & Corkindale, 2014; Ika & Donnelly, 2017): ● a lack of consensus among scholars on which of the CSFs are really “critical” ● a dearth of exploration of the empirical interrelationships between different CSFs ● a variety of competing theoretical explanations attempting to explain why projects succeed or how they can succeed ● a narrow focus of the literature on short-term, project management success, or the old “iron triangle” of time, cost, and quality, rather than business case, stakeholder, green, or societal success ● a propensity to take CSFs as being essentially static, rather than dynamic or evolving over the life cycle of the project ● a tendency to offer little guidance in terms of practice, especially as project success knowledge often occurs in hindsight, not foresight ● a lack of emphasis on complexity and uncertainty ● a mismatch between research on success criteria and research on success factors; that is, the expansion of success criteria has significantly outpaced our ability to predict project success. Thus, CSF lists need constant upgrading to address newly introduced measures of project success; e.g., sustainability or net-zero criteria.

84  Research handbook on project performance Hundreds of success factors have been proposed over the years to the point that it has been suggested, in a tongue-in-cheek manner, that any new scholar that proposes a new CSF should be required to eliminate two existing CSFs (Ika, Diallo, & Thuillier, 2012, p. 114). As Dalcher (2012, p. 656) notes: Ironically, the idea of critical success factors was meant to address success in a different fashion. Rockart (1979) asserted that there were a small number of critical factors that were specific to a manager and critical to their success. These factors were therefore specific rather than general. Indeed, Rockart asserted that one could not generate a generic list of factors.

Another significant problem with this continuous, incremental identification of new CSFs is that we simply add them to a steadily lengthening list, without attempting to address them jointly in real project settings. Thus, new CSFs are constantly being proposed and, within reason, empirically proven; however, much of this current generation of research lacks a willingness to examine new CSF candidates within the larger pool of all items, thereby potentially minimizing joint and even contradictory effects of CSFs. Specific project classes, settings, and other contingency variables are still highly relevant to the study of CSFs, but the lack of larger studies of multiple constructs constrains our understanding. We argue that project management research should abandon the narrow and unproductive quest for universal, non-contextual, project success factors (e.g., Dvir et al., 1998; Ika, 2009). In light of the complexity and uncertainty associated with the delivery of projects both in the short and long terms and the differing if not conflicting perceptions of stakeholders on project success, we propose a switch from success factors to success conditions. Notably, while CSF research has focused a lot on things such as events that affect project success (Ika, 2009), it has rarely focused on success conditions (see Table 7.2 for rare exceptions). This needs to change! Turner (2004, p. 349) defines project success conditions as “things that must be in place before a project can have a successful outcome.” We take this definition as a point of departure but note that it offers a static conceptualization of success conditions. Indeed, events (both positive and negative) occur in a project and the conditions that must be in place for the project to succeed may change and others may arise as time goes by. As Ika and Donnelly (2017) and Ika et al. (2021) demonstrate, there are initial success conditions that prevail before the business case approval and emerging success conditions that arise after the business case approval (e.g., during project execution or at the operations or benefits realization phase). Hence, following Ika and Donnelly (2017), success conditions are the necessary states of being; that is, circumstances or prerequisites that must exist or emerge for project success to occur. As they include the circumstances that exist prior to the business case approval or that emerge thereafter, success conditions could help make more progress. Indeed, they can, in contrast to success factors, deal with key issues such as environment, time, and complexity/uncertainty that impact project outcomes including project management, business case, stakeholder, green, and societal success. Consequently, instead of asking what makes projects successful, we should rather ask: under what circumstances do projects work and more importantly (Ika & Donnelly, 2017, p. 59): “What is occurring in the project setting that prompts us to believe that project success will occur?” To be sure, we are not the first authors to highlight the concept of success conditions. Hirschman (1967, p. 188) submitted that much “remains to be done in understanding the conditions for failure and success of projects.” He then advised looking into what happens before and after the project as this constitutes the essence of “the dilemma of design” (p. 146).

Don’t ask what makes projects successful, but under what circumstances they work  85 Table 7.2

Four key frameworks of success conditions

Murphy et

Clearly established specifications and design

al. (1974)

Realistic schedules Realistic cost estimates Avoidance of buy-ins Avoidance of over-optimism Favourable interface with legal-political environment Conceptual clarity

Morris &

Positive attitude to success shared by all parties

Hough

Workable properly defined project, careful monitoring of external factors

(1987)

Clear understanding of the impact of the definition on the schedule and finance Implementation structure cognizant of organization and contracting with clear communication and controls Good, well-qualified personnel, and tolerance towards errors, even with the greatest experts

Turner

The success criteria should be agreed with the stakeholders before the start of the project, and repeatedly at

(2004)

configuration review points throughout the project A collaborative working relationship should be maintained between the project owner and project manager, with both viewing the project as a partnership. The project manager should be empowered, with the owner giving guidance as to how they think the project should be best achieved, but allowing the project manager flexibility to deal with unforeseen circumstances as they see best The owner should take an interest in the performance of the project

Ika &

Structural conditions:

Donnelly

Legal/regulatory frameworks

(2017)

Financial resources Contextual environment Institutional conditions: Beneficiary organization capacity: Accountability/public participation Capability to commit New technical expertise Capability to attract resources Capability to manage diversity Capability to adapt knowledge and skills Implementing agency capacity: Capability to commit New technical expertise Capability to attract resources Capability to manage diversity Capability to adapt and self-renew Managerial conditions: Project leadership Project monitoring Project design Stakeholder coordination Meta-conditions: Multi-stakeholder commitment Collaboration Alignment Adaptation

86  Research handbook on project performance He further cites “a minimum of mutual toleration and understanding” between the parties involved in the project as a vivid example of a critical condition for its success (p. 150). Moreover, context, institutions and project management circumstances – whether existing or emerging – matter for the manifestation of project outcomes. Consider, after Ika and Donnelly (2017) and Ika et al. (2021), three success conditions, whether they occur before or after the business case approval: (1) Structural or political, economic, physical/geographic, sociocultural, historic, demographic, and environmental circumstances; for example, as noted earlier, the economic condition of “the US’s great recession” delayed the start of the Honolulu rail project. (2) Institutional circumstances such as governance, principal–agent, corruption, organizational capabilities, and compliance with the legal procurement regulatory framework; for example, in the case of the Honolulu rail project, the winning contractor bid did not deliver value for money. (3) Managerial or initiation, planning, implementation, monitoring and evaluation, benefits realization problems, behavioural factors, managerial agency, agility, temporal ambidexterity, and “sustainability by the project”; for example, there was poor planning, over-optimism, and mismanagement in the Honolulu rail project. Table 7.2 also points to four meta-conditions after Ika and Donnelly (2017): multi-stakeholder commitment, collaboration, alignment, and adaptation, which are in interrelationships with the above threefold categories of success conditions. Ika and Donnelly (2017, p. 61) termed these “meta-conditions” “as they appeared to incorporate not only the structural, institutional, and project management conditions but also provided a stronger link between and project context and success factors such as supervision, monitoring, design, coordination, consultations, understanding the project environment, competency of project staff.” Moreover, as perceptions of project success also depend on who you ask, we propose that success conditions should be appreciated by internal stakeholders such as project funders and managers and they should agree on a shared, inter-subjective appreciation of those success conditions in order to make decisions and enact them in a timely manner, through managerial agency (Ika et al., 2021). This set of success conditions are more practitioner-friendly as they hold the potential of a “diagnosis” instrument. In a manner similar to other professions like meteorology or medicine, project management can also benefit from the use of “diagnostic” conditions to gauge the state of their projects and make changes to increase the likelihood of a positive outcome. Project managers can use the presence or absence of the conditions to assess the likelihood that success will (or will not) occur and adjust their project practice accordingly. For instance, the presence of strong alignment and adaptability conditions may indicate the possibility of novel adjustments to changing environmental circumstances or, as mentioned earlier, indicate the potential of a project intervention to expand or scale out. (Ika & Donnelly, 2017, p. 59)

Figure 7.1 displays the success conditions and Table 7.3 offers practical guidance in terms of how to apply the meta-conditions.

Don’t ask what makes projects successful, but under what circumstances they work  87

Source: Adapted from Ika and Donnelly, 2017.

Figure 7.1

Project success conditions

Table 7.3

Meta-conditions and their practical application (adapted from Ika & Donnelly, 2017, p. 58)

Meta-

Process (how conditions are achieved)

Application

Multi-

Attainability of objectives (strengthened

Attainability of objectives

stakeholder

commitment)

Break down objectives, make them attainable; regular

conditions

engagement

commitment

Collaboration

Demonstrating project value (strengthened

Demonstrating project value

commitment)

Build narrative; provide tools; create sharing opportunities

Ability of stakeholders (enabled effective

Ability of stakeholders

collaboration)

Complementary teams; mutual accountability through joint ownership

Inclusiveness (enabled effective

Inclusiveness

collaboration)

Create spaces for interaction; mediate tension; facilitate partnerships

Alignment

Planning and design (contributed to

Planning and design

alignment)

Plan incrementally; involve implementing stakeholders in

Mutual interest (contributed to alignment)

Mutual interest

design and planning stages Find the win-win-win scenario for multiple key stakeholders; timing Adaptation

Monitoring (contributed to adaptation)

Monitoring

Support (contributed to adaptation)

Support

Observe for opportunities and risks; act in a timely manner Motivate; advise; facilitate; provide guidance

88  Research handbook on project performance Finally, we would reiterate that this argument to switch from success factors to success conditions is critical, as an important paradox prevails in project management research regarding success factors and ultimate project success; namely that CSF research, voluminous though it has become over the years, is hamstrung by a fundamental misunderstanding of its relationship to project success. Since Ika’s (2009) reconceptualization of project success, numerous additional articles have identified the fact that modern project management is changing to adapt to a more complex environment within which it operates and, at the same time, the discipline is moving to include multiple new metrics, including “green,” or sustainability in project development, health and safety, success in achieving the business case, and so forth (e.g., Carvalho & Rabechini, 2017; Zwikael & Meredith, 2021; Wang et al., 2022). In effect, we have been steadily moving the goal posts. “Project success” in 2022 means a very different thing than what we understood it to mean in 1972, or even in 2002. Unfortunately, a scan of much of the current CSF literature demonstrates that this acknowledgement has been slow to take place. Scholars mostly continue to assume a narrowly focused set of success criteria, usually centred on traditional measures of time, cost, functionality/quality, and some assessment of (often internal) stakeholder satisfaction (cf. Müller & Turner, 2007). Thus, our dependent measure is evolving while much CSF literature has failed to keep pace.

CONCLUSION AND OUTLOOK Project success and CSFs remain crucial yet complex, multidimensional, contingent, and dynamic notions at the heart of project management theory and practice. As project management often fails and business cases frequently underperform and disappoint stakeholders, the quest for CSFs continues to be of interest to practitioners and scholars alike. This chapter takes stock of decades of research and updates and recalibrates the most significant literature on CSFs. The chapter highlights the importance of CSFs such as benefits realization practices, external environment, (external) stakeholder engagement, managerial agency, agility/flexibility, temporal ambidexterity, and sustainability management practices. The chapter questions CSF research and invites practitioners and scholars to abandon the narrow and unproductive search for success factors and focus instead on the investigation of success conditions in the face of complexity and uncertainty. The chapter indicates the need for empirical research to tackle the following questions: (1) Under what circumstances do projects work (or do not)? And are there other meta-conditions than multi-stakeholder commitment, collaboration, alignment, and adaptation? (2) How do emerging success conditions (e.g., after the business case approval) relate to initial success conditions (e.g., before the business case approval)? And how do meta-conditions relate to both initial and emerging conditions? (3) What’s the role of managerial agency in the (timely) response to success conditions? (4) To what extent can temporal ambidexterity of project funders and managers help in dealing with emerging success conditions? (5) How do project funders and managers come to a shared feeling on project success conditions?

Don’t ask what makes projects successful, but under what circumstances they work  89

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Don’t ask what makes projects successful, but under what circumstances they work  91 Rubin, I.M., & Seeling, W. (1967). Experience as a factor in the selection and performance of project managers. IEEE Transactions on Engineering Management, 14(3), 131–134. Serrador, P., & Pinto, J.K. (2015). Does agile work? A quantitative analysis of agile project success. International Journal of Project Management, 33(5), 1040–1051. Shenhar, A.J., & Dvir, D. (2007). Reinventing Project Management. The Diamond Approach to Successful Growth and Innovations. Harvard Business School Press. Slawinski, N., & Bansal, P. (2015). Short on time: Intertemporal tensions in business sustainability. Organization Science, 26, 531–549. Slevin, D.P., & Pinto, J.K. (1987). Balancing strategy and tactics in project implementation. Sloan Management Review, (Fall issue) 33–41. The Standish Group International Inc. (2020). Chaos 2020: Beyond Infinity. Technical report. Turner, R. (2004). Five necessary conditions for project success (Editorial). International Journal of Project Management, 22, 349–350. UN. (2015). Transforming Our World: The 2030 Agenda for Sustainable Development. A/RES/70/1. United Nations. Unterhitzenberger, C., & Bryde, D. J. (2019). Organizational justice, project performance, and the mediating effects of key success factors. Project Management Journal, 50(1), 57–70. Wang, T., Xu, J., He, Q., & Chan, A.P.C. (2022). Studies on the success criteria and critical success factors for mega infrastructure construction projects: A literature review. Engineering, Construction and Architectural Management. In press. Williams, T.A., Gruber, D.A., Sutcliffe, K.M., Shepherd, D.A., & Zhao, E.Y. (2017). Organizational response to adversity: Fusing crisis management and resilience research streams. Academy of Management Annals, 11, 733–769. Winch, G.M., Dongpin, C., Maytorena-Sanchez, E., Pinto, J., Sergeeva, N., & Zhang, S. (2021). Operation Ward Speed: Projects responding to the COVID-19 pandemic. Project Leadership and Society, 2, 100019. Zwikael, O., & Meredith, J. (2021). Evaluating the success of a project and the performance of its leaders. IEEE Transactions on Engineering Management, 68(6), 1745–1757.

8. Understanding the causes and effects of low-risk management: implementation in projects using the DEMATEL algorithm Chia-Kuang Lee, Wen-Nee Wong, Nurhaizan Mohd Zainudin and Ahmad Huzaimi Abd Jamil

1. INTRODUCTION According to Zavadskas et al. (2010), construction projects are risky in general. In Malaysia, the construction industry can be defined as one of the most challenging and risky industries as compared to the others. The activities for construction are rife with risks and uncertainties. Oliveira (2017) stated that risk can be defined as the occurrence of possibility of either positive or negative events that happen to be recognized as uncertainties. Risks can be categorized into either external or internal risks (PMI, 2013; Zhi, 1995; Abderisak & Lindahl, 2015). External risk can be defined as the uncertainties that exist outside of the project that will be influenced by the surrounding or environment factors, while internal risks are uncertainties that exist in the project itself. External risks include economic and political factors that may affect the risk management of construction projects (Adeleke et al., 2018). However, while negative outcomes or consequences can be associated with risks to projects, they also have the possibility of being seen as chances of positive events (Adeleke et al., 2018; Farooq et al., 2018; Goh et al., 2012). According to Adeleke et al. (2018), it is necessary to manage the possible risks in order to ensure there is no threat being brought to the project to ensure project success. Some of the effects that might occur because of the negative risks or negative events in the construction project are project delays and cost overruns. According to Abd El-Karim, Mosa El Nawawy and Abdel-Alim (2017), the common scenario that happens among stakeholders (contractors, clients, suppliers and owners) of the project are estimations of costs and schedules that are inaccurate. In order to adapt to any circumstances or unexpected events that might occur in the project, it is important to make both budgeting and scheduling flexible. Based on the studies by Goh et al. (2012), most of the construction firms in Malaysia only practice risk identification and qualitative risk analysis but not the risk analysis and risk response: 17.78% of organizations were willing to employ a formal risk management process in their practices or construction projects (Goh et al., 2012). One of the weaknesses of the construction industry is to cope with risks successfully. Thus, it is essential to have implementation of risk management in either projects or the companies. This could lead to improvement in profits and reputation and ensure business success.

92

Understanding the causes and effects of low-risk management  93 The causes and effects of low-risk management implementation in the construction industry need to be researched in order to intervene in the relationship between them effectively. Therefore, the objectives of this chapter are threefold: 1. To identify the causes of low-risk management implementation. 2. To determine the effects of low-risk management implementation. 3. To develop the causal relationship among causes and effects of low-risk management implementation.

2.

LITERATURE REVIEW

2.1

Risk in the Construction Industry

Risk can be explained as an event that has impact on the project objectives with positive or negative outcomes that take place in the environment (Iqbal et al., 2015). According to Iqbal et al. (2015), risk can also be defined as the exposure or the probability of occurrence to gain or loss multiplied by its respective magnitude. Based on research by Bon-Gang et al. (2014) and Zavadskas et al. (2010), risk can be assessed using various types of information. The level of risks will affect the success and implementation of risk management in the construction industry. According to the Project Management Institute (PMI) (2004), because of the involvement of different contracting parties, such as contactors, clients, suppliers and owners, the projects in construction are perceived to have more inherent risks. As construction projects involve numerous stakeholders, the possibility of risks tends to increase as they are expected to complete volatile tasks with a complex procedure and finish within a limited period (Odimabo & Oduoza, 2013). The causes of risks or uncertainties can be from different sources such as commitment from the project parties, project team performances and the condition of the environment (Abd El-Karim et al., 2017). Failure to cope with risks will cause stakeholders such as clients, contractors and the public to suffer (Zavadskas et al., 2010). Consequently, managing projects with high risks effectively remains challenging for industry practitioners (Kapliński, 2009). Therefore, it is necessary to understand the causes and effects of poor risk management that might affect the project. 2.2

Risk Management Implementation

According to the Project Management Book of Knowledge (PMBOK), risk is an uncertain event that can either be positive or negative. Olsson (2008) stated that risk is generally an event that is likely to occur and could positively or negatively affect the project outcomes in terms of the triple constraints and other relevant criteria that are related to the project performance. Additionally, risk management is considered as a process of identifying, analyzing and responding to project risks that is systematic and iterative, which helps to decrease the probability of project failure (Florio & Leoni, 2017). It consists of five steps: Risk Planning Identification, Qualitative Analysis, Quantitative Analysis, Response Planning, and Risk Monitoring and Controlling. The process helps the project team to predict the unpredictable and control the project risks. According to Carbone and Tippett (2004), it is important to have

94  Research handbook on project performance a supportive system to plan for and handle the risks and uncertainties of the project activities. It is a vital management instrument that helps to control construction project risks (Mills, 2001). However, because of the uniqueness of construction projects, there is a problem of lacking enough data to refer to when managing the project risks as there are no two identical projects. Therefore, the implementation of risk management in the construction industry is different from other industries where references are available to take up as an actuarial assessment (Elshandidy et al., 2018). Based on the Association for Project Management (2004), risk management in the construction industry needs a pragmatic approach because of its variables such as technical, engineering, innovative, procurement and strategic content. Risk management has become an essential and important element of project management (Chapman & Ward, 2003), with a direct effect on project success, since risks are usually assessed by their potential impact on project objectives (Zou et al., 2007). 2.3

Causes of Low-Risk Management Implementation

While there have been many studies conducted on project risk management, the manifestation of causes to low-risk management implementation is a less-explored topic (Kutsch & Hall, 2010). The failure in identifying and eliminating the causes for risk management will affect the practices of risk management and thus lead to adverse effects such as financial losses, delay of project, loss of customer trust, loss of competitive advantage and negative press. Therefore, there is a strong need to improve project success (Yim et al., 2015). 2.3.1 Resistance to change (A) According to Lundy and Morin (2013), employees’ resistance to change is one of the frequently encountered causes for implementing effective risk management. It happens when there is uncertainty of change or pressure. Tummala and Burchett (1999) stated that the primary reasons that caused resistance to change among employees include lack of clarity, interference with interests and reluctance to learn. Resistance to change can be one of the most powerful causes of the organization having low implementation of risk management in projects. It has effects on both evolutionary and strategic type of changes but is believed to be generally higher in strategic changes than evolutionary ones (Pardo & Fuentes, 2003). Some of the other causes include different perceptions among employees and management, barriers in communication and gaps in capabilities in organizations. All these can cause the organization to have even stronger resistance to changing to implement risk management in construction projects. 2.3.2 Lack of managerial support and communication (B) Another factor of low-risk management implementation stems from the lack of support from the top management of an organization (Liu et al., 2015). Repeated interactions and communication with the top management help to gain the confidence of employees and prevent project failure (Malik et al., 2019). Poor communication between top management and the project team will lead to risk avoidance as the employees are uncertain without direction (Bhoola et al., 2014; Aziz et al., 2019). This will affect the closeness of relationships and employee engagement in the project. Berger and Meng (2014) stated that communication is the cornerstone of determining the success of an organization as it is a two-way process that involves constructive feedback. Watson (2012) emphasized that it is essential for the organization to

Understanding the causes and effects of low-risk management  95 have a risk manager with excellent communication skills with employees and the project team pertaining to the implementation of risk management. 2.3.3 Low-risk attitude (C) Risk attitude refers to the orientation of an individual toward taking risks where this can vary from risk-averse (very unwilling to take risks) to risk-seeking (very willing to take risks) (Winsen et al., 2014). Every individual has their own perceptions of risk and these can cause the individual to handle risks differently based on their own perceptions. An individual’s positive and negative evaluation of characteristics of different types of behaviors represents the base of the attitude (Dikmen et al., 2018). However, this attitude can be improved and reinforced through knowledge acquisition. Absence of formal training in project risk management would impede the implementation of risk management. Training is an enabler of competency (Hanna et al., 2016). 2.3.4 Lack of resources (D) Farr-Wharton (2003) suggests that inadequate resources can result in project failure, regardless of the efforts of the team. Resources include funds, manpower, equipment and machines. A lack of resources affects the implementation of risk management in any project. According to Olsson (2008), an organization requires more than having a good project plan or monitoring and control systems and should focus on implementing effective strategies for risk management. Proper risk management may incur high costs for an organization as it includes planning, estimating, costing, financing and other forms of costs control. Organizations that do not have any experts in risk management will need sufficient training and thus increase in their expenses (Ikechukwu et al., 2017). 2.3.5 Lack of knowledge in risk management implementation (E) According to Dikmen et al. (2018), knowledge is fundamental in cultivating favorable attitudes toward project risk management. Bratianu (2018) stated that a proper risk analysis before initiating a project will help in reducing risks that may occur later in a project and this cannot be done without adequate knowledge in risk management. Besides that, it is important to understand how risk management techniques are being utilized in phases of risk management that are undertaken in a project (Dikmen et al., 2018). Organizations should also provide proper training for risk managers to ensure they are well equipped with knowledge of the project activities so that they can demonstrate and show support to the other employees. Good planning for a risk management process comes from knowledge to prevent project failure (Frese & Sauter, 2003; Zieba & Durst, 2018). Roshana and Akintoye (2005), however, stated that risk management is still rhetorical in the Malaysian construction industry due to insufficient knowledge. Therefore, it is important for the industry to reinforce both awareness and knowledge in risk management. 2.3.6 Poor risk culture in the organization (F) As early as 1998, risk culture was defined as the perception of a manager of the organization’s propensity to take risks and of the leadership of organizational propensity to either reward or punish the risk-taking (Bozeman & Kingsley, 1998). The Institute of International Finance (IIF) then referred to culture as “the norms and traditions of behavior of individuals and groups within an organization that determine the way in which they identify, understand,

96  Research handbook on project performance discuss and act on the risks the organization confronts and the risks it takes” (Wood & Lewis, 2018). According to Bostanci (2013), risk culture is extremely important for risk management practices in an organization. Risk culture can affect all risk management-related activities and ultimately decides whether risk management structures, methods and procedures will benefit or damage an organization (Paalanen, 2013). 2.4

Effects of Low-Risk Management Implementation

Risk management implementation is very important in the construction industry as it can reduce project failure (Wang & Moczygemba, 2015). A construction project may be defined as successful when it has satisfied the time, cost and quality constraints. A successful project should achieve satisfaction for all stakeholders (Chan & Kumaraswamy, 1998). However, many of the construction companies tend to skip this as they see it as time-consuming and increasing project cost. Failure in implementing proper effective risk management will cause more impact to the project. 2.4.1 Project delay/time overrun (G) Project time overrun is defined as an extension of time beyond the contractual time as per agreed stage (Endut et al., 2009). According to Shi, Cheung and Arditi (2001), the impact of project delay often relates to the completion of the project. Sweis et al. (2008) mentioned that almost all types of construction projects experience delay. According to Al-Momani (2000), schedule delay has always been one of the major causes of project failure in Malaysia. Ballesteros-Perez et al. (2015) also stated that delays in construction projects are recognized as one of the most prominent in the industry. Based on Dandage, Mantha, Rane and Bhoola (2017), delays in the schedule will directly affect the project cost due to the inflation, contract termination and resulting delaying damages. This is often defined as mismanaged event(s) and is one of the project risks. Delays in the schedule will cause even more negative effects to the project stakeholders such as contractors, clients and the project team. The impact of delaying in construction projects is not just limited to contracting and consulting the clients but also extends to the national economy, especially in developing countries (Faridi & El-Sayegh, 2006; Al-Kharashi & Skitmore, 2009). 2.4.2 Cost overrun (H) Cost overrun can be defined as an extra cost beyond the contractual cost agreed during the tender stage (Endut et al., 2009). According to Enshassi et al. (2009) and Sweis et al. (2008), cost overruns have frequently happened in construction industries in many developed and developing countries. It is also among the most common phenomena in the construction industry (Koushki et al., 2005; Ikechukwuet al., 2017). The construction industry plays a vital role in the socio-economic growth of the country, especially in developing countries; therefore, it is important to ensure the project is completed within budget as this affects the overall development of the country. Based on a global study on construction project performance by Flyvbjerget al. (2003), cost overrun was identified as the major problem where nine out of ten projects faced overrun in the range of 50% to 100%, and this had immediate consequences for the stakeholders and country’s economy (Flyvbjerg et al., 2004). Angelo and Reina (2002) stated that the problem of cost overrun is critical and needs to be further studied to alleviate

Understanding the causes and effects of low-risk management  97 the problem in future as it can cause a slower payout and reduce early return on the investment made. 2.4.3 Accidents (I) According to Idris (2019), accident risk in the construction sector is higher as compared to other sectors. The accidents that happen on construction sites not only increase the fatality rates of workers but also have a huge impact on the company. Páez and Mejía (2011) mentioned that current industrial health and safety uses common corresponding standards but they are poorly applied and thus generate difficulties in project development associated with risks; if these risks are not proper evaluated, they can end up affecting the regular progress of the construction work (Alkhadim et al., 2018). The numbers of site accidents and deaths related to work are still alarmingly high despite the efforts to improve the performance of health and safety in the industry. According to Lee, Chen and Fo (2018), accidents that occur at construction sites are either caused by the negligence of the company or the workers themselves, which will affect the operation of construction. However, accidents that are caused by the human factor can be avoided by having a proper and effective risk management implementation. 2.4.4 Conflicts/disputes (J) Conflict can be defined as “a clash between hostile or opposing elements or ideas” (Guan, 2007), while a dispute is “any contract question or controversy that must be settled beyond the jobsite management” (Diekmann & Girard, 1995). According to Verma (1998) and Rauzana (2016), conflict is inevitable and unavoidable in a project as the project stakeholders have different perceptions in the construction industry. Conflict often arises in the consecution phase of a project when the team fails to meet the stakeholders’ expectations. This issue remains a challenge in the industry as it has high potential to lead to project failure (Walton & Dutton, 1969; Kassab et al., 2010). Therefore, it is essential for the organization to be aware of the importance of implementing risk management to the projects in order to minimize any of the damages that might occur. 2.4.5 Failure to meet desired quality and requirements (K) Ultimately, the importance of risk management is to enhance the project performance and meet the required standards for its quality (Flanagan & Norman, 1993; Malik et al., 2019). Sabariyahe et al. (2010) stated that the basic elements of project success are measured in cost, time and quality performance. As different parties have different perceptions of the term “quality”, the broadest sense of quality might change along the project’s life cycle (Chionis & Karanikas, 2018). According to Jin and Yean (2006), risk management is essential in influencing the performance of a successful project. There is a close relationship between effective risk management and project success (Wadesango & Shava, 2018). The risk identification process will help in identifying the potential risks that might influence the objectives of a project (Baloi & Price, 2003). Moreover, Sundarajan (2004) stated that there will be consequences such as cost overruns, project delay, changing capital structure and poor quality of the end product if the risk events are not handled and managed properly. Therefore, it is essential to have proper mitigation strategies against the risks to ensure the desired performance of the project can be achieved.

98  Research handbook on project performance

3. METHODOLOGY 3.1

Systematic Review

A systematic review has been done to achieve objectives 1 and 2. It was first started by framing the research questions for review. Based on Ke et al. (2009), search keywords must be set to meet the requirements of the study. Next, the data sources were selected for this study. It is important to select a comprehensive and extensive search from relevant database and journals (Khan et al., 2003). Appropriate journals that are related to the study were obtained and the “Scopus” database was used for the whole systematic review process. Then, a preliminary search was done using the search keywords within the defined specific elements such as the titles, keywords and abstract. This ensured the consistency of the search results. The keywords for this study included “Project Risks” and “Construction Risks” with the document type of “Article or Review”. To assess different qualities, the articles and journals from the search results were then analyzed. They were filtered and limited to the subject areas such as “Business, Management and Accounting”, “Decision Sciences”, “Economics, Econometrics and Finance”, “Energy”, “Engineering”, “Environmental Science” and “Social Science”. The process was then continued by conducting a detailed review of the remaining filtered articles and journals related to the topics of interest. 3.2

Decision-Making Trial and Evaluation Laboratory (DEMATEL) Method

3.2.1 Introduction to the DEMATEL method DEMATEL (Decision-Making Trial and Evaluation Laboratory)is used to achieve objective 3 of the study by developing the causal relationship among the causes and effects. DEMATEL method was first introduced in 1972 by the Science and Human Affairs Program of the Battelle Memorial Institute of Geneva. It aimed to study the complex and intertwined problematic group. According to Gabus and Fontela (1972), it has been used to assist in solving many global complex problems such as scientific, economic and political issues by considering the attitudes of experts involved. It is now widely accepted as one of the best tools to solve the cause-and-effect relationship among the evaluation criteria (Liou et al., 2007; Tzeng et al., 2007; Wu & Lee, 2007; Lin & Tzeng, 2009; Sujak et al. 2018). According to Wu and Tsai (2011), DEMATEL can help in identifying the interdependencies between the factors of the same level in a decision-making network structure using the relations of cause-and-effect between the factors. DEMATEL generates an Impact-Relation Map (IRM) effectively. 3.2.2 Procedures of the DEMATEL method Step 1: collect experts’ opinion and calculate the average matrix Z The opinions of the experts/targeted respondents were collected by interviewing them using the designed questionnaire. Each expert was required to give their opinion using an integer score through a pair-wise comparison. The degree to which the expert perceived factor i effects on factor j is denoted as xij . The range of the integer score is respectively from 0 (no

Understanding the causes and effects of low-risk management  99 impact), 1 (low impact), 2 (moderate impact), 3 (high impact) to 4 (very high impact). The integer score was automatically set to zero (0) when i = j. An n x n

zij 

1 m k  xij (8.1) m i 1

The factor that has a higher integer score indicates that the greater improvement in i is required to improve on j. The average matrix is also named as initial direct-relation matrix Z. It helps to indicate the initial direct effect that each criterion exerts on and receives from other criteria. Step 2: create and compute the normalized initial direct-relation matrix D The normalized initial direct-relation matrix D = [ d ij ], where all the values in the resulting matrix D are ranged between [0,1]. The formula used is shown below: D=

λ

* Z

(8.2)

or

 dij  nxn

=

 �  zij 

nxn

(8.3)

where

  1 1   (8.4) ,   Min  max 1  i  n n  z  max 1  i  n n  z    j 1  ij   i 1  ij    All the elements in this normalized initial direct-relation matrix D will only fall within the range between zero and one. Step 3: attain the total relation matrix T The total-influence matrix T was obtained by utilizing the equation of which I is an

T  D  I  D  in 1

n x n identity matrix. The element of tij represents the indirect effects that

factor i had on factor j, and the matrix T reflects the total relationship between each pair of system factors.

T  D  I  D

1

(8.5)

100  Research handbook on project performance Step 4: compute the sums of rows and columns of matrix T In the total-influence matrix T, the sum of rows and sum of columns were being computed separately using the following formulas. They are represented by vectors r and c, respectively.

r   ri nx1  c  c j 

'

 t  n

(8.6) j ij nx1 n

lxn

'

   jtij  (8.7)   lxn

'

c j  is denoted as the transposition matrix. th Let ri be the sum of i row in matrix T. The value of ri indicates the total given both direct

where

and indirect effects that factor i has on the other factors. th Let c j be the sum of the j column in matrix T. The value of

c j shows the total received

both direct and indirect effects that all other factors have on factor j. If j=1, the value of (ri + c j ) represents the total effects both given and received by factor i. In difference, the

(ri − c j ) shows the net contribution by factor i on the system. In addition, when (ri − c j ) is positive, factor i will be the net cause. When (ri − c j ) is negative, factor i will be

value of

the net receiver (Tzeng et al., 2007). Step 5: set a threshold value (α) It is necessary to set up a threshold value in order to obtain the diagraph. According to Yang (2008), this calculation aims to eliminate some minor effects elements in matrix T as the threshold value is set to filter out some of the insignificant effects. The directed graph will then only show the effects that are greater than the threshold value as it represents the average of the elements in the matrix T. The formula used for the calculation is:

   n

n

i 1

j 1 ij

N

[t ]

(8.8)

where N is the total number of elements in matrix T. Step 6: construct a cause-and-effect relationship diagram According to Shieh et al. (2010), the cause-and-effect diagram was constructed by mapping all coordinate sets of ( ri + � c j , ri − c j ) to visualize the complex interrelationship where

 r  � c  represents the horizontal axis (x-axis) while (r − c ) represents the vertical axis i

j

i

j

(y-axis). It is also used to provide information to judge which are the most important factors and how influence affected factors. The factors that tij is greater than α are selected as shown

Understanding the causes and effects of low-risk management  101 in the cause-and-effect diagram (Yang, 2008). The plot graph that results clearly defines the interrelationship between the factors.

4.

RESULTS AND DISCUSSION

4.1

Demographic Profile

Data were collected from 17 individuals including project managers and engineers who were considered experts in the construction industry as they all had at least 10 years’ experience contributing to the industry. In order to collect the data required, a set of questionnaires was developed fitting the requirements of the DEMATEL method. The experts were then interviewed face-to-face to fill in the questionnaire. They were asked to determine the degree to which the causes and effects influence each other by answering in Likert-scale form. The background of the respondents is presented in Table 8.1. Table 8.1

Respondents’ demographic profiles

 

Frequency

Percentage (%)

Gender:

 

 

Male

11

64.70

Female

6

35.30

 

 

 

Type of company:

 

 

Main contractor

9

52.94

Subcontractor

3

17.65

Consultant

4

23.53

Other

1

5.88

 

 

 

Experience (years):

 

 

10–15

12

70.59

16–20

1

5.88

>20

4

23.53

Total

17

 

4.2

Causes of Low-Risk Management Implementation

The causes have been labeled as follows: ● ● ● ● ● ●

A – Resistance to change B – Lack of managerial support and communication C – Low-risk attitude D – Lack of resources E – Lack of knowledge in risk management implementation F – Poor risk culture in organization

102  Research handbook on project performance Table 8.2

Average matrix Z of causes

 

A

B

C

D

E

F

Sum

A

0

2.705882

2.117647

2.705882

2.705882

2.588235

12.82353

B

2.882353

0

2.352941

2.529412

2.470588

2.470588

12.70588

C

2.352941

2.294118

0

2.411765

2.647059

2.411765

12.11765

D

2.470588

2.705882

2.411765

0

2.470588

2.470588

12.52941

E

2.705882

2.411765

2.411765

2.294118

0

2.529412

12.35294

F

2.117647

2.411765

2.470588

2.470588

2.294118

0

11.76471

Sum

12.52941

12.52941

11.76471

12.41176

12.58824

12.47059

 

Table 8.3

Normalized direct-relation matrix D

 

A

B

C

D

E

F

A

0

0.211009

0.165138

0.211009

0.211009

0.201835

B

0.224771

0

0.183486

0.197248

0.192661

0.192661

C

0.183486

0.178899

0

0.188073

0.206422

0.188073

D

0.192661

0.211009

0.188073

0

0.192661

0.192661

E

0.211009

0.188073

0.188073

0.178899

0

0.197248

F

0.165138

0.188073

0.192661

0.192661

0.178899

0

Table 8.4

Total relation matrix T

 

A

B

C

D

E

F

A

4.758211

4.932154

4.651193

4.892458

4.945509

4.905279

B

4.907026

4.723028

4.630708

4.848634

4.898257

4.864234

C

4.687653

4.684002

4.295732

4.652855

4.716837

4.671347

D

4.826954

4.839227

4.57948

4.626227

4.839993

4.806484

E

4.783029

4.76682

4.525881

4.722353

4.62213

4.753721

F

4.562547

4.578364

4.35124

4.545026

4.584939

4.40132

Step 1: collect experts’ opinion and calculate average matrix Z In this phase, the essential causes and influence of causes over one another were identified with the assistance of the experts using DEMATEL. As mentioned earlier in section 3.2.2, the steps involved in DEMATEL were applied. In this step, the causes identified from the literature were rated by the experts on a scale of 0–4. The ratings indicate the influence of one cause on another. From these ratings, the average matrix Z was obtained and tabulated in Table 8.2 using equation 8.1. Similarly, all the following steps were conducted as outlined in the previous section. Step 2: create and compute normalized initial direct-relation matrix D The direct-relation matrix D was normalized using equations 8.2, 8.3 and 8.4 and the results are tabulated in Table 8.3. Step 3: attain total relation matrix T From the normalized matrix, total relation matrix T was computed using equation 8.5 and the resulting matrix is shown in Table 8.4.

Understanding the causes and effects of low-risk management  103 Table 8.5

Sum of influence received

 

SUM R

SUM C

R+C

R-C

A

29.0848

28.52542

57.61022

0.559385

B

28.87189

28.5236

57.39548

0.348292

C

27.70842

27.03423

54.74266

0.674191

D

28.51836

28.28755

56.80592

0.230812

E

28.17393

28.60767

56.7816

-0.43373

F

27.02344

28.40238

55.42582

-1.37895

Step 4: compute the sums of rows and columns of matrix T The total influences received and given by each dimension were calculated using equations 8.6 and 8.7 and the results are shown in Table 8.5. Step 5: set a threshold value (a) The threshold value was set to filter out some of the insignificant effects. The threshold value was calculated using equation 8.8 and obtained a value of  � 4.705024. Step 6: construct a cause-and-effect relationship diagram An influence diagram was created on the basis of influence of each dimension on others. It explained the role of each dimension in relation to others. The diagram is shown in Figure 8.1. The x-axis represents the degree of influence exerted by a dimension, while the y-axis represents the extent of influence experienced by a factor from others. The direction of arrows represents the influences among the factors.

Figure 8.1

Causes of low-risk management implementation

The diagraph presented in Figure 8.1 reveals the relationship among the causes of low implementation of risk management. The term +� c j shows how much importance a given factor

104  Research handbook on project performance

ri −� c j indicates whether the factor belongs to the causal group or effect group. The factor would appear to be in the causal group if its ri −� c� j value is positive and belongs to the has, while

effect group if it is a negative value. In Table 8.5, resistance to change (A) is the most important cause of low-risk management implementation as it has the largest value of ri +� c j ( r1 +� c1 = 57.61022), whereas low-risk attitude (C) is the least important cause as it has the smallest value of 54.74266). Regarding the

ri +� c j ( r3 +� c3 =

ri +� c j values, the prioritization of the importance of the causes is

resistance to change (A) > lack of managerial support and communication (B) > lack of resources (D) > lack of knowledge in risk management implementation (E) > poor risk culture in organization (F) > low-risk attitude (C). Based on the value of ri −� c j , the causes are divided into (i) causal group and (ii) effect group. i. The causal group contains the factors that have a positive value of

−� c j . The highest

ri −� c j value also indicates that it is the most critical factor that is influential in low-risk management implementation and has the greatest direct impact on others. In this study, resistance to change (A), lack of managerial support and communication (B), low-risk attitude (C) and lack of resources (D) are classified in the causal group as they have positive ri −� c j values of 0.559385, 0.348292, 0.674191 and 0.230812, respectively. Based on the matrix in Table 8.4, it is found that factors A, B, D and E had a mutual interaction as all their values are greater than the threshold value (   4.705024) . ii. The effect group contains the factors that have the negative value of influenced by the other factors. The lowest

ri −� c j and is largely

ri −� c j value indicates the factor to be the most

influenced factor in low-risk management implementation. In this study, it shows that lack of knowledge in risk management implementation (E) and poor risk culture in organization (F) are categorized in the effect group with the values of -0.433731 and -1.378949, respectively. Poor risk culture in organization (F) is also the factor that is affected most by other factors because of its lowest ri −� c j value. 4.3

Effects of Low-Risk Management Implementation

The effects have been labeled as follows. ● ● ● ● ●

G – Project delay/time overrun H – Cost overrun I – Accidents J – Conflicts/disputes K – Failure to meet desired quality and requirements

Under each perspective, the effects of low-risk management implementation were analyzed using the same DEMATEL procedures as described. Listed below are the tables and diagraph

Understanding the causes and effects of low-risk management  105 Table 8.6

Average matrix Z of effects

 

G

H

I

J

K

Sum

G

0

3.411765

1.941176

3.176471

3.058824

11.58824

H

2.647059

0

2.352941

2.882353

3.058824

10.94118

I

2.294118

2.352941

0

2.176471

2.529412

9.352941

J

2.411765

2.647059

1.764706

0

2.647059

9.470588

K

2.823529

3.117647

1.941176

2.941176

0

10.82353

Sum

10.17647

11.52941

8

11.17647

11.29412

 

Table 8.7

Normalized direct-relation matrix D

 

G

H

I

J

K

G

0

0.294416

0.167513

0.274112

0.263959

H

0.228426

0

0.203046

0.248731

0.263959

I

0.19797

0.203046

0

0.187817

0.218274

J

0.208122

0.228426

0.152284

0

0.228426

K

0.243655

0.269036

0.167513

0.253807

0

Table 8.8

Total relation matrix T

 

G

H

I

J

K

G

1.85431

2.283191

1.653441

2.225666

2.225396

H

1.949077

1.953248

1.603508

2.109564

2.125899

I

1.714367

1.884653

1.261588

1.836335

1.863109

J

1.745793

1.929322

1.413884

1.705365

1.896672

K

1.95011

2.156218

1.571968

2.104092

1.907654

Table 8.9

Sum of influences received

 

SUM R

SUM C

R+C

R-C

G

10.242

9.213657

19.45566

1.028347

H

9.741295

10.20663

19.94793

-0.46534

I

8.560051

7.504389

16.06444

1.055662

J

8.691035

9.981022

18.67206

-1.28999

K

9.690042

10.01873

19.70877

-0.32869

Threshold value,

± = 1.876977

for effects of low-risk management implementation. Table 8.6 shows the average matrix Z of effects; Table 8.7 shows the normalized direct-relation matrix D, Table 8.8 shows the total relation matrix T and Table 8.9 shows the sum of influences received. Following that, Figure 8.2 shows the causal relationship among the effects of low-risk management implementation. Based on the ri +� c j values in Table 8.9, this shows that the most important effect of low-risk management implementation is cost overrun (H) with its highest while the lowest

ri +� c j value of 19.94793,

ri +� c j value of 16.06444 belongs to the least important effect, which is

accidents (I). The importance of the effects can be arranged in the order of cost overrun (H) > failure to meet desired quality and requirements (K) > project delay/time overrun (G) > con-

106  Research handbook on project performance

Figure 8.2

Effects of low-risk management implementation

flicts/disputes (J) > accidents (I), based on the ascending order of

ri +� c j values shown in

Table 8.9. The effects are then divided into (i) causal group and (ii) effect group regarding their

ri −� c j

values. i. In this study, the effect factors classified under causal group are project delay/time overrun (G) and accidents (I) due to the positive ri −� c j values of 1.028347 and 1.055662. This also shows that factors G, H, J and K have mutual interactions with each other based on their values that are greater than the threshold value (  1.876977 ). ii. The other factors such as cost overrun (H), conflicts/disputes (J) and failure to meet desired quality and requirements (K) are categorized under the effect group with their respective values of -0.46534, -1.28999 and -0.32869. This also shows that the factor J is affected the most by other factors as it has the lowest ri −� c j value. 4.4

Causes and Effects of Low-Risk Management Implementation

By using the same DEMATEL procedure as described earlier, the relationship between causes and effects of low-risk management implementation was also examined and is shown in Tables 8.10, 8.11, 8.12 and 8.13. The causal relationship among causes and effects of low-risk management implementation is depicted in Figure 8.3.

Understanding the causes and effects of low-risk management  107 Table 8.10

Average matrix Z of causes and effects

 

A

B

A

0

2.705882 2.117647 2.705882 2.705882 2.588235 2.882353 2.882353 2.352941 2.705882 2.352941 26

C

D

E

B

2.882353 0

C

2.352941 2.294118 0

D

2.470588 2.705882 2.352941 0

E

2.705882 2.411765 2.411765 2.294118 0

F

G

H

I

J

K

Sum

2.352941 2.529412 2.470588 2.470588 2.647059 2.647059 1.882353 2.647059 2.470588 25 2.411765 2.647059 2.411765 2.411765 2.411765 2.705882 2.117647 2.352941 24.11765 2.470588 2.470588 3.235294 3

1.882353 2.470588 2.882353 25.94118

2.529412 2.588235 2.235294 2.411765 2.411765 2.352941 24.35294

F

2.117647 2.411765 2.470588 2.470588 2.294118 0

2.294118 2.470588 2.411765 2.411765 2.352941 23.70588

G

0

0

0

0

0

0

0

H

0

0

0

0

0

0

2.647059 0

I

0

0

0

0

0

0

2.294118 2.352941 0

J

0

0

0

0

0

0

2.411765 2.647059 1.764706 0

K

0

0

0

0

0

0

2.823529 3.117647 1.941176 2.941176 0

3.411765 1.941176 3.176471 3.058824 11.58824 2.352941 2.882353 3.058824 10.94118 2.176471 2.529412 9.352941 2.647059 9.470588 10.82353

Sum 12.52941 12.52941 11.70588 12.41176 12.58824 12.47059 26.23529 27.17647 21.64706 25.94118 26.05882    

Table 8.11

Normalized direct-relation matrix D

 

A

B

A

0

0.103139 0.080717 0.103139 0.103139 0.098655 0.109865 0.109865 0.089686 0.103139 0.089686

C

D

B

0.109865 0

C

0.089686 0.087444 0

D

0.09417

E

0.103139 0.091928 0.091928 0.087444 0

F

0.080717 0.091928 0.09417

0.09417

0.087444 0

0.087444 0.09417

G

0

0

0

0

0

0

0

H

0

0

0

0

0

0

0.100897 0

I

0

0

0

0

0

0

0.087444 0.089686 0

J

0

0

0

0

0

0

0.091928 0.100897 0.067265 0

K

0

0

0

0

0

0

0.107623 0.118834 0.073991 0.112108 0

F

G

0.089686 0.096413 0.09417

F 0.09417

G

H

I

J

K

0.100897 0.100897 0.071749 0.100897 0.09417

0.091928 0.100897 0.091928 0.091928 0.091928 0.103139 0.080717 0.089686

0.103139 0.089686 0

Table 8.12

E

0.09417

0.09417

0.123318 0.11435

0.071749 0.09417

0.109865

0.096413 0.098655 0.085202 0.091928 0.091928 0.089686 0.091928 0.091928 0.089686

0.130045 0.073991 0.121076 0.116592 0.089686 0.109865 0.116592 0.08296

0.096413 0.100897

Total relation matrix T

 

A

A

0.080624 0.174119 0.150403 0.173305 0.174208 0.169948 0.324178 0.336611 0.267963 0.322575 0.312134

B

C

D

E

H

I

J

K

B

0.178997 0.079949 0.157171 0.16716

C

0.15869

D

0.164626 0.172017 0.155982 0.07777

E

0.171269 0.161967 0.157161 0.157572 0.078074 0.165375 0.303306 0.303929 0.260955 0.301222 0.29989

F

0.149103 0.158458 0.155949 0.159678 0.154982 0.073947 0.287208 0.304082 0.255268 0.294202 0.293277

G

0

0

0

0

0

0

0.064978 0.188322 0.120766 0.179368 0.175866

H

0

0

0

0

0

0

0.153071 0.068844 0.131075 0.166103 0.171862

I

0

0

0

0

0

0

0.133579 0.141824 0.042477 0.134629 0.146201

J

0

0

0

0

0

0

0.138292 0.152337 0.106317 0.05923

K

0

0

0

0

0

0

0.158194 0.174855 0.117626 0.167752 0.067097

0.166239 0.165576 0.311174 0.323255 0.248352 0.314864 0.309655

0.156773 0.071765 0.159815 0.168329 0.160223 0.29505

0.30641

0.268436 0.288935 0.297301

0.164765 0.164159 0.333515 0.338954 0.25115

0.313788 0.327141

0.151008

108  Research handbook on project performance Table 8.13

Sum of influences received

 

SUM R

SUM C

R+C

R-C

A

2.486068

0.90331

3.389378

1.582758

B

2.422392

0.903282

3.325674

1.51911

C

2.331726

0.848431

3.180158

1.483295

D

2.463866

0.8953

3.359166

1.568565

E

2.360721

0.906596

3.267317

1.454124

F

2.286155

0.899227

3.185382

1.386927

G

0.7293

2.502544

3.231844

-1.77324

H

0.690956

2.639424

3.330379

-1.94847

I

0.598709

2.070385

2.669095

-1.47168

J

0.607184

2.542668

3.149852

-1.93548

K

0.685524

2.551433

3.236957

-1.86591

Threshold value,

Figure 8.3

± = 0.145972

Causes vs effects

 

Table 8.13 shows that resistance to change (A) has the highest

ri +� c j value of 3.389378 as

the most important factor in low-risk management implementation with its position at the most top-right corner of the diagraph, whereas the least important factor in this study is accidents (I) due to its lowest ri +� c j value of 2.669095 and its position at the bottom-left of the diagraph. Based on the

ri +� c j values, this shows that the prioritization of importance of these factors

can be arranged in the order of resistance to change (A) > lack of resources (D) > cost overrun (H) > lack of managerial support and communication (B) > lack of knowledge in risk management implementation (E) > failure to meet desired quality and requirements (K) > project

Understanding the causes and effects of low-risk management  109 delay/time overrun (G) > poor risk culture in organization (F) > low-risk attitude (C) > conflicts/disputes (J) > accidents (I). All the factors have been categorized into (i) causal group and (ii) effect group based on their ri −� c j values. i. In this study, all the causes of low-risk management implementation fall within the causal group based on their positive ri −� c j values. It is found that resistance to change (A) has the greatest direct impact on the effects and has the highest correlation as it has the highest ri −� c j value ( r1  c1  1.582758) among the factors. Table 8.12 also shows that all the factors in the causal group have interactions with all the factors in the effect group based on their values that are greater than the threshold value,   0.145972. ii. The effect group consists of all the effects of low-risk management implementation as they have negative ri −� c j values. The factor that is influenced the most by the other factors is cost overrun (H) based on its lowest

ri −� c j value ( r8 −� c8 = -1.948468). It can be con-

cluded that all the effect group factors are influenced by all the causal group factors and their interactions are shown in Table 8.12 and Figure 8.3.

5.

CONCLUSION AND IMPLICATIONS

Risk management is essential in influencing project success as low-risk management implementation is detrimental to projects. Previous studies have been carried out to investigate the causes and effects that may influence project success but less has been done to draw conclusions on the risk factors to be improved. By using the DEMATEL method, this study has determined the causes and effects of low-risk management implementation and the causal relationship between them in the form of diagraphs. The results show that the relationships among all causes and effects are significant. The results also show that the most critical cause of low-risk management implementation is resistance to change. Therefore, organizations should focus more on this issue in order to improve the use of risk management in construction projects. Change is always difficult in the beginning as it means new ways of doing things and people may fear the unknown. Therefore, it is important for organizations to provide their direction, goals and parameters to the employees in order for them to understand the need for change. Organizations may start off in managing resistance to change by preparing courses for their employees. It helps to provide employees with insights and better understanding of the importance of implementing risk management in projects. They can also provide training programs and workshops for the employees to get proper knowledge, skills and information on risk management in construction projects. It is very important for organizations to communicate with their employees regarding the change that is going to be made. This enables the managerial team to understand the thoughts and responses that employees have to even the simplest change. They should also encourage their employees to voice their opinions on the proposed change as this helps in reducing their uncertainties. Minimizing employees’ resistance to change helps to improve communication between the managerial team and employees. Moreover, it also helps to increase the engagement

110  Research handbook on project performance of employees in the project by encouraging them to advocate for change. Additionally, the progress of going through changes will facilitate in gaining employees’ support and go more smoothly by being open, sincere and honest. In a nutshell, the implementation of risk management in the construction industry can be improved by managing the causes carefully to minimize the impact on the project and avoid project failure.

ACKNOWLEDGEMENTS The authors would like to thank the MTUN Commercialisation Fund and Universiti Malaysia Pahang (university reference UIC191204) for supporting this study.

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9. Managing risk in Indian construction projects Chakradhar Iyyunni and Sunil Kumar

INTRODUCTION We intend to explore the impact of any series of evolving uncertainties that cloud project execution and the role of the Indian context for evaluating the performance of Indian construction projects. Poor valuation of projects, poor financing, poor governance schemes, and, finally, mismanaged project executions can plague a project. In the book An Uncertain Glory (Sen & Dreze, 2013), the authors portray an economic, social, and political scenario that helps the reader understand the story of India’s checkered development in various (also infrastructure) sectors. There are two main forces that are important to consider – state government vs. central government subject (for example, water is a state subject) and public sector vs. private sector owner or contractor organizations. The former, state vs. central subject, indicates external pressures in the form of regulations while the latter, public vs. private, involves internal performance pressures within the organizations. By managing risk in infrastructure development projects, we contend the uncertainty can be reduced. Mahatma Gandhi said that “[bridging] the difference between what we do and what we are capable of doing would suffice to solve most of the world’s problems.” This bridge is a risk management framework that incorporates appropriate risk behavior (risk neutrality as opposed to risk averseness or risk-addicted behavior) and preventive mitigations and contingent countermeasures (to avoid bias, student syndrome, etc.). Flyvbjerg et al. (2003), Samset et al. (2006), Miller and Lessard (2001), Miller and Floricel (2005), Miller and Lessard (2008), Kahneman and Tversky (1979), Kahneman and Lovallo (1993), and Tversky and Kahneman (1986) discuss the issues in the life-cycle of megaprojects and the management of risks and the global context of decisions. In the context of Indian projects, organizations also exhibit varying appetites for risk when bidding for new projects based on their current performance on their project portfolios. Unjustified preferential partnerships can cause trouble between customers and sub-contractors and can result in the incomplete accounting of changes to scope besides ignoring of variances in contractual clauses. Irrespective of the nature of organizational structure, a balanced matrix or weak/strong matrix or functional, when a strong role is not provided to the risk management function, management is being reckless and control of project performance is almost impossible. Additionally, risk-informed autonomous project teams prevent project failure. Jha and Iyer (2007) and Bhattacharya et al. (2013) discuss measures in people orientation to manage processes in project performance. Appropriate measures of risk-based communication is the norm and allows relevant stakeholders to step in and manage the risks when appropriate. In our case studies to assess attitudes on a variety of risks throughout the project life-cycle, we find that maladaptive risk behaviors can be controlled if competent personnel manage the risks. Yet, sometimes, we succeed only partially stemming from the various biases of project personnel. 115

116  Research handbook on project performance We seek a model of project team management that has learning and opportunity exploration in its DNA, thereby infusing “Hope” in all relevant stakeholders. The management of Indian projects requires multi-level interventions with strong project governance and project leadership such as that demonstrated in the construction of phase 1 of the Delhi International Airport project and the Delhi Metro project. We can assess the impact of risk and show hope by studying cascading and compounding risk conditions associated with emerging risk scenarios that arise out of shifts in multiple environmental conditions. Using quantitative risk analysis, such as Monte Carlo analysis or a combination of techniques (Iyyunni, April 21, 2016), along with applying the analytical hierarchy process (AHP), we integrate ways to deal with barriers stemming from poor forecasting to poor decision-making. There is a general pessimism about the performance of Indian public sector projects due to the same factors that influence the infrastructure industry throughout the world (Miller & Lessard, 2001). Some of these factors are primarily social (Priemus et al., 2008) and industrial psychological such as managing stakeholder engagement (Alladi & Iyyunni, 2015); i.e., the contractually negotiated best interests of each stakeholder (social factor) and within the risk appetite of stakeholders. Lack of perception or sensing environmental risks, anchoring and other biases, and lack of reward for exceptional performance can lead to risk aversion. Success in Indian Projects Many Indian construction organizations are viable due to their successful portfolio, program, and project management in the face of large, complex projects with stringent costs and schedules and VUCA (volatile, uncertain, complex, ambiguous) or BANI (brittle, anxious, nonlinear, incomprehensible) environments. Galileo said, “Measure what is measurable; make measurable what is not so.” Mindfully maneuvering multi-level social factors while monitoring technological elements is a balance that’s imperative for the project team to succeed. An insight/hypothesis this chapter considers is a normative behavior – Indian project managers do not succeed because they (and most stakeholders) expect failure and are not driven to change this status quo. However, a self-acceptance and awareness that they have a strong influence in attaining agreed project outcomes can be the difference between success and failure. Banerjee and Duflo (2011) and Duflo (2012) indicate that being hopeful can be a competency – which we interpret as building “hope in a virtuous cycle” (as opposed to a vicious cycle of pessimism), which can lead to better big or small decision-making capacity, building confidence, which in turn inspires trust and accountability (Sisodia & Mackay, 2013). The contextual basis for evaluating the performance of Indian projects is discussed as a series of evolving uncertainties that cloud project execution. We will use case studies that compound the mechanisms of risk to the impact and consequences of risk directly.

LITERATURE REVIEW The evolution of the Delhi Metro project (Dayal, 2012) reveals many failures, but there were few bad decisions or rarely a win-lose or lose-lose agreement between stakeholders. The “difference,” in Mahatma Gandhi’s statement above, between success and failure is applying the

Managing risk in Indian construction projects  117 risk lens under dynamic conditions. We integrate ways to deal with barriers stemming from poor forecasting (Sen & Dreze, 2013) to poor decision-making (Flyvbjerg et al., 2003). Industry Environment Evolving uncertainties may cloud elements of Indian infrastructure projects and impact elements of project execution such as project financing, owner commitment, and the contractual environment. Project managers’ lack of familiarity with structured decision-making or the use of decision-making tools results in either over-optimistic risk projections that stem from an under-estimation of risks, or anchoring of past experience, and/or a lack of understanding of project managers’ bias toward risk averseness. The VUCA environment is endemic to all sectors of the Indian economy. The IT industry is able to cope with similar project needs and economic environments because they use agile life-cycle models to endure fast-paced delivery, evolving/use of proprietary technologies, and the vagaries of customers’ industry’s business life-cycles. The Indian construction industry is in a similar situation. Project success depends on project type, complexity, site conditions, the owner’s disposition, and environmental conditions. Sanyal and Iyyunni (2014), Remington (2012), and Shenhar and Dvir (2007) advocate a method to characterize complexity by using industry and project team specific characterization for novelty, technology, complexity, and pace. The Achilles’s heel is the unwarranted use of a huge number of human resources on Indian projects. This large number of people working on Indian projects leads to a large number of micro-decisions made during project execution by personnel who are inadequately trained, dis-empowered, and lack the ethic of teamwork. Jha and Iyer (2007) prescribe three critical success factors, namely commitment, competence, and coordination, for Indian construction projects. Risk Management Risks can be grouped into two generic categories; i.e., internal and external factors. Internal project risk factors include the following: (1) (2) (3) (4)

delivery/operational risks technological risks financial risks, and procurement/contractual risks.

External project risk factors include the following: (1) (2) (3) (4)

political risks environmental risks social/cultural risks, and economic risks.

The organization’s senior stakeholders must ensure that the risk profile is adequate, accurate, defensible, and focuses on risk management from pre-bid to closing. A risk management

118  Research handbook on project performance program (Chapman & Ward, 2011) should include identification and quantification of assessments and monitoring and controlling of risk in the context of governance-reporting. Challenges to Effective Risk Management Flyvbjerg et al. (2003) noted that successful management of risk is tough; it is an “involved and continuously evolving process because each day, every decision made by management may eliminate some risk elements while at the same time introducing new risk elements into a mega-project’s environment.” The changes in a dynamic project environment introduce additional difficulties. PMI’s PMBOK (2015) advocates a structured and continuous process for managing risk that “involves repeatedly implementing and completing a series of steps taken in a sequential order over the entire life of the megaproject” (Chapman & Ward, 2011). Project managers use these risk-based activities to manage the technical risk of construction activity with respect to scope and quality. Project managers’ integration of risk-based actions create their organization’s risk culture by: (1) translating project strategy into tactical/operational objectives, and (2) assigning appropriate job responsibilities to each manager and employee for the management of risk. These actions support effective accountability, performance measurement, and reward, and promote operational efficiency at all levels. The organizational culture around risk must align the risk framework, process, culture, and management with organizational priorities by linking the organizational values to the management of risk, the organization’s “appetite for risk,” an organizational structure/culture that supports de-centralized control or distributed decision-making, and to available data and information to support risk management activities. Managing stakeholder engagement with external clients throughout the life-cycle of the project becomes more important. Including project stakeholders who are external to the organization recognizes the need to include anybody or anything that may be affected by the execution or existence of a mega-project. For example, external stakeholders may include the following: (1) non-financial stakeholders such as the local community in the area where the megaproject will be constructed (2) affected parties for moving utilities (3) physical environments that might be affected during the performance of the project, and (4) the local/state/central governments that must approve the mega-project. Ultimately, a risk management program is only effective if it meets the needs of both the mega-project and all of its stakeholders. Risk and Governance The London Stock Exchange and RSM Robson Rhodes LLP noted in a 2004 report that “profits are the reward for successful risk-taking in a modern competitive economy. Companies that

Managing risk in Indian construction projects  119 are overly cautious will miss opportunities and are unlikely to succeed in the longer run. Even more certain failure awaits those who take risks recklessly.” The board, senior management, and the project sponsor should all ensure project risks are managed effectively. These stakeholders have a proactive role to recognize that risks are dynamic. The dynamic risks of mega-projects (Miller & Lessard, 2001, 2005, 2008; Flyvbjerg et al., 2003; Priemus et al., 2008; Rolstadas et al., 2011) should lead these stakeholders to a proactive role in the project. Over the last three decades, risk management has evolved from the management of knownunknowns of execution risks to the management of uncertainties to, recently, the management of unknown-unknown factors such as political risks, social risks, economic risks, technological risks, legal risks, and environmental risks (Chapman & Ward, 2011). Risk evaluations may range from labor productivity, cost of materials and equipment, and capital costs to economic conditions. The Australian Securities Exchange (ASX Corporate Governance Council, 2006) also includes operational, compliance, and strategic external risks. Importantly, these risks can impact the reputation and brand of a company and investor sentiment. Further, in Russia (FERMA, 2003), organizational risk spans market risk and includes critical success factors and an understanding of threats and opportunities toward organizational objectives. Social Risks and Political Risks Management of social and political risks can be very difficult. Zurich Insurance Group’s Corporate Responsibility Manager Karin Reiter states “protecting your company can’t be achieved by insulating your operations from its interdependencies with society. Instead, business resilience requires embracing these dependencies” (Unruh, 2016, p. 1). From a systemic perspective, Japp and Kusche (2008) discuss the modernity, material, and social-conflict dimensions of social risks. Contractual, legal, and regulatory policies are not effective methods to manage social risks during execution. Different types of risks require different approaches to mitigation as suggested later. (1) Anchors for integration of communication to manage a (structural) shift in societal communication toward a focus on decisions. This approach recognizes the past is the history of data before the decision and the future is the consequence. This focus makes the “now” of time visible; it forms the fundamental basis for a concept of risk in the context of a theory of modern society. (2) Transmutation of risks. The political system promotes worries (e.g., re-election) and expectations. Japp and Kusche suggest that “regulatory/organizations” try to shift the (social) risk from political/economic to other risk types. (3) Management of social-conflict dimension by appreciative inquiry. (a) A society emphasizing responsibility for one’s own actions without social recognition could lead to violent discharge (b) The inability to identify any common ground and communication aimed at consensus is bound to fail; only a pragmatic assumption of difference can provide the basis for discourse. Here, pragmatism means abstaining from any attempt at “real” or “authentic” understanding! But there is an acknowledgment of differences.

120  Research handbook on project performance Power in Projects and Managing Social Risks Flyvbjerg et al. (2003) and Priemus et al. (2008) argue that social science should be recast as Aristotle’s practical wisdom along with Foucault’s understanding of power: the reinvigorated understanding of social phenomena by emphasizing contexts, interpretations, and an in-depth understanding of existing power relations.

MODELS OF DECISION-MAKING To better understand how Indian companies do not handle risk well, we must ask: “Why do Indian companies make poor decisions about project risk?” To answer this question, we will start by taking the models, fallacies, assumptions, and challenges presented by Tversky and Kahneman (1986), Kahneman and Lovallo, (1993), and Lovallo and Kahneman (2003) and assess them in the Indian context. Models Social scientists create metaphors as ways to understand a phenomenon. “Gambling” has been described as an apt metaphor for risk in decision-making because the consequences are uncertain and each option is, actually, a probability distribution over outcomes. This situation justifies the use of Monte Carlo simulation (@Risk, 2015; Iyyunni, 2013, 2016; Kumar, 2016; Laufer et al., 2015). March and Shapira (1987) discuss a model where managers reject the rational model in the interpretation of their role. The rational model for a decision-maker has the following characteristics: (1) business decisions are choices among gambles with financial outcomes (2) it assumes managers’ judgments of the odds are expected to maximize utility (i.e., Bayesian), and (3) it acknowledges and accepts uncontrollable risks because they are offset by the chances of gain. March and Shapira view “risk” as a challenge to be overcome by the application of skill and “choice” as a commitment to the goal, but they do not deny the possibility of failure. Decision-makers are not “Bayesian forecasters” or “optimal gamblers.” Decision-makers are subject to conflicting biases of unjustified optimism and unreasonable risk aversion. Managing the balance between these two isolation errors affects the risk-taking propensities of individuals and organizations. Fallacies, Assumptions, and Challenges March and Shapira (1987) found the following fallacies project managers hold toward decision-making. The following are fallacies espoused by project managers: (1) decision-makers have a strong tendency to believe their problems are unique

Managing risk in Indian construction projects  121 (2) decision-makers isolate current choice from future opportunities, and (3) decision-makers neglect statistics of past projects in evaluating current plans. March and Shapira (1987) also found the following assumptions are made about project managers as decision-makers: (1) Self-image: project managers idealized self-image is not as a gambler but as a prudent and determined agent, who is in control of both people and events. The reality is, however, that project managers are not in control of either people or events. (2) Cognition analysis: project managers accept “choice as a gamble” as a model for decision-making but not as the rationality for the decision. (3) Project managers do not take a large enough set of criteria to assess alternatives, thereby tilting toward poor decisions. (4) Project managers have an assumption of infinite rationality. In other words, project managers are not aware of the concepts of requisite holism or bounded rationality, which could allow for realistic assessments. Project managers’ main challenges in decision-making are as follows: (1) The fear of taking/managing risks causes an overly cautious attitude. This attitude probably results from a failure to appreciate the effects of statistical aggregation while mitigating relative risk. (2) Making overly optimistic forecasts result from the adoption of an inside view of the problem. That is, these forecasts anchor the plans and scenarios on the bias of this inside view. Saving face – i.e., protecting personal reputation – takes primacy over managing project risk. Anchoring bias works against a project manager in a typical situation of his or her sponsor telling him/her that, “if the situation has happened before, why should we allow it to happen now or if it has not happened in the past, why do you think it will happen now?” Following Kahneman and Lovallo (1993), in case study 3, we explain that a conflict between risk aversion and anchoring bias can cause timid choices. Essentially, risk aversion stems from narrow decision frames and is the price of social isolation. The lack of both inside and outside perspective and unnecessary organizational optimism leads to bold forecasts. “Managers accept risks, in part, because they do not expect that they will have to bear the consequences (somebody else will!)” (March & Shapira, 1987). This is also applicable, in our opinion, to project managers. Hope as a Capability in Managing Projects We apply Duflo’s (2012) work “Hope as a Competency” to decision-making in projects. Does hope function as a capability; i.e., are people who are not empowered, in contexts or scenarios, devoid of hope and hence make bad decisions? We answer a qualified yes to this question. Based on Duflo’s work in Banerjee and Duflo (2011) and Duflo (2012), the following sub-phenomena can be expected:

122  Research handbook on project performance Hope-deficit – “hope” intrinsically allows people to realize their potential and that anticipation of a non-rewarding, bleak future can worsen their rational capacity. It is rational not to be over-invested in a business or decision. Also, irrational entrepreneurs exhibit optimism bias (Kahneman & Lovallo, 1993). (2) Vicious circle of negative shocks – external negative shocks, outside the control of an individual, can cause stress leading to a pessimistic explanatory style (Seligman, 2006). This pessimistic explanatory style tends to promote passivity and lower resilience that leads to the inability to avoid shocks or resist them – leading to a self-fulfilling, vicious cycle. (3) Avoiding the future or non-active attitude toward the future – a psychological sanctuary may prevent or affect making tough decisions or understanding contextual risks. If managers are more prone to being blamed, they will spend less time thinking about the future and, hence, could be less likely to be protected from risks. Project managers must have a proactive orientation of dealing with situations emerging in projects. It is one of the habits of successful project managers (Laufer et al., 2015). (4) Lack of perspective and loss aversion – pessimism about “the possibility that anything can change” may lead to large losses due to extreme conservatism. This is risk aversion or may even be risk paranoia. Hopelessness destroys both the will and the ability to invest in one’s future and one’s capabilities. (1)

CASE METHOD Flyvbjerg et al. (2003) and Priemus et al. (2008) developed methodologies for dealing with specific contexts such as “emphasizing little things,” “getting close to reality,” “studying cases and contexts,” and “looking at practice before discourse.” Also, these authors recommend the embrace of communal validity supplemented by extensive analyses of power and power relations between stakeholders and to learn through immersion and by studying real-world examples that focus more on case studies. Drouin et al. (2013) have also discussed project management research methodologies via the study of case scenarios. Four case studies identify various issues that have become pertinent in the Indian context as outlined below: (1) project managers are not hands-on with risk management (2) when tools are applied without processes, the outcome is a poorer understanding of risk, which leads to (3) unjustified point-probability estimates for project risk (4) the use of expected value without the backdrop of baseline risk contingency (5) the qualitative assessments represented by a 5 × 5 matrix have become decisions, but it is not clear how the cell is assigned in the matrix (we advocate use of relative probability and relative impact measures so that the 5 × 5 matrix is effectively used), and (6) risk assessments do not get updated often enough without an embedded scan for new risks. Without the use of the above points, risk review/assessments do not yield the desired “(risk) quality” – which we define as efficiency in risk processes and the effectiveness of the risk framework.

Managing risk in Indian construction projects  123

CASE STUDY 1 Scenario: A team of 30 engineering and construction managers were given risk management training and asked to evaluate risks from certain construction contexts. The managers were also asked to evaluate/self-assess their risk appetite for each of the construction contexts. We considered two risk categories: engineering risks and construction risks. The first case demonstrates the use of risk attitude in risk assessments. This use reflects the confidence in successfully managing project risk via the appropriate strategies and tactics. We introduced a straightforward way of assessing risk appetite. We quantify the risk appetite curve (Hillson & Murray-Webster, 2012) from 1 (risk paranoid) to 9 (risk addicted) as shown in Figure 9.1.

Figure 9.1

Digitization of the risk appetite curve

Observations: (1) Engineering managers who assessed the engineering/design risks and construction managers who assessed the construction risks were both found to be risk neutral to risk-seeking/accepting (from 6 to 9). The managers agreed that they were confident in managing the said risk. (2) Engineering managers who assessed construction risks and construction managers who assessed engineering/design risks were both found to be risk neutral to risk averse (from 1 to 4). The managers agreed that, when they were asked to assess risks that they had no exposure to, they had poor confidence in managing it.

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CASE STUDY 2 Scenario: Broad Construction Company (Xu, 2014) provided a video of a hotel construction project executed at a Chinese site for use as a case study. Observations: (1) The super-fast construction of a 30-story hotel is replete with lessons ranging from detailed planning to efficient utilization of equipment and a close working relationship with local government with which the logistics is integrated with the execution (Just-In-Time) at the construction site. (2) The organization’s project prowess allowed them to repeat and sustained this type of delivery for over 15 years. (3) The story we want to make visible and highlight is the organizational policies of this company. The workers are trained and are full-time employees, and the CEO has a strong focus on workers’ interests and their families. These organizational policies create committed, competent workers (see, for example, Lutchman, 2017). (4) Another big reason for the success of Broad Construction Company stems from their exquisite planning; therefore, no (big) decisions can be made during the execution of the project and all the workers have precise instructions. The story in India, however, is that there is an “insurmountable” difficulty in obtaining local approvals from the appropriate stakeholders (i.e., decisions are made against you). None of the above four observations hold in the management of Indian projects, or Indian construction organizations or generally, for the Indian construction industry. A number of risk management next-practices are suggested in our work (Iyyunni, January 2015).

CASE STUDY 3 Scenario: Kahneman and Lovallo (1993) revealed that poor decisions are often due to the conflict between risk paranoia and anchoring bias. The following example illustrates this thought. Imagine that a project manager faces the following pair of concurrent decisions. Decision 1: Choose between: (A a sure gain of $240 (B) 25% chance of gaining $1000 and 75% chance of gaining nothing.

Managing risk in Indian construction projects  125 Decision 2: Choose between (C) a sure loss of $750 (D) 75% chance of losing $1000 and 25% chance of losing nothing. Kahneman and Lovallo (1993) found that 84% chose (A) and 16% chose (B); 13% chose (C) and 87% chose (D). The data shows the test participants preferred risk aversion when options are favorable and are risk-seeking when options are not-favorable. Observations: (1) In the Indian context, amongst project practitioners, our observations are similar in proportion, but the reasons are not precisely risk aversion or anchoring bias but, rather, notions of gain and loss. (2) The project managers who harbor these notions could be linked to the fact that Indian professionals are moving from Hofstede’s country-specific culture type of being “high” in the Uncertainty Avoidance Index (UAI). We tested this reasoning by changing the probability and impact/consequence numbers to see if the behavior would change significantly: it did not! The project managers seem “opportunistic” (i.e., they are not risk savvy), but there are no formal risk assessments; the managers are grabbing benefits when possible; the full extent of the benefits, however, may not be realized. If probability and consequence ranges/distributions are given, assessments of confidence levels within a Monte Carlo simulation (@Risk, 2015; Iyyunni, January 2015) would be easier. The simulation would also assess the combined effects of risk aversion and anchoring bias.

CASE STUDY 4 We consider risk assessment as a set of decisions (Iyyunni, 2013; Iyyunni & Purohith 2013). Scenario: The following risks are envisioned. There is a construction project with major excavations (earthwork) with unknown stratified hard and soft rock formation as site condition. The variance of subcontractors’ commitment to the project impacts the mobilization and availability of manpower. Another factor influencing the project is creating construction work-front(s) (the location of current activity in a construction project) for the remaining scope for delivering substantial progress quickly. Finally, the condition of the machinery (which usually deteriorates with time and unknown schedules of preventive maintenance). The project began in March/April of 2014 and was slated to finish June 2016.

126  Research handbook on project performance The risk management session discussed later happened in the first week of September 2015 wherein the senior project personnel were on hand including the project director, deputy project manager, and ten construction managers. Case Process/Observations: The question posed for the team to evaluate was whether overall risk increased as the project progressed. According to most classical estimates due to the fact that project personnel may be afflicted by anchoring bias, most will claim that risk reduces as milestones are achieved and sub-structures completed. This scenario ignores the compounding mechanism between risks. We used the analytical hierarchy process (AHP) technique (Iyyunni et al., 2014; Iyyunni & Purohith 2013) and expert choice software (Expert Choice, 2014) to make our assessment. The objective of this process was to assess the risk associated with the “progress of earthwork.” We used four criteria: sub-contractor manpower availability (stakeholder risk), creation and availability of work-front (execution risk), condition of machinery (technology risk, inherent risk), and nature of strata (inherent risk). The time-periods evaluated were September/November 2014, March/May 2015, and September/December 2015. The criteria weights were used for pair-wise comparisons where each comparison was estimated by two construction managers with at least 10 years of construction experience. The pair-wise comparison is shown in Figure 9.2.

Figure 9.2

Pair-wise comparison for the criteria set

The weights for each criterion are as follows: sub-contractor manpower availability (34.8%), creation and availability of construction work-front (15.3%), condition of machinery (30.2%), and nature of strata (19.7%). The key factors were: (1) the rain during July/August made the management of strata easier (2) the latter phase of the project made work-front availability harder (3) the latter phase of the project meant that there was excessive use of equipment that resulted in the poor condition of the equipment, and (4) manpower was moving away to newer projects. The sensitivity analysis of the four risks as a function of time are shown in Figure 9.3. Figure 9.3 gives a pair-wise comparison (with respect to sub-contractor availability, work-front

Managing risk in Indian construction projects  127 availability, machinery, nature of strata) between alternatives for each criterion (September/ November 2014, top; September/December 2015, middle; March/May 2015, bottom).

Figure 9.3

Sensitivity analysis of the criteria with respect to the objective

Figure 9.4 shows the evaluation of risk for the future time-period, September/December 2016.

Figure 9.4

Four criteria for overall project risk evaluation

We claim that the above assessment is reasonably robust because changes in criteria weights will not impact the overall evaluation/ranking between the alternatives. The risk during September/December 2015 was almost 20% higher than in March/May 2015, and the overall risk was reduced only 25% from the beginning of the project. Most risk texts claim that there is a rather steep drop in risk when this time has elapsed in the project. The poor risk assessment of September/December 2015 period was averted with the mitigations discussed above. The question is, “Why has a highly competent project team missed this assessment?” This requires an understanding of the interactions between risks belonging to different (project management) functional groups.

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DISCUSSION At the higher level, the challenges for risk management in the Indian project scenario are organizational in nature: be they structural, cultural, or senior management distracted by the pressures in managing program, portfolio, and governance requirements. It’s mostly a social rather than technical challenge, though the socio-technical combined effect is self-evident. (1) Herbert Simon in his Nobel Prize in Economics address (Simon, 1978) mentioned two laws of organizational behavior. The second law is “the use of the right person for each activity.” We don’t see evidence of Simon’s second law applied systematically across projects. (2) Ronald Coase, another winner of the Nobel Prize in Economics, had an insight obtained in 1937 when he noticed “decreasing returns to the entrepreneur function, with increasing overhead costs and increasing propensity for an overwhelmed manager to make mistakes in resource allocation” (Coase, 1991). Coase (1991) highlighted the risks of losing accountability via bad outsourcing practices and unnecessary activities by employees such as filling up reimbursement bills for company travel. This is endemic to construction industry globally and specifically to the Indian construction industry. (3) These risks lead to the promotion of vested interests (i.e., self-interest) over organizational interests. While the extent and impact of this problem is not clear in the Indian context, these problems are usually tagged with managerial excuses such as their “hands are tied.” This situation appears to be a poor delegation of decision-making (Loosemore et al., 2003) in the hierarchy of an organization. We have alluded to this in the literature review section. (4) She (2010) demonstrates the delineating role of trust in project alliancing. She (2010) highlights that trust between organizational stakeholders is an important attribute for conscious cultures. Trust is necessary to create a conscious organization that has a sense of purpose, strong stakeholder integration, a conscious culture and management, and conscious leadership (Sisodia & Mackay, 2013). This concept or trust can be applied to projects and create a useful project governance model. Infrastructure projects are a reflection of the social milieu (Miller & Lessard, 2001), and India is no exception. In India, the economic growth is not linked to increased human capability (Kumar, 2016), and project organizations reflect the societal structures (Flyvbjerg et al., 2003) as evidenced by a (1) lack of trained resources and (2) no freedom to the higher-paying jobs for the unskilled workers. This situation illustrates the fallacy of shared trust in decision-making in the Indian context. In India, project team members focus on managing the boss’ expectations rather than meeting project objectives and is a major organizational condition that is managed poorly. In the short run, the manager wins and the project objectives lose. Harvey (2007a) suggests using group methods to create processes to avoid the Abilene paradox or mismanaged agreement to help avoid the risk of the poor understanding and management of group emotion (Adams & Anantatmula, 2010). Harvey (2007b) also suggests mitigating this risk through straightforward interactions based on eschewing negative fantasies, assessing real risks, and accountability based on values and ownership.

Managing risk in Indian construction projects  129 (1) Dainty et al. (2005) discusses human resources management from the different perspective of behavioral competencies. Jha and Iyer (2007) and Lutchman (2017) discuss the need for focus on the commitment, coordination, and competence aspects of people management. Lutchman’s people-readiness model based on the commitment and competency requirements of the people engaged in projects is crucial. This commitment stems from (a) meaningful work (including motivation, purpose, challenge, autonomy, etc.) (Amabile & Kramer, 2011) and (b) managing the base level of Maslowian needs of taking care of safety and security of their family members; this is not the state of the Indian construction worker (Kumar, 2016). (2) The Delhi Metro Rail Corporation project team suggests a host of steps to manage stakeholder sentiments that led to satisfying overall expectations (Dayal, 2012) and, hence, success of the project. The interpersonal working relations (amongst stakeholders) are excellent – as per the TACTILE model spelled out by Sisodia and Mackay (2013), the project should be a success – and it was. (3) Laufer et al. (2015) suggest a number of leadership and communication strategies, such as develop collaboration, integrate planning and review with learning, prevent major disruptions, maintain forward momentum – for project managers to contend with stakeholder management and leading teams. Based on Dayal (2012), Sisodia and MacKay (2013), and Laufer et al. (2015), we see that potentially successful strategies are available for project managers. With these available strategies and if Indian project managers understand their strengths and surrounding culture, then we have a competency issue (Coase, 1991; Lutchman, 2017) which is not understood by the construction managers for managing their effectiveness and delivering on project objectives. (4) The practice of “good human behavior practices” supports agency and development (i.e., motivation, alignment, and increased competency) (Iyyunni, January 2015), and Dainty et al. (2005) provides the basis for regaining hope in project execution. (5) Further, the addition of Sushil’s (2005) flow-stream strategies in the project context provides huge opportunities for raising the hope and success for project managers. (6) Henisz et al. (2014) have worked on developing a perspective for managing local community stakeholders which is yet to catch on with the government, private owners, or construction (main) sub-contractors in Indian construction projects. These strategies help to manage the social risks of projects – which are as important within the organizational context as in the external context. (7) Loosemore et al. (2003) show that a key characteristic of construction project environments is their unpredictability relative to static production industries. Briscoe and Hall (1999) discuss the demands a project places upon managers to respond flexibly to rapidly changing circumstances so that they can re-plan and re-focus their strategies for meeting competing project objectives. Together, these conditions make it imperative for project managers to have a strong “future orientation” that is risk neutral and, in the face of crises, use proactive or preventive tactics (Remington, 2012) to navigate through these challenges. (8) Dainty et al. (2005) evaluated 43 characteristics for understanding a role-based competency evaluation and developed a predictive model for construction project managers’

130  Research handbook on project performance performance. Two parameters of particular interest here are self-control and team leadership. (a) “Self-control” consists of a number of elements including self-motivation, enthusiasm, self-discipline, and ambition, along with time management and taking initiative, reasoned and considered decision-making, and analytical and conceptual thinking. (b) “Team leadership” consists of managing team socio-dynamics (see also Adams & Anantatmula, 2010) and a clear, single-minded approach to decision-making. Chinowsky et al. (2008, 2010; Chinowsky & Songer 2011) give a detailed characterization and methodology for managing the social (and stakeholder) milieu.

CONCLUSIONS Duflo’s (2012) hope as a competency, capacity, and capability has been explored above. The challenge with managing risk is dealing with the hopelessness, in the Indian context, that stems from partially competent teams, workers’ lack of commitment, and organizations being overly focused on profit margins. Hope Model We propose a “hope model” for risk attitude, which forms a virtuous cycle of the following elements: (1) Competence (knowledge, skills, experience, exposure) (Lutchman, 2017) (2) Role (effectiveness and/or stress) (Pestonjee, 1998) (3) Opportunity (4) Understanding risk/consequence of action or in-action (Banerjee & Duflo, 2011) (5) Emotional intelligence (Goleman, 1995) (6) Managing interpersonal relationships (through transactional analysis) (7) Curiosity for options and disciplined experimentation (Banerjee & Duflo, 2011) (8) Team support (Kloppenborg et al., 2003) (9) Organization support (Kloppenborg et al., 2003), and (10) Failure immunity (Matson, 2013). This simple model addresses Duflo’s (2012) challenge of the hopelessness and Harvey’s (2007a) contextual analysis of vicious cycles in both interpersonal relationships and as “mismanaged” agreements in teams. The list of parameters in the model and their qualitative strength were discussed in-depth in a four-hour training session with 30 construction managers from Water Infrastructure projects of a large infrastructure construction contractor.

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REFERENCES Adams, S. L. and Anantatmula, V., “Social and behavioral influences on team process,” Project Management Journal, September 2010, 41(4), 89–98. Alladi, A. and Iyyunni, C., “Stakeholder management: Cross sectional study”, PMI India Research & Academic Conference, Mumbai, February13–15 2015. Amabile, T. and Kramer, S., Progress Principle, Harvard Business Review Press, 2011. Banerjee, A. V. and Duflo, E., Poor Economics: A Radical Rethinking of the Way to Fight Global Poverty, Public Affairs, 2011. Bhattacharya, S., Momaya, K. S., and Iyer, K. C., “Strategic change for growth: A case of construction company in India,” Global Journal of Flexible Systems Management, March 2013. Briscoe, J. P., and Hall, D. T., “Grooming and picking leaders using competency frameworks: Do they work? An alternative approach and new guidelines for practice,” Organizational Dynamics, 1999, Autumn, 28(2), 37–52. Chapman, C., and Ward, S., How to Manage Project Opportunity and Risk: Why Uncertainty Management Can Be a Much Better Approach Than Risk Management, Wiley, 2011. Chinowsky, P. S., and Songer, A. D., Organization Management in Construction, Routledge, 2011. Chinowsky, P. S., Diekmann, J., and Galotti, V., “The social network model of construction,” Journal of Construction Engineering and Management, 2008, 134(10), 804–810. Chinowsky, P. S., Diekmann, J., and O’Brien, J., “Project organizations as social networks,” Journal of Construction Engineering and Management, 2010, 136, 452–458. Coase, R. H., The Institutional Structure of Production, Nobel Prize lecture, December 9, 1991. Dainty, A. R. J., Cheng, M.-I., and Moore, D. R., “Competency-based model for predicting construction project managers’ performance,” Journal of Management in Engineering, January 1, 2005, 21(1). Dayal, A., “25 management strategies of Delhi Metro,” Delhi Metro Rail Corporation Ltd, 2012. Drouin, N., Muller, R., and Sankaran, S., Novel Approaches to Organizational Project Management Research: Translational and Transformational (Advances in Organization Studies), Copenhagen Business School Press, 2013. Duflo, E., Lack of Hope and Persistence of Poverty: Hope as a Competency, Marshall Lecture, Oxford University, 2012. Expert Choice Software, 2014, www​.ExpertChoice​.Com. Flyvbjerg, B., Bruzelius, N., and Rothengatter, W., Megaprojects and Risk: An Anatomy of Ambition, Cambridge University Press, 2003. Goleman, D., Emotional Intelligence, Bloomsbury, 1995. Harvey, J. B., The Abilene Paradox and Other Meditations on Management, Jossey-Bass, 2007a. Harvey, J. B., “How come every time I get stabbed in the back my fingerprints are on the knife? And other meditations on management,” Jossey-Bass, 2007b. Henisz, W., Dorobantu, S., and Nartey, L., “Spinning gold: The financial and operational returns to external stakeholder engagement,” Strategic Management Journal, 2014, 35(12), 1727–1748. Hillson, D. and Murray-Webster, R., Understanding and Managing Risk Attitude, Gower, 2012. Iyyunni, C., “Residual risk quantification in the engineering outsourcing industry through Monte Carlo simulation,” PMI Research Conference, January 31 to February 2, 2013. Iyyunni, C., “Insights into schedule risks from quantitative analysis,” Palisade Risk Conference 2015 – Best Practices in Risk and Decision Analysis, Mumbai, January 13, 2015. Iyyunni, C., “Project priority and pressures from portfolio management,” PMI India Research & Academic Conference, Mumbai, February 13–15, 2015. Iyyunni, C., “Razor’s edge: Managing risk in the Indian software industry,” Palisade Risk Conference 2016 – Best Practices in Risk and Decision Analysis, Bengaluru, April 19, 2016. Iyyunni, C., “Regaining hope: Ensuring Indian mega-project scope and schedule performance,” Palisade Risk Conference 2016 – Best Practices in Risk and Decision Analysis, New Delhi, April 21, 2016. Iyyunni, C. and Purohith, M. S., “Understanding uncertainty in account-specific project pipeline management via milieu analysis in engineering outsourcing industry,” Project Management (India) National Conference, September 27–28, 2013. Iyyunni, C., Trivedi, V., and Anantatmula V., “An analysis of the process in deriving further benefits of an AHP model,” International Symposium of the Analytic Hierarchy Process 2014, Washington, DC, June 30 to July 2.

132  Research handbook on project performance Japp, K. P. and Kusche, I., “Systems theory and risk” in Social Theories of Risk and Uncertainty: An Introduction, edited by Jens O. Zinn, Blackwell Publishing Ltd., 2008. Jha, K. N. and Iyer, K. C., “Commitment, coordination, competence and the iron triangle,” International Journal of Project Management, 2007, 25, 527–540. Kahneman, D. and Tversky, A., “Prospect theory: An analysis of decision under risk,” Econometrica, 1979, 47(2), 263–291. Kahneman, D. and Lovallo, D., “Timid choices and bold forecasts: A cognitive perspective on risk taking,” Management Science, 1993, 39(1), 17–31. Kloppenborg, T. J., Shriberg, A., and Venkatraman, J., “Project leadership,” Management Concepts, 2003, 1–137. Kumar, S., personal communication(s), 2016. Laufer, A., Hoffman, E. J., Russell, J. S., and Cameron, W. S., “What successful project managers do,” MIT Sloan Management Review, Spring 2015, 43–51. Loosemore, M., Dainty, A. R. J., and Lingard, H., Managing People in Construction Projects: Strategic and Operational Approaches, E&FN Spon, 2003. Lovallo, D. and Kahneman, D., “Delusions of success: How optimism undermines executives’ decisions,” Harvard Business Review, July 2003. Lutchman, C., Project Execution Management, CRC Press, 2017. March, J. and Shapira, Z., “Managerial perspectives on risk and risk taking,” Management Science, 1987, 33, 1404–1418. Matson, J., Innovate or Die, Amazon, 2013. Miller, R. and Lessard, D. R., Strategic Management of Projects, MIT Press, 2001. Miller, R. and Floricel, S., “Project risks,” in A. Manseau and R. Shields (eds), Building Tomorrow: Innovation in Construction and Engineering, Ashgate, 2005. Miller, R. and Lessard, D. R., “Evolving strategy: Risk management and the shaping of mega-projects,” in H. Priemus, B. Flyvbjerg, and B. van Wee (eds), Decision in Mega-Projects, MPG Books, 2008. Pestonjee, D. M., Stress and Coping: The Indian Experience, Sage, 1998. PMI, Project Management – Body of Knowledge, Project Management Institute (USA), 2015. Priemus, H., Flyvbjerg, B., and van Wee, B., Decision in Mega-Projects, MPG Books, 2008. Remington, K., Leading Complex Projects, Gower Publications, 2012. @Risk 6.0 Software, 2015, Palisade Corporation, http://​www​.palisade​.com/​risk. Rolstadas, A. Heltand, P. W., Jergeas, G. F., and Westney, R. E., Risk Navigation Strategies for Major Capital Projects: Beyond the Myth of Predictability, Springer Series in Reliability Engineering, 2011. Sanyal, S. and Iyyunni C., “Scope management of R&D projects,” National Conference on Industrial Engineering and Technology Management (NCIETM), National Institute of Industrial Engineering (NITIE), October 29–31, Mumbai, 2014. Samset K., Berg, P., and Klakegg, O. J., “Front-end governance of major public projects,” Concept Research Program, Technical University of Norway, May 2006. Seligman, M. E. P., Learned Optimism, Vintage, 2006. Sen, A. and Dreze, J., Uncertain Glory: India and Its Contradictions, Allen Lane Publishers, 2013. She, L.-Y., “Understanding the conditions of trust between governance and management within project alliancing.” PhD. Faculty of Architecture, Building and Planning, University of Melbourne, 2010. Shenhar, A. and Dvir, D., Reinventing Project Management: The Diamond Approach to Successful Growth and Innovation, Harvard Business School Press, 2007. Simon, H., “Rational decision-making in business organizations,” Nobel Prize lecture, December 8, 1978. Sisodia, R. and MacKay, J., Conscious Capitalism, Harvard Business School Press India Limited, 2013. Sushil, “A flexible strategy framework for managing continuity and change,” International Journal of Global Business and Competitiveness, 2005, 1(1), 22–32. Sushil, personal communication, September 2016. Tversky, A. and Kahneman, D., “Rational choice and the framing of decisions,” The Journal of Business, 1986, 59(4), S251–S278. Unruh, Gregory, “Strategies for business resilience,” MIT Sloan Management Review, September 20, 2016. Xu, D., “How to build a skyscraper in two weeks – interview of Broad Group CEO Zhang Yue,” McKinsey Quarterly, May 2014. See also www​.youtube​.com/​watch​?v​=​Hdpf​-MQM9vY.

10. Risk analytics for project success Ruchita Gupta, Karuna Jain, and Charu Chandra Gupta

PROJECTS IN A VUCA ENVIRONMENT Globalization, hyper-competition, and shorter technology and product life cycles have created an environment that is volatile, uncertain, complex, and ambiguous (VUCA), putting pressure on companies to innovate at a faster pace. Today, organizations are engaging in Industry 4.0 and digital transformation driven by convergence and integration of technologies— cyber-physical systems, Internet of Things, Artificial Intelligence, Robotics, etc. driving speed of projects in one way but also increasing their complexity. Further, this poses challenges for project managers in terms of upskilling employees. Kaivo-oja and Lauraeus (2018) mentioned a shift in mindset to tackle the challenges of VUCA—(1) a global mindset by thinking beyond geographic boundaries, valuing integration across borders, and appreciating regional and cultural diversity, (2) an innovation mindset by fostering development and the implementation of new ideas, (3) a virtual mindset, handing over activities to external providers, and (4) a collaborative mindset by engaging in business partnerships as well as entering into coopetition. Bringing this change of new mindset within the organization further adds to the new risks in projects. To mitigate the impact of a VUCA environment on projects, organizations and project leaders need to know the type and severity of challenges they are dealing with in each unique project.

UNDERSTANDING PROJECT SUCCESS A project is considered successful only if it performs according to the specified project needs. Hence, the role of the project manager is considered to be highly critical while defining and shaping the desired targets of project execution (Shao, 2018). Traditionally and most commonly a project is known to be a successful project if it is completed on time and within budget. However, the project success needs to be measured on other important parameters also (Albert et al., 2017): efficiency, impact on customer, impact on team, business success, and future (Figure 10.1). One of the recent examples of the construction of the Qatar stadium for FIFA World Cup 2022, a groundbreaking architectural achievement, revealed unethical practices and mistreatment of migrant workers on the part of contractors responsible for the various sites and developments. This attracted severe criticism from human rights groups. Can it be classified as a successful project?

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Figure 10.1  

Success measures of a project

WHY PROJECTS FAIL

Innovation (be it a product, process, service, or business model) is one of the major drivers of economic growth, and the needs of every organization are often risky and result in failure if organizations neglect or oversee the risk management process. For example, 16 failures out of 38 innovation projects were reported in European industry companies (Tepic et al., 2013; Shenhar et al., 2016). One of the critical reasons for project failure is undervaluing the measures of project success and giving high importance to only the schedule and budget. Projects fail due to project team members’ failure to carry out designated activities properly (execution). The case of Sydney Opera House (conceptualized in 1956, construction started in 1959 with a budget of AUS $7 million), where construction started before the designs were ready, indicated that the planners left gaps in the project plan by failing to anticipate all the project’s required activities and work streams (white space). The project was delayed by 10 years with AUS $102 million. Further, the case of Heathrow Terminal 5 (joint project by the British Airport Authority and British Airways, initiated in 1996 and launched in 2008 with the goal of redefining the customer experience) clearly highlights that team members executed all tasks flawlessly—on time and within budget with new technologies adopted—but did not interweave all the project elements together at the end to deliver the intended results (complexity and integration). This damaged the reputation of British Airways and British airlines with huge financial losses. Further, ignoring early warning signs given by ground staff to present the project as being certainly successful highlighted the denial and avoidance of uncertainty by the project management team. One recent example of a successful project is India’s Mars Orbiter Mission (MoM) by ISRO (Indian Space Research Organization) in 2014 (budget of $74 million, 15 months). The project credited into its account cost-effectiveness, short period of realization, economical mass-budget, miniaturization of five heterogeneous science payloads, etc. The mission to Mars gained the reputation of being a difficult space exploration as only 21 out of the 51 attempted missions turned out to be successful. The project demonstrated perfect planning,

Risk analytics for project success  135 execution, and integration with risk identification and well-crafted management strategies (www​.isro​.gov​.in). Thus, it is critical for project team to: (1) understand how components of the ecosystem might be changing (2) predict the nature of the impact and cause–effect relationships (3) know response alternatives available and predict the possible consequences of the response choice. A survey conducted by PMI in 2018 indicates that 29% of project failure happens due to the absence of risk identification and its management. Further, recently it has been seen that use of standardized risk management practices has led organizations to enhance their performance (PMI, 2021). Still, there is no accepted framework to distinguish among projects posing difficulty in understanding the characteristics and risk level of the project. Further, it has been reported that many corporations engage in innovative new product development and dedicate significant funding to them while only weakly engaging with risk analytics. The use of risk analytics to inform decision-making was valued, but was unsystematic due to insufficient training in risk analytics and its understanding (Hartwig & Mathews, 2020). The below sections attempt to highlight the dimensions of project and risk analytics.

UNDERSTANDING THE PROJECT DIMENSIONS The first and most important task when you receive a project in hand is to develop the project charter and understand its objectives, stakeholder involvement, timelines, budget, and project success parameters. Further, the right characterization of the project and understanding the project key dimensions during the initial stage of the project will aid the project manager toward project success. Risk is defined as an uncertain event or condition that, if it occurs, has a positive or negative effect on a project objective (Simon et al., 1997). Importantly, not every uncertainty becomes risk but every risk is uncertain. Uncertainty that matters to you and diverts you from achieving the project objectives is risk. One of the frameworks useful to understand the overall project risk is the Diamond Typology framework built on four dimensions: novelty, technology, complexity, and pace (NTCP),developed by Shenhar and Dvir (2007) as shown in Figure 10.2(a). The NTCP framework is useful for understanding project characteristics and enables an assessment of the overall risk of the project at large as well as at subproject level within the project and program. The diamond size depicts the risk level, and the larger the size of the diamond, the higher the risk involved, as shown in Figure 10.2(b). Novelty is not only defined by how new the product is to its markets and potential users but also indicates whether the project is incremental, modular, architectural, or radical in nature. It indicates whether the organization has dealt with similar kinds of projects in the past or if it is the first time they are doing it, and how much shift is required from current capabilities and skills to achieve the project objectives. Complexity depends on the size, number, and variety of elements and the interconnections among them. Based on complexity, projects can be categorized as assembly projects (a collection of elements, components, or modules combined into a unit that performs a single function); system projects (complex collection of interactive elements and subsystems performing multiple functions to meet a specific operational need);

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Figure 10.2

NTCP framework and risk levels

and array projects (large, widely dispersed collections of systems that function together to achieve a common purpose). In the current scenario of fast-changing technologies, understanding the technology dimension of the project becomes critical. The type of technologies to be embedded in the project will provide insights into technological know-how and its accessibility before the project enters into an execution phase. Further, it gives an initial assessment of the mode and mechanism of technology acquisition needed for the project. Super-high-tech projects are those requiring development of new technologies that do not exist at the time of project initiation, and are part of the project effort. Pace determines the project urgency and is classified as regular (delays not critical); fast-competitive (time to market is important for the business); time-critical (completion time is crucial for the success-window of opportunity); and blitz (immediate solution is necessary). Once the project riskiness is known, based on risk-benefit/ opportunity analysis, the decision to approve the project immediately, reject immediately, or put it on hold for further consideration is taken, and for the approved or projects put on hold, the risk management process is initiated.

RISK MANAGEMENT PROCESS The risk management process involves four key stages from risk identification to risk assessment to risk analysis to risk control and monitoring. The first step before identifying risk is to create a work breakdown structure (WBS) and clearly identify the work packages. Each work package needs to be looked at carefully to identify risk and plan the contingency measures for each of the work packages accordingly (Dey, 2002), as shown in Figure 10.3.

Risk analytics for project success  137

Source: Dey, 2002.

Figure 10.3

Risk management process

 

There is a strong desire to increase insights about the past, present, and future for higher-quality decisions. Risk identification is conducted by employing qualitative techniques, whereas risk assessment and analysis requires both qualitative as well as quantitative models and techniques depending upon the type of project/domain and insights needed for the project.

QUALITATIVE MODELS AND TECHNIQUES FOR RISK IDENTIFICATION AND ASSESSMENT Qualitative techniques widely used to identify risks are documentation reviews, brainstorming sessions, nominal group techniques, and the delphi technique, as presented in Table 10.1. Once the risks are identified, risk categorization is done and a risk breakdown structure (RBS) is created as shown in Figure 10.4 for the oil refinery construction project (Gupta et al., 2021). RBS is a hierarchical structuring of risks defining the total risk exposure of the project. It differs with respect to sources of risk, type of projects, and the environment as well as industry sectors. It is therefore necessary for any organization wishing to use the RBS as an aid to its risk management to develop its own tailored RBS.

Figure 10.4

Risk breakdown structure

Source: Gupta et al., 2021.

 

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Risk analytics for project success  139 Table 10.1

Risk identification techniques (adapted from Chapman, 1998)

Characteristics

Brainstorming

Nominal Group Technique

Delphi

Group size

7–12

7–10

No rule of thumb (range 5–30 depending on complexity of

Group characteristics

Heterogeneous group

Heterogeneous group

characterized by members

characterized by members

with

with

substantially different

substantially different

problem in hand) Heterogeneous experts

perspectives of the project

perspectives of the project

Member equality

Member dominance occurs

Member equality

Respondent equality

Discussion intensity

Criticism is ruled out

Discussion for clarity

No discussion

Quantity/quality desire

Number i.e., quantity

Quantity and quality

Consensus

Degree of group

Social needs of members

Social needs of members

Unaffected

compatibility

may

may

Degree of bias

affect members’ responses

affect members’ responses

 

Yes

No biases, as the members are kept anonymous

A qualitative risk analysis also deals with the prioritization of the identified project risks using a pre-defined rating scale. Risks will be scored based on their probability or likelihood of occurring and the impact on project objectives should they occur. As the impact of risks encountered in past projects is imprinted on the psyche of the project manager and will be remembered in future projects, experts are requested to give their judgment on probability (P) of occurrence and the degree of impact (I) for all the identified risks on the identified project objectives, such as cost, time, quality, scope, team performance, efficiency, etc. The experts provide their inputs on the probability of occurrence of risks using: very high, high, medium, low, and very low, as well as inputs on the degree of impact of risks using: critical, major, cautionary, minor, and negligible on project objectives, such as budget, schedule, or quality, as shown in Figure 10.5. The risks are then plotted on the probability–impact matrix to understand which are most critical to be looked at as a priority.

Figure 10.5

Probability–impact matrix

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QUANTITATIVE MODELS USING ANALYTICS FOR RISK ASSESSMENT To make the best decisions about innovation projects, leaders need answers to the following questions: which risks should be prioritized, what are the interactions, what mitigation strategy works, what issues are trending, and how should contingency be planned? Risk analytics provides the answers to the above and uses data-driven models where data can be collected on project sites and/or generated using procedures for eliciting experts’ judgments. It includes (1) risk prioritization techniques and 2) risk interaction techniques. The techniques can be categorized under (a) statistical and machine learning models (Gondia et al., 2020), (b) multi-criteria decision-making models (MCDM), (c) interpretive structural modelling (ISM), (d) social network analysis (SNA), and (e) simulation models.

RISK PRIORITIZATION TECHNIQUES A very simple risk ranking and prioritization technique is to convert the subjective evaluations of probability (likelihood of occurrence) and impact received from experts into a quantitative scale (validated by experts) as presented in Table 10.2. A five-point Likert rating scale for impact and probability can also be used (where very high impact/probability = 5, high impact/ probability = 4, moderate impact/probability = 3, low impact/probability = 2, and very low impact/probability = 1). This method for assessment has been frequently used by researchers (Gondia et al., 2020; Kassem et al., 2019; Xia et al., 2017). The risk score can then be simply calculated as probability × impact. The risk score can be calculated for each work package and hence the work package and risk with a higher risk score needs more attention toward designing appropriate strategies to manage it, as shown in Figure 10.6. Table 10.2

Sample scales for quantitative probability and impact

Scale

Impact

Probability of occurrence

 

0–20%

Very low (VL)

Very low (VL)

 

20–40%

Low (L)

Low (L)

 

40–60%

Moderate (M)

Moderate (M)

 

60–80%

High (H)

High (H)

 

80–100%

Very high (VH)

Very high (VH)

 

  Impact value (Index)

Description

Probability value (Index)

Description

0.05

Contributes to no or

0.1

Nonexistent or very rare

0.1

Contributes to 20% time overrun

Risk analytics for project success  141

Figure 10.6

Risk ranking using RBS-WBS

Multi-criteria decision-making (MCDM): this is a hierarchical structure capturing both tangible and intangible risk factors to consider in the decision (Saaty, 2012). It is based on the idea of pairwise comparisons to gain the relative importance of one criterion (here the risks) over another. Researchers have attempted to prioritize risks using Analytical Hierarchy Process (AHP) in combination with other MCDM techniques like Delphi, Analytical Network Process (ANP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and Decision-Making Trial and Evaluation Laboratory (DEMATEL) across different sectors: construction (Dey, 2002); new product development (Chen et al., 2006); mining (Banda, 2019); PPP projects (Zhang et al., 2019), etc. However, the traditional MCDM techniques are limited in handling uncertain data and in scenarios where expert opinions are difficult to capture with an exact value. To overcome this drawback, the fuzzy numbers are used to capture the features of interval judgments and the most likely values, known as Fuzzy MCDM. Risk Interaction Techniques Because of the project complexity and involvement of multiple stakeholders (such as client, consultant, contractor, subcontractor/supplier, end user, financial organization, government, environmental organization, professional association, media, public, labor union, assessor/certifier, researcher, and others), especially in large and mega projects, not only identification of risk but also identifying their (risks as well as stakeholder) interactions appears to be critical, which is likely to trigger the occurrence of one or more risks. Researchers have demonstrated different risk interactions that can occur during a project life cycle as shown in Figure 10.7 (Yuan et al., 2018; Kwan & Leung, 2011).

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Figure 10.7

Risk interactions

 

The techniques used to study the interrelationships and dependencies among the identified risk are as follows. Semantic Network Analysis (SNA). The application of SNA has been in the last few years extending into the area of project management, although this implementation is at a very initial stage. Recently, Yang and Zou (2014), Yuan et al. (2018), Zarei et al. (2018), and Bashir et al. (2020) applied SNA to understand the main causes of delay in large and complex construction projects, as well as their interrelationships. SNA includes: (1) the recognition of key risk factors and stakeholders; (2) the recognition of elements determining and defining each of the risk factors; (3) analysis of risk effects through the risk structure matrix (risk relationship is defined by the impact from one risk to the other, and the likelihood of the interaction between the risks); and (4) visualization of a risk network as shown in Figure 10.8. Initially, focus group or the Delphi technique is employed to get information on risks from experts in the field. Then, each concept/occurrence (risk factor) is considered as a node in a network and the relationship between concepts is based on the co-occurrence of concepts. SNA software packages like SocNetV, UCINET, NetMiner, NetDraw, and Pajek, etc. ease the plotting of the network.

Risk analytics for project success  143

Figure 10.8

Illustration of SNA for project risk

 

Interpretive Structural Modeling (ISM) ISM uses experts’ practical experience and knowledge to generate a multilevel structural model. ISM has indicated higher capability to capture dynamic complexity by imposing order and direction on the complex relationships among risks in a project, indicating how the risk propagates in the system, as shown in Figure 10.9. It has demonstrated its capabilities in different domains such as international projects of piping, steel, and construction (Dandage et al., 2018, 2019; Gupta et al., 2021); virtual organizations (Alawamleh & Popplewell, 2011); and renewable energy projects (Eswarlal et al., 2011). Decision-Making Trial and Evaluation Laboratory (DEMATEL) This reveals not only the relationship structure between the risk factors but also causality, and identifies the critical factors through the matrix calculation (Zhang et al., 2019). The structure of the DEMATEL network is presented in Figure 10.10.

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Source: Gupta et al., 2021.

Figure 10.9

Illustration of ISM, an example of oil refinery construction

 

Figure 10.10 DEMATEL network for risk relationships

Risk analytics for project success  145  

Bayesian network Bayesian networks (BN) are based on graphs and probability to describe the probabilistic relationships among the uncertain variables (here risks). BN is composed of two parts, namely a qualitative and a quantitative part. The qualitative part of a BN is a directed acyclic graph (DAG), in which nodes with several states represent the variables of interest with uncertainty, expressed in probability, and the directed arcs pointing from a parent node to a child node represent the causal and conditional dependency relationship between those two nodes. The quantitative part, which consists of a set of conditional probability, is obtained from empirical data or given by expert judgments (one way to identify is through pairwise comparison). The demonstration of BN for risk in new product development project is presented in Figure 10.11 (Chin et al., 2009; Khodakarami & Abdi, 2014). A comparison of different data-driven quantitative techniques is presented in Table 10.3.

Source: Chin et al., 2009.

Figure 10.11 Bayesian network of new product development risk

146  Research handbook on project performance Table 10.3

Comparison of quantitative techniques for risk assessment and analysis

Features

AHP

ANP

TOPSIS

DEMATEL

ISM

BAYESIAN

SNA

Sample size

5–10

5–10

5–10

10–15

10–15

Depends on

Depends on

complexity

complexity

(experts)

and number of

requirement Purpose

Prioritization

Prioritization

Prioritization

Intensity of

Risk

Risk

stakeholders Risk and

direct and

propagation;

relationships:

stakeholder

indirect risk

multilevel

ability to

relationships

relationships

hierarchy

incorporate conditional monitoring and bring dynamic changes

Number

7–10

 

Many

 

Many

Many

Many

NA

YES

NA

YES: cause

YES:​

YES: cause and

YES

and effect

order and

effect analysis

analysis,

direction on

mutual

the complex Structured

‘What-if”’ analysis Information

method

to explore the

of risks consideration (attributes) Relationships among risks

relationships

Flexibility and Highly

Highly

Structured

influences Structured

effort

structured

structured

method

method

method, easy

method and

effect of changes in process is

to implement

complex

some nodes on the

quite

changes in other

time-

nodes

consuming

collection

Large computational Limitation

 

 

 

effort Cannot

Cannot

be used to

quantify or

determine impact reluctant to

determine the

explicitly

of risk events

provide data

likelihood of

demonstrate

One-way causal

concerning

risk events

influences

relationship

the anonymity of the data

among those Software

Stakeholders

Cannot

collected

Super

elements Super

Super

decisions

decisions

decisions

Online output  

Genie, HUGIN

SocNetV,

Netica

UCINET, NetMiner, NetDraw, Pajek

 

Risk analytics for project success  147 Monte Carlo simulation This involves random sampling of uncertain variables based on defined probability distribution functions. Through this random sampling, a probability distribution of the output variable can be determined, and the probability of failure calculated. The main criterion for selecting the appropriate probability distribution for input variables is the knowledge of characteristics of risk factors. One critical step in a Monte Carlo simulation is to develop a model of relationship between dependent variable (example-objective/performance of project—in terms of cost or budget or schedule or quality, etc.) and independent variables (risk factors). Crystal Ball in Excel is one piece of software providing risk assessment and aiding the project manager’s decision-making.  

RISK RESPONSE STRATEGIES Risk response planning involves development of responses to the identified risks that are appropriate, achievable, and affordable. There are four risk response strategies as shown in Figure 10.12. Depending upon the severity of risk, the strategy can be adopted.

Figure 10.12 Risk management strategies ● Avoid: seeking to eliminate the uncertainty by making it impossible for the risk to occur (i.e., reduce probability to zero), or by executing the project in a different way that will achieve the same objectives but that insulates the project from the effect of the risk (i.e., reduce impact to zero), such as revising the project plan to remove the risk.

148  Research handbook on project performance ● Accept: recognizing that residual risks must be taken, and responding either actively by allocating appropriate contingency, or passively doing nothing except monitoring the status of the risk. ● Transfer: identifying another stakeholder better able to manage the risk, to whom the liability and responsibility for action can be passed. ● Reduce/mitigate: reducing the size of the risk in order to make it more acceptable to the project or organization, by reducing the probability (risk prevention) and/or the impact (risk adaptation). Risk prevention refers to actions taken in the planning stage to reduce the probability of occurrence of risk events by acquiring additional information, improving communication with clients, hiring experienced project managers, and choosing more reliable contractors. In risk adaptation, actions are implemented in the execution stage and aim at alleviating negative impacts resulting from the occurrence of risks. The selection of strategy is based on controllability of project risk, risk-handling costs, and project characteristics (project size, technological complexity, level of schedule slack, and external economic and political factors) (Fana et al., 2008). When the project scale and the expected loss are large, and controllability is high, and when the complexity of a project (defined as ease of conducting internal and external communication among parties, obtaining necessary information, keeping project specifications/scope intact, etc.) is low, a risk-prevention strategy is suitable. Further, for projects with little slack and high pressure for on-time completion, the unit cost of a crash is high, and a risk-prevention strategy is preferred (Fana et al., 2008). If controllability is low and prevention cost is very high, a risk adaptation strategy is preferred. Finally, in the situation where the controllability of the project is not clear, a mixed strategy could be adopted as shown in Figure 10.13.

Source: Fan et al., 2008.

Figure 10.13 Risk mitigation strategy Further, when the projects are complex and involve multiple stakeholders, as discussed earlier, there exist interrelationships and interdependencies among risks that can either increase or

Risk analytics for project success  149 decrease the probability of occurrence of other risk(s) as well as their effects. After a risk has considered the effect from another risk, the dependent risk is then called posterior risk (Kwan & Leung, 2011). The effects of risk dependencies can either increase or reduce the probabilities of those affected risks. A non-favorable effect will increase the probability of a risk and a favorable effect will lower its probability. Based on the favorability of dependency effect and the degree of dependency effect, an appropriate risk response strategy can be selected (Kwan & Leung, 2011) as shown in Figure 10.14.

Source: Kwan and Leung, 2011.

Figure 10.14 Risk dependency response strategy Some of the response actions recommended by researchers in their studies are presented in Table 10.4.

150  Research handbook on project performance Table 10.4

Risk response strategies and actions

Risk

ACTIONS

New regulations

Ensure the project is complying with local planning commission’s development plan

STRATEGY AVOID

and laws

Establish joint ventures with renowned local partners, especially the central

TRANSFER

government agencies or state-owned enterprises Obtain insurance for political risks Public image

TRANSFER

Maintain good relationship with local government and higher officials

MITIGATE

Comply with local and international civil laws and standards, local social and cultural

AVOID

values Maintain good reputation and image to the public

MITIGATE

Give donations to renowned nongovernmental organizations, which are involved in

MITIGATE

elevating the living conditions of poor Provide residents with substantial subsidies in case of acquisition of land that involves

MITIGATE

relocating residents Market demand Competition

Employ reputable third-party consultant to forecast market demand

AVOID

Look for generic application of the products

MITIGATE

Conduct market study and obtain exact information of competitive projects

MITIGATE

Adopt as much as possible domestic product/labor to reduce cost

MITIGATE

Establish agreement with local government agency to reduce/exempt from import

TRANSFER

formalities Unanticipated

Undertake pre-project planning to minimize design errors

MITIGATE

design changes and

Inviting vendor to attend design meeting

MITIGATE

errors

Frequent reviews, adopting agile approach

MITIGATE

Get design liability insurance

TRANSFER

Adopt design and build option, which enables contractor to design in harmony with site TRANSFER conditions thus minimizing design/drawing disputes Unstable

Developing contingency plans for labor shortage

MITIGATE

Hiring a consulting company for design phase

MITIGATE

More dependence on national suppliers

MITIGATE

Design incentive mechanisms for timely delivery

MITIGATE

organizational environment Management commitment and support Supplier related

Choosing a more stable supplier (with frequent monitoring on financial and reputation) AVOID Requirement

On-site customer surveys to optimize requirement analysis

MITIGATE

Adopting proven technology

AVOID

Parallel innovation process

MITIGATE

changes Technology

 

RISK MONITORING AND CONTROL

Risk monitoring and control is the final stage of the risk management process. It aims to monitor the status of identified risks, identify new risks, ensure the proper implementation of agreed responses, and review their effectiveness, as well as monitoring changes in overall project risk exposure as the project progresses. For this purpose, a risk register is used, which serves the purpose of helping the project team review project risks on a regular basis throughout the project life cycle. Risk review meetings may be held to assess the current status of risks to the project, and project review meetings should include status reports from the project team

Risk analytics for project success  151 Table 10.5

Sample of a risk register

Project title: Documented by: Revised date: Risk identification ID Reported Date of by  

 

report

Risk analysis

Risk resolution

Description Risk Description Severity Occurrence Risk of risk

(D/M/Y)    

type of risk  

impact  

rating

rating

Preventive Action Risk

rating action

Date of Date of

taken

priority action action taken

Note

completed

 

 

 

by  

no.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

     

 

 

 

 

 

   

on key risks and agreed responses. The risk level as well as risk dependencies may change during the project life cycle. The residual (risk that remain after all of the response strategies have been implemented) and secondary risks (direct result of implementing a risk response) are looked at after implementing the risk management strategies. The risk register contains the above information in the form of a table (as shown in Table 10.5), Excel sheet, or any form of database (Patterson & Neailey, 2002) convenient to the organization. (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13)

The area of the project in which the risk may materialize Risk identification number Brief description of the risk Probability or likelihood of the risk occurring, determined within the risk assessment phase Impact value (impact of the risk, often in separate terms of time, cost, quality, or other related project objectives framed) Total impact value Risk score (combination of the probability and total impact values) Ranking of the risk within the project (ranked risks are those with a high severity and are active within the project) Tracking of the risk (i.e., has the risk increased, remained the same, or decreased in severity since the previous month?) Risk response strategy Risk owner Whether the risk is active on the register Whether the risk has been solved.

As this stage caters for accountability of the process to ensure that an adequate level of reporting is present, an agile approach (iterative and incremental) to monitoring is beneficial. This approach will enable frequent interactions across all iterations with the stakeholders. In such approach stakeholders are aware of the process and acceptance levels of the risks are decided.

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SUMMARY AND CONCLUSIONS It is imperative that project risk management is one of the most important domains enabling project success. The high failure rates of projects across sectors with especially cost and time overrun clearly demand organizations develop competence in risk management and its techniques. Unfamiliarity with and unawareness of the emerging techniques in the field of analytics has until now restricted their use. The authors have attempted to present a snapshot of a few relevant techniques other than the traditional ones that can be used in the VUCA environment currently being faced by almost all organizations. Further, it has been observed that much of the research has been directed toward study of independent risks and their effects and response actions. In fact, the analytical approaches that employ MCDM have recently dominated the literature. However, risk dependency is one of the most critical aspects to be seen and requires more attention and case studies for experiential learning. Risk response actions needs to be integrated well when dependency happens and need further research. Further, the risk register captures the independent risk, which needs modification to adapt risk dependency aspects and posterior risks effects. The findings indicate that there is heavy reliance on practical experience and professional judgment when assessing risk. Adoption of the available machine learning tools is quite limited and in an emerging phase in the area of project risk management. The caselet of an aviation project highlights the importance of moving toward an agile approach to risk mitigation when dealing with complex projects with multiple stakeholders. When teams meet on a frequent (even daily) basis, they are better prepared to react to scope and schedule changes and adapt as necessary. Such modifications align the project continuously for value delivery of the project and its success.

CASELET: MANAGING RISK IN A COMPLEX AVIATION PROJECT India’s development of the light combat aircraft (LCA) Tejas (a flying military machine with supersonic speed) is a live example where proactive risk management played a big role in its success. The triple constraints of time, cost, and scope with high-quality standards were met. We take you back to the 1990s. One of the authors was then in a senior position in the design team at HAL Lucknow. The LCA is the smallest, most lightweight, multi-role fighter of its class in the world designed to meet the stringent operational requirements of the Indian Air force. It incorporates state-of-the-art technologies. The need for a small, lightweight fighter to replace the MiG-21 series of aircraft and to bridge the ever-widening technology gap was the objective of the LCA project. The project was like a movement, which perhaps does not occur very often in history. The development of the LCA is the most complex high-technology hardware and software development program ever undertaken in India. The road for its development was rough and the team encountered many challenges. Novelty: The project was novel—a breakthrough in nature as it was a completely new product, never done before, with totally new infrastructure to undertake design and development. In other words, novelty was high. Further, the capabilities and competencies (as the

Risk analytics for project success  153 existing workforce of the organizations had very limited experience) needed to be built to meet the user requirements. This required the development of a cohesive team. Technology: The challenge was that the fighter should be a state-of-the-art fighter to remain in service for more than two decades to come. Thus, the technology should be advanced; i.e., a quantum jump in technology was needed. The technology was very high. The critical question was the accessibility of such technologies within the given time frame. However, access to such technologies was difficult, especially due to sanctions imposed on India by other countries. The technologies required for the project were not available off the shelf due to their nature of being sensitive defense technologies that were guarded by firms and their respective governments as their golden hens. The second technical challenge was to meet the stringent requirements of the user who for obvious reasons wanted the contemporary performance and technologies. Complexity: The project had a very high level of complexity and high interdependency of systems with weight and volume constraints. Complexity was understood not only from technical aspects (such as avionics, fuel, engine, integrated flight control system, etc.) but also there was high managerial complexity due to the involvement of multiple stakeholders and distributed teams, and material flow and facilities spread all over India. One hundred major work centers (industries, R&D labs, academic institutions) and 300 small-/medium-scale industries participated in this breakthrough project (Harinarayana, 2004). Pace: The then frontline fighter aircrafts (MiG-21 series) used by the Indian Air Force were becoming outdated by the 1990s. They needed replacing to cater to the new needs of the Air Force. Development of such a class of fighter (LCA) would need almost 15 to 20 years of sustained effort even by developed countries. Thus, the project became time-critical and of an urgent nature. Thus, the NTCP framework (as shown in Figure 10.15) puts the LCA project in a very high-risk category, suggesting that if not managed properly it will result in failure. The risks were identified in the early phase of the project, to list a few: (1) (2) (3) (4) (5) (6) (7) (8) (9)

Availability and accessibility of latest technologies Lack of know-how and know-why of advanced technologies Limited availability of expertise Bureaucratic style of functioning Restrictions/sanctions imposed by other countries Changes in requirements from the customer Denial of foreign technical assistance Long development time and heavy cost by supplier Supplier availability.

The nature of the project demanded development and manufacturing of highly complex, tight tolerance hardware and components for aerospace, considering the safety of aviation and defense personnel in such mission-critical projects. Thus, it was clear that the project could not be dealt with in a conventional way and rather an innovative approach needed to be applied by: ● looking at things differently ● doing things differently ● coordinating activities seamlessly.

154  Research handbook on project performance

Figure 10.15 LCA project: NTCP characteristics The project team members took the challenge together with one aim and goal and used synergies, perseverance, hard work along with technology, project management, and risk management competencies. A proactive risk assessment approach was adopted during the project life cycle not only from the management perspective but also to ensure certification, to have the confidence with operating crew and designers, the key stakeholders in the project. The risk assessment was carried out and risks were categorized as high, medium, and low. The risks were tracked and monitored down to realization during development (Harinarayana et al., 2003). Risk Management Strategy As no single organization had experience in such a project, it was decided to use existing institutions involving distributed work centers with 148 organizations spread over 29 locations within India (Kumar, 2014, 2021), rather than using a centralized work center model. A decentralized development and production strategy was adopted to avoid as well as mitigate the risks. To reduce the delays in decision-making (both financial and technical) and speed up the technology development, infrastructure creation, and product development, a new body (virtual organization) called the Aeronautical Development Agency (ADA) was created. It created flexibility in the management structure, enabling active participation and cohesive decision-making among industry, R&D bodies, academia, and the customer (air force, Indian Navy). This was the first project of this nature and scale undertaken by the organizations-ADA under Defence Research and Development (DRDO-ADA) and Hindustan Aeronautics Ltd

Risk analytics for project success  155 (HAL). The total design and development work was partitioned into various work blocks, work block elements, and work packages, about 1,200 in total. Each work element was clearly defined and the interfaces with other elements specified (Harinarayana, 2004). During one of the critical phases of integration of the LCA prototype at HAL Bangalore, one of the line replacement units (LRUs) had a procurement problem (the vendor was charging an exorbitant price and there was a long development time), affecting the LCA development time adversely. The design team at HAL Lucknow was given the task to take the challenge and develop it in-house. This was a very high-risk proposal considering the fact that the LRU was a class-1 aircraft electric system and if anything happened the electric supply system of the aircraft would fail, leading to disruption of the electric supply to other systems and thus failure of the systems. The team took the plunge. The team gave due focus to eliminate/reduce the effect of risk at the earliest stage before the risk had a negative impact on the project objectives. A proactive and agile approach was applied for dealing with risks. Various stages of the life cycle (from concept to prototype) of the LRU were dealt with using different combinations of risk methods and approaches as per the requirement of the unique work package. At all stages, frequent reviews and risk reviews were conducted involving the customer, ADA, the quality regulating agency, and other stakeholders. In some review meetings higher management was also involved actively. The result was that the LRU was developed, tested, and fitted successfully in the LCA prototype before the expected date. Further, technical risks were mitigated by making small project groups with domain experts from different organizations. Most of the group members were stationed at the site of the subproject. The LCA development was a formidable task and a calculated risk, particularly against the background in which Indian aeronautics had grown to that point. The LCA team consisting of about 1,000 engineers, designers, and staff worked for about 72 hours/week for 11 long years (Kumar, 2021) to deliver the project, meeting the project performance parameters of quality. Key Takeaways It is said that ‘there can be a slip between a cup and a lip’; i.e., even a very small project also has a risk. In fact, some risks are always present in all projects. The risk management methodology adopted was not to eliminate all the risks and spend resources on removing them totally; instead, the focus was on reducing the risk to an acceptable level. The agile approach was adopted and very frequent reviews (sometimes daily) were done to reduce the overall project risks to a level that was acceptable to the key stakeholders such as the project sponsor, regulatory agencies, and the vendors. The involvement of the project team along with stakeholders in the reviews minimized the bureaucratic delay and enabled quick decision taking. At some points changes were incorporated into the schedule, budget, and scope to deal with certain risks. The approach adopted the changes and was very effective in identifying and mitigating the risks beyond the visual range (unforeseen) at an early stage. The LCA experience shows that in highly complex and risky projects, project performance and its success depends on the selection of partners who can work cooperatively at a higher level of operational trust.

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Risk analytics for project success  157 Kumar, Y. (2021). Execution Made Easy: Practical Tips for Large Scale Projects. Independently published. Kwan, T. W., & Leung, H. K. N. (2011). A risk management methodology for project risk dependencies. IEEE Transactions on Software Engineering, 37 (5), 635–647. Patterson, F. D., & Neailey, K. (2002). A risk register database system to aid the management of project risk. International Journal of Project Management, 20 (5), 365–374. PMI (2021). Pulse of the Profession 2021. https://​www​.pmi​.org/​learning/​thought​-leadership/​pulse/​pulse​ -of​-the​-profession​-2021 Saaty, T. L. (2012). Decision Making for Leaders: The Analytic Hierarchy Process for Decisions in a Complex World. RWS Publications. Shao, J. (2018). The moderating effect of program context on the relationship between program managers’ leadership competences and program success. International Journal of Project Management, 36 (1), 108–120. Shenhar, A. J., & Dvir, D. (2007). Reinventing Project Management: The Diamond Approach to Successful Growth and Innovation. Harvard Business Review Press. Shenhar, A. J., Holzmann, V., Melamed, B., & Zhao, Y. (2016). The challenge of innovation in highly complex projects: What can we learn from Boeing’s Dreamliner experience? Project Management Journal, 47 (2), 62–78. Simon, R., Hillson, D., & Newland, K. (1997). Project Risk Analysis and Management (PRAM) Guide. Association for Project Management. Tepic, M., Kemp, R., Omta, O., & Fortuin, F. (2013). Complexities in innovation management in companies from the European industry. European Journal of Innovation Management, 16 (4), 517–550. Xia, N., Zhong, R., Wu, C., Wang, X., & Wang, S. (2017). Assessment of stakeholder-related risks in construction projects: Integrated analyses of risk attributes and stakeholder influences. Journal of Construction Engineering and Management, 143 (8). Yang, R. J., & Zou, P. X. W. (2014). Stakeholder-associated risks and their interactions in complex green building projects: A social network model. Building and Environment, 73, 208–222. Yuan, J., Chen, K., Li, W., Ji, C., Wang. Z., & Skibniewski, M. J. (2018). Social network analysis for social risks of construction projects in high-density urban areas in China. Journal of Cleaner Production, 198, 174–189. Zarei, B., Sharifi, H., & Chaghouee, Y. (2018). Delay causes analysis in complex construction projects: A semantic network analysis approach. Production Planning and Control, 29 (1), 29–40. Zhang, L., Sun, X., & Xue, H. (2019). Identifying critical risks in Sponge City PPP projects using DEMATEL method: A case study of China. Journal of Cleaner Production, 226, 949–958.

11. Building capability for project success: examining the preparedness of emerging professionals using a university capstone project case study Michelle Turner and Guinevere Gilbert

INTRODUCTION This chapter presents the findings of a study that explored the perceived employability of project management students undertaking a capstone project in the final year of their four-year project management university degree. The study aimed to investigate how the capstone project contributed to students’ professional preparedness from the perspectives of students and mentors. In the beginning of the chapter we consider pathways into project management, draw on the literature to consider the concept of employability, and identify approaches to curriculum review. We then outline the method we used to collect data and present our findings. In the discussion we explore our key findings in the context of employability and consider how the capstone project can be revised to contribute more strongly to the preparedness of our project management graduates. It is anticipated that the findings of the study can be used to modify the curriculum underpinning the capstone course so that the perceived employability of students is enhanced and contributes to professional preparedness.

THE RIGHT PERSON IN THE RIGHT JOB Having the right person in the right job is imperative for success in business. This underscores the significance of preparing new entrants with the requisite skills and knowledge to undertake a project according to time, cost, quality, and stakeholder specifications. This is against a backdrop where the failure rate of projects continues to be high and organisations find it difficult to deliver projects that meet time, cost, and quality specifications and achieve stakeholder satisfaction (KPMG et al., 2019). The Project Management Institute (PMI; 2017) reports that organisations are losing an average of $97 million for every $1 billion invested due to poor project performance. While the skills, knowledge, and experience of the project professional alone do not contribute to project success or failure, they play an integral role. Furthermore, empowering a new generation of talent with the necessary project management skills and knowledge is critical in addressing the talent gap (PMI, 2021a). Organisations are faced with a substantial talent shortage which can exacerbate the already high failure rates. According to the PMI (2021a), there is a gap between the demand for project management skills and the availability of talent. By 2030 it is anticipated that the global economy will require 25 million new project professionals. To achieve this target, 2.3 million new project 158

Building capability for project success  159 professionals will be required every year. Developing competent project professionals to meet the current and future demand is on the critical path for achieving project success. There are various pathways through which emerging project professionals gain the requisite skills and knowledge they require to be considered competent (KPMG et al., 2019). In this chapter, we focus on emerging project professionals undertaking a four-year university degree in project management. Peach and Gamble (2011) report that students expect that universities will prepare them for professional practice. This highlights the importance of ensuring that linkage between students’ learning and their future career aspirations is actively fostered through teaching practice and course design (Wingrove and Turner, 2015). Universities, therefore, are a critical stakeholder in the development of the graduate’s employability (Bridgstock, 2009; Clarke, 2018). Our chapter explores the development of perceived employability of final-year project management students through participation in a capstone course. The focus of this study, the planning and execution of a project for social benefit by final-year project management students, is a major component of a capstone course. The course is described in more detail in a later section of the chapter.

DEVELOPING EMPLOYABILITY There exist multiple and varied definitions of employability (Bridgstock, 2009). According to Clarke (2018), one widely accepted definition of employability is: the capability to move self-sufficiently within the labour market to realise potential through sustainable employment. For the individual, employability depends on the knowledge, skills and attitudes they possess, the way they use those assets and present them to employers and the context (e.g. personal circumstances and labour market environment) within which they seek work. (Hillage and Pollard, 1998, p. 12)

In their definition of employability, Hillage and Pollard (1998) incorporate four key elements of employability: (1) what knowledge, skills, and attitudes (“assets”) people have to offer employers; (2) deployment in terms of the extent to which people are aware of what they have and how they choose to use it; (3) how people present themselves to employers; and (4) the context in which people seek employment. In contrast to Hillage and Pollard’s (1998) definition, employability of graduates is often framed by universities and governments using a narrow skills-based approach. This approach fails to consider the complexity of employability and has received considerable criticism (see, for example, Bridgstock, 2009; Holmes, 2001; Knight and Yorke, 2003; Smith et al., 2016). An important limitation of the skills-based approach to employability is the lack of reference to “self”. Self-efficacy, self-confidence, and self-esteem are central to employability and are linked to the willingness to act, motivation, positive attitude towards problems, and the development of positive relationships and lifelong learning (Römgens et al., 2020). Self-belief is understood to underpin action and should be developed alongside and through the development of skills within the context of the disciplinary curriculum (Turner, 2014). The focus on “self” introduces a subjective appraisal element to employability, and this is acknowledged by Vanhercke et al. (2014) who use the term “perceived employability” to describe “the individual’s perception of his or her possibilities of obtaining and maintaining employment” (p. 594). Clarke (2018) also acknowledges the critical role of perceived employ-

160  Research handbook on project performance Table 11.1

Six dimensions of graduate employability

Employability dimension

Description

Professional practice and standards

Competent for autonomous, responsible, and ethical practice

Integration of theory and practice

Can integrate theory and practice

Lifelong learning

Willing to continue to learn to improve practice and able to identify areas for self-development

Collaboration

Can work with other people effectively, fairly, and cross-culturally

Informed decision making

Uses information in judicious ways for specific work-related purposes

Commencement-readiness

Has confidence and self-awareness to seek and gain employment in a job market

ability in her integrated model of graduate employability and acknowledges the importance of subjective as well as objective measures of employability. In recognition of the complexity of employability and the lack of consensus around what constitutes graduate employability, Smith et al. (2016) took an approach which incorporated domains related to employment-related skills, general knowledge and skills, and knowledge to develop a graduate employability model. The model is multidimensional and consists of six elements, as shown in Table 11.1. Importantly, the model moves away from a narrow skills-based approach which has been used to signal employability, as well as incorporating a “self” element.

EXAMINING THE CURRICULUM Clarke (2018) contends that the employability of graduates has practical implications for universities. At university, degree-relevant knowledge, skills, and competencies can be taught through well-designed curricula and evaluated through scaffolded assessment tasks. This highlights the value of critically reviewing the curriculum to examine how it is impacting on a student’s perceived employability. Curriculum review and alignment with course and programme learning outcomes is therefore an important practice which can occur at multiple pedagogical levels. According to Wijngaards-de Meij and Merx (2018), one useful approach to guide curriculum review consists of four categories: ● ● ● ●

Focus on the content and structure of a single unit. Focus on the content and structure at a programme level. Curriculum is understood from the point of view of the student’s learning experience. Curriculum is approached as the co-construction of knowledge between student and teacher.

The focus of our study is the examination of a capstone course and its capacity to contribute to graduate employability. Using the approach of Wijngaards-de Meij and Merx (2018), we focus on a single unit from the point of view of the student and mentor. Capstone courses are typically undertaken in a student’s last year or semester of their programme and provide them with an opportunity to apply the knowledge they gained throughout

Building capability for project success  161 their undergraduate degree (Holdsworth et al., 2009). Capstone courses service three key functions: ● consolidate, extend, and apply previous learning ● provide a vehicle for professional socialisation and the development of professional identity to assist students’ transition to employment ● confirm that students have mastered skills relevant to their professional discipline (van Acker and Bailey, 2011). Very little work has been done on examining the value of a project management capstone project and its impact on employability, with the exception of Gilbert and Wingrove (2019). In a project management university context, Gilbert and Wingrove (2019) found that students’ employability was enhanced through participation in a live capstone project as opposed to participation in a simulated capstone project. Communicating with business stakeholders, planning and implementing a project, and experiencing the need to vary plans and roles as tasks change all contributed to employability. Gilbert and Wingrove’s (2019) quantitative-based findings support the initial understanding of the relationship between the capstone project and employability, but additional research is required to reveal factors influencing employability associated with the curriculum.

METHOD Research Context A case study approach was used to explore the impact of perceived employability of students undertaking the capstone project. A case study research approach is used to generate an in-depth, multifaceted understanding of a complex issue in its real-life context (Crowe et al., 2011). The capstone course is situated within the final year of a four-year Bachelor-level degree in project management at a large urban university in Australia. The degree is accredited by the PMI’s Global Accreditation Centre for Project Management Education Programs, and endorsed by the Australian Institute of Project Management. In the degree, first-year students are introduced to the basic concepts of project management. The second year of the degree focuses on technical skills which enhance students’ employability, such as scheduling, coordinating, and contract administration. The third year develops soft skills, and the fourth year explores contextual application of project management skills. The capstone course is undertaken over one semester in the fourth year and has the following learning outcomes: ● develop an evidence-based project management plan which addresses all elements of the project development life cycle ● critically analyse and synthesise project management theory and apply this knowledge to project management ● critically evaluate decision making and its impact on project success ● apply effective teamwork and communication skills to develop and communicate a feasible and strategic project plan

162  Research handbook on project performance The capstone course includes three assessments: an individual academic essay, a series of individual reflective videos, and the planning and implementation of a project which must benefit society and be aligned with a United Nations Sustainability Goal. It is this project for social benefit which provides the context of this research. Although students complete the other assessments simultaneously with the project, the learning outcomes of the individual assessments focus on critical thinking rather than on the application of project management skills and knowledge acquired during the four-year programme. To commence the project, students self-select into small groups ranging in size from three to five. Groups are provided with criteria to guide the selection of the project, but these are intentionally broad to maximise the sense of ownership and autonomy. The guidelines encourage students to use their personal life experiences, seek beneficiaries in their local community, and not to focus on raising money but instead on raising awareness which initiates discussion around appropriate performance indicators and success criteria. Projects involving alcohol are prohibited. The student groups have 12 weeks to plan, implement, and close each project. Beyond the completion date, no milestones are set. Groups are expected to develop and work to their own schedule. Each group is allocated a mentor from industry whose role is two-fold: to advise the group on project processes and to assess the group’s project management maturity. Mentors are invited from professional connections with the project management degree. All mentors have five or more years of experience working as a project professional and some are alumni. Mentors are asked to assess the group’s maturity at the start at the semester using a provided rubric, and to subsequently discuss their assessment with the students and provide advice regarding adopting maturity behaviours during the semester and prior to the second assessment. The course coordinator collaborates with the mentors on group maturity to ensure consistent use of the rubric between mentors. The mentors are advised that the minimum requirement is two meetings over the 12 weeks of the semester which are required in order to assess any change in group maturity. The frequency of meetings is at the discretion of the mentors and students, and some meet on a fortnightly basis. Mentors are initially allocated to one group, but with experience and if personal time allows, some mentors take on two groups in subsequent years. Connecting mentors with groups is an organic and iterative process. Once groups have identified a project, a list of projects is sent out to mentors for them to select from. If a mentor has a known interest in a beneficiary, then the connection is directly suggested. Projects that are not immediately selected by a mentor may then be matched up with mentors based on the mentor’s experience with the capstone course. Sample Perceived employability of students was explored from two perspectives. The first perspective was from the students who had recently completed the capstone project. Students were invited to participate in the research by the course coordinator based on the criteria that they had completed the degree and were no longer in an academic-dependent relationship with the course coordinator, and that they had chosen to remain in contact with the university through the alumni LinkedIn group. An invitation to participate in the research was sent to alumni via LinkedIn. The second perspective was project professionals who had mentored a student group. Mentors were invited to participate in the research by the course coordinator based on the criteria that they actively participated in the mentoring process in the semester immediately preceding the research. Mentors were individually emailed an invitation to participate.

Building capability for project success  163 Table 11.2

Sample interview questions

Employability dimension

Students

Mentors

Professional practice and

Did the group discuss expected performance

Did group members take responsibility for

standards

standards?

their actions?

Integration of theory and practice What project management knowledge and skills do you think you applied to the capstone project?

Did the group apply knowledge and skills learned from the project management programme to the project?

Lifelong learning

Were you able to identify project management

Did the group identify what skills they

skills that you did not have?

might be missing and worked to fill these gaps?

Collaboration

Can you give an example of how you collaborated Did the group improve their collaboration as a group?

during the capstone project? What examples can you give for this?

Informed decision making Commencement-readiness

How did you collect and assess the quality of

Did you observe the group improve their

information obtained during the capstone project?

use of information to inform decisions?

How employable did you feel at the start of the

Did group members develop confidence

capstone course (week 1) and at completion of the in their ability to apply for and find capstone course (week 12)? A 5-point scale was

employment during the capstone course?

used where 1=not very employable and 5=very employable.

Instruments Interviews were conducted with students and mentors to explore the six domains of employability outlined by Smith et al. (2016). Interviews ranged in duration from 25 to 60 minutes. During the interview, students were asked to respond to the questions in relation to their experience of the capstone project. Mentors were asked to respond to questions in relation to their experience of mentoring a student group. Table 11.2 provides sample questions for students and mentors according to the employability dimensions. All interviews were conducted online, recorded, and transcribed verbatim. Data analysis followed the three steps outlined by Creswell (2014): general interpretation of each respondent’s story, qualitative data from each interview is hand coded and deconstructed, and data is aggregated into themes which are attributed with meaning. Analysis of the data occurred in two stages. Coding of the student’s transcripts was analysed, followed by coding of the mentors’ transcripts. In the final stage of analysis, the codes were aggregated into themes. Ethics approval had been received by the researchers’ university and the research was undertaken after students’ final results had been confirmed, audited, and released.

RESULTS Participants Interviews were conducted with nine students. At the time of the interview, all students had graduated from the project management programme within a year of undertaking the capstone project. Although the students were alumni at the time of the interview, we asked them about their experience as a student and therefore we refer to them as “students” when we report the

164  Research handbook on project performance results. All students had completed the capstone course during the same semester, and seven out of the 15 student groups formed that semester were represented. Three of the nine students were from the same group, and six were from different groups. Out of the nine students interviewed, six were either employed in a career role at the start of the capstone course or were offered a career role before the end of the capstone course. Capstone project outputs were influenced by local COVID restrictions which limited face-to-face interaction. The students favoured online outputs such as websites, podcasts, exercise plans, and music events. Projects focused on topics related to climate change and the environment, homelessness, and mental well-being. The students were particularly aware of issues related to mental well-being and this topic featured in many projects. Interviews were undertaken with six mentors. Three had mentored capstone projects in previous years, and three were new to the capstone project. All mentors were familiar with the project management curriculum and areas covered during the degree. Three mentors were alumni who had completed the project management degree in previous years. Themes Seven key themes emerged from the interviews: collaboration versus task allocation, working together – the impact of familiarity, group conflict, skills gap identification, confidence, application of course knowledge and skills, and the role of the mentor. Participant quotes are used to illustrate and support the findings (Eldh et al., 2020). In reporting the findings, participant’s names have been changed to protect confidentiality. Collaboration versus Task Allocation According to the PMI (2021b, p. 28), “creating a collaborative project team environment involves multiple contributing factors, such as team agreements, structures, and processes. These factors support a culture that enables individuals to work together and provide synergistic effects from interactions”. Students were asked questions about collaboration and often referred to the ability to allocate tasks to group members. For example: “Especially because we did have [student name removed] who was an international student and he can’t actually go and ring people or he can’t do this and do that. So then you had to prioritize something for him to do that was both valuable to the group as well as challenging for him” (Theo), and “being able to communicate well and being in an environment where you had to communicate those sort of things. And it was your responsibility to do those things. It felt like each member had a role to play” (Robert). The allocation of tasks is something that groups do throughout their tertiary education and are encouraged to do as a way of ensuring equitable work distribution within group assignments. While allocation of tasks to group members is an important activity, it falls short of the PMI definition of collaboration (PMI, 2021b). During the capstone project, once allocated a task, some students then worked on that task without sharing the information until the end of the project. Theo offers an explanation for this: “I like to work on my own stuff and write little notes, and I don’t want other people seeing it or getting rid of it”. It is possible that not sharing work with other team members until the end may be a sign of lack of confidence in the quality of work. It may also be an individual preference in which some students prefer to work on their own.

Building capability for project success  165 Only two students considered working in a group as more than simply allocating tasks to group members. For example, one student noted that they used a file sharing platform so that they were able to read and contribute to other components of the finished product besides their own. Another student explained that her group members had an online meeting in which they sat and worked on their individual documents as if they were co-located in a room on campus, where they were able to ask each other questions if needed: “Even though we sat there quietly, sometimes you know individually working there was still that digital, group environment” (Elizabeth). Working in a group was dynamic, and often driven by one or two group members. It was observed by students that group activity occurred more frequently at the start of the project when the scope was being established. Once the scope was agreed upon and the tasks delegated, students tended to work individually. However, when project deadlines were imminent group activity increased again as students paired up to complete tasks within the time constraint: “But you know we sat down and we came up with a layout that you know we both liked” (Francine) and “after we had quite a few meetings … together we sort of collaborated, which is good” (Francine). For mentors, it was evident when collaboration was present or not at the start of the capstone project and whether it developed over time. One mentor commented: “The student asked the team a question like whether or not he should do a certain activity, like he directed it to the group and I was really happy because I was like OK, you’re engaged with your group. You’re not just speaking to me. Now you’re speaking amongst each other” (Sarah) and “they understood each other’s work … they all had their part to talk to, and they started to overlap … if one person was talking, someone would also join in and clarify that point … they didn’t just know their part, they knew other people’s parts” (Brendan) and “so yes, I did see a clear increase in collaboration over the life of the project” (Ian). Working Together – the Impact of Familiarity Almost all students recognised the benefit of working in a group they had not previously worked with. For example, as a result of working with different groups throughout the degree, one student commented: “I can work with just about anybody now” (Sarah), and another commented on the value of working in an unfamiliar group at university: “You don’t get to pick who you work with in the workplace. More often than not, there’s going to be a spread of some people that are really great, hopeless or are not interested, or any combination in between. And if you practice those skills in university you’re better prepared for employment” (Brendan). Despite acknowledging that working with an unfamiliar group helped students to develop their skills in people management, most students preferred working in a group they had previously worked with. One student said she made a conscious decision to work with people she knew: “cause I knew what I was getting myself into” (Elizabeth). Another student inferred that as the capstone project was such a big unknown experience, working with people he knew reduced some of the uncertainty. There was also a strong sense of students wanting to “hit the ground running” (Robert) which was more easily achieved when the group had prior experience of doing group work together. One student, Theo, described how he waited until week two of the course to see if there were any groups he could join so that he would be working with new people. However, he was contacted by friends and he ended up working with them. Peer pressure appeared to play

166  Research handbook on project performance a role in this decision to join a group. Theo could have said “no thanks” to his friends, but it was easier to say yes than to explain that he wanted to work with a new group. As a result of his cohort having completed the course in previous years, one student was forced to find a new group to join and this presented challenges for him. Mitchell reported that his group members did not have the same intentions or high expectation as he did: “I just think they didn’t see any value in it. From my opinion I thought they just saw it as a degree and capstone is just another subject and it’s just another 12 credits they needed to get”. Mitchell worked hard to encourage the group: “Maybe they weren’t as motivated as me … if we’re only going to put X amount of effort into this, how can I squeeze as much effort as I can get out of them and on top of that, how could I make that effort as effective as possible?” This was a learning curve for Mitchell and perhaps he benefited from being a mature student, having previously worked in non-project management related roles in the USA and Japan. Although he describes the group as in conflict because of the other members’ lack of interest in the course, he does recognise the development of his leadership skills and his confidence and ability to hold his group members accountable for their tasks. Eventually, he says, his motivation to achieve the best grade also slipped – partly because he was reportedly the only one who was motivated and partly because he had other assignments due at the same time. The mentors observed a stark difference in group development between familiar and unfamiliar groups. Familiar groups began the project with a reasonable to good level of perceived collaboration, communication, organisation, and professional behaviour, but they failed to improve. In contrast, unfamiliar groups were perceived by mentors to experience a poor start to the capstone course but then usually a significant improvement in coordination and professional practice. Group Conflict Despite most groups having worked together in previous assignments, interpersonal conflict was experienced by all students. On most occasions this was caused by a difference of opinion relating to the scope or output of the project, or disagreement relating to what the group members expected to personally achieve from the course – a good grade, or a quality project. Conflict relating to allocated tasks not being completed on time was often associated with group members who were already employed. None of the students reported that any conflict was ongoing throughout the duration of the project. It was always resolved quickly, either through discussion as a group, individual contemplation of the options, or through one-to-one conversing. Several students who were employed during the period of the project seemed to use their own experience to assist with resolving conflict in situations when a group member had not met their peer’s expectations. The approach taken was often a private conversation away from the group. For example, one student commented: “I kind of understood that there was something happening in the background ‘cause I was experiencing the same thing [work/study balance]. So it was good to sit down and just clarify” (Francine). The nature of such a conversation would have required the negotiating parties to develop skills in communication, compromise, preparing and developing a reasoned, logical argument, and in listening, all of which are highly desirable soft skills, if not in the very early stages of a career, then as a career develops (Deloitte Access Economics, 2017).

Building capability for project success  167 In the majority of cases, the groups kept their disagreements and associated resolutions away from mentor interactions. One mentor reported a sense that the group were “frustrated” with each other (Karen) and another quite the opposite – that her group was complacent (Penny). It is not known whether the students made a conscious decision or not to involve or exclude the mentor in their within-group disagreements. During interviews, the students rarely offered a comment on the mentor’s contribution to the project unless asked, suggesting that students did not feel that their mentors were part of the team and thereby not part of the conflict resolution process. Skills Gap Identification Part of lifelong learning and self-management of careers is the ability to identify skills that are missing but required in order to acquire or maintain employment. Academics may take for granted the safe context of a university assignment, where mistakes can be made without significant hardship, but this is not normally conveyed to students at the start of the capstone project. We asked students how they allocated roles and tasks to group members in order to explore if students reflected on what skills they would like to develop or consolidate during the capstone project assignment. We found that students allocated roles to group members based on their strengths rather than their weaknesses: “I personally put my hand up to do quality because I actually manage our quality assurance system at work … this is definitely best suited to me” (Grace) and “I was too ignorant to even know what I was lacking” (Mitchell). Mentors also noticed this preference: “Where someone was more comfortable doing a schedule they got the schedule” (Brendan). Only one student reported that as a result of the capstone project she became more aware of her skills gap. For example, when describing her approach to using a computer program (Excel) which is not very familiar, she explained her approach to learning: “I do just worry mostly about computer skills. That’s one area where I get sweaty under the armpits when I think about doing an Excel spreadsheet. I have spent a lot of time trying to learn Excel” (Elizabeth). Confidence Student’s development of confidence in their ability to “seek and gain employment in a job market” (Smith et al., 2014, p. 146) was measured quantitatively by asking about their perceived employability at the start and end of the capstone project using a scale of one to five. All students reported a higher score in their perceived employability at the end of the capstone course. The increase in perceived employability may be partly attributed to the offer of professional employment. In cases where the student was employed at the start of the capstone course, the increase was minor (for example, from 4/5 to 4.5/5). For students who had gained project-related employment during the capstone course, the increase was generally bigger (for example, from 3.5/5 to 4.5/5). The results suggest that students’ perception of employability may be impacted to a large extent by their current employment status rather than their experience of undertaking the capstone project. Irrespective of employment status, mentors reported that some students seemed to grow in confidence during the project: “He definitely gained a lot more confidence … ‘cause he

168  Research handbook on project performance was always asking – is there anything else that we should be doing?” (Karen). In this context, asking questions was considered to be a sign of confidence by the mentor. Ironically, confidence to ask questions may have eventuated as a result of the mentor creating an environment of psychological safety which then gave students permission to ask questions and not feel intimidated for fear of “sounding stupid”, feeling embarrassed, or being disregarded. Another sign of confidence perceived by some mentors was the willingness of students to turn on their camera during an online meeting and initiate discussion. However, mentors reported that some students did not speak unless asked a direct question, and their cameras remained off. Application of Course Knowledge and Skills – Connecting the Dots Two mentors used the phrase “connecting the dots” to describe the ability to draw on project management theory and implement it into practice. Mentors believed that part of their role was to help students translate theory into practice. For example, one mentor commented: “They knew there was an element of having to do it [risk management] but they couldn’t connect the dots to being able to make it relevant to what they were actually doing” (Bryson). Similarly, another mentor commented: “Getting them [students] to understand how we use project management, what we do and then giving them the skills to really think about it” (Karen). According to the mentors, the adoption of tools, techniques, skills, and knowledge developed during the project management degree was inconsistent. For example, one mentor reported that there was: “very little evidence of them [the students] stopping and thinking OK what are the relevant skills that I’ve learnt. Let’s use those learnings to help improve the outcome of the project. There was no project management plan, there was no WBS [work breakdown structure]. There was no schedule. There was no risk management consideration and I had to prompt all these things … They’ve done it because they’ve been asked to do it, and they’ve done what they felt was necessary to answer the question. It was not the case that they had actually stopped and thought about what the purpose of a risk assessment and risk plan was and used it to help drive value or to their WBS that was completely lacking” (Brendan). Similarly, other mentors reported that there was limited adoption of course-related knowledge and skills, and there was a need to prompt students to apply these in their projects. For example, Sarah asked her group: “Have you thought about the safety management plan? Stuff that I bet that they would have learned through their studies. It’s just kind of bridging that gap [between curriculum content and the capstone project]”. Some knowledge was adopted more frequently across groups, such as stakeholder management plans and risk management plans. In contrast, some groups did not integrate any of their prior learnings into the capstone project. For example, one of the students commented: “To be honest, no we haven’t looked back [at the curriculum covered in the degree]. We just honestly worked with the flow” (Charlotte). There was a sense from some students that experience of project-related employment may be more influential and valued than knowledge and skills learned through the university curriculum. For example, one student commented that she was undertaking quality management in her paid employment and applied that knowledge in her project: “For me it [quality management] was sort of like second nature. You know it’s been engraved into me” (Francine). This student went on to comment that once employed, some students disregard knowledge gained through the curriculum: “People, they forget things or delete all the documents and stuff, wipe

Building capability for project success  169 the slate clean, which I did too. You know, I actually deleted most of my [university] work” (Francine). Mentor’s Role Mentors perceived their role was integral to the success of the capstone project. For example, one mentor described how a brutally honest conversation with their group triggered a sudden improvement in project management and professional behaviour. “Some of the feedback in regards to prompting and leading questions like, have you checked with Council? Have you checked with the [stakeholder]? Have you done this and that? Kind of started the trigger [performance]” (Bryson). In contrast to the perception that mentors played a key role in the group’s success, many students did not mention the mentor at all during the interview. Furthermore, students did not mention mentors in the context of their perceived employability. This might suggest that students viewed the contribution of mentors differently to how mentors understood their contribution. Mentors perceived that their role changed during the capstone project, from giving approval to one of guidance through asking questions designed to prompt project management practice and behaviour. None of the mentors expected more than was reasonable for final-year students, and all those interviewed were excited by the growth in the groups that they had mentored. For mentors, the focus was not just on the successful achievement of the project outcome, but also on the process: “It’s not just about having a perfectly planned and executed and delivered project, it’s about all of the things that happen to get you there” (Brendan). Importantly, it was considered that the learning comes from the journey of the project, not the end result. Capstone is about “all the things that happen to get you there”. Observing the improvement of the group was extremely satisfying for mentors, as they felt they had contributed to the development of the group and the successful completion of the project. Mentors didn’t always want an “easy” group – this strips away the value that they can add to the group. Having said that, mentors didn’t want to allocate their time and energy to a group that made little to no effort. When they encounter a group that appeared not to care about the project (such as the group mentioned previously where the project was “just another 12 credit points”), mentors tended to reduce their effort accordingly.

DESIGNING FOR DIVERSITY OF EXPERIENCE At the start of the project management programme, first-year students can be considered as mostly a homogeneous group in terms of their project management related knowledge, skills, and experience. As our students move through the four years of the degree, that homogeneity evolves into a group of students who differ according to their knowledge, skills, and experience in project-related work. Our results highlighted the diversity of project-related experience, skills, and knowledge within the student cohort. This diversity presents as a challenge for the design of the capstone course and associated assessments. Assessments must be designed in such a way that enables growth and learning for a heterogeneous group of students who have varying learning needs and priorities around project-related skills development and knowledge. Course designers play an integral role in achieving this somewhat challenging task.

170  Research handbook on project performance Our findings showed that the employability of students improved during the capstone project, as evidenced by the increase in self-ratings between the start and end of the capstone project. Our results also showed that self-rated employability differed according to employment status. For those already employed, the benefit of the capstone project appeared to be the refinement of soft skills and the ability to view a project framework from a holistic perspective. In contrast, for those students who were not yet employed, the capstone project offered the ability for skill development and to apply knowledge from the degree to a live project from start-up to completion. The diversity of confidence, skills, and knowledge demonstrated by students acknowledges the importance of “self” in perceived employability. The focus on “self” introduces a subjective appraisal element to employability, and this is acknowledged by Vanhercke et al. (2014) who use the term “perceived employability” to describe “the individual’s perception of his or her possibilities of obtaining and maintaining employment” (p. 594). Again, this highlights the importance of designing a capstone project which enables our students to develop a sense of employability according to their own growth requirements while also meeting the requirements of the course learning outcomes. One way to achieve this is to encourage students to identify the project management tools and knowledge areas they find more difficult or have yet to fully grasp, and to use the capstone project as a “safe place” in which to practise and develop.

RECALL VERSUS INTEGRATION The project management university programme consists of eight semesters (two semesters per year over four years), and the capstone project is implemented in semester eight of the programme. A capstone course serves three purposes, one of which is to consolidate, extend, and apply previous learning (van Acker and Bailey, 2011). Our findings showed that students consistently integrated some knowledge areas into their capstone project, whereas other knowledge areas were often overlooked. When we consider this finding from a programme perspective, the knowledge areas which were most consistently recalled by students were those more recently covered during the programme. For example, the Project Risk Management course is taught in semester five, and the Project Planning and Communications is taught in semester six of the programme. The reluctance of students to reflect upon the earlier knowledge and skills acquired during the project management degree, and their preference to view courses as discrete blocks of information, suggests that more emphasis needs to be placed on scaffolding learning throughout the programme. According to Wijngaards-de Meij and Merx (2018), curriculum review can occur at two levels. In this study we focused on the content and structure of a single unit and how it supported the development of student’s employability. Our findings reiterate that the acquisition of project-related skills and knowledge must take a whole-of-programme approach. Completion of the capstone course is very much an amalgamation of student’s programme-wide learning across the four-year degree. Throughout the eight semesters of the programme, the curriculum can be designed in such a way that prior skills and knowledge learned is reinforced and applied in subsequent courses. This will assist students in gaining the most benefit from the capstone course which seeks to consolidate, extend, and apply previous

Building capability for project success  171 learning, and confirm that students have mastered skills relevant to their professional discipline (van Acker and Bailey, 2011). The findings also have implications for curriculum design at the course level. To facilitate the integration of project-related knowledge accumulated through the programme, students will be encouraged to view the curriculum not just from a single course perspective but from a programme perspective (Wijngaards-de Meij and Merx, 2018) and to refer to previously acquired knowledge and skills in the development and implementation of their capstone project.

INTEGRATING QUANTIFIABLE AND NON-QUANTIFIABLE SKILLS The PMI (2022) recognises the importance of a well-rounded skill set for project professionals consisting of technical skills, people skills, and strategic and business management skills. In the project management programme, the development of technical and soft (people) skills occurs throughout the programme. Arguably, technical skills are easier to observe and quantify than soft skills. In our research for example, students demonstrated that they integrated technical skills and knowledge through the development and implementation of risk management plans and communication plans. In contrast, integration of soft skills into the capstone project was more difficult to assess, and appeared to be less of a focus for students. During the third year of the degree, students develop knowledge of soft skills such as group development, conflict management, individual differences, and matching people to roles. The integration of soft skills and knowledge into the capstone project is an important element which should be emphasised to students in the future. In relation to employability, soft skills are considered essential for project professionals and are a critical aspect of career success (Ramazani and Jergeas, 2015). While our results suggest that students did not intentionally integrate soft skills and knowledge learned through the programme into the capstone project, some important findings emerged. Our results showed that soft skill development can occur during the capstone project itself, and is influenced by factors such as group composition and whether group members had prior experience in working together or not. Groups with prior experience of working together plateaued in terms of soft skill development compared to groups that had not worked together before the capstone project. Therefore, in future courses, students will be encouraged to work in a group of unfamiliar peers to maximise their soft skill development. Our findings suggest that student group development does tend to reflect the many stage-theories of group development such as Tuckman’s five stages of forming, storming, norming, performing, and adjourning (Tuckman, 1965) and more recently Karriker’s model in which group development is cyclical (Karriker, 2005). For example, groups with prior experience of working together skipped the first and second stages of group development and commenced the capstone project at the performing stage. Furthermore, the observed rapid increase in collaborative behaviour when a capstone project deadline was imminent also reflects the punctuated equilibrium model of group behaviour (Gersick, 1988) which suggests that there is still potential for group development to occur later in the capstone project. An interesting finding related to group composition comes from the reasons why students preferred to work with friends over strangers. These students chose to work with a familiar

172  Research handbook on project performance group with the intention of being able to “hit the ground running”. Effectively, the students had integrated risk management mitigation into their project by choosing to work with people who they knew and trusted. Using a risk management lens to inform their decision-making process is an important learning and one which warrants further reflection by students. The evaluation of the risk and adoption of a mitigation strategy is a skill useful for employment (Arain, 2010). Another soft skill which was demonstrated in all groups was conflict resolution. All groups experienced some form of conflict, usually relating to the project scope or to the unsatisfactory completion of tasks. Resolution was found to occur through two methods. Firstly, group discussion, followed by individual reflection and then coming together to agree on a scope. Secondly, individual students observed an issue and addressed it privately. Conflict is common on projects (PMI, 2021) and the ability to manage conflict is an important component of employability for project professionals. Arguably the most important soft skill for project success is the ability to collaborate with the team on project tasks (Bond-Barnard et al., 2018). Students are not a homogenous mass and it is in the area of collaboration that the biggest individual differences were observed. Some students preferred not to collaborate with their group whilst others enforced online group meetings for individuals to work simultaneously but remotely. Our results also showed that collaboration was more obvious at the start of the capstone project during establishment of the project scope. It then decreased dramatically whilst students worked on their individual tasks but then increased again at the end of the project when deadlines were imminent. Given its importance in project management, knowledge and skills in collaboration is an area which requires nurturing throughout the four-year degree. This can be achieved through carefully designed group-based assessments which commence in year one of the degree and are scaffolded throughout the entire four years.

ALIGNING EXPECTATIONS OF THE MENTOR’S ROLE Mentors were engaged to act as an advisor to students as well as to assess their work. However, our results identified that mentors and students had different expectations of the role of a mentor. Mentors highlighted that their advice had resulted in the addition of project-related activities deemed critical for successful project delivery. This is consistent with the literature which acknowledges that the role of the mentor is one of advisor who facilitates the transfer of knowledge and skills (Bermudez et al., 2018). Mentors also perceived that their role evolved from advisor in the beginning of the project to one of support. However, in exploring employability in the context of the capstone project, students did not often refer to the role of the mentor. It’s possible that some students regarded the role of the mentor as superfluous. Although some students had minimal engagement with their mentor, this did not seem to impact on the mentor’s satisfaction with the experience. Mentor satisfaction seemed to be more influenced by the mentor’s own desire to look for development and growth in the students. Our results showed that students consider confidence to mean ready to find employment, work with people, and to use their discipline-related skills. This is in contrast to how mentors assessed student’s confidence. For some mentors, confidence was judged by whether students asked questions of them in relation to the capstone project. Students may choose not to ask questions of those who they perceive to be in position of power (such as experienced project professionals) for a wide range of reasons, and this may or may not be due to confidence. For

Building capability for project success  173 example, one student described how her group had asked questions of their mentor but the questions were ignored. As a result, the group “felt so uncomfortable” and didn’t approach the mentor again. Individuals are more likely to ask questions when a psychologically safe space has been created and they don’t feel judged. Furthermore, feeling safe can facilitate relationship building with mentors (Tsuei et al., 2019). Creating a psychologically safe space in the mentor–student relationship is one area which could potentially help to improve the student’s engagement with mentors, and students’ willingness to ask questions. Some mentors also judged students’ confidence according to whether they switched on their cameras during online meetings. Switching on cameras enabled observation of body language such as eye contact. Besides being a sign of student’s confidence, other mentors believed that switching on cameras signposted respect and engagement. For example, a mentor commented that one group member never turned his camera on which showed disrespect: “it is completely disrespectful to mentors who give up their time to mentor students. Change the course so that students who don’t turn on their camera in remote meetings actually lose marks”. How people present themselves to employers is considered an essential element of employability (Hillage and Pollard, 1998). Mentors have the potential to coach and guide students on work protocols and expectations, which is aligned with the purpose of a capstone course as providing a vehicle for professional socialisation (van Acker and Bailey, 2011). In our study it appears that students did not capitalise on their opportunity to learn from mentors about the profession and related work protocols. This may have been the case as most students were already in professional employment and may have received mentoring from their employer. Aside from lack of confidence, it is worth examining alternate reasons for why students did not switch on their cameras. Some students have advised faculty that their laptop does not have an inbuilt camera. Other students are self-conscious about their background as they may be participating in the online meeting from their bedroom. Some students have Internet connections which limit their ability to switch on their camera. Research has also identified that being on camera can have a detrimental impact on individuals by contributing to fatigue, and in turn weakening their engagement and contributions in meetings. This effect was found to be stronger for females (Shockley et al., 2021). For mentors of future capstone projects, it is important for them to understand the reasons why students do what they do without judgement. In this example, having their camera off may not automatically reflect a student’s disrespect or lack of engagement. Again, this highlights the importance of creating a psychologically safe space in the mentor–student relationship that facilitates open and respectful dialogue to enable understanding, trust, and growth to support students’ employability.

CONCLUSION This chapter described a study undertaken to explore how a capstone project impacted on the perceived employability of final-year project management students from the perspective of both students and mentors. Our findings are invaluable in the further development of the capstone project. We acknowledge that our findings may not be relevant to capstone projects in other disciplines, and this is an opportunity for future research. Furthermore, we collected data from a limited sample of students and mentors, and therefore caution should be exercised in generalising findings to other students undertaking project management-related capstone projects. Future research can evaluate the implementation of interventions seeking to improve

174  Research handbook on project performance the role of the capstone project and its relationship to employability. Notwithstanding these limitations, one of the goals of a university is to prepare students for a successful transition into the workplace. This is enabled by the confidence and self-belief to apply the knowledge and skills learned at university. We believe that our study contributes to students’ professional preparedness through the examination and refinement of our project management capstone project.

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Building capability for project success  175 Peach, D. and Gamble, N. (2011) “Scoping work-integrated learning purposes, practices and issues”. In S. Billett and A. Henderson (Eds.), Developing Learning Professionals (pp. 169–186). Springer. Project Management Institute (2017) PMI’s Pulse of the Profession In-Depth Report: Success Rates Rise – Transforming the High Cost of Low Performance. Project Management Institute. Project Management Institute (2021a) Talent Gap: Ten-Year Employment Trends, Costs, and Global Implications. Project Management Institute. Project Management Institute (2021b) A Guide to the Project Management Body of Knowledge (PMBOK Guide) and The Standard for Project Management. 7th edition. Project Management Institute. Project Management Institute (2022) The PMI Talent Triangle. Project Management Institute. Accessed 30 March 2022. https://​www​.pmi​.org/​learning/​training​-development/​talent​-triangle Ramazani, J. and Jergeas, G. (2015) “Project managers and the journey from good to great: The benefits of investment in project management training and education”. International Journal of Project Management, 33(1), pp. 41–52. Römgens, I., Scoupe, R., and Beausaert, S. (2020) “Unraveling the concept of employability, bringing together research on employability in higher education and the workplace”. Studies in Higher Education, 45(12), pp. 2588–2603. Shockley, K.M., Gabriel, A.S., Robertson, D., Rosen, C.C., Chawla, N., Ganster, M.L., and Ezerins, M.E. (2021) “The fatiguing effects of camera use in virtual meetings: A within-person field experiment”. Journal of Applied Psychology, 106(8), pp. 1137–1155. Smith, C., Ferns, S., and Russell, L. (2014) The Impact of Work Integrated Learning on Student Work-Readiness: Final Report. Australian Government Office of Learning and Teaching. Accessed 25 March 2022. https://​espace​.curtin​.edu​.au/​handle/​20​.500​.11937/​55398 Smith, C., Ferns, S., and Russell. L. (2016) “Designing work-integrated learning placements that improve student employability: Six facets of the curriculum that matter”. Asia-Pacific Journal of Cooperative Education, 17(2), pp. 197–211. Tsuei, S.H.-T., Lee, D., Ho, C., Regehr, G., and Nimmon, L. (2019) “Exploring the construct of psychological safety in medical education”. Academic Medicine, 94(11S), pp. S28–S35. Tuckman, B.W. (1965) “Developmental sequence in small groups”. Psychological Bulletin, 63(6), pp. 384–399. Turner, N.K. (2014) “Development of self-belief for employability in higher education: Ability, efficacy and control in context”. Teaching in Higher Education, 19(6), pp. 592–602. van Acker, L. and Bailey, J. (2011) “Embedding graduate skills in capstone courses”. Asian Social Science, 7(4), pp. 69–76. Vanhercke, D., De Cuyper, N., Peeters, E., and De Witte, H. (2014) “Defining perceived employability: A psychological approach”. Personnel Review, 43(4), pp. 592–605. Wijngaards-de Meij, L. and Merx, S. (2018) “Improving curriculum alignment and achieving learning goals by making the curriculum visible”. International Journal for Academic Development, 23(3), pp. 219–231. Wingrove, D. and Turner, M. (2015) “Where there is a WIL there is a way: Using a critical reflective approach to enhance work readiness”. Asia-Pacific Journal of Cooperative Education, 16(3), pp. 211–222.

12. Role of project management maturity in project performance Vittal S. Anantatmula

INTRODUCTION Projects are routinely planned and executed to operationalize strategic goals and to improve operational needs and efficiencies. Needless to say, projects contribute to the operational and financial success of the organization (Anantatmula & Rad, 2016), and project management is widely recognized as a critical competency for organizations to thrive in the present global economy. Organizations select, plan, and execute projects, which can broadly be classified as internally and externally funded projects. For externally funded projects on behalf of clients outside of the organization, efficiency is the means by which the profit is enhanced. However, if the organization is in the business of providing service, manufacturing, or research, the majority of the projects are probably funded internally, and these projects aim to create increased operational efficiency, new products, or new markets. A nonprofit organization’s approach is different as projects in this organization are executed either internally or externally to serve a social cause and profit is not necessarily its purpose. However, in every type of organization, the underlying project management principles of effective and efficient use of resources are still valid. This is where the project performance assumes great importance. While the importance of project performance cannot be emphasized any further, it is equally important to establish a continuous improvement plan to enhance project performance. Learning from the past, sharing knowledge, and then improving project management practices and processes on a regular basis are what many sophisticated organizations do to improve their performance. This requires a broad view of completing a project on target to improving project management performance for enhancing performance of future projects. Ultimately, this approach should lead to managing higher profits and setting industry standards for project performance. This is possible with maturity in managing projects. Maturity in managing projects implies established, proven, and innovative practices and procedures that lead to success in planning and completing projects. Given organizational project management maturity leads to better profits through efficiency in operations and effectiveness in using resources, organizations are encouraged to promote, measure, and improve project management performance (Anantatmula & Rad, 2016). The success of an individual project is observed through measuring the performance in achieving the desired task-related values for the project such as scope, cost, and duration, and quality, which is integral to scope specifications. However, matured organizations, in addition to attending to the task aspects of the project, focus on the foundation for this success, which is provided by project teams and to the organizational issues of the project. In a nutshell, successful project results were the manifestation of productive project teams, supporting organizational functions, and processes during the execution of the project. 176

Role of project management maturity in project performance  177 With advances in information and communication technologies and consequent support from technological applications, and the growth of the project management profession due to efforts led by professional associations such as Association for Advancement of Cost Engineering International (AACEI), Project Management Institute (PMI), and International Project Management Association (IPMA), we expect better project performance and maturity in managing projects. But it is not the case and research suggest that many projects fail. A comprehensive literature review in the next section presents sets of project success factors, project management performance factors, and project management maturity factors. Two research methodologies are designed to explore relationships among these factors. The first study uses a survey questionnaire targeting project managers and project management professionals. The second research study focuses on in-depth objective analysis and understanding of project management-related practices, processes, and procedures implemented in selected organizations that have been historically successful in managing projects. A discussion section presents analysis of the survey results and the concluding section presents summary findings, recommendations, and future research efforts.

LITERATURE REVIEW A project manager has control over internal factors that include time, cost, and scope. External client factors largely depend on the articulation of clients’ requirements and needs. Eventually, these requirements translate into external factors such as usefulness, satisfaction, and effectiveness of the project deliverable. However, these measures of external success occur only after completion of the project and the release of the project deliverables. Both the internal and external factors contribute to project performance. The aim of this literature review is to identify key factors on project success, project management success, project performance factors, project management maturity, and the PMO (project management office). This extensive literature review serves to design a comprehensive list of questions for the survey. Project Success and Project Management Success Project success and project management success are different from normal definitions that we use to define critical success factors. The project success is often defined in terms of achieving project goals and project management success uses the conventional performance measures that include completing project within time, cost, and meeting scope and quality (Cooke-Davies 2002). Project performance is assessed in terms of successfully completing the project (Cheng, Ryan, & Kelly, 2012). Often, project success is defined in terms of cost, time, and scope. Managing cost and schedule within set goals reflects efficiency (Razmdoost & Mills, 2016) of a project and together, cost and schedule lead to efficient management (Mir & Pinnington, 2014), while the measures of project performance include schedule, budget, quality, and customer satisfaction (Berssaneti & Carvalho, 2015). The definition of project success has evolved from a traditional definition of completing the project within time, cost, and scope to a broadened focus of meeting stakeholder requirements and to achieving customer satisfaction (Jugdev & Müller 2005). Project success is defined by

178  Research handbook on project performance Table 12.1  

Project success measures Traditional measures of

New measures of project

project success

success

Evolved measure of project success

Management

On the project

On the product

emphasis Focus

Project management and

Economic, financial, and use

management measures of time, cost, and

implementation

of product or service

scope, resulting in measures of client

Success perspective

On the process

On the deliverable

satisfaction, utilization, and benefit to

Perspective of

PM and project team

Client/end user

Measured by

Internal factors

Type of factors

Tactical factors

Measurements

Time, cost, scope

A comprehensive measure of project success that combines the project

the organization. The time frame for this External factors under client’s project success measure is both short-term control (taken during the project life cycle and Strategic factors

Client satisfaction, organization benefit

Assessed

At project completion

At some time in the future

Time frame

Short-term

Long-term

at the completion of the project) and long-term (assessed at some point in the future when organizational benefits from the project deliverable can be measured).

Adapted from Dyett (2011).

providing value to all key stakeholders, namely the project team, the project sponsor and the sponsoring organization, clients, and end users. Baker, Murphy, and Fisher (1988) also highlighted the importance of customer satisfaction as a measure of project success. A decade later, another study identified project success dimensions that include project design goals, impact on customer, benefits to the executing organization, and preparing for the future (Shenhar, Levy, & Dvir, 1997). Of these, project design goals and impact on the customer are short-term. The remaining two success dimensions – benefit to organization and preparing for the future – have a long-term impact. However, complete assessment of project performance cannot be completed before the delivery of project outcomes and use by the customer or end user (Razmdoost & Mills, 2016). Project success is a complex, ambiguous concept that changes during the project life cycle. Project cost, time, and scope are important project success factors during project execution phase; however, after project completion and delivery of the product to the customer, these success factors lose their importance; satisfaction of the customer and other key stakeholders assumes greater importance as the project success factor (Özdemir Güngör & Gözlü, 2016). Nevertheless, cost and schedule are very important for project management performance. Jugdev and Müller (2005) suggest that projects are about managing expectations, which often are subjective perceptions of success. If a project is highly complex and uncertain (Yu & Kwon, 2011), it is better to define project success factors clearly and beyond the basic understanding of success. Furthermore, project success criteria may differ from project to project, and they can be categorized as project progress benefits and project performance benefits (Ojiako, Johansen, & Greenwood, 2007). In general, project success should be measured by taking various aspects into consideration such as project cost and time targets, the deliverable that accomplishes enterprise strategic objectives, and the enterprise financial objectives (Rad & Anantatmula, 2010). Success factors can also be classified into four groups: factors related to projects, the project managers and team members, the external environment, and organizational factors (Belassi & Tukel, 1996). Dyett (2011) classified project success measures into traditional measures, new measures, and evolving categories (Table 12.1).

Role of project management maturity in project performance  179 In summary, project success can be measured with three different sets of attributes: the client view (scope, quality, and client satisfaction), the team view (scope, cost, and time), and the enterprise perspective (financial and commercial aspects). Further, the contention is that unspoken and personal indices influence the perception of failure and success. Project Performance Factors A structured project management promotes discipline-specific knowledge and training of project personnel, establishes project management policies and procedures, priorities for projects, and consistent project management processes. Such a work environment makes it easier to deploy promising project management practices that lead to predictable project outcomes, improve management performance, and enable knowledge management (Özdemir Güngör & Gözlü, 2016). People-related factors contribute to project team performance and, in turn, project teams are directly responsible for project performance. The literature review in this section focuses on people-related project performance factors and organization factors that contribute to project success. Effective communication also plays a critical role in project team development, conflict management, negotiations, decision-making, and project performance (Anantatmula, 2016). Clearly defined goals, top management support, project plan and implementation processes, efforts to identify expectations of clients and stakeholders, project monitoring and feedback, sufficient communication with key stakeholders, and ability to handle unexpected problems are some of the factors in improving project performance and project success (Schultz et al., 1987; Pinto & Slevin, 1987). A few other studies considered factors such as clearly defined project mission, detailed plans, communication, and top management support as predictors of project success (Larson & Gobeli, 1989; Hartman & Ashrafi, 2002). Top management support was an important contributor of project success (Fedor et al., 2003). Another study (Özdemir Güngör & Gözlü, 2016) found that strategic top management support enables more effective operational support that, in turn, increases project performance. Project Management Maturity As projects focus on managing limited resources efficiently and effectively, portfolio management plays an important role in selecting projects that align with organizational and strategic goals. Portfolio management promotes execution of projects that are beneficial to the organization, as resources are not invested in projects that do not support strategic goals of the organization. Well-designed, effective project portfolio management improves project management maturity (Voss, 2012). Portfolio management promotes execution of projects that are beneficial to the organization, as resources are not invested in projects that do not support strategic goals of the organization. Project management maturity, although not directly related to project performance, is considered to be significantly related to business performance; obviously, it is important to have an organizational culture in place that supports knowledge sharing, collaboration, and empowerment to deal with issues related to project time, budget, and expectations (Yazici, 2009). However, contrary to these findings, maturity in project management processes demonstrated a strong association with a high project success rate for innovation projects (Besner & Hobbs, 2008). It is interesting to note that Zqikael et al. (2008) proposed a maturity model

180  Research handbook on project performance for improving project performance based on several top management support factors such as communication, quality management, advanced project management techniques, selection of project manager, measuring project success, and knowledge management system. Project management maturity models can also benchmark project management performance. Some of these models present a framework to improve project management capabilities and develop promising practices that will result in executing projects successfully (Pennypacker & Grant, 2003). However, the tendency to focus on project management and ignore other intangible strategic assets limits the competitive advantage offered by maturity models (Jugdev & Thomas, 2002). Organizational factors that contribute to project success, such as organizational culture, style, size, structure, the level of project management maturity also influence project success (Dyett, 2011). Organization culture and the context assume significance in forming project-friendly organizations (Rad & Anantatmula, 2010). These literature findings on project success factors, project performance factors, project management maturity, and PMO were used to develop a survey questionnaire and a structured interview case study questionnaire. These two instruments were used to explore relationships among all these factors and are discussed in the next section. Research Method Two independent studies collected data using the foundational literature review findings. The first study used a survey questionnaire designed to target project managers and project management professionals as participants of the study. This study used data from the perspective of project management professionals and project managers. The second research study was a case study designed for in-depth objective analysis and understanding of project management-related practices, processes, and procedures implemented in organizations that have been historically successful in managing projects. The first study focused on what is considered important for project success from people’s perspective; whereas, the second study focused on organizations’ project systems and practices that contribute to project success. Survey Questionnaire The survey questionnaire is based on factors shown in Table 12.2. It presents a literature review summary of the factors representing project success, project performance, and project management maturity. The survey was distributed among project managers and project management professionals. The survey respondents (106 responses) identified communication, top management support, and clearly defined project mission as the top three project performance factors followed by changes in project goals and collaborative culture. Of these, one can see a direct relation between changes in the project goals and project performance. Likewise, the study identified that customer satisfaction, meeting customer needs, accomplishing project scope and quality specifications, and fulfilling project objectives in terms of deliverables are considered as the top five project success factors. Our results suggest that a satisfied customer is considered more important than meeting customer needs, which underscores the importance of communication with the client and other key stakeholders. Research results of both project performance factors and project success factors underline the importance of communication as a key factor of project performance.

Role of project management maturity in project performance  181 Table 12.2

Factors identified from the literature review

Project performance factors

Project success factors

Organization PM maturity indicators

Project size

Completing within cost

Formalized and established project

Project policies and procedures

Completing within time

management procedures

Communication

Meeting project scope

Project portfolio management

Clearly defined project mission

Meeting project objectives

Project management office (PMO)

Changes in project goals

Meeting quality expectations

Project manager is a qualified PMP

Priority of the project

Meeting customer satisfaction

(Project Management Professional)

Top management support

Meeting customer needs

Project planning tools and techniques

Senior management expectations

Collaborative culture

Financial success Commercial success

Sources: Anantatmula (2010), Anantatmula and Rad (2013), Anantatmula and Rad (2016), Berssaneti and Carvalho (2015), Cooke-Davies (2002), Dell (2013), Hartman and Ashrafi (2002), Jugdev and Müller (2005), Kendall and Rollins (2003), Larson and Gobeli (1989), Park (2009), Pinto and Slevin (1987), Rad (2003), Razmdoost and Mills (2016), Shenhar, Levy, and Dvir (1997), Turner (1999), Voss (2012).

Research results on project management factors suggest that project portfolio management function within the organization improves the likelihood of three project performance factors: assigning priority for projects, meeting quality expectations, and meeting project objectives, whereas the presence of project portfolio management yields only one project success factor: customer satisfaction. The results also suggest that PMO may not have a direct influence on project performance or success factors. In summary, these results suggest the presence of project management maturity – consisting of portfolio management and formalized project management processes – improves project success and project performance. Case Study Method The case study used a set of questions for a structured, in-depth interview of senior-level managers. No specific project management maturity model was used in designing the questionnaire. The questionnaire was developed based on collective experience in managing projects, teaching, and conducting research on project management for several decades. The structured interview consisted of 469 questions addressing practices and processes related to projects, proposals, portfolio management, project teams, and enterprise sophistication factors such as the PMO, knowledge management, portfolio management, and organizational maturity factors. Key elements of the interview questionnaire are captured in Table 12.3.

 

182  Research handbook on project performance Table 12.3 Questionnaire

Key elements of the structured interview questionnaire Selected key issues addressed

topic Projects

Stakeholder analysis, guidelines for clearly defined client requirements and project deliverables, and norms

(106 questions)

for developing deliverable WBS. Initiation: strategic and financial objectives, availability of sufficient resources and funds, definitive plans, and detailed estimate. Plan: clear definition of objectives, well-defined deliverables, assumptions and constraints of plans and resources, and expected accuracy of plans and thresholds. Monitor: WBS level at which project is monitored, frequency of progress data collection and responsible party for data collection, earned value and level at which it is determined, and thresholds for variations in cost and schedule. Closeout: comparison of planned vs. actual project plan data, frequency of fine-tuning project constraints, changes to enterprise objectives, harmony level of the project team, frequency and magnitude of conflicts, project performance analysis and responsible party, and lessons for future projects.

Proposals

Models for planning, crafting, and allocation of resources for developing proposals.

(64 questions)

Identification of prospect: new market, new technical specialty, financial constraints such as cash flow, profit targets, desired accuracy level for estimates, financial health of the client, and types of contracts expected. Draft proposal: cost for preparing the proposal draft, responsiveness to technical and administrative issues, meeting or exceeding the expectations of the client, and success ratio of the proposals.

Portfolio

Portfolio data: measurable indices of cost, scope, quality, strategic and financial goals, and models for

management

managing these indices, periodic validation, and revision of formal and sophisticated prioritization model to

(111 questions)

align with changing enterprise objectives. Portfolio management: periodic review of the models and systems for prioritization, resource allocation, fully commissioned portfolio management team, and infrastructure for project management. Project portfolio prioritization data: information on scope, quality, cost, schedule, information on alignment of internal projects with enterprise strategic and financial objectives, and balanced portfolio of all project groups. Proposal portfolio prioritization: information collection on wide range of issues with the proposal and the performing organization. Proposal portfolio sophistication: fully quantified and quantifiable model with distinct attributes, formalized scoring of proposals that include project, team, and organization issues, and supporting organization structure. Proposal portfolio pipeline statistics: information on various important indices such as average profit, likelihood of winning the contract, statistics about proposals (size and range), winning proposal ratio, and return on investment for proposal development process.

Role of project management maturity in project performance  183 Questionnaire

Selected key issues addressed

topic Teams

● Use of various performance attributes of individuals to assign members for project teams.

(39 questions)

● Application of checklists (of indications) about how organization specifies personal interactions among team members ● Assess how individuals relate with each other using the checklist of personal interactions. ● Detailed list of team dysfunction symptoms and monitoring team’s performance, harmony, and productivity.

Enterprise

Checklists to determine sophistication of processes and practices in managing projects:

(149 questions)

Project management: ● Planning of project that includes WBS, risk, cost, schedule, and contracts, stakeholder management, integration during planning, resource allocation model. ● Portfolio management team that effectively manages multiple critical issues about projects, teams, organizational factors. ● Team development and management issues that include tools for planning, progress reporting, and change management, training, authority, responsibility, and accountability. Sophistication attributes: Monitoring and measuring various attributes related to competency of people, cohesiveness of the team, organization-wide support to projects (project-friendly organization). Sophistication in evaluating projects: Monitoring and measuring success in meeting project objectives, success during all phases of a project (initiation, plan, execution, monitoring, and closeout). Sophistication in managing portfolios and programs: ● Prioritization models to address strategic and financial goals, and funding imperatives. ● Processes for midstream review (preference to high-priority projects and programs). ● Formalized procedures for managing multiple projects and managing resources for high-priority projects and programs. Sophistication in creating a project-friendly organization: ● Level of comprehensiveness of PMO and its functions in measuring and monitoring to: ● Strengthen long-term enterprise-oriented functions of PMO. ● Strengthen and celebrate short-term team-focused supporting functions. Managing knowledge areas: Encourage continuous improvement of skills of individuals in managing projects and develop processes to strengthen planning efforts in cost, scope, schedule, quality, risk, contracts, communication among team members, and managing stakeholders. Checklist to measure and monitor project-friendly attributes Checklist to measure and monitor project success indicators Checklist to measure and monitor project management success indicators Components of maturity model: ● People issues ● Project facets issues ● Enterprise issues ● Existence of processes for projects, proposals, and portfolios ● Compliance of processes for projects, proposals, and portfolios Achieving success using these processes for projects, proposals, and portfolios

The comprehensiveness with which the study addressed all areas of project management through interview questions and the anticipated time required to participate in this study prevented some organizations from participating in the study. Three organizations known to have good project management practices and sustained success in managing projects, one each from the US, Japan, and India, agreed to participate in the study. All the three organizations have a long history of managing projects successfully, manage global projects with revenues

184  Research handbook on project performance ranging from $1 billion to $13 billion and employed more than 2,500 people in project-related activities. Existence and efficacy of processes in all five sections of the questionnaire and assessing the overall percentage of affirmative responses (presence of a practice or process) was used to determine an overall maturity level for each organization. If an organization responded affirmatively in the range of 80 to 89% for a set of items and it implemented them with efficacy, a maturity level of four was assigned for that section. All five sections of the questionnaire were evaluated independently, and a total percentage score determined the maturity level assigned to each organization. Interview responses from these case studies and results analysis suggested that project management maturity factors are likely to have contributed to sustained success in managing projects. Further, analysis of the responses from all three organizations suggests that the presence of project management maturity factors coincides with the presence of project performance factors, although direct relation between these two sets of factors could not be ascertained.

CONCLUSION The research results suggest that communication and top management support are important for improving project performance and project success. Further, the results show that customer satisfaction and meeting customer needs are considered more important success indicators. Organizations with formal project management processes are likely to use project performance planning tools and complete projects within cost and time. All three case studies suggest that the presence of portfolio management may likely promote formal project management practices and policies. Further, all three companies that participated in the study suggested that the presence of portfolio management and project management maturity factors increases the project performance and incidence of project success.

NOTE This chapter is a brief version of an original research paper and a full version is available: Anantatmula V. S. and Rad, P. F. (2018). Role of organizational maturity factors on project success. Engineering Management Journal, 30(3), 165–178. DOI: 0.1080/10429247.2018.1458208.

REFERENCES Anantatmula, V. (2010) Project manager leadership role in improving project performance. Engineering Management Journal, 22 (1), 13–22. Anantatmula, V. (2016) Project teams: A structured development approach. Business Expert Press: New York. Anantatmula, V. and Rad, P. F. (2013) Linkages among project management maturity, PMO, and project success. In Engineering, Technology and Innovation (ICE) & IEEE International Technology Management Conference, 2013 (pp. 1–12). IEEE. Anantatmula, V. and Rad, P. F. (2016) Attributes of project-friendly enterprises. Business Expert Press: New York.

Role of project management maturity in project performance  185 Baker, B. N., Murphy, D. C., and Fisher, D. (1988) Factors affecting project success. In Cleland, D. I. and King, W. R. (eds.). Project Management Handbook. Van Nostrand Reinhold: New York. Belassi, W. and Tukel, O. L. (1996) A new framework for determining critical success/failure factors in projects. International Journal of Project Management, 14 (3), 141–151. Berssaneti, F. T. and Carvalho, M. M. (2015) Identification of variables that impact project success in Brazilian companies. International Journal of Project Management, 33 (3), 638–649. Besner, C. and Hobbs, B. (2008) Discriminating contexts and project management best practices on innovative and noninnovative projects. Project Management Journal, 39, S123–S134. Cheng, E. W., Ryan, N., and Kelly, S. (2012) Exploring the perceived influence of safety management practices on project performance in the construction industry. Safety Science, 50 (2), 363–369. Cooke-Davies, T. (2002) The “real” success factors in projects. International Journal of Project Management, 20 (3), 185–190. Dell, D. (2013) From the ground up. PM Network (October 2013), 27. Dyett, V. (2011) Roles and characteristics of the project manager in achieving success across the project life cycle. Proquest Dissertations and Theses 2011. Section 1381, Part 0454 135 pages (Ph.D. dissertation). Florida: Lynn University. Fedor, D. B., Ghosh, S., Caldwell, S. D., Maurer T. J., and Singhal, V. R. (2003) The effects of knowledge management on team members’ ratings of project success and impact. Decision Sciences, 34 (3), 513–539. Hartman F. and Ashrafi R. (2002) Project management in the information systems and information technologies industries. Project Management Journal, 33 (3), 5–15. Jugdev, K. and Thomas, J. (2002) Project management maturity models: The silver bullets of competitive advantage? Project Management Journal, 33 (4), 4–14. Jugdev, K. and Müller, R. (2005) A retrospective look at our evolving understanding of project success. Project Management Journal, 36 (4), 19–31. Kendall, G. I. and Rollins, S. C. (2003) Advanced Project Portfolio Management and the PMO: Multiplying ROI at Warp Speed (pp. 23–54). J. Ross Publishing: Boca Raton, FL. Larson, E. W. and Gobeli, D. H. (1989) Significance of project management structure on development success. IEEE Transactions on Engineering Management, 36 (2), 119–125. Mir, F. A. and Pinnington, A. H. (2014) Exploring the value of project management: Linking project management performance and project success. International Journal of Project Management, 32 (2), 202–217. Ojiako, U., Johansen, E., and Greenwood, D. (2007) A qualitative re-construction of project measurement criteria. Industrial Management & Data Systems, 108 (3), 405–417. Özdemir Güngör, D. and Gözlü, S. (2016) An analysis of the links between project success factors and project performance. Sigma: Journal of Engineering and Natural Sciences, 34 (2), 223–239. Park, S. H. (2009) Whole life performance assessment: Critical success factors. Journal of Construction and Engineering Management, 135 (11), 1146–1161. Pennypacker, J. S. and Grant, K. P. (2003) Project management maturity: An industry benchmark. Project Management Journal, 34(1), 4–11. Pinto J. K. and Slevin, D. P. (1987) Critical factors in successful project implementation. IEEE Transactions on Engineering Management, 34 (1), 22–27. Rad, P. F. (2003) Project success attributes. Cost Engineering, 45 (4), 23–29. Rad, P. F. and Anantatmula, V. (2010) Successful Project Management practices. Emerald Group Publishing: Bingley, UK. Razmdoost, K. and Mills, G. (2016) Towards a service-led relationship in project-based firms. Construction Management and Economics, 34 (4–5), 317–334. Shenhar, A., Levy, O., and Dvir, D. (1997) Mapping the dimensions of project success. Project Management Journal, 28 (2), 5–13. Schultz, R. L., Slevin, D. P., and Pinto, J. K. (1987) Strategy and tactics in a process model of project implementation. Interfaces: Institute of Management Sciences, 17 (3), 34–46. Turner, J. (1999) The handbook of project-based management: Improving the processes for achieving strategic objectives. McGraw-Hill: New York. Voss, M. (2012) Impact of customer integration on project portfolio management and its success: Developing a conceptual framework. International Journal of Project Management, 30 (5), 567–581.

186  Research handbook on project performance Yazici, H. J. (2009) The role of project management maturity and organizational culture in perceived performance. Project Management Journal, 40 (3), 14–33. Yu, J. H. and Kwon, H. R. (2011) Critical success factors for urban regeneration projects in Korea. International Journal of Project Management, 29 (7), 889–899. Zqikael, O., Levin, C., and Rad, P. (2008) Top management support: The project friendly organization. Cost Engineering, 50 (9), 22–30.

PART III NEXT PRACTICES

13. Addressing the performance gap with lean-led design Hafsa Chbaly and Maude Brunet

INTRODUCTION Project definition represents the first phase of a project life cycle, during which client needs are defined and translated by the architects into design solutions (Forgues et al., 2018). In fact, about 80% of professionals’ decisions that will determine the outcome of the project and the work environment are made during this phase (Whelton et al., 2003). If the client needs are poorly defined, this may lead to considerable changes such as exceeding the initial budget, delays in project delivery, and client dissatisfaction (Safapour & Kermanshachi, 2019). In hospital projects, an “ill”-performed project definition might have a significant impact on nurses’ performance. A study realized in 36 hospitals in USA showed that the inappropriate design of work environment has consequences for nurses walking distance, which is about 5 km by dayshift. These long distances reduced their time spent on patient care activities to only 19.3% (Hendrich et al., 2008). Further, an unsuitable work environment might cause not only long walking distances for nurses but also healthcare service disruptions or hospital-acquired infections, which represent the main cause of injuries or patients’ deaths in the USA (Becker & Parsons, 2007; Hamilton, 2020). An unsuitable working environment in a hospital is illustrated with the example of burned patients. As these patients were usually hospitalized in intensive care units, doctors noticed that their death rate was high. This was due not only to their burns, but also to a nosocomial infection – that is to say, germs resistant to antibiotics – which was present in the intensive care units (Santucci et al., 2003). The solution was therefore to create new independent services for these burned patients, in order to offer them more suitable and safer care spaces to avoid infections or any other complications. Defining and formalizing client needs during the project definition phase is therefore important to create more suitable working environments and thus improve patient safety. However, this phase is usually neglected. Further, conventional non-participative practices seems inadequate so far, leading to a “design performance gap” (Forgues et al., 2018; Tzortzopoulos et al., 2009). One of the solutions suggested to address this design performance gap is to apply a participatory approach, namely lean-led design (Grunden & Hagood, 2012). This chapter aims to explore why conventional practices lead to a “design performance gap” in healthcare projects and how a lean-led design approach could address this issue. The first section presents the complexity of defining needs in healthcare projects. The second section looks at how the “design performance gap” is defined and why conventional practices lead to that. The third section explores how a lean-led design approach could enhance practices based on a mega-hospital case study. Finally, implications and concluding remarks are presented. 188

Addressing the performance gap with lean-led design  189

THE COMPLEXITIES OF DEFINING NEEDS IN HEALTHCARE FACILITIES Defining client needs in hospital projects is a complex task, due to two main reasons. The first one is about the definition of who is the client. In fact, in such projects, a client is represented by many entities and individuals. A “client” is at the same time the funders (usually the government), project managers (representant of the client), and users (doctors, nurses, patients, staff, etc.). Each client has their own needs, perceptions, and interests that could be in contradiction with others (Apaolaza & Lizarralde, 2020). To take a concrete example: administrative and maintenance staff seek to reduce operating costs, nurses need quick access to all the equipment necessary to provide care, and doctors focus on improving the functioning of their services to provide better care for their patients. Supposedly, every doctor wants the same thing: to help their patients get and stay healthy. The problem is that every doctor can have a different view of the meaning of getting and staying healthy and how to achieve that in practice. The second reason for defining client needs complexity is about the nature of the needs. In fact, in hospital projects, the needs that should be defined are uncertain. They are evolving in time due to the demographic changes and the rapid advances in medical technologies, among other things. According to the World Health Organization, about 80% of the entire population could develop cancer within the next 20 years (WHO, 2020). The increase in certain diseases or in the overall population means that certain medical departments need to enlarge their work areas, which implies a reorganization of space. Further, the constant evolution of technologies requires not only adjustments in clinical practices, but also reconfigurations of the workspaces. As an example of that, robotic systems are increasingly used for some surgeries, so the architectural design of operation departments should change accordingly and reflect the latest technology advancements as well as patients’ care requirements. To do so appropriately, architects must be aware of new trends, and take into account the new needs of users. Given these two main challenges in defining clients’ needs for hospital projects, the traditional project definition practices do not seem appropriate, as they cannot address this level of complexity.

DESIGN “PERFORMANCE GAP” WHEN USING TRADITIONAL PRACTICES In the conventional practices, client needs are established without the participation of clients-users (Blyth & Worthington, 2010). What typically happens is that just the funders (client sponsor) or their representants are involved in the project definition phase. Users are neglected or rarely consulted (Blyth & Worthington, 2010; Forgues et al., 2018). However, if architects do not involve users in the process, how could they properly understand how they perform medical operations and thus propose an efficient design solution? In conventional practices, needs are defined based on past statistical data, and future activities are projected by taking into account demographic trends, new practices, and technologies. Based on that, designers deduce with mathematical calculation rules, some of which are recognized or elaborated, the square meters required, and the number of rooms, stretchers, beds, etc.

190  Research handbook on project performance Further, in hospital projects, different aspects should be considered simultaneously: technical, functional, and social (Hicks et al., 2015). However, with conventional practices, the focus during the project definition process is more on technical aspects (e.g., structural and mechanical), leaving out other ones (Serugga et al., 2020). Client needs are mainly defined by external architects and clinical managers that do not have enough resources or information to take into account the abovementioned issues. Architects usually make assumptions on the basis of their understanding of user needs, which is influenced and affected by their own cultural and personal background (Whelton, 2004). Kamara et al. (2002) argue that architects tend to concentrate on design sooner than on capturing client needs and defining clear requirements. They also argue that very often the client does not have control over the definition process and the architect plays the central role, likely holding the belief that the “Expert knows best”. Thus, many project definition inefficiencies can be attributed to the lack of client involvement (Barrett & Stanley, 1999; Kamara & Anumba, 2001) which gives the project suppliers (i.e., architects and engineers) the predominant perspective in the process. Because of that, apparent deficiencies in design quality and performance of healthcare buildings have been noted when using conventional practices. It was reported that these practices have failed in fulfilling client needs (Serugga et al., 2020; Tzortzopoulos et al., 2009). More specifically, it results in three misalignments: (1) between the real client needs and what architects perceive of them, (2) between what architects perceive of client needs and how architects translate them into specific requirements using an architectural and technical vocabulary, and (3) between the specific requirements and the actual design solution proposed by the architects. These three misalignments constitute the “design performance gap”. To address this gap, participative approaches like lean-led design have been recommended (Caixeta et al., 2019; Grunden & Hagood, 2012).

BRIDGING THE “PERFORMANCE GAP” WITH LEAN-LED DESIGN Lean-led design is defined as a “systematic approach to healthcare architectural design that focuses on developing, and integrating safe, efficient, waste-free operational processes in order to create the most supportive, patient-focused physical environment possible” (Grunden & Hagood, 2012, p. 18). This approach is seen as the most appropriated one to deal with the “performance gap” during healthcare project definition as it allows the client (user) participation (Chbaly et al., 2021; Schouten et al., 2020). For the purpose of better understanding the differences between the traditional and participative approaches, we undertook a case study of the New Complexe Hospital (NCH), located in Quebec, Canada (Chbaly, 2021). The project, estimated at 1,97 G$, is a merger of two hospitals in Quebec. The purpose of this consolidation was to simplify access to the care management systems and to reduce the distance between different hospital services, thereby improving the quality of patient care. The complexity of this project is not only due to the need for construction of new buildings but also because of maintaining the regular operation of the two functioning hospitals. To deal with this complexity, the clinical management team members of NCH adopted a lean-led design approach during the project definition stages.

Addressing the performance gap with lean-led design  191 This approach consisted of the implementation of five lean workshops between 2014 and 2015. Each workshop was held to cover different topics: ● Workshop 1 (building a patient-centered hospital): The objective was to define common principles along with a common vision of the future hospital. ● Workshop 2 (building a patient-centered hospital): The objective was to comprehend the reality and workflow of the two hospitals merged and identify existing problems. ● Workshop 3 (combining our strengths): The objective was to define the location of the hospital sectors while thinking about workflow effectiveness. ● Workshop 4 (imagining the future hospital together): The objective was to illustrate the different possibilities of positioning hospital sectors on the site and to keep the best implementation hypothesis. ● Workshop 5 (defining and validating our operating modes): The objective was to transform practices while thinking about this new organization and to prepare for the transition. Those workshops were designed to allow communication and collaboration between the different sectors with specific consultation periods, and involving the main clients including the users in the process. More than 300 people including external observers from the Ministry of Health, architects, project managers, clinicians, and patients participated in these events. Patients who participated during those workshops were selected from a database of volunteers. Most of them suffered from chronic illness (e.g., kidney disease, reduced mobility). However, due to the difficulty of recruiting them, these patients did not represent all hospital departments. Thus, unlike in the conventional approach, where users are rarely involved and consulted during the process of project definition, in this context users (clinicians and patients) were involved throughout the process. These users were not passive as with conventional practices; they had more power in the process with a more proactive position since their level of involvement was high. This involvement permitted considering the many different points of views of clients as well as functional and technical requirements. It also helped designers to better understand needs and thus align them with the building design (Caixeta & Fabricio, 2021). User involvement in the project definition process is, itself, indicative of user power and influence over the decision-making process. In the NCH project, the users participated in the process of selecting the best hypothesis of the implementation of the different sectors of the hospital. In fact, designers had proposed five hypotheses and all of them were rejected by the users. Based on this initial evaluation, designers reviewed the implementation hypotheses and after some days of work proposed two more, of which one was accepted by the users. Nevertheless, involving a large number of client (users) in the project definition requires more work for the architects than with conventional practices. Implementing a lean-led design approach requires that architects bring decision-making closer to users and to open up the discussion. To do so, not only are designing skills necessary, but also knowledge in other disciplines such as sociology and marketing, among others, in order to turn ideas into viable practice (Caixeta et al., 2019). Also, implementing participatory approaches, such as lean-led design, is challenging especially when setting priorities, as they are subjective and related to

192  Research handbook on project performance users’ perceptions. As an example, during lean-led workshops, all doctors wanted to have a proper office; however, it was not possible due to the limited budget. Thus, designers took the decision to design shared offices because having individual offices was not as important as having individual patient rooms. Deciding on what needs are more important than others is not an easy task and can complexify the decision-making process. Moreover, designers and users (clinicians and patients) speak two different languages, and have different vocabularies and referents. One is architectural, the other medical. So when they have to work collectively during the workshops to define needs and the hospital space design, a lot can be lost in the process. Before the workshops were organized in the NCH project, six training sessions of about one hour were organized by the internal team of the clinical management. The objective was to introduce or refresh some lean concepts and architectural vocabulary regarding scale (area, square meters, etc.) and thus facilitate a mutual understanding and perception of user spaces by using a common vocabulary. To this end, the organizers of these sessions used reference points such as a football field, an ice rink, etc. Thanks to a better comprehension of the dimensions of each area, participants were able to quickly see the need to reduce patient movements and organize the essential activities and services in a more efficient manner. Further, to maximize the common alignment between designers and users, different visualization tools and techniques were used during the workshops. For instance, during Workshop 5, as the objective was to test or validate operating modes, the participants used small and full-size mock-ups. The idea was to reproduce standardized rooms in an environment mock-up on a small scale to facilitate the understanding of spaces for participants, using removable walls. The rooms presented in the full-scale mock-up were often “standard rooms” or particular rooms, as, for example, rooms in a care unit, intensive care units, examination rooms, etc. By using visualization tools and techniques, participants could better understand the solution. They also give a clear idea about information discussed which makes it easier for users to comprehend and therefore identify problems or areas that need to be improved. Hence, contrarily to traditional project definition practices where the visualization tools and techniques are usually neglected, in a lean-led design approach they are usually used at the start of the process. Furthermore, standardization of the designed spaces represents one of the principles used in the NCH project during the project definition. The objective is to deal with the uncertainty of needs by making the space much easier and more flexible for architects to design (Grunden & Hagood, 2012). Doing things the same way every time should facilitate the development of safer spaces for patients, for instance by providing efficient and comfortable rooms in terms of size and configuration. An example of that is to always locate the space for family members to the left of the patient (Grunden & Hagood, 2012). The reliability that results from a standardized space may sometimes make a life-or-death difference for patients. However, unifying rooms is not easy to achieve in mega hospitals because several spaces and rooms are unique and could not be standardized, for instance in the case of emergency stretcher space (Chbaly, 2021). Another particularity of lean-led design is that it includes an analysis of the seven trajectories in hospitals: (1) patients, (2) staff, (3) visitors, (4) supplies, (5) equipment, (6) medication, and (7) information (Hicks et al., 2015). In the NCH project, this analysis was realized during Workshop 2. To take the example of patients’ trajectories, participants in the workshop illustrated current care trajectories of five fictitious patients, representative of about 80% of the

Addressing the performance gap with lean-led design  193 sectors including one exclusive to each hospital. Based on that, the participants identified similarities and differences between both hospitals, as well as different problems. The purpose was to minimize the waiting time, optimize and create secure trajectories, and promote information and care continuity to facilitate patients trajectories (Smith et al., 2020). Unlike with conventional practices, in a lean-led context all participants work together to think about the best way to create unified trajectories and efficiently organize the care sectors before calculating the square meters or proposing a conceptual design. The participants analyze the current processes and assess how they could be optimized in order to generate an understanding of all the activities of the organization toward a systemic generalization. The workshops included real patients who were encouraged to participate and give testimonies to all participants; it was even acknowledged that they helped raise awareness about various issues that were not clear and evident at first to clinical staff and designers. Having said that, involving users in the project definition process can facilitate not only a mutual understanding, but also a mutual learning. Contrarily to the traditional unidirectional mode, a participatory approach enables designers to learn new medical practices, and for users (doctors and nurses) to learn and discover the different limits of the building (Chbaly, 2021). Another point to note is that in the NCH project, the balance of power between users and designers changed since users had acquired an understanding of the working scenario and they were seen as co-designers during the project definition. This does not appear to be a common practice. In the usual process of management, the predominant perspective is of the architects and not of the user (Caixeta et al., 2019; Grunden & Hagood, 2012; Smith et al., 2020). Thus, the lean-led design approach presents by itself a structured innovation encouraging participants to resolve problems through a shared understanding and exploration of possible solutions (Grunden & Hagood, 2012). Lean-led design as a managerial innovation enables the development of a shared understanding among stakeholders, which could lead to better project and organizational performance (Damanpour & Aravind, 2012). It promotes new methods of working, helping to designing care services around the patient. However, the time and investments required for undertaking such an approach are not to be minimized, be it the structure to put in place, a dedicated team, or physical and material resources (such as full-size mock-ups), along with other compensatory measures for having the participants in each of the workshops. To conclude, a lean-led design approach was applied in the NCH project in order to firstly reduce the complexity of merging two hospitals, since each had its own culture, and operational methods to provide healthcare services. Secondly, it was implemented in order to address the “design performance gap” by involving different clients. Based on the presented example, we have identified different benefits of using such a participatory approach (e.g., creating a shared understanding). The case study reviewed helps to identify and highlight the main differences between the conventional and the lean-led design approach, which we summarize in Table 13.1. The first difference is about the involvement of users in the project definition phase. In the traditional mindset, they are usually neglected. The second difference is about the starting point of each approach. While traditional practices start with defining the functional and space program (for instance, calculating the number of offices and beds), a lean-led design approach starts by analyzing and optimizing the current situation of the hospital processes. This helps to improve the operations of the future hospital by removing waste (e.g., the patient’s waiting time) before defining the number of offices required or the square meters.

194  Research handbook on project performance Table 13.1

Conventional versus lean-led design approaches

  1

Participants

Conventional approach

Lean-led design approach

Clinical managers of the hospital

Clinical managers of the hospital

Project managers

Project managers

Funders

Funders Users (clinicians, patients, etc.)

2 3

Starting point Methods/tools

Starts with a space program (number of rooms,

Starts with an analysis and optimization of the

stretchers, beds, etc.)

current processes

Documentation

Documentation

Interviews

Workshops Small and full-size mock-up

4

Focus

Design solution

User (patient) needs

5

Decision-making

Experience-based

Consensus

The third difference is that in the participatory approach, architects use methods/tools such as workshops and mock-ups in order to define client needs. This is not a common practice in the traditional mindset. Another difference is about the project definition focus. While the focus of conventional practices is on providing a design solution on time and on budget, a lean-led design focus is on patients to get more effective care. A leading principle to this end was to provide for versatile, agile, and accessible care and services. The last difference identified is about decision-making. In fact, with traditional practices decisions about the client needs are made by the architects based on their experience. This means that these decisions are not taking into account people who will use the facility, unlike with the lean-led design approach, where decisions are made collectively involving all client stakeholders.

CONCLUSION The “design performance gap” is frequently associated with conventional practices especially in hospital projects, where clients are multiple and needs are changing over time. Apparent deficiencies in the design quality of hospitals raise an important necessity for enhancing the traditional ways of working. This chapter illustrates through the case of a Canadian hospital megaproject how a lean-led design approach aimed at bridging the performance gap by involving clients (users) during the project definition. The lean-led design approach implemented by the clinical management of this hospital enables commitment as well as communication between architects and users (doctors, patients, etc.). Further, unlike with conventional practices, it begins with an in-depth questioning of current ways of doing things before moving on to architectural concerns, placing the patients at the center of the reflection. The aim is to create spatial configurations that facilitate the operations of healthcare services, making them safer and more efficient. The results and discussion of this chapter have brought forward important considerations regarding the role of early client stakeholders’ involvement by illustrating how a lean-led approach contributed to project definition. The main differences between this approach and the conventional one are also highlighted, and could also be applicable to similar large-scale

Addressing the performance gap with lean-led design  195 projects, where many functions and different users interact (for instance, cultural buildings or airports).

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196  Research handbook on project performance Whelton, M., Ballard, G., & Tommelein, I. D. (2003). A knowledge management framework for project definition. Journal of Information Technology in Construction (ITcon), 7(13), 197–212. World Health Organization (WHO) (Organisation mondiale de la Santé). (2020). L’OMS présente des mesures de lutte contre le cancer qui pourraient sauver 7 millions de vies. https://​www​.who​.int/​ fr/​news​-room/​detail/​04–02–2020​-who​-outlines​-steps​-to​-save​-7​-million​-lives​-from​-cancer​?fbclid​=​ IwAR3V​2MiJMno9Zo​L05nEAZF0O​STciSpK8RL​Vd8Ci9UXWA2nvVJSbFcB​_oNIo.

14. Fixed capacity and beyond budgeting: a symbiotic relationship within a scaled agile environment Yvan Petit and Carl Marnewick

INTRODUCTION With the advent of agile approaches to managing software development projects, large organizations have begun to implement agile at scale; i.e., on many projects and on large projects in their organization. Scaling agile has an impact on various other aspects of the organization, such as human resources, finance and the way scheduling and planning are done. Organizations that were used to authorize new projects with stage gates to confirm the project scope, budget and schedule are now faced with a new environment where the development is more continuous and closer to a manufacturing flow. Planning in a scaled agile environment is done based on a fixed capacity basis and not on a project-driven basis. This has implications for how performance gets planned and measured and it implies that the way costing, budgeting and resource planning are done is also affected. Project teams are accustomed to the traditional way of planning for projects based on the project life cycle and financial evaluation (Project Management Institute, 2017). Resource allocation and the costing of the project are traditionally based on the schedule and scope. A department or division, such as the IT department, has multiple projects within their portfolio and the cost of these projects is then offset to the customers or sponsors of the product. The demand is high on the project team to deliver more within less time, which might lead to increased cost due to overtime. The result is that the costing of the project becomes problematic when the overall budget of the department or division is exceeded. The rationale of fixed capacity is that a resource has a limited capability of work that can be done within a certain period. The delivery of the final product thus depends on the capacity of the team members and nothing else. The cost of the team is static, as total cost to company (CTC) for each team member does not change. The only variable is the time that it will take to deliver the product. A team will work at their fixed capacity and will deliver features at a regular time. There is little research on the impact of fixed capacity on the costing and budgeting within a department. While current research is focused on flow within a lean production environment and the concept of beyond budgeting is researched from an accounting perspective, this chapter attempts to highlight the symbiotic relationship between fixed capacity and beyond budgeting. This symbiotic relationship has an impact on how teams are being accounted for, how budgeting is done and how product development is monitored and controlled. This chapter contributes to the current but limited body of knowledge regarding fixed capacity and beyond budgeting within a scaled environment. The first part of the chapter deals with the relationship between fixed capacity and beyond budgeting. The research methodology entailed a single case. The single case provides in-depth 197

198  Research handbook on project performance knowledge and analysis of how an organization employed the concepts of fixed capacity and beyond budgeting. The chapter concludes with analysis and discussion sections.

LITERATURE REVIEW Fixed Capacity In a scaled agile environment, organizations focus on maximizing the delivery of applications and services (Laanti, 2014; Turetken et al., 2017). Product development flow is crucial. To achieve this, organizations establish a fixed capacity model and then prioritize features accordingly, so that they address a rate that matches the fixed capacity. With fixed capacity, the aim is to visualize the workflow within a project and to prioritize the work-in-progress (WIP) in accordance with the capacity of the team. The objective is to maintain a constant flow of work and product output rather than requesting additional resources when demand exceeds supply. Fixed capacity offers transparency and flexibility to the team and the organization at large (Hür Bersam & Gül Tekin, 2019). The fixed capacity model allows organizational strategies to drive the overall pattern of activity (Johnston & Gill, 2017; Marnewick & Marnewick, 2019). One advantage of the fixed capacity model is that it tends to achieve release of products at a more predictable rate than the project-driven approach (Johnston & Gill, 2017). This improves the performance of the team and the project itself. With the introduction of flow and fixed capacity, the funding and administration around projects must change. Business units buy fixed capacity at a certain price and then work is prioritized for implementation (Marnewick & Langerman, 2018). The budget allocation must therefore move from a project-driven allocation to a fixed capacity allocation. The implication is that traditional budgeting of projects changes and, in a projectized environment, opens the door for the introduction of the concept of beyond budgeting (Hope & Fraser, 2003a, 2003c). The prerequisite for fixed capacity is the notion of flow. Flow is achieved through the reduction of waste in the process. This is a direct result of the introduction of lean software development that is used to optimize development processes (Kišš & Rossi, 2018). Lean software development is built on seven principles, i.e. (i) eliminate waste, (ii) decide as late as possible, (iii) amplify learning, (iv) deliver as fast as possible, (v) empower the team, (vi) build integrity in and (vii) see the whole (Kišš & Rossi, 2018). To achieve flow, the team needs to control the amount of work that they perform or the current WIP items or features. The introduction of flow impacts the way projects are estimated. The focus is on what can be delivered (scope or features) within the fixed capacity of the team (time). Cost is a constant. Figure 14.1 is a graphical depiction of how fixed capacity has changed the way constraints are managed. In the more traditional way of doing projects, the features (scope) are predetermined as part of the project scope management process. The scope determines the schedule and cost. The complexity and urgency of the project determine the schedule and costing. More money is poured into the project to deliver more features (scope creep) within the fixed time frame. When an organization follows an agile approach, cost, time and quality are fixed; e.g., resources work eight hours a day at a fixed hourly rate (salary). The variable is how many features they can deliver within a 40-hour work week and by extension within a sprint of three to four weeks. Estimation at the beginning of an initiative is used to predict how much the team can get done in a given time frame or sprint (fixed) and at a given cost (fixed). Estimation is

Fixed capacity and beyond budgeting  199 not used as a target that should be achieved as closely as possible to measure performance, as is the case with the scheduling of projects using a Waterfall approach (Engwall & Jerbrant, 2003; Kupiainen et al., 2015; Zika-Viktorsson et al., 2006).

Source: Casanova (2013).

Figure 14.1

Impact of flow on project constraints

A good illustration of flow control is Kanban where work is pulled only when there is capacity. Flow is maintained in a such a way that it enables continuous value creation to customers through the constant delivery of products or services (Mandić et al., 2010). The emphasis is on creating value for the customer by reducing waste (e.g., time and staffing) (Poppendieck & Cusumano, 2012; Swaminathan & Jain, 2012), in comparison to a project-driven approach where work is pushed (Kupiainen et al., 2015). Figure 14.2 illustrates the linkage between flow and fixed capacity and eventually beyond budgeting. Fixed capacity results in a constant flow. A new budgeting process must be implemented based on this new way of utilizing resources.

Figure 14.2

Relationship between flow, fixed capacity and beyond budgeting

Traditional budgeting depends on an up-front estimation of cost and scope. In an agile environment, this is not the case and budgeting cannot be based on cost and scope as they are not fixed (Cao et al., 2013). The use of traditional budgeting conflicts with some of the principles of a scaled agile environment.

200  Research handbook on project performance Traditional Budgeting Bhimani et al. (2008) (cited in Goode & Malik, 2011) define a budget as a quantitative future plan created by managers to assist the implementation of this plan. A more recent definition by Vierlboeck et al. (2019) links the definition of budgeting to performance: ‘Budgeting is the process of operational allocation for financial resources to an organization’s units, as well as the analysis and selection of investment opportunities/possibilities in order to create value and a record for subsequent measurement.’ Budgeting plays an important part in most organizations, as it steers the organization (Réka et al., 2014) and represents an important control system for the majority of organizations (Becker, 2014; Lohan, 2013). It involves many management processes such as strategy formation and implementation, evaluation of performance as well as motivating employees (Hänninen, 2013). It has become so institutionalized that most of the accounting literature just assumes that firms carry out an annual budgeting exercise (Henttu-Aho & Järvinen, 2013). However, traditional budgeting has been criticized for some time now (Heupel & Schmitz, 2015; Hope & Fraser, 2003b; Lohan, 2013; Nguyen et al., 2018). Neely et al. (2003), Bogsnes et al. (2016) and Ekholm and Wallin (2011) identify a long list of disadvantages of annual budgeting: ● ● ● ● ● ● ● ● ● ●

a very time-consuming process weak links to strategy stimulates unethical behaviors assumptions quickly outdated provides illusions of control decisions are made too early decisions are made too high up often prevents the right things from getting done often leads to the wrong things being done a language ill-suited for performance evaluation.

Goode and Malik (2011) cite research showing that the budget creation uses up to 20% of management time and that even the leanest and most efficient companies take 79 days to organize their budgets, while 210 days are spent in the worst-practice companies. This is a considerable amount of time for a firm to spend on an activity that arguably adds no value to the business. However, numerous organizations continue to use it (Libby & Lindsay, 2010; Lorain, 2010; Réka et al., 2014). The reason for this, according to Bourmistrov and Kaarbøe (2013), is the variety of purposes it serves but also the comfort zone that it provides to management. Budgets have been ingrained in the culture of business and managers find it extremely difficult to shift to a system without budgets (Goode & Malik, 2011). Because of the criticisms of traditional budgeting, researchers and practitioners have stated that there is a need for a new and improved system that will be a better fit in today’s agile business environments (Goode & Malik, 2011; Lohan, 2013; Réka et al., 2014). Some authors suggest improvements to the budgeting process (Hansen et al., 2003; Libby & Lindsay, 2010) or other forms of budgeting such as bottom-up budgeting, top-down budgeting, hybrid approaches, incremental-based budgeting, zero-based budgeting, activity-based budgeting and beyond budgeting (Vierlboeck et al., 2019). However, a solution proposed by several studies to solve the problems caused by traditional budgeting is the abandonment altogether of the

Fixed capacity and beyond budgeting  201 fixed annual performance contract supported by the principles of ‘beyond budgeting’ (Daum et al., 2005; Hansen et al., 2003; Hope & Fraser, 2003a, 2003d; Réka et al., 2014). Beyond Budgeting Beyond budgeting is a management control system that seeks to improve performance using flexible sense-and-respond mechanisms (Hope & Fraser, 2003a; Lohan, 2013) as opposed to a yearly corporate budget. The groundwork of beyond budgeting commenced in the mid-1990s (Hope & Fraser, 2003a, 2003c; Nguyen et al., 2018) following the first initiatives in Sweden in the 1980s (Wallander, 1999). Daum et al. (2005) states that the journey of beyond budgeting began because of the growing dissatisfaction with the traditional management approach based on traditional budgeting. Beyond budgeting is defined as an alternative performance management model that enhances organizational adaptability and responsiveness by incorporating changes in the business culture and entire management control system (Nguyen et al., 2018; O’Grady et al., 2017; Sandalgaard, 2012). The focus of beyond budgeting is a management model that is more empowered and adaptive and that is beyond the traditional command-and-control. Beyond budgeting is a holistic management approach that is based on relative performance evaluation, subjectivity, rolling forecasts and nonfinancial performance measures (Sandalgaard, 2012). Beyond budgeting is based on 12 principles that form the basis of an adaptive performance management approach (Hope et al., 2011; Nguyen et al., 2018). It supports organizations to achieve alignment between the leadership principles and the management processes. The alignment provides the foundation of how organizations ensure that there is no disconnect between what is said and what is done (Bogsnes et al., 2016). Table 14.1 presents the 12 principles of beyond budgeting. These principles are divided into two groups. The first six principles are known as leadership principles and the second six are known as process principles. The leadership principles are concerned with creating a flexible organizational structure and the process principles deal with designing an adaptive management process that allows performance management to adapt quickly and effectively to the complex and competitive environments. It should be noted that one of the principles of the management processes is to make resources available as needed and not through annual budget allocations. It is the investigation of the implementation of this principle (or not) that triggered this research in a large financial organization.

202  Research handbook on project performance Table 14.1

Principles of beyond budgeting (Bogsnes et al., 2016)

Leadership principles

Management processes

 

DO

DO NOT

 

DO

Purpose

Engage and inspire

Not around

Rhythm

Organize

DO NOT Not around

people around bold and

short-term

management

calendar year only

noble causes

financial targets

processes dynamically around business rhythms and events

Values

Transparency

Govern through shared

Not through

values and sound

detailed rules and

judgment

regulations

Promote open

Do not restrict it

information for

Targets

Set directional,

Avoid fixed targets

ambitious relative goals Plans and

Make planning

Not a top-down

forecasts

a continuous and

annual event

inclusive process

self-management, innovation and learning Organization

Cultivate a strong

Not around

Resource

Make resources

Not through annual

sense of belonging

centralized

allocation

available as needed

budget allocations

and organize around

functions. Avoid

accountable teams

hierarchical

Give teams the freedom Do not

Performance

Evaluate

Not for rewards

and capability to act

evaluation

performance

only and not based

holistically and

on measurements

control and bureaucracy Autonomy

micromanage them

with peer feedback for learning and development Customers

Focus on connecting

Avoid conflicts of

everyone’s work with

interest

customers’ needs

Rewards

Reward shared

Not on meeting

success against

fixed performance

competition

targets

 

Advantages of Beyond Budgeting In the area of performance management, beyond budgeting provides many benefits (Nguyen et al., 2018). When adaptive performance management principles are applied – e.g., in the case of agile – it creates more ambitious strategies and fast response, less waste, improved customer service and a greater focus on learning and ethical behavior. Beyond budgeting ensures that managers create an open and challenging working environment to attract and keep employees (Nguyen et al., 2018). Employees will deliver continuous performance improvement using their knowledge and judgment to adapt to changing environments. Beyond budgeting enables an organization to manage its performance and to decentralize its decision-making process without the need for traditional budgeting (Hope & Fraser, 2003a). Decentralization involves converting centralized, hierarchical structures used in traditional budgeting into networks of small, self-managing teams, resulting in radical changes to organizational structures. The structural changes will reduce the complexity of environments and increase the adaptability of the organization overall (Hope & Fraser, 2003d). Valuckas (2019) found that due to globalization and technology advancements, organizations are forced to adapt, become more agile

Fixed capacity and beyond budgeting  203 and support employee-empowered initiatives. Beyond budgeting provides the organizational guidance needed to create an environment where organizations can thrive (Sahota et al., 2014). It has been implemented in a multitude of organizations and various industries (Matějka et al., 2021; Tian et al., 2015) including the agri-food industry (Sandalgaard & Nikolaj Bukh, 2014), oil and energy (Østergren & Stensaker, 2011) and financial institutions (Mitchell, 2005). Some researchers have also begun to research beyond budgeting in relation with agile implementation (Honkonen, 2020; Sirkiä & Laanti, 2015; Vierlboeck et al., 2019). Challenges of Beyond Budgeting Adopting beyond budgeting does not come without challenges. Valuckas (2019) found that the implementation of beyond budgeting has many pitfalls. Shifting from traditional budgeting to beyond budgeting requires a change in the whole culture of the organization (Nguyen et al., 2018). This is in line with the culture change associated with the adoption of agile and scaling agile (da Silva et al., 2015). The mindsets of the employees need to change completely. Achieving this is difficult because employees tend to fall back into old habits (Heupel & Schmitz, 2015). Matějka et al. (2021) compared 80 organizations that have implemented beyond budgeting to a group of 121 organizations that have not. They found evidence that two well-established management control practices seem difficult to abandon: reliance on the annual budget for decision-making and reliance on financial measures for performance evaluation. Extra time will be required so that employees familiarize themselves with the new implemented system and its tools used to manage the organization (Tian et al., 2015). According to Rickards (2006), organizations operating without budgets increase their liquidity risks because financial institutions are not able to evaluate the risk of beyond budgeting organizations. Summary and Research Question Summarizing some of the findings presented in this literature review, agile at scale introduces new forms of organization based on a continuous flow of product development. This can be supported by planning a fixed capacity and letting the exact development scope being planned on a continuous basis. This can be achieved by putting an organization in place with a fixed capacity. Although some argue that beyond budgeting models are conceptually similar and appear to align well with agile methods (Lohan et al., 2010), this approach appears to be somewhat contradictory to one of the principles of beyond budgeting suggesting more flexible resource allocation. Some organizations have been trying to implement both agile at scale and beyond budgeting. This has been the basis of some initial reflections and research by practitioners and academics (Honkonen, 2020). The research question was therefore as follows: How are the principles of fixed capacity and beyond budgeting used to manage performance in a scaled agile environment?

RESEARCH METHODOLOGY The research was done in two phases. The first phase was of a qualitative nature and focused on fixed capacity and beyond budgeting. The aim of this phase was to determine how fixed

204  Research handbook on project performance capacity and beyond budgeting influences the performance of the agile teams. The second phase was of a quantitative nature and was targeting the financial department of the case and their perceptions around beyond budgeting. A single case was investigated in detail and the rationale for a single case is that the institution under investigation implemented both fixed capacity and beyond budgeting in their deployment of a scaled agile framework. This approach seemed more appropriate as the research was exploratory (Yin, 2017). A semi-structured interview guide consisted of 11 questions focusing on portfolio management and on how initiatives are derived and linked back to the organizational strategies. Some questions focused on fixed capacity and the budgeting process. Cunningham (2008) and Kwok and Ku (2008) suggest semi-structured interviews as an excellent way to gather detailed information. Interviewees are then given the opportunity to elaborate in a way that is not possible with other methods, but they are able to share information in their own words and from their own perspectives. Case Description The implementation of SAFe was studied at the Bank,1 one of the largest African banking groups by assets with a long history in Africa. It is listed on the Johannesburg Stock Exchange (JSE). The financial institution is currently among the largest organizations in South Africa by market capitalization. It offers a wide range of banking and financial services in 20 countries in Africa. The company employs over 6,000 people in its IT department. It serves millions of personal customers with thousands of ATMs. The company embarked on the agile journey in 2015 to accomplish the following: (1)

Be closer to the business. This is achieved by shaping solutions with the business as well as co-creating software, and replacing business specifications and feasibility assessments with prototypes. (2) Deliver products in weeks rather than years. Software should be developed faster and deliver a minimum viable product. Teams should experiment and fail often. (3) Build more usable/simple software. This is achieved through obsessively focusing on customer experience and reducing hurdles. (4) Adopt new technologies faster. The company should take full advantage of new technologies, e.g. A/B testing to optimize designs, click-flow analyses to optimize the process and analytics to predict customer behavior. At the time of the research, the agile transition was 70% within the Bank’s Group IT division and the adoption of beyond budgeting was 100% across the entire company. Phase 1 – Interviews

Nineteen interviews were scheduled with various individuals within the Bank’s Group IT division. Saturation was reached well before the conclusion of the 19 interviews, but it was decided to conduct all the interviews because they had already been scheduled. The interviewees were selected based on their involvement with the Bank’s SAFe journey. The interviews were conducted by the researchers themselves. The 19 interviewees comprised four people from the business itself who were direct customers of IT and ultimately the agile process, two people from the agile portfolio office, four portfolio project managers, the CFO of Group IT,

Fixed capacity and beyond budgeting  205 Table 14.2

Summary of interviews

Role

Identifier

Division

Duration

Pages

Agile project officer

Apo-1

Group it

00:58:44

35

Agile project officer

Apo-2

Group it

00:58:38

32

Business manager

Bm-1

Pbb

00:45:51

21

Business manager

Bm-2

Pbb

00:51:06

29

Business manager

Bm-3

Cards, payments, gss, vaf

00:31:54

23

Business manager

Bm-4

Pbb

00:28:40

18

Chief information officer

Cio-1

Cards, payments, gss, vaf

00:59:58

31

Chief information officer

Cio-2

Pbb

00:52:31

16

Coach

Coach-1

Group it

00:36:02

24

Coach

Coach-2

Cib

00:46:59

33

Chief operating officer

Coo

Group it

00:40:46

16

Finance

Cfo

Group it

00:36:13

27

Project portfolio manager

Ppm-1

Cards, payments, gss, vaf

00:51:11

33

Project portfolio manager

Ppm-2

Pbb

00:48:38

30

Project portfolio manager

Ppm-3

Cib

00:55:26

32

Project portfolio manager

Ppm-4

African regions

00:51:58

39

Release train engineer

Rte-1

Cards, payments, gss, vaf

00:30:01

31

Release train engineer

Rte-2

Cards, payments, gss, vaf

00:36:37

28

Release train engineer

Rte-3

Pbb

00:34:52

14

14:16:05

512

Total

two CIOs within Group IT, three release train engineers, one COO and two agile coaches. Table 14.2 provides a summary of the 19 interviews.

RESULTS The transcriptions went through an iterative process of open coding that summarized the data into smaller meaningful units called codes and themes (Bryman & Bell, 2017; Saunders et al., 2016). The coding process was facilitated using ATLAS.ti. Codes were chosen as derived from the researchers or in vivo codes. A continual refinement process was used to merge similar codes as well as discard those deemed to lack sufficient data to support themselves. ATLAS.ti’s coding and co-occurrence matrices were used to identify relationships between codes and themes as well as possible new themes within the data (Bryman & Bell, 2017). A further refinement process was followed to remove codes that could not be accurately linked to existing themes. Fixed Capacity Three themes emerged from the interviews. The first theme is the benefits, although the Bank is still in the early stages of moving to a fixed capacity approach. The second theme is the challenges of moving from a project-driven approach to a fixed capacity approach. The third theme is the maturity path.

206  Research handbook on project performance Benefits of fixed capacity Respondent APO-1 clarified the reason why the Bank introduced fixed capacity: That is why we were very expensive as well because frankly in certain instances we were willing to throw money at a problem versus obviously moving to this new ways of working we actually fixed the money which then by default fixed the capacity and what then needed to give is the scope is variable because you prioritize things based on the capacity that you have … in the past we had an ethos that was certain things we were able and willing to throw money at problems as opposed to trade it off against other reporting things in order to fit into a fixed capacity.

One of the benefits was that the various team members can see how much an initiative will cost given the limited resources allocated to the initiative. So I have got a fixed capacity, effectively it will cost me X many millions for this team, they are there for the year. My job is therefore to help the guys optimize that capacity [BM-1]. So now what we are getting is better sizing of what can be done in 12 weeks and that is being improved upon. So, commitments are being realistic now and therefore delivery is actually getting improved and more flow [APO-2].

PPM-4 compared fixed capacity to a runway: where a lot of airplanes need to land. They have only got X amount of capacity to do business readiness, to do testing, etcetera so they need to make sure when they prioritize work some work will come here that we will deploy then during the PI there, but they are also busy with some of their own things. So there are a lot of trade-offs that needs to happen. How much can we actually do so things do not sit on the shelf?

The responsibility of fixed capacity lies with the product owners and ‘with the PI session they will then say okay we know this is your fixed capacity so let us look at what is the features that we can deliver in the next PI to talk to’ [PPM-1]. PPM-2 summarized it as ‘so what I have in terms of the resource construct would equate to their budget.’ Apart from the micro-level view of fixed capacity, there is also a macro view covering countries and divisions: So we know that fixed capacity is based, per country they have got a fixed headcount and staff as well as budgets [PPM-4]; whilst at a macro level this program is relatively flat from a fixed capacity point of view, you see individual portfolios with massive spikes and drops [CFO].

The benefits that the Bank reaped from the fixed capacity approach relate back to the benefits mentioned in the literature review section. The Bank achieved a more predictable rate of delivering features and this was achieved through the transparency and flexibility of the PI sessions. Challenges of fixed capacity The introduction of fixed capacity is not easy as people are ‘conditioned’ to operate in a project-driven environment. APO-1 stated the following: ‘So yes, the fixed capacity is a constant struggle and there are multiple dimensions to it, but you know, always also something that I guess we hope to try to get better at on a regular basis.’ Another challenge that the teams faced was that team members were still allocated to more than one feature team, which had a negative impact on the fixed capacity: ‘So we have got more than 80% of the people that book to more than one feature team code … we actually find that that person is splitting the time across multiple feature teams’ [CFO].

Fixed capacity and beyond budgeting  207 Maturity path The Bank realized that the introduction of fixed capacity was a long-term process and that there was no magic wand. The CFO summarized the journey as follows: ‘as an organization we are talking fixed capacity we still have a way to go to get to the point where we are fully mature to make sure that you have the philosophy of dedicated teams, dedicated capacity.’ This statement was echoed by one of the agile project officers [APO-1] from an operational perspective: ‘I need more capacity, I guess we are grappling with how do we maturely, semi-independently evaluate.’ The entire journey was summarized by APO-1, stating that: you are now funding fixed capacity and you must come and prioritize what that fixed capacity delivers and does not deliver. But we have not pushed in far enough yet to get to the point where the old way of thinking about how finances should be done, how budgeting should be done to answer your question versus how we think Group IT’s finance and the Group IT Organization thinks budgets should be done, there are still lots of friction and things there.

The next section provides insight into the impact of fixed capacity on the budgeting process. There was a move away in the organization from demand-driven budgeting to a budget based on fixed capacity. Beyond Budgeting No specific themes were identified from the coding exercise and the results are discussed in general. The challenge for the Bank was to move from a demand-based budget to a fixed capacity budget. The CFO summarized the journey as follows: In the old world, you had very demand-based project budgeting. So, your old project-based budgeting was very demand-based and you ended up with a number in the system with absolutely no regard to the capability to deliver. From a budget and a forecasting point of view is we have effectively taken out SAFe design and we cost based on the bodies involved. The challenging thing for us is shifting an organization where things were on demand versus managing resources. But it has made from an organization point of view our ability to cost fixed capacity, you often talk about feature teams and SAFe models being fixed capacity, so we cost fixed capacity.

The CFO confirmed the theory that demand-based budgeting no longer worked for them in this new environment and that they had to adjust their budgeting process. They introduced beyond budgeting as a new management style to align with the notion of fixed capacity. This shift introduced some benefits. The benefit of moving to fixed capacity and beyond budgeting was that ‘you are not fighting for money anymore. You are not fighting for prioritization’ [CFO]. The benefit was not perceived only by the finance department. The various departments within Group IT also realized the benefits of beyond budgeting. ‘It is a matter of showing so what if we say to business I am charging you R10 million, all they would want to know is what the hell did I get for that okay’ [PPM-1]. The allocation of resources and the subsequent budget were done during the quarterly PIs. ‘If there is a need for allocation then what we do is I facilitate a stand-up meeting where I have finance on their budget and their resource plan’ [APO-2]. An additional benefit was that everyone was involved in this process and supported the new way of budgeting and

208  Research handbook on project performance Table 14.3

Ranking of leadership principles and management processes

Leadership principles

Ranking

Process principles

Ranking

Transparency

1

Resource allocation

1

Value

2

Targets

2

Organization

3

Plans and forecasts

3

Customers

4

Rhythm

4

Purpose

5

Performance evaluation

5

Autonomy

6

Rewards

6

cost allocation. APO-2 continued and stated that ‘if there is any change, HR gets aligned, the budget gets aligned as well as the resource models, we are all in one.’ The billing or charge of resources was also easier as the charge-out model relied on the number of resources required to deliver a certain capability. PPM-1 reiterated that ‘we have actually now got your resource plan per resource to a feature team on your costs and that is what gets on charged to business, to those guys.’ The journey from traditional budgeting to beyond budgeting was not easy and challenges were part of the journey. The biggest challenge related to the culture of the bank. The CFO for Group IT mentioned that there are massive challenges round that for an organization that has not been strong at resource management as a capability, it has been quite a challenge. We cost at that level … What beyond budgeting talks about is a very different organizational thinking where you have got such a good understanding of the organization that traditional budget processes do not work the way it should be.

Phase 2 – Quantitative Analysis A quantitative follow-up was done focusing on the finance department of Group IT.2 This follow-up involved the people within the finance department that were directly affected by the introduction of beyond budgeting. The purpose was to understand how they perceived beyond budgeting in relation to the principles (leadership and processes) as well as the benefits and challenges. Table 14.3 provides insight into the perceived importance of the various leadership principles as well as the management processes. The ranking was determined using weighted average scores (Yang et al., 2017). The top-ranking principle was transparency, which entails the promotion of information for self-management. This is in line with the results of the interviews where Coach-1 described this ‘in terms of process and transparency and making the projects visible.’ This was echoed by PPM-1 who was responsible for the implementation of JIRA. She stated that ‘my focus, mine was also to get easy reporting out of things, that is visibility, transparency. So that was for me to get that into place.’ The lowest-ranking leadership principle was autonomy, which gave the team freedom and the capability to act. The top-ranking process principle was resource allocation where resources were made available as needed. The lowest-ranking process principle was rewards, which were shared based on success. The perception was that rewards were still based on fixed performance targets. Figure 14.3 provides insight into why the finance department opted for beyond budgeting. The top reason was flexibility, followed by value creation.

Fixed capacity and beyond budgeting  209 Table 14.4

Benefits of beyond budgeting

Benefits

Ranking

Faster response

1

Less manipulative behavior among managers

2

Open and challenging working environment

3

Optimize customer value

4

Innovative strategies

5

Lower costs

6

Figure 14.3

Reasons for beyond budgeting

Table 14.4 provides the ranking of the benefits as experienced by the finance department. It must be noted that the follow-up study was done in year two of implementing beyond budgeting. The top-ranking benefit was faster response. This can be attributed to the fact that budgets were created based on the fixed capacity and as the capacity changed, so did the budget. This happened almost in real time. The finance department had not yet seen a tremendous reduction in costs and overheads and that was the reason for ranking lower costs in the last position. When it comes to the challenges (Table 14.5) that the department faced in implementing beyond budgeting, the notion of falling back into old habits was ranked the highest. This is easy to understand as the team’s average experience in traditional budgeting was 13 years versus a one-year average experience in beyond budgeting. Table 14.5

Challenges of implementing beyond budgeting

Challenges

Ranking

Employees tend to fall back into old habits

1

Managers are not capable of making the transition successfully

2

Change within the whole culture of the organization

3

210  Research handbook on project performance

DISCUSSION The introduction of flow and fixed capacity is not an easy process, and this was acknowledged by the various interviewees. What is evident from the interviews is that this is a process and that the maturity around flow and fixed capacity needs to improve. Improved maturity will maximize the benefits already being felt. These benefits were the reduction in costs and a new way of prioritizing the delivery of products and services. The reduction of costs was attributed to the fact they did not throw more money at a problem, but that the team itself needed to resolve the issue within the constraints of their capacity. The prioritization was a direct influence of fixed capacity as fixed capacity focused on frequent releases of the product or service. In the more traditional way of prioritizing, projects were prioritized based on the allocated budget and who shouted the loudest. No emphasis was placed on the needs of the customer as a basis of prioritization. A challenge of introducing flow and fixed capacity was found to be the culture of the organization. In the case of the Bank’s Group IT, they realized that they had to move away from a culture of being project-driven to a culture of flow and fixed capacity. This was a challenge as team members were still allocated to more than one team, resulting in less flow and therefore less fixed capacity. The move to beyond budgeting also had its challenges. These challenges manifested in the move from a demand-based budget to a fixed capacity budget. The results in Table 14.3 highlight that although the agile teams experienced autonomy, the finance department still did not perceive the same level of autonomy. This is supported by the ranking of the challenges in Table 14.5. The results underline the notion of a change in culture. They further highlight that, although the Bank was only one year into the beyond budgeting adoption, they were already seeing flexibility and the creation of value. The top benefit was faster response in the allocation and alteration of the budgets. It is evident from the interviews as well as the follow-up questionnaire that there is a symbiotic relationship between fixed capacity and beyond budgeting. One concept cannot be optimally introduced and performed without the other being also optimally introduced and performing. Fixed capacity forces the introduction of beyond budgeting as the demand-based budgeting process is not conducive for allocating resources in a scaled agile environment. The opposite is also true. Beyond budgeting introduces a focus on capacity and moves away from demand. This almost forces the organization and teams to introduce fixed capacity if this has not already been done. It can be stated that the introduction and scaling of agile have resulted in new ways of working. These new ways of working include the introduction of flow and fixed capacity. This in turn has resulted in a different way of budgeting. Budgeting is based on fixed capacity and is no longer demand-based. This answers the research question that there is indeed a symbiotic relationship between fixed capacity and beyond budgeting. Which one comes first is still open to debate but once one of the concepts is introduced, the introduction of the other concept is a natural outcome. Performance can be managed using beyond budgeting and fixed capacity. The leadership principles of beyond budgeting create an environment where performance is encouraged. Employees are empowered by these principles to perform without supervision and create self-motivation and fulfillment. The process principles are very much focused on performance with resource allocation identified as the top principle. The optimal allocation of resources

Fixed capacity and beyond budgeting  211 links directly with fixed capacity where resources are optimally utilized. The guessing of estimates is to a certain extent eliminated providing the organization with a realistic measure of what can be delivered at what cost.

CONCLUSIONS The focus of this chapter is on the symbiotic relationship between fixed capacity and beyond budgeting. The introduction of scaled agile implies a different way of working and this new way of working has a ripple effect on the entire organization, including the finance department. The literature suggests that to improve customer satisfaction, organizations should focus on flow and fixed capacity. The introduction of fixed capacity implies that demand-driven planning can no longer take place. Demand-driven planning is the root of traditional budgeting and the demise of this type of planning manifests in the new phenomenon of beyond budgeting. The results indicate that in the instance of this case study, the organization is reaping the benefits of fixed capacity as well as of beyond budgeting. The organization is experiencing teething problems, but the hope is that these will minimize as the organization matures in this regard.

NOTES 1. 2.

Fictitious name to preserve anonymity. The authors would like to acknowledge the contribution of Nadia Jordaan to the data collection and analysis of the quantitative data of this research project.

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15. Cross-cultural integration in the next practices of project management: a qualitative study Dhruv Pratap Singh and Mahesh S. Raisinghani

INTRODUCTION Global projects and teams that cut across different cultures are being increasingly adopted by MNCs (multinational companies) to succeed in today’s competitive economy (Neeley, 2015). Concurrently, the component of culture for a global workforce has not been studied much in the management and project management literature (Connaughton & Shuffler, 2007; Cramton & Hinds, 2014; Gibson, Huang, Kirkman, & Shapiro, 2014; Hinds, Liu, & Lyon, 2011). This shortcoming is conspicuous given that “projects are entering an era of increased internationalization” (Konanahalli et al., 2014) in which one of the key challenges to the success of global projects and teams concerns the cultural differences that exist among members (Lee-Kelley & Sankey, 2008). Dinsmore argued in 1998 that to be triumphant, organizations will have to alter their industry methods from being hierarchical-operative groups to becoming agile, entrepreneurial-enterprises comprising multiple projects portfolios that are steady and resilient. This requires an agile, more economical, more reliable mode of performing business consolidated in a project management culture. Judgev (2010) asserted that there is a prominent link between the project management structure, the culture of the organization, and the success of the project. The main objective of our study is to identify how best practices and cultural variables moderate or directly relate to the project outcomes. These variables will be iterated and augmented throughout the research to finally propose a theory that will help answer the burning arguments related to culture’s importance, relevance, and impact on project success.

KEY TERMINOLOGIES The sixth edition of the PMBoK Guide explains the project as a temporary endeavor (that means it has a definite beginning and an end), to create a unique product, or unique service, or some unique results (PMBOK, 2017). The sixth edition of the PMBoK Guide further explains project management as follows: “Project management is the application of 5 project management process groups (initiation, planning, execution, monitoring and controlling, and closing), 10 areas of knowledge (integration, scope, schedule, cost, quality, resources, communications, risks, procurement, and stakeholder), 49 processes, and 1000+ITTOs (inputs, tools and techniques, outputs), plus the ability to tailor and implement these knowledge, skills, tools, and techniques to meet the requirements of the project.” (PMBOK, 2017).

214

Cross-cultural integration in the next practices of project management  215 A project is a complex, nonroutine, onetime effort limited by time, budget, resource, and specifications (Gray & Larson, 2008). The differentiating characteristics of projects from routine, repetitive daily work/operations are: ● ● ● ● ●

A defined life span A well-defined objective Typically involves people from several disciplines A project life cycle Specific time, costs, and performance requirements.

The field of project management is both an art and a science. One can teach anyone a lot of the science, but the art of project management takes interest, motivation, and experience to master. Another definition of project management comes from the Association for Project Management (APM), which is an equivalent organization to PMI based in the United Kingdom. According to APM, project management is the application of processes, methods, skills, knowledge, and experience to achieve specific project objectives according to the project acceptance criteria within agreed parameters. Project management has final deliverables that are constrained to a finite timescale and budget. (See https://​www​.apm​.org​.uk/​ resources/​what​-is​-project​-management.) Both PMI and APM describe project management as a field, with reference to a set of skills. Those skills often come from other fields, often referred to as reference disciplines. For example, strategic management is a field of knowledge that is a sub-domain of management in general (not necessarily limited to project management). Leadership is another discipline that is not uniquely used in project management. Project management methodology, as described by Ward (2000), is a highly detailed description of the procedures to be followed in a project life cycle. This methodology often includes forms, charts, checklists, and templates to ensure structure and consistency. However, in general, project managers use a set of tools and techniques that are commonly associated with project management such as WBS, Gantt charts, schedule network diagrams, earned value analysis, and so forth. Project management courses often focus on teaching project managers how to master creating and using these tools and techniques. In general, project management is not geared toward optimizing a single person’s goals ahead of the project’s goals. Instead, project management focuses on allies working together to complete a project. For this alliance to work there has to be a degree of trust, cooperation, and honesty. Project outcomes: In this study, by project outcomes we refer to project success or project failure. Project success: A project is considered to be a success if the project management ensures the completion of the project within agreed-upon time, within the provided resources and budget, and most importantly should meet the requirements of the customer (Bodicha, 2015). The sixth edition of PMBoK regularly mentions project success in its chapters. However, it doesn’t define project success; rather, it asserts that the project charter should outline the criteria of success and goals of the project. Setting up the criteria of success (critical success factors, CSFs) during the planning procedure, and accordingly, failure if not achieved, is extensively supported in the literature. In their research, Lim and Mohamed (1999) proposed that project success needs to be viewed from the prospects of different types of stakeholders (such as the manager of the project, members of the team, senior management, functional teams, CEO, directors, suppliers, vendors, customers, and other third parties). They identified two aspects:

216  Research handbook on project performance a macro aspect, which sums up all stakeholders and a micro aspect, which reflects only those stakeholders who have direct involvement with the completion of the project. Ramos and Mota (2015) also proposed that these different stakeholders have a different attitude and viewpoint on the success of the project. For better understanding, let us take the example from Thomsett’s findings (Thomsett, 2002). The Sydney Opera House costed 16 times more than its original planned cost and took four times more time than originally planned. The same opera house is now regarded as a success for the country, and concurrently a failure from the perspective of project management. Another example from a 2001 study by Cooke-Davies is the project of the Millennium Dome located in London, which was delivered within the planned time and budget. However, many people in Britain viewed it as a failure as it did not produce the wonder and allurement it was expected to (Cooke-Davies, 2002). Project failure: According to Pinto and Mantel’s study of 1990, the notion of failure in the project is vague. However, they also intimated there are a few shared perspectives that indicate some features are heavily linked to anticipated failure in the project (Pinto & Mantel, 1990). These shared perspectives were categorized as internal and external processes. The internal processes are composed of the completion of the project within agreed-upon scope, cost, and time; moreover, the external processes are effective measures of the project’s client and/or eclectic external pressures. Premature closure or termination of the project can also be regarded as a project that failed. Pinto and Kharbanda’s study in 1996 mentions common constituents that are linked with project failure such as the deficiency of studies to check the feasibility of the project, neglecting the environment of the project, higher supervision of project managers and project teams, the absence of post-project evaluations to document lessons learned, placing political desires over the goals of the project, and much more (Pinto & Kharbanda, 1996). As of 2010, Judgev also states one of the prime reasons for the failure of the project. It is that the culture of the organization may not support the project (Judgev, 2010). “Culture in information systems” has at least four meanings: national cultures, corporate and organizational culture, Internet culture, and cultural industries (Koster et al., 2022). National culture refers to the effect that national, regional, or ethnic cultures may have on the use of information systems, especially online behavior on social media or buying behavior on e-commerce sites. Information and communication technologies (ICTs) have provided the infrastructure for multinational businesses, created new cultural connections irrespective of geographic boundaries and distances, and allowed an increasingly mobile global population to be connected and interconnected. “Corporate or organizational culture” refers to the values and beliefs within organizations and how they impact adoption and use of information systems. Turning this around, studies in this area could explore how the adoption of new enterprise systems changes organizational culture. In a less normative meaning, it may also refer to the social capital or the symbolic human capital issues that impact use and investments on technology within companies. Organizational culture is described as the collection of morals, ethics, faiths, and behavioral patterns that supervise how the organization’s members complete the work. Several organizational determinants were associated with the effectiveness of the team. Previous research by Kotter and Heskett (1992) and Wagner and Spencer (1996) found that businesses that stress fundamental managerial segments, such as clients, stakeholders, workers, and leadership, exceed in performance compared with those that don’t consider cultural characteristics. As per the studies by Asbury (1989) and Schein (2004), any organization’s culture in its fundamental

Cross-cultural integration in the next practices of project management  217 state relates to an arrangement of shared morals, ethics, faiths, and behavioral patterns that unite everyone in the frame together. Internet culture is both represented and embodied by the millennial and digital native generations and how they leverage and interact with Internet and mobile resources differently from other generations, and what impacts this may bring to organizations that wish to attract the digital workforce. Finally, “cultural industries” refers to the study of new industries that are enabled by information systems and technology to promote the diffusion of cultural artifacts and digital products worldwide, pop culture musing being an example. In the context of this study that is in the domain of project management, we focus on national culture and organization culture.

LITERATURE REVIEW AND SYNTHESIS According to a study in 2005 by Willard, the determinants for the success of the project management are schedule compliance, budget compliance, the accuracy of the project (specifications and quality requirements are met), changing requests, and, if applicable, safety as well. Moreover, these determinants incorporate benefit realization to the organization and the client, satisfaction and engagement of stakeholders, fulfillment of the requirements for the user, answering the puzzles related to the project, improvement, methods, and systems (Willard, 2005). There is an indication through the literature of project management by Leintz and Rea and Cleland, which indicates that project culture is important to project success (Leintz & Rea, 1999; Cleland, 1999). In 1993, Hobbs and Ménard defined project management as a way of practicing beliefs and behavior patterns that can be related to as a project culture. A study conducted by Judgev (2010) explained the connection among organization’s culture and success of the project utilizing a metaphor of a riverboat in which culture is perceived as the river; the project is imagined as the boat. A conductive organizational culture to complete the project is considered as rowing downstream. These kinds of organization have an environment where collaboration and different functional expertise work together normally, there might be some conflicts but they are acknowledged and taken care of, and perfection is the operator. Meanwhile, the environment where project management is not effective is like rowing upstream. Almost all the things demand added labor, an extended time period, and extra vigilance. Within this kind of organization collaboration would be dissuaded, conflict would be prevailing or neglected, uncertainty is bypassed, and projects would encounter numerous obstructions. Rees-Caldwell and Pinnington (2013) surveyed the influence of the culture of a nation on project management among Arab and British cultures and discovered notable distinctions in scheduling, modification, assimilation, and interaction variables. They inferred that the culture of a nation shaped how a project manager performs the planning of the project (Wang, Jiang, & Pretorius, 2016). Research by Power et al. in 2010, between Asia and Western nations, illustrated the influence of the culture of the nation and recommended the consequence of the cultural component of individualism in ascertaining plant-level speculation and outcomes in Asian markets (Power, Schoenherr, & Samson, 2010). In 2014, Mueller reviewed the cultural precursors of sharing knowledge among several teams in projects and observed augmented

218  Research handbook on project performance effects of schedule, project structure, adjustment, and openness relating to the process concerning sharing of knowledge (Mueller, 2014). In 1993 Triandis and Hofstede presented the fundamental grounds of knowledge based on their research regarding usual cultural distinctions that concentrated on the values related to work (Triandis & Hofstede, 1993). Hofstede’s most popular model was in 2010, which is reaped from variations in cultures of different nations, incorporates dimensions of power-distance (PDI), individualism-collectivism (INV), masculinity-femininity (MAS), uncertainty-avoidance (UAI), short-long-term-orientation (LTO), and indulgence-restraint (IND) (Hofstede, Hofstede, & Minkov, 2010). In a thorough investigation of the literature by Henrie and Sousa-Poza in 2005 we can argue that culture does influence the project outcome. In their investigation, they proposed that culture might be a vital contributor to the failure of the project. Moreover, they argued that culture is significantly not broadly summarized in the literature; moreover, there were not many efforts to scale it (Henrie & Sousa-Poza, 2005). In 2008, Ajmal and Koskinen additionally reasoned that the culture of the organization can be associated with the failure of several projects and that a notable responsibility of the project manager is to consolidate the culture of the organization and cultures of the profession into one project culture (Ajmal & Koskinen, 2008). In spite of the fact that culture has been investigated at various levels concerning the culture of the nation, culture of the business, and culture of the organization, which is investigated extensively, there is nevertheless not any understanding of an authentic description of the term. Most of the descriptions of culture of the organization include components concerning fundamental opinions (Schein, 1992). In a study by Smircich (2017), the deviation of definitions was indicated. Smircich showed that the concept of the culture of the organization has certainly originated from anthropology. Consequently, there is no uniformity concerning the definition of culture in terms of anthropology; it is also expected that there may be numerous descriptions and purposes in the area of studies related to the organization. According to the findings of Hofstede et al. in 2010, values are described as the individual’s choices in issues related to their job and life (Hofstede et al., 2010). However, practices are described as detailed opinions by the representative of perspectives of the professional atmosphere or real work scenarios. This information makes culture more easily understandable. This is advantageous to progress culture from the aspect of practices of the organization because practices are easily noticeable and assessable and can thus be linked with organizations and related directly to the person and the performance of the organization (Christensen & Gordon, 1999). The 2005 study by Ives from a sequence of conversations attended with managers reasoned that sufficient sponsoring and governance, defined scope and CSFs, project structure and authorization, resource availability and availability of funding, and the context of the organization were significant constituents for the success of the project (Ives, 2005). In 2007, Suda recommended that leaders or managers of the project have numerous possibilities to build and develop a project culture in useful forms, barring that the designed culture needs to be in alliance with the principal culture that is the organization’s culture (Suda, 2007). This is an essential component of the development of the team for any projects and a wholesome environment for the team and setting the staging processes to assure the success of the project. The study explains that teams of the project and companies have unique characters, value regularities, and a particular way that they will work things up in order to

Cross-cultural integration in the next practices of project management  219 achieve success. The better a leader or manager of the project knows the notion of culture, the extra efficient she or he will become in winning support from the project team and other stakeholders and supervising the project through the countless puzzles of the organization. Leaders or managers of the project regularly deal with numerous distinct cultures concurrently. They usually operate inside the central culture of the company, including the subcultures of distinct divisions or operating with external clients who have their own kernel culture. Knowing and addressing the semantics of culture is important for the success of the project. Efficiently interacting with the enclosing culture can better evolve layouts, policies that are more suitable and acknowledged and noble, by neglecting practices that meddle with the beliefs and values of the client’s organization. Based on BMG Research’s (2014) findings, determinants concerning the success of the project incorporate communication, collaboration, coordination, coherence, conflicts, climate, abundancy, and performance of the team. These determinants influence the project’s successful completion in multiple areas. The skills and competence of the project team furthermore contribute to the success of the project. Fellows and Liu (2016) maintain that culture provides a context and set of cues within which project members make sense of one another and their mutual endeavors. From the perspective of global teams, Messner in 2015 developed a measure of intercultural communication effectiveness in which he explored how effective individuals are applying their intercultural competencies in actual intercultural interactions. The results showed promise for identifying shortcomings in relevant skills; e.g., the communication needed for international teamwork (Messner, 2015). In 1993, Hofstede asserted with his research that the culture of the nation can be described as the values and faith practices supported by a community of people, which are acquired at the very beginning of one’s life, and are very challenging to alter (Triandis & Hofstede, 1993). Shore asserted with his research in 2008 that the culture of the organization evolves inside the circumstances of the culture of the nation and executive leadership (Shore, 2008). In 1993, Hofstede mentioned that it can be described as the disseminated perspicacity of professional practices of the organization inside units of the organization (Triandis & Hofstede, 1993). The 2006 study by Turner proposed that as the executive leadership molds the organization’s culture, leadership in the project molds the culture of the project (Turner, 2006). Finally, in the 2008 study, Shore added that the culture of the project is the disseminated perspicacity of the work practices of the project, guided by both the project leader/manager and the culture of the organization (Shore, 2008). It is described as how project planning, execution, and control are applied.

RESEARCH METHODOLOGY This research project adopted a qualitative approach to answer the research question: Should we include culture integration in the best practices of project management? For this purpose, a protocol for semi-structured interviews was drafted (see Appendix 15A.1). Cooper and Schindler (2011) asserted that the interviews render invaluable data gathering, conceding for explanation and extension of follow-ups, inquests, and responses throughout the interview, consequently enhancing the intrinsic quality of the data/information collected.

220  Research handbook on project performance In the initial phase of the project, LinkedIn messages, phone calls, WhatsApp messages, e-meets at virtual career fairs, virtual parks, and email contact with potential interviewees validated their interest to participate in the research. The interview protocol was framed and termed as a “virtual coffee chat session” to enable more interactive participation. Calendly was used as an automated meeting scheduling tool and for collecting demographic information. Calendly eased the meeting scheduling process, and this way the participants could focus more on the rich conversations and discussions. Appendix 15A.2 explains the step-by-step guide to scheduling a virtual coffee chat. As per the interview protocol annexed in Appendix 15A.1, the participants were asked for their consent to record the conversation and use it for research purposes. After seeking their consent, the semi-structured questionnaire was discussed. Around 30 potential participants were contacted, out of which 18 were able to schedule a meeting, and two participants responded in .docx format due to their busy schedule and time restraints. So, in total, the sample size is 20. While 20 may seem like a diminutive sample, according to Mason (2010), in qualitative research, the size of the sample is irrelevant because the interpretation of the research is based on the quality of data (Mason, 2010). The interview lasted from around 20 minutes to 155 minutes, making an average of one hour. Participant demographics are displayed in Tables 15.1 and 15.2. Table 15.1

Summary of participant demographics

Count of subject

 

 

Age, work location, origin, education level

Female

Male

  Grand Total

18–24 years old

3

3

6

Colombia

1

 

1

 Colombia

1

 

1

  Bachelor’s degree (BA, BS, BEng, etc.) Italy

1

 

1

1

 

1

 Romania

1

 

1

  High school Mexico

1

 

1

1

 

1

 Mexico

1

 

1

  High school UK

1

 

1

 

1

1

 United Kingdom

 

1

1

  A level (college/6th form) USA

 

1

1

 

1

1

 United States

 

1

1

  Bachelor’s degree (BA, BS, BEng, etc.) Virtual offices

 

1

1

 

1

1

 United States

 

1

1

  Bachelor’s degree (BA, BS, BEng, etc.) 25–34 years old

 

1

1

4

2

6

Belgium

 

1

1

 France

 

1

1

  Master’s degree (MA, MS, MEng, etc.) Germany

 

1

1

1

 

1

 India

1

 

1

Cross-cultural integration in the next practices of project management  221 Count of subject

 

 

 

  Bachelor’s degree (BA, BS, BEng, etc.) Portugal

1

 

1

1

 

1

 Brazil

1

 

1

  Master’s degree (MA, MS, MEng, etc.) UK

1

 

1

1

 

1

 United Kingdom

1

 

1

  Bachelor’s degree (BA, BS, BEng, etc.) Virtual offices

1

 

1

1

1

2

 Botswana

1

 

1

  Bachelor’s degree (BA, BS, BEng, etc.)

1

 

1

 Ghana

 

1

1

  Bachelor’s degree (BA, BS, BEng, etc.) 35–44 years old

 

1

1

1

2

3

France

 

1

1

 Italy

 

1

1

  Master’s degree (MA, MS, MEng, etc.) India

 

1

1

 

1

1

 India

 

1

1

  Bachelor’s degree (BA, BS, BEng, etc.) Latvia

 

1

1

1

 

1

 Latvia

1

 

1

  Master’s degree (MA, MS, MEng, etc.) 45–54 years old

1

 

1

1

2

3

Canada

1

 

1

 Canada

1

 

1

  High school UK

1

 

1

 

1

1

 South Africa

 

1

1

  Master’s degree (MA, MS, MEng, etc.) USA

 

1

1

 

1

1

 United Kingdom

 

1

1

  Master’s degree (MA, MS, MEng, etc.) Over 55

 

1

1

1

1

2

France

1

 

1

 France

1

 

1

  Master’s degree (MA, MS, MEng, etc.) India

1

 

1

 

1

1

 India

 

1

1

  PhD Grand total

 

1

1

10

10

20

Table 15.2

Details of participant demographics

Count of subject

Company size

 

 

 

 

Work experience 0–2 yrs

0–500

500–5k

5k–10k

Over 10k

Grand total

5

1

1

1

8

 Capital markets

 

1

 

 

1

 Coaching

5

 

 

 

5

 Management consulting

 

 

 

1

1

 Marketing

 

 

1

 

1

222  Research handbook on project performance Count of subject

Company size

 

 

 

 

3–5 yrs

 

 

 

1

1

 Fintech 6–10 yrs

 

 

 

1

1

2

 

 

 

2

 Engineering and research

1

 

 

 

1

 Talent acquisition officer 11–15 yrs

1

 

 

 

1

1

2

 

1

4

 Aerospace industry

 

1

 

 

1

 Agile coach

1

 

 

 

1

 Project management 26–30 yrs

 

1

 

1

2

 

 

 

2

2

 Capital markets

 

 

 

1

1

 Financial services 31–40 yrs

 

 

 

1

1

 

 

 

1

1

 Capital markets 41–50 yrs

 

 

 

1

1

 

1

 

1

2

 Academician

 

1

 

 

1

 Program management Grand total

 

 

 

1

1

8

4

1

7

20

Data Analysis and Visualization After collecting the data, computer-assisted qualitative data analysis software called ATLAS. ti 9 was used to analyze the data. The recorded videos were directly coded using the software. However, in 4 out of 18 recordings, the transcribed document was used to generate codes. A total of 383 quotations and 93 codes were recorded. These codes and quotations were then visualized using linkage-network diagrams. Multicultural delights See Figure 15.1 on the companion website. See Figure 15.2 on the companion website. Multicultural challenges In order to understand the pain points of the participants, things they are struggling with, or what they like the least about working in projects involving multicultural environment, linkages were established among the following codes: ● ● ● ● ● ● ● ●

Cultural influence on level of informality Cultural influence on perceived deadlines Cultural influence on perceived productivity Cultural influence on perceived work ethics Cultural prejudice Don’t fit in any culture Language and accent barriers Communication challenges

Cross-cultural integration in the next practices of project management  223 See Figure 15.3 on the companion website. See Figure 15.4 on the companion website. Influence of project culture See Figure 15.5 on the companion website. See Figure 15.6 on the companion website. Influence of leadership See Figure 15.7 on the companion website. Influence of project management best practices See Figure 15.8 on the companion website. Proven and recommended practices of participants See Figure 15.9 on the companion website. See Figure 15.10 on the companion website. Notable Anecdotes There were a dozen notable anecdotes. One example may help the reader ascertain the gravity of the issue. It pertained to a company culture where the person conveying the bad news is the one perceived as the antagonist. This could lead to a corporate culture where nobody wants to be the harbinger of bad news.

IMPLICATIONS FOR THEORY AND PRACTICE This chapter stands at the intersection of research and practice, and presents a structured, logical, and systematic organization of ideas on the various facets of national and organization culture in project management, and their impact on project performance. Project performance aims to improve project management success (faster, better, cheaper), which consequently results in project success (deliverables meeting client goals such as cost, time, quality, and value). Two main PM standards (PMI and IPMA) assign importance to processes and procedures to manage and improve project performance. For our chapter, we have considered the impact of cultural integration in the project management knowledge areas, project phases and processes, project teams, resources, scope, cost, time, quality assurance, conflicts, changes, and risk, as they all impact project performance.

FUTURE RESEARCH DIRECTIONS As we adjust to the new normal and make a business model shift during the Covid-19 pandemic, it is important to reflect on where is value now and next for creating the right ecosystem. In learning from the past and charting the future of project management from a cross-cultural context, the key question is: What are the best and/or next practices in building a collaborative

224  Research handbook on project performance enterprise using the project management principles, technologies, tools, and techniques in the age of digital convergence? Cultural aspects have been identified as a key determinant for project success, yet more research is needed to understand the complexities underlying cultural and value-related aspects. The Covid-19 pandemic has furthermore pushed this topic to the forefront of scholarly interest, showcasing how culture may impede or support rapid digital innovation efforts (e.g., remote work, digital business models, etc.). For example, organizations with different cultural bases have shown markedly different implementations of remote work, from extending a culture of trust and self-governance to using remote-work equipment in order to oversee their employees in their home-office environment (Limaj & Obwegeser, 2022). Digital technologies are changing the scale, scope, and speed at which changes occur in the workplace. These technologies enable new opportunities for connectivity and collaboration, but also alter value creation paths and pose project management challenges such as how to implement new technologies to change or extend traditional business practices, logics, and models. Emerging technologies such as the Internet of Things (IoT) and artificial intelligence/ machine learning yield a wide range of new applications and project management research issues from a cross-cultural perspective. Some of these challenges pertaining to organization and/or project culture can severely undermine the various resources of organizations. Understanding the full potential of these technological innovations and trends requires that we produce technical solutions and address corresponding changes in how we manage them. The rapid normalization of digital technologies in some industries has even threatened the survival of long-standing organizations that were unable to manage the changes required to compete. Thus, cross-cultural project management from various theoretical perspectives and methodological approaches becomes more crucial for organizational success in this new hyper-competitive marketplace than ever. Figure 15.11 illustrates some future research directions. In addition, the impact of culture in project management within online communities can be explored. Online communities group people who are distributed across the globe but share interests, professional or personal goals, rituals, and tacit or explicit policies, and interact primarily through computer-mediated communication tools. While cross-cultural studies may shed some light on the behavior of these distributed communities, geographical boundaries tend to fade in online communities, even when the communities start within a specific location. While studying behaviors across national boundaries or groupings is a good starting point, more in-depth analyses of self, groups, social, and professional identity can supplement the development of a unique “culture” of an online community. Regardless of the unit of analysis, researchers are increasingly aware that users’ identities – and their internalization of cultural meaning – affect both their adoption and use of technology (Osatuyi & Passerini, 2022). See Figure 15.11 on the companion website.

CONCLUSION A thorough analysis of all the 93 codes and 383 quotations answers the research question. The straightforward answer is yes, culture management should be included in the best practices

Cross-cultural integration in the next practices of project management  225 of project management (according to 90% of participants). However, while extinguishing the burning question, this research has also ignited some more research questions, for instance: ● Should cultural management be integrated as a separate knowledge area in the PMBoK? Or as an add-on topic under the qualities of a project manager? ● Is cultural integration hitting the root cause? Or is there more to it? Like diversity and inclusion? As far as the research objectives are concerned, they have been met, but thanks to the exploratory nature of this research, there is scope for more exploration. The study identified and confirmed the gap in the best practices project management and ignited a basis to introduce either a new chapter or topic in the PMBoK Guide next edition as Project Culture Management. It has always been debatable whether cultural integration is a necessity to project management or just another nuisance. This research answers such questions. This will help: ● Practitioners augment the project performance and decrease the risk of project failure due to negligence of cultural intelligence, management, and integration. ● Academicians see a new dimension and work on solutions to better integrate cultural management. ● Organizations achieve better project performance through effective cultural integration.

NOTE Companion website material is available at https://www.e-elgar.com/resourcefiles/anantatmula

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226  Research handbook on project performance Fellows, R., & Liu, A. M. M. (2002). Impact of behavioural compatibility on project procurement. In Perspectives on culture in construction, CIB Report No., 275. CIB Publications. Fellows, R., & Liu, A. M. M. (2016). Sensemaking in the cross-cultural contexts of projects. International Journal of Project Management, 34(2), 246–257. Gibson, C. B., Huang, L., Kirkman, B. L., & Shapiro, D. L. (2014). Where global and virtual meet: The value of examining the intersection of these elements in twenty-first-century teams. Annual Review of Organizational Psychology and Organizational Behavior. https://​doi​.org/​10​.1146/​annurev​-orgpsych​ -031413–091240 Gray, C. F., & Larson, E. W. (2008). Project management: The managerial process, 4th edition. McGraw-Hill/Irwin. Henrie, M., & Sousa-Poza, A. (2005). Project management: A cultural literary review. Project Management Journal. https://​doi​.org/​10​.1177/​875697280503600202 Hinds, P. J., Liu, L., & Lyon, J. (2011). Putting the global in global work: An intercultural lens on the practice of cross-national collaboration. Academy of Management Annals. https://​doi​.org/​10​.1080/​ 19416520​.2011​.586108 Hobbs, B., & Ménard, P. M. (1993). Organizational choices for project management: The AMA handbook of project management. The AMA Handbook of Project Management. AMACOM Division of American Management Association International. Hofstede, G., Hofstede, G. J., & Minkov, M. (2010). Cultures and organizations: Software of the mind. In Cultures and Organizations. McGraw Hill. Ives, M. (2005). Identifying the contextual elements of project management within organizations and their impact on project success. Project Management Journal. https://​doi​.org/​10​.1177/​ 875697280503600105 Judgev, K. (2010). Project management: The managerial process. International Journal of Managing Projects in Business. https://​doi​.org/​10​.1108/​17538371011076145 Konanahalli, A., O. Oyedele, L., Spillane, J., Coates, R., von Meding, J., & Ebohon, J. (2014). Crosscultural intelligence (CQ): Its impact on British expatriate adjustment on international construction projects. International Journal of Managing Projects in Business. https://​doi​.org/​10​.1108/​IJMPB​ -10–2012–0062 Koster, A., Monod, E., & Passerini, K. (2022). Culture in information systems. Track Description for SIG Culture, AMCIS. Kotter, J. P., & Heskett, J. L. (1992). Corporate culture and performance. Free Press. Lee-Kelley, L., & Sankey, T. (2008). Global virtual teams for value creation and project success: A case study. International Journal of Project Management. https://​doi​.org/​10​.1016/​j​.ijproman​.2007​.08​.010 Leintz, B. P., & Rea K. P. (1999). Breakthrough technology management. Academic Press. Lim, C. S., & Mohamed, M. Z. (1999). Criteria of project success: An exploratory re-examination. International Journal of Project Management. https://​doi​.org/​10​.1016/​S​0263–7863(​98)00040–4 Limaj, E., & Obwegeser, N. (2022). Cultural and value related aspects in information systems. Mini-track description for SIG CCRIS-Global, International, and Cross-Cultural Research in Information Systems, AMCIS. Mason, M. (2010). Sample size and saturation in PhD studies using qualitative interviews. Forum Qualitative Sozialforschung. https://​doi​.org/​10​.17169/​fqs​-11​.3​.1428 Messner, W. (2015). Measuring existent intercultural effectiveness in global teams. International Journal of Managing Projects in Business. https://​doi​.org/​10​.1108/​IJMPB​-05–2014–0044 Mueller, J. (2014). A specific knowledge culture: Cultural antecedents for knowledge sharing between project teams. European Management Journal. https://​doi​.org/​10​.1016/​j​.emj​.2013​.05​.006 Neeley, T. (2015). Global teams that work. Harvard Business Review (October). Osatuyi, B., & Passerini, K. (2022). Culture in online communities. Mini-track description for SIG Culture, AMCIS. Pinto, J. K., & Kharbanda, O. P. (1996). How to fail in project management (without really trying). Business Horizons. https://​doi​.org/​10​.1016/​S​0007–6813(​96)90051–8 Pinto, J. K., & Mantel, S. J. (1990). The causes of project failure. IEEE Transactions on Engineering Management. https://​doi​.org/​10​.1109/​17​.62322 PMBOK. (2017). PMBOK guide, 6th edition. Project Management Institute.

Cross-cultural integration in the next practices of project management  227 Power, D., Schoenherr, T., & Samson, D. (2010). The cultural characteristic of individualism/collectivism: A comparative study of implications for investment in operations between emerging Asian and industrialized Western countries. Journal of Operations Management. https://​doi​.org/​10​.1016/​j​.jom​ .2009​.11​.002 Ramos, P. A., & de Miranda Mota, C. M. (2015). Exploratory study regarding how cultural perspectives can influence the perceptions of project success in Brazilian companies. Producao. https://​doi​.org/​10​ .1590/​0103–6513​.173114 Rees-Caldwell, K., & Pinnington, A. H. (2013). National culture differences in project management: Comparing British and Arab project managers’ perceptions of different planning areas. International Journal of Project Management. https://​doi​.org/​10​.1016/​j​.ijproman​.2012​.04​.003 Schein, E. H. (1992). Organizational culture and leadership. Jossey-Bass. Schein, E. H. (2004). Organizational culture and leadership. Jossey-Bass. 18th BledCom International Public Relations Research Symposium. Shore, B. (2008). Systematic biases and culture in project failures. Project Management Journal. https://​ doi​.org/​10​.1002/​pmj​.20082 Smircich, L. (2017). Concepts of culture and organizational analysis. In The Anthropology of Organisations. https://​doi​.org/​10​.4324/​9781315241371–20 Suda, L. (2007). Linking strategy, leadership and organization culture for project success. PM World Today, IX(ix), 1–11. Thomsett, R. (2002). Radical project management. Prentice Hall Professional. Triandis, H. C., & Hofstede, G. (1993). Cultures and organizations: Software of the mind. Administrative Science Quarterly. https://​doi​.org/​10​.2307/​2393257 Turner, J. R. (2006). Choosing appropriate project managers: Matching their leadership style to the type of project. Project Management Journal. https://​www​.pmi​.org/​learning/​academic​-research/​choosing​ -appropriate​-project​-managers​-matching​-their​-leadership​-style​-to​-the​-type​-of​-project Wagner, D. B., & Spencer, J. (1996). The role of surveys in transforming culture: Data, knowledge, and action. In Organizational Surveys: Tools for Assessment and Change. Wiley. Wang, N., Jiang, D., & Pretorius, L. (2016). Conflict-resolving behavior of project managers in international projects: A culture-based comparative study. Technology in Society. https://​doi​.org/​10​.1016/​j​ .techsoc​.2016​.07​.004 Ward, L. R. (2000). Project management terms: A working glossary (PMBOK Guide), 2nd edition. Project Management Institute. Willard, B. K. (2005). Project success: Looking outside traditional project metrics. Project Management Wisdom. Retrieved from http://​www​.pmforum​.org/​library/​papers/​2006/​Proj​_Mgmt​_Metrics​.pdf

228  Research handbook on project performance

APPENDIX 15A.1 CODES Table 15A.1

Codes

Code

Grounded

Density

Code groups

Acquiring vs. applying knowledge

10

0

Contradictory

Adaptable to change

21

1

Proven and recommended practices

Advanced planning

2

0

 

Age diversity

4

1

Diversity

Agile mindset builds culture

1

0

Add-on exploration

Agile mindset builds people skills

1

0

Add-on exploration

Agile vs. classical project management

1

0

Contradictory

Agreed-upon communication channel

9

0

Communication

Bias for same culture teams

2

0

Team building

Build trust by giving autonomy

13

0

Team building

Contradictory Build trust by giving credit

3

0

Team building

Build trust to get the job done

27

0

Team building

Building personal connection

38

0

Team building

Charismatic leadership

7

0

Leadership

Clarifying and confirming

11

1

Proven and recommended practices

Collaborating with different cultures

26

1

Cultural delights

Communication challenge

17

1

Communication

Confronting failures/issues

29

1

Proven and recommended practices

Counseling and helping colleagues

8

1

Proven and recommended practices

Cultural diversity

12

2

Diversity

Cultural influence on level of

11

1

Multicultural challenges

8

1

Multicultural challenges

1

1

Multicultural challenges

Cultural delights informality Cultural influence on perceived deadlines Cultural influence on perceived productivity Cultural influence on perceived work ethics

13

1

Multicultural challenges

Cultural integration in best practices

1

0

Contradictory

Cultural intelligence

28

1

Cultural delights

Cultural prejudice

5

1

Multicultural challenges

Culture vs. people skills

21

0

Contradictory

Culture-based preference

1

1

Cultural delights

Defining national culture

6

0

National culture

Developing consensus

36

1

Proven and recommended practices

Different perspectives

18

1

Cultural delights

Diversity and inclusion

16

3

Diversity

Don’t fit in any culture

4

1

Contradictory

Don’t micromanage the team

4

0

Team building

Multicultural challenges Don’t want to rock the apple cart

1

0

Add-on exploration

Education and training

21

1

Proven and recommended practices

Establishing common language

4

0

Communication

Extrinsic organizational culture

11

0

Organizational culture

Cross-cultural integration in the next practices of project management  229 Code

Grounded

Density

Code groups

Facilitating and moderating the

11

1

Proven and recommended practices

discussions Further research possibilities

9

0

 

Gender discrimination

3

0

Multicultural challenges

Gender diversity

4

1

Diversity

Discrimination Hofstede’s dimensions criticized

1

0

Add-on exploration

Hofstede’s dimensions recommended

1

0

Add-on exploration

Insignificance of project culture

3

0

Project culture

Insignificant influence of national culture

4

0

National culture

Interesting stories

11

0

 

Intrinsic organizational culture

13

0

Organizational culture

Language and accent barrier

10

2

Multicultural challenges

Leadership role

21

0

Leadership

Leading by example

6

0

Leadership

Learning from different cultures

25

1

Cultural delights

Linguistic discrimination

3

0

Multicultural challenges

Making tough decisions

6

1

Proven and recommended practices

Discrimination Micromanage the team

2

0

Team building

Multicultural experience

4

1

Cultural delights

Multicultural challenges

27

7

Multicultural challenges

Multicultural delights

22

7

Cultural delights

National culture influence on

6

0

National culture

12

0

National culture

organizational culture National labor regulations

Organizational culture

Nation’s influence on best practices

1

0

National culture

Organizational hierarchy

9

0

Organizational culture

Organization’s influence on best

6

0

Organizational culture

practices Overcoming storming stage

6

0

Add-on exploration

Pay or compensation discrimination

3

0

Multicultural challenges

Perceived impact by each individual

5

0

 

Personality influence on level of

1

0

Contradictory

Discrimination

informality Personality-based preference

2

0

Contradictory

Project culture dependence on

4

0

Project culture

8

0

Project culture

Project culture dependence on project duration 4

0

Project culture

national culture Project culture dependence on

National culture

organizational culture

Organizational culture

Project culture dependence on project manager 5

0

Project culture

Project management best practices

26

0

 

Proven and recommended practices of

19

12

Proven and recommended practices

Racial discrimination

5

0

Multicultural challenges

Recognition by leaders

4

0

Leadership

participants Discrimination

230  Research handbook on project performance Code

Grounded

Density

Code groups

Recommendation for working against time

5

0

Add-on exploration

zone Respecting everyone and every culture

33

1

Proven and recommended practices

Retrospection and lessons learned

18

1

Proven and recommended practices

Self-organized teams

4

0

Organizational culture

Senior leadership influence on

20

0

Organizational culture

3

0

Leadership

Team building organizational culture Shared leadership

Leadership

Sharing commonalities

10

1

Proven and recommended practices

Sharing the vision

9

1

Proven and recommended practices

Significance of culture

27

0

 

Significance of organizational culture

22

0

Organizational culture

Significance of project culture

22

0

Project culture

Significant influence of national

18

0

National culture

culture Similar cultures influencing common language 2

0

 

Strong communication plan

0

Communication

15

Time zone difference

5

0

Add-on exploration

Tuckman’s stages of group

3

0

Add-on exploration

development

APPENDIX 15A.2 QUOTATIONS An additional 383 quotations from the subjects of this study are available at: https://​drive​ .google​.com/​file/​d/​1vrT​l12cEtLsFK​TrSsd7hLdK​8mTEALlzL/​view​?usp​=​sharing

16. Project management lessons learned: essential safety features Kam Jugdev

Based on personal experiences and candid conversations with practitioners, the conundrums of why we fail to learn from our mistakes are both frustrating and intriguing. There are differences between what is formally conveyed in a lessons-learned report versus what can be shared in small group and one-to-one conversations. In this chapter, I am interested in examining how lessons learned are addressed in the Project Management Institute’s (PMI’s) 2021 standard – the Project Management Body of Knowledge Guide (PMBOK® Guide) – compared to the more recent literature on lessons learned. To begin, a road trip analogy is used in this introduction to frame the topic of project management lessons learned. The section that follows outlines the research question and explains the first methodology used to conduct a content analysis of lessons-learned terms used in the PMBOK® Guide. Thereafter, the second methodology is presented. This methodology was based on Google Scholar searches using a set of key terms to assess how journal abstracts addressed project management lessons learned. Then, the chapter presents a discussion leveraging the data-information-knowledge-wisdom pyramid (Rowley, 2007), and is followed by a conclusion. Do you recall your last road trip? Picture the passengers in the backseat as project team members, clients, and other stakeholders. As the project manager, picture yourself driving with the project sponsor directing/navigating the trip from the front passenger seat. Notice how your perspective from the driver’s seat allowed you to use the rearview mirror and dashboard features to safely see the road behind you. Recall that your passengers were able to look out the windows and helped with directions. Remember that you had one windshield and multiple rearview mirrors. Convex rearview mirrors are affixed with the warning that “objects in (the) mirror are closer than they appear”. This safety feature is a good warning about how close potential dangers may be. Given the price of gas, some of you may have wanted to get from point A to point B inexpensively (cost). Or maybe you wanted to get somewhere faster (time). Perhaps you went on this trip for a better experience (scope/quality) in terms of enjoying the excursion and roadside stops you made in contrast to the last road trip which was the road trip from hell because… [insert an explanation here]. Regardless of which criterion was most important to each passenger (stakeholder), individuals will describe the success of the road trip project in various subjective and objective ways. Now think about what you would learn about the project by reading individual reports or a group report on the trip. Compare this with what you would learn about the experience by having a candid and objective discussion with everyone involved as they discuss what went well, what did not go well, and what could be improved. In doing so, you will be able to appreciate how reading a document (explicit knowledge, also known as know-what) conveys one type of knowledge whereas the discussed learnings are more nuanced and insightful (involving 231

232  Research handbook on project performance tacit knowledge, also known as know-how). When discussions involve experiential learnings with probes and with everyone contributing to a topic, this is knowledge building. The criteria of time, cost, and scope pertain to project performance success; project performance relates to improving project management success. Success extends beyond the project life cycle criteria of time, cost, and scope. Success depends on stakeholder perspectives and efficiency and effectiveness metrics. Success has also been studied in the context of strategic levels of the firm; i.e., program, portfolio, and firm levels. Success, then, is multidimensional and contingency driven. Project management academics, practitioners, and professional associations have underscored the importance of project and project management success for decades. The safety reminder on rearview mirrors is a good warning about how important it is to learn from prior project experiences to avoid dangers on subsequent projects. These types of look-backs are typically called lessons learned. Lessons learned are a process and not an activity. Lessons learned involve sharing knowledge about “the good, the bad, and the ugly” at regular project intervals. Preferably, the intent is to share experiential learnings to avoid repeating costly mistakes. In practice, lessons learned tend to be rushed onetime activities, completed as a requirement, and conducted superficially. The term “lessons learned” may involve negative connotations due to prior experiences involving emotionally charged meetings, raised voices, blame games, and shouting matches. The next section examines how lessons learned are addressed in the PMBOK® Guide.

RESEARCH METHODOLOGY PART 1: A CONTENT ANALYSIS OF LESSONS-LEARNED TERMS IN THE GUIDE TO THE PROJECT MANAGEMENT BODY OF KNOWLEDGE As this research handbook is on project performance, the question explored is as follows: Using content analysis (words and phrases), how does the 2021 PMBOK® Guide’s approach to project lessons learned compare with a Google Scholar assessment of journal abstracts from 2000 to 2021? Since PMI is the premier global professional association offering standards and other publications, I began by reviewing the definitions in the 2021 PMBOK® Guide. Then, using the term “lessons learned” and related synonyms along with words and phrases identified from the definitions in the guide, I did a content analysis of the PMBOK® Guide. Unlike a systematic content analysis methodology (either theoretically based, used to build a model, or describe the phenomenon) (Hsieh & Shannon, 2005), the intent was to look for initial patterns and relate them to the abstracts on lessons learned. As such, abridged integrated reviews are presented (Snyder, 2019). Within the literature and in practice, other terms for lessons learned include after action reports, audits, debriefings, postmortems, project reviews, and post-implementation evaluations (Disterer, 2002). Often, the terms used in the lessons-learned context are industry specific. The section within the PMBOK® Guide (2021) that is most relevant to lessons learned is on Models, Methods, and Artifacts. Frequently used terms relevant to lessons learned are presented in Table 16.1.

Project management lessons learned  233 Table 16.1

Terms related to lessons learned as defined in the PMBOK® Guide

Key term

Definition

Artifact

A template, document, output, or project deliverable (p. 235)

Benefits management plan

The documented explanation defining the processes for creating, maximizing, and sustaining the benefits provided by a project or program (p. 236)

Business value

The next quantifiable benefits derived from a business endeavor that may be tangible, intangible, or both (p. 236)

Explicit knowledge

Knowledge that can be codified using symbols such as words, numbers, and pictures (p. 240)

Knowledge

A mixture of experience, values and beliefs, contextual information, intuition, and insight that people use to make sense of new experiences and information (p. 242)

Lessons learned

The knowledge gained during a project, which shows how project events were addressed or should be addressed in the future, for the purpose of improving future performance (p. 242)

Lessons learned register

A project document used to record knowledge gained during a project, phase, or iteration so that it can be used to improve future performance for the team and the organization (p. 242)

Log

A document used to record and describe or denote selected items identified during execution of a process or activity. Usually used for the modifier, such as issue, change, or assumption (p. 242)

Register

A written record of regular entries for evolving aspects of a project, such as risks, stakeholders, or defects (p. 246)

Report

A formal record or summary of information (p. 247)

Retrospective

A regular occurring workshop in which participants explore their work and results in order to improve both the process and product (p. 247)

Tacit knowledge

Personal knowledge that can be difficult to articulate and share such as beliefs, experiences, and insights (p. 251)

Phrases from the literature such as after action reports, debriefs, post-implementation evaluations, and postmortem were not used in the guide. Throughout, the PMBOK® Guide used the term “lessons learned” (as defined in Table 16.1) 23 times. The other references to lessons learned mentioned knowledge from prior projects (p. 16); i.e., historical information (p. 149). Lessons learned were described as positive outcomes of process adaptations (p. 46) or periodic meetings used to identify and share knowledge (p. 180) and improve processes and efficiency (p. 71); i.e., update project plans (p. 114), or help to improve team performance (p. 180). Lessons learned helped with the risk review process, for example to identify threats (p. 127). Although the guide referred to appreciative inquiry methods for lessons-learned meetings (p. 135), appreciative inquiry was undefined. Appreciative inquiry is based on a four-stage process of discovery, dream, design, and destiny and unlike traditional problem-solving, which can involve negativity and criticism, appreciative inquiry involves asking questions to bring out the best potential in people (Cooperrider & Whitney, 2000). The term “register” (a documented record) was used 30 times and grouped with logs. The term was used to describe the lessons learned, risk, and stakeholder registers (p. 185). For example, the lessons-learned register recorded knowledge for future improvements (p. 185). The term “register” was also used in the context of explicit and tacit knowledge (p. 77). Although the terms “audit”, “database”, and “repository” were not defined in the guide, they were discussed therein and referred to as either formal or informal (p. 148). The word “audit” was used in 13 instances and discussed in terms of reviews (p. 48), quality assurance activities (p. 72), and types of audit, such as process, procurement (p. 79), and contracting audits (p. 148). Databases (noted six times) were categorized under data assets, which spanned databases, document libraries, metrics, data, and related prior project artifacts (p. 17). Reference was also made to commercial databases; i.e., for estimating (p. 18). The term “repository”

234  Research handbook on project performance (noted four times) was worded as a question: “Does the organization have a formal knowledge management repository that a project team is required to use, and is it readily accessible?” (p. 149). This was the only reference made to a requirement. The repository was also discussed in the context of a risk register to record related outputs (p. 185). Given that PMI has a vast reach, there is room for improvement. In assessing the PMBOK® Guide, although the definition for lessons learned referred to knowledge gained during a project, the guide only referred to lessons learned or retrospectives in discussing the last stage of the six-stage life cycle labeled close (p. 47), even though the lifecycle stages were startup, plan, development, test, deploy, and close. The word “register” was used the most (30 times) and it is a documented record or artifact. Although it was good to see that audits were referred to in the context of a process, this was not consistent as the term was also used for various activities. Readers may easily miss the point that the repository must be used, and this begs the question of how important the requirement aspect is from PMI’s perspective. Related to language, some terms in the guide were not defined and reflected unusual terminology, such as appreciative inquiry, artifacts, database assets, evolving aspects, methods, models, modifier, and symbols. As the guide is presented in a structured, systematic, and, dare I say, dry manner, it was further unusual to read vocabulary from appreciative inquiry because appreciative inquiry uses phrases such as positive potential, looking for the best in people, lived values, stories, and expressions of wisdom. Next, I used Google Scholar searches to assess how the academic literature addressed project management lessons learned.

RESEARCH METHODOLOGY PART 2: JOURNAL ABSTRACTS REVIEWED ON PROJECT MANAGEMENT LESSONS LEARNED (2000–2001) As snapshots in time, citation indices reflect academic impact. Indices have different advantages and disadvantages. For example, although the Web of Science focuses on high-impact journals, Google Scholar searches the entire web. Library databases offer keywords to identify sources, but consumers searching for articles and authors developing keywords and their manuscripts may not necessarily use the database terms. Although a constraint of Google Scholar is that the advanced search features are limited to words and phrases either anywhere in the article or the title of the article, it is easier and more convenient to use. I entered the following terms in Google Scholar and narrowed the search to the 2000–2021 timeframe. Based on the terminology used in the PMBOK® Guide, I also used the words “repository” and “retrospective”. Using the “Advanced Search” feature, I limited the search to “articles published in” the terms journal or project management. A list of the words used for the options “words in the title or text” follows – after action, evaluation, knowledge, learning, lessons, lessons learned, post project, review, project management, retrospective, repository, and retrospective. I identified 24 articles for the following review but there are more references at the end of the chapter and in-text because additional sources were used to explain concepts. Beginning with an explanation on knowledge and learning to frame lessons learned, workplace learning extends beyond cognitive and educational (formal) learning that perceives of knowledge as static (unchanging) content passed like a ball from person to person. Readers are urged to think about knowledge as relational, social, dynamic, and a process involving

Project management lessons learned  235 different ways of practice-based knowing (Fenwick, 2008). This is because knowledge changes with active involvement. Learning includes self-directed, collective, informal, and tacit learning (Bratton et al., 2004), including situated learning theory (a workplace learning theory) whereby skills are developed by participating in a community of practice (COP) (Roberts, 2006). Turning to the abstracts reviewed, Kotnour (2000) examined organizational learning in project management environments using the quality management plan-do-study-act cycle. Quality improvement relates to organizational processes and practices. Drawing from the literature on single- and double-loop learning, McClory et al. (2017) proposed a “triple loop of learning” to address lessons-learned challenges affecting success. However, this term lacks a theoretical basis. From a process management and perspective systems thinking perspective (wherein the elements of the entire system are interrelated), Chronéer and Backlund (2015) presented a conceptual model on how project-based organizations can support organization-wide project learning process to improve project learnings. Schindler and Eppler (2003) made the distinction that process-based lessons learned were procedural and focused on learnings whereas documentation-based lessons learned were representations (artifacts). Julian (2008) found that project management office leaders embedded prior project knowledge into routines for project management teams to use. Koskinen (2012a) examined the dynamic interactions and changes between processes specific to organizational learning. Chronéer and Backlund (2015) discussed intra- and inter-project learning in project-based organizations. Kotnour (2000) related project knowledge to project performance and emphasized that learning takes place within and between projects. Related to intra- and inter-project learning, Julian (2008) explored the role of project management office leaders as learning facilitators. Social capital refers to one’s network of relationships whereby individuals have a common sense of identity and shared norms, values, trust, cooperation, and reciprocity (Adler & Kwon, 1999; Coleman, 1988). Social capital helps organizations develop higher-order forms of social capital, which in turn help create more intellectual capital (Nahapiet & Ghoshal, 1998). Julian (2008) emphasized the importance of developing social capital so that project management office leaders could facilitate further learnings. Bartsch et al. (2013) examined how project team social capital fosters learning within the organization through intraorganizational social ties of project team members with other organizational employees. In doing so, intraorganizational social ties reduced organizational barriers to learning. However, Eriksson et al. (2017) found that whereas explorative and exploitative learning processes enhanced learning within a project, these practices did not extend to inter-project learnings. Several articles focused on COPs, an extension of situated learning theory. In a COP, individuals can participate as much or as little as they feel comfortable doing so. Lee et al. (2015) proposed that reputation, enjoyment, and managerial support influenced a person’s participation intensity in a COP. Bresnen et al. (2005) used the situated learning perspective to examine current and new routines. They found that the degree to which novel managerial initiatives interfered with existing practices and disrupted power and knowledge in the organization influenced change. Jugdev and Mathur (2013) also adopted the situated learning theory lens. They contrasted the limitations of lessons learned via codified knowledge sharing practices to the less formal ways in which knowledge is shared and circulated, such as through COPs. Sense et al. (2011) also used situated learning theory and the COP lens to study lessons learn. Briefly, their publications highlighted project teams as learning generators (embryonic COPs)

236  Research handbook on project performance (Sense, 2003a), political issues related to the learning process (Sense, 2003b; Sense & Antoni, 2003), team member cognitive styles as a factor related to learning practices (Sense, 2007a), the importance of a supportive learning environment (Sense, 2007b), the relevance of social systems to enhance learning (Sense, 2008, 2011), and the sponsor’s role to steward project learning (Sense, 2013). Both dynamic capabilities and absorptive capacity involve an organization using its knowledge and learnings to further develop existing capabilities and understand the value of new information. Briefly, dynamic capabilities involve an organization’s ability to constantly integrate, build, and reconfigure internal and external competences (Teece et al., 1997). Related to dynamic capabilities, absorptive capacity has to do with an organization’s ability to take in external information and develop innovative capabilities (Cohen & Levinthal, 1990). Absorptive capacity is composed of potential absorptive capacity and realized absorptive capacity (Zahra & George, 2002) whereby knowledge is acquired, assimilated, transformed, and exploited to create dynamic organizational capabilities. Bakker et al. (2011) examined how knowledge transfer occurred between projects and the parent organization. Their findings suggested that knowledge transfer was a complex process, and that absorptive capacity was embedded within the organization versus held by the project manager, alluding to the concept of knowledge transforming as it is shared versus it only being codified, uniform, and tangible. The authors stressed that project managers needed to focus on organizational and relational processes. As rules are revised, the new rules become an outcome of organizational learning. Leal-Rodríguez et al. (2014) used these concepts in their empirical study showing that their concept of relational learning moderated potential absorptive capacity and reinforced the link to realized absorptive capacity. Also using process thinking, Koskinen (2012b) introduced problem absorption (a form of experiential learning) as an organizational learning mechanism whereby existing organizational rules and norms are used to address new problems. Drawing on the dynamic competence lens, Mainga (2017) identified factors inhibiting knowledge transfer across projects, such as time pressure, the focus on short-term deliverables, and fear of sanctions if mistakes were acknowledged. Schindler and Eppler (2003) highlighted two challenges of lessons learned as the reluctance to learn from mistakes and the lack of discipline to use documentation such as manuals. Julian (2008) used the phrase “red light learning” to describe punitive lessons-learned practices that demoralized learning. Reflective practices were described as positive ways to embed learning. The importance of a safe environment to discuss lessons learned was emphasized along with cultural changes related to reducing power distance, placing more concerted efforts on teambuilding, and creating a learning climate supportive of experimenting. Finally, Shepherd et al. (2011) discussed how those with stronger commitments to the firm perceived of their organization as normalizing failure. These individuals reported experiencing less painful negative emotions of project failure. Although relevant, the concept of organizational commitment was not one that emerged in this review. The next section discusses the aforementioned two sets of findings.

ANALYSIS OF THE TWO SETS OF METHODOLOGIES An earlier review of the Project Management Journal and the International Journal of Project Management (1994–2003) identified project evaluation and improvement (which pertain to lessons learned) as a subject of growing significance (Crawford et al., 2006). Most of that lit-

Project management lessons learned  237 erature was anchored in the knowledge management or quality improvement literature and discussed the benefits of lessons learned and barriers to learning. Although limited to abstracts, this chapter identified additional topics in lessons learned since the Crawford et al. review. It may help to think about knowledge and learning in terms of the wisdom hierarchy consisting of the data-information-knowledge-wisdom pyramid and the processes and transformations between these components (Rowley, 2007). The findings in this chapter indicate that the guide focused on the information component near the base of the wisdom pyramid. Most of the definitions in the PMBOK® Guide focused on documentation, codified knowledge, and artifacts. The guide described lessons learned as “what” in concrete terms. Surprisingly, although there is an extensive body of literature on success and benefits realization, these terms were missing from the definitions in the guide. Project success was referred to marginally as part of effective communication, in the context of the role of the project sponsor as a critical success factor to achieve positive outcomes from a project, and in terms of key performance indicators as quantifiable measures to evaluate project success. In contrast, the abstracts stressed process and the dynamic nature of learning. The abstracts addressed advanced concepts related to knowledge and understanding (nearing the apex of the wisdom pyramid) and addressed how and why aspects to include multiple ways of knowing (Davenport & Prusak, 1998) as well as knowledge as changeable. The abstracts covered such concepts as organizational routines, social capital, knowledge co-creation, knowledge circulation, knowledge transformation, COPs, and situated learning theory. The themes of learning at the individual, team, intra-project, intra-project, organizational, and interorganizational levels were also evident in the abstracts. Learning in the workplace extends beyond cognitive and educational learning to knowledge as relational and dynamic.

CONCLUSION Just as rearview mirrors are essential safety features for successful road trips, the processes of lessons learned are vital to project and project management success. Drawing on concepts from learning, knowledge, and management, the PMBOK® Guide With respect to methodological limitations, this chapter involved a word and phrase assessment of the PMBOK® GuideAddressing these types of limitations would be avenues for further research. Lessons-learned processes involve sharing different types of data, information, knowledge, and wisdom within and between organizations. Lessons learned involve formal and informal learning practices. Our learning and sharing practices resulted in knowledge changing as it circulates. We can improve our project management practices by keeping a diligent eye on the rearview mirror and conducting lessons learned throughout and beyond project life cycles.

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238  Research handbook on project performance Bakker, R. M., Cambré, B., Korlaar, L., & Raab, J. (2011). Managing the project learning paradox: A set-theoretic approach toward project knowledge transfer. International Journal of Project Management, 29(5), 494–503. Bartsch, V., Ebers, M., & Maurer, I. (2013). Learning in project-based organizations: The role of project teams’ social capital for overcoming barriers to learning. International Journal of Project Management, 31(2), 239–251. Bratton, J., Helms-Mills, J., Pyrch, T., & Sawchuck, P. (2004). Workplace learning: A critical introduction. Garamond Press. Bresnen, M., Goussevskaia, A., & Swan, J. (2005). Organizational routines, situated learning, and processes of change in project-based organizations. Project Management Journal, 36(3), 27–41. https://​ doi​.org/​905189981 Chronéer, D., & Backlund, F. (2015). A holistic view on learning in project-based organizations. Project Management Journal, 46(3), 61–74. Cohen, W. M., & Levinthal, D. A. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35(1), 153–175. Coleman, J. S. (1988). Social capital in the creation of human capital. American Journal of Sociology, 94(Supplement), S95–S120. Cooperrider, D. L., & Whitney, D. (2000). A positive revolution in change: Appreciative inquiry. In R. T. Golembiewski (Ed.), Handbook of organizational behavior (2nd ed., pp. 633–652). Routledge. Crawford, L., Pollack, J., & England, D. (2006). Uncovering the trends in project management: Journal emphases over the last 10 years. International Journal of Project Management, 24(2), 175–184. https://​doi​.org/​10​.1016/​j​.ijproman​.2005​.10​.005 Davenport, T. H., & Prusak, L. (1998). Working knowledge: How organizations manage what they know. Harvard Business School Press. Disterer, G. (2002). Management of project knowledge and experience. Journal of Knowledge Management, 6(5), 512–520. https://​doi​.org/​10​.1108/​17538371211192928 Eriksson, P. E., Leiringer, R., & Szentes, H. (2017). The role of co-creation in enhancing explorative and exploitative learning in project-based settings. Project Management Journal, 48(4), 22–38. Fenwick, T. (2008). Understanding relations of individual-collective learning in work: A review of research. Management Learning, 39(3), 227–243. Hsieh, H.-F., & Shannon, S. E. (2005). Three approaches to qualitative content analysis. Qualitative Health Research, 15(9), 1277–1288. https://​doi​.org/​10​.1177/​1049732305276687 Jugdev, K., & Mathur, G. (2013). Bridging situated learning theory to the resource‐based view of project management. International Journal of Managing Projects in Business, 6(4), 633–653. Julian, J. (2008). How project management office leaders facilitate cross-project learning and continuous improvement. Project Management Journal, 39(3), 43–58. Kline, M. (2021). Quotation #11. https://​quotefancy​.com/​morris​-kline​-quotes Koskinen, K. U. (2012a). Organizational learning in project-based companies: A process thinking approach. Project Management Journal, 43(3), 40–49. Koskinen, K. U. (2012b). Problem absorption as an organizational learning mechanism in project-based companies: Process thinking perspective. International Journal of Project Management, 30(3), 308–316. Kotnour, T. (2000). Organizational learning practices in the project management environment. International Journal of Quality & Reliability Management, 17(4/5). https://​doi​.org/​https://​doi​.org/​ 10​.1108/​02656710010298418 Leal-Rodríguez, A. L., Roldán, J. L., Ariza-Montes, J. A., & Leal-Millán, A. (2014). From potential absorptive capacity to innovation outcomes in project teams: The conditional mediating role of the realized absorptive capacity in a relational learning context. International Journal of Project Management, 32(6), 894–907. Lee, L., Reinicke, B., Sarkar, R., & Anderson, R. (2015). Learning through interactions: Improving project management through communities of practice. Project Management Journal, 46(1), 40–52. Mainga, W. (2017). Examining project learning, project management competencies, and project efficiency in project-based firms (PBFs). International Journal of Managing Projects in Business, 10(3), 454–504.

Project management lessons learned  239 McClory, S., Read, M., & Labib, A. (2017). Conceptualising the lessons-learned process in project management: Towards a triple-loop learning framework. International Journal of Project Management, 35(7), 1322–1335. Nahapiet, J., & Ghoshal, S. (1998). Social capital, intellectual capital, and the organizational advantage. Academy of Management Review, 23(2), 242–266. https://​doi​.org/​10​.5465/​amr​.1998​.533225 Project Management Institute (2021). A guide to the Project Management Body of Knowledge (PMBOK® Guide (7th ed.)). Project Management Institute. Roberts, J. (2006). Limits to communities of practice. Journal of Management Studies, 43(3), 623–639. Rowley, J. (2007). The wisdom hierarchy: Representations of the DIKW hierarchy. Journal of Information Science, 33(2), 163–180. https://​doi​.org/​10​.1177/​0165551506070706 Schindler, M., & Eppler, M. J. (2003). Harvesting project knowledge: A review of project learning methods and success factors. International Journal of Project Management, 21(3), 219–228. Sense, A. J. (2003a). Learning generators: Project teams re-conceptualized. Project Management Journal, 34(3), 4–12. Sense, A. J. (2003b). A model of the politics of project leader learning. International Journal of Project Management, 21(2), 107–114. Sense, A. J. (2007a). Learning within project practice: Cognitive styles exposed. International Journal of Project Management, 25(1), 33–40. Sense, A. J. (2007b). Structuring the project environment for learning. International Journal of Project Management, 25(4), 405–412. Sense, A. J. (2008). Conceptions of learning and managing the flow of knowledge in the project‐based environment. International Journal of Managing Projects in Business, 1(1), 33–48. Sense, A. J. (2011). The project workplace for organizational learning development. International Journal of Project Management, 29(8), 986–993. Sense, A. J. (2013). A project sponsor’s impact on practice-based learning within projects. International Journal of Project Management, 31(2), 264–271. Sense, A. J., & Antoni, M. (2003). Exploring the politics of project learning. International Journal of Project Management, 21(7), 487–494. Shepherd, D. A., Patzelt, H., & Wolfe, M. (2011). Moving forward from project failure: Negative emotions, affective commitment, and learning from the experience. Academy of Management Journal, 54(6), 1229–1259. Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research, 104, 333–339. https://​doi​.org/​https://​doi​.org/​10​.1016/​j​.jbusres​.2019​.07​.039 Teece, D. J., Pisano, G., & Shuen, A. (1997, March). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509–533. https://​doi​.org/​10​.1002/​(sici)​1097–0266(​199708)18:​ 73.0.co Zahra, S. A., & George, G. (2002). Absorptive capacity: A review, reconceptualization, and extension. Academy of Management Review, 27(2), 185–203.

17. Projects as vehicles of learning Arthur Shelley

INTRODUCTION Over the past three decades most organizations have become projectized in response to rapid changes in knowledge, technology and customer expectations. That is, management has shifted from being process orientated (to maintain best practices) to programs of projects that constantly change the way in which organizations operate. Almost every industry has moved from processes, through projects as occasional changes to upgrade, to projects as how they deliver their objectives. Projects are no longer occasional improvement programs; they maintain organizations in a constant state of transformation. This is necessary to ensure that they remain relevant, competitive, efficient and effective. In recognition of this, the seventh edition of the PMBOK® (PMI, 2021) has been restructured to be principles based instead of process orientated. The other significant shift in the latest PMBOK® is significantly more recognition of the intangible aspects of Project Management (PM), both as inputs and outputs/ outcomes. This chapter extends this view of the value of projects in sustaining performance by recognizing projects as vehicles of learning and highlighting how project-based learning can be optimized by the way in which the project is designed, led, planned and managed. Processes were how we maintained control, whereas projects are how we change the world to what we want it to become (Shelley, 2017). Processes are an excellent way to achieve consistent results, when the world remains stable in predictable environments. However, the world is no longer predictable nor stable. Everything is constantly changing, and fast. In this VUCA (Volatile, Uncertain, Complex and Ambiguous) environment, quickly adapting to better options is essential to ongoing relevance, competitiveness and sustained performance. Consequently, PM, and more importantly project leadership, has become a critical capability. This chapter explores why projects have emerged, not just as the way to deliver outputs (a “thing” – building, system upgrade, next application, new venture); they are the vehicle through which the capabilities to deliver the teams, relationships, confidence, trust and social connections, to be ready for future projects and future desired outcomes. The irony is that to consistently achieve the best possible outputs and outcomes, people need to have experienced the challenges of real projects in genuine contexts. Theoretical case studies, often used in formal learning, do not provide the same high-quality learning experiences as being part of real projects. Hands-on experience in a range of complex projects is the best way to develop these capabilities (knowledge, skills and behaviors) so critical for future success. The overriding question being addressed in this chapter is: How can projects be designed and implemented so that the learning opportunities for the team are as important as the other outputs and outcomes? That is, the success measures of the project include the intangible aspects, such as the learning experience, relationships and confidence of the team members. In some cases, the key outcome is a high-performing team itself, something that can add significant value to the organization in future. 240

Projects as vehicles of learning  241

LITERATURE REVIEW In our current complex world where change is happening rapidly, one of the most important capabilities is learning to learn, so that our capabilities remain relevant (WEF, 2020a). Remaining relevant and competitive are important success factors in both personal and professional life. The social aspects of individual professionalism and organizational performance are increasingly being recognized as important future success capabilities (WEF, 2020b). Aligned with this is learning to collaborate has become a more important capability (Freeth & Caniglia, 2020). Whilst project-based, social and collaborative learning approaches are not yet widely used in mainstream education, some such programs being introduced with success. For example, in Victoria, Australia (Victorian Department of Education & Training, 2020) and Finland (Zilliacus et. al., 2017), learning in real contexts with collaborative learning and social development is being practiced to a greater extent. These balanced and holistic approaches to learning (Miller et al., 2018) enable people to adapt better to the constant changes in the world and become more productive citizens. We benefit from regular critical reviews of our capabilities for gaps in future needs, to determine what is best for our specific circumstances as we move forward. Well-designed and facilitated education experiences are necessary for comprehensive capability development and to ensure that learners want to continue to engage in lifestyle learning (Shelley & Goodwin, 2018). Traditionally, formal education has been focused on “gaining existing knowledge” rather than building capabilities to interact with the real world in the present and the future. Whilst possessing knowledge is an important part of capability, developing well-adapted people to constructively participate in, and contribute to, society requires application skills and social confidence as well (Miller, 1997). The benefits of holistic education to develop such people and teams involves them engaging in a range of practical experiences to supplement the theoretical aspects. Real projects are an excellent context in which such experiences can be facilitated (Shelley & Goodwin, 2018). Projects provide the opportunity to not just apply knowledge; they enable new knowledge to be cocreated in real contexts (Shelley, 2020b). There have been several approaches described over the years to provide more experiential and or comprehensive education. These have variously been listed under a range of banners including action learning (Revans, 1980; Keys, 1994), experiential learning (Kolb & Kolb, 2009, 2017), social learning (Van Epp & Garside, 2014; Heyes, 2016; Kefalaki & Diamantidaki, 2020), collaborative learning (Essmiller, 2020; Freeth & Caniglia, 2020), student-centered learning (Wright, 2011; Lim et. al., 2019), gamification (Sousa-Vieira et al., 2016; Schulz et al., 2015), project-based (Blumenfeld et al., 1991; Perrault & Albert, 2017; Yasseri et al., 2018), problem-based (Bethell & Morgan, 2011) and the list goes on. However, they have not yet become widely used in mainstream formal education (Miller et al., 2018). The concept of holistic education to develop well-rounded citizens who positively contribute to society is not new. This was the basis of the concept of Paideia which was practiced in ancient Greece and described by Adler (1982). Also Bloom et al. (1956) described three domains for comprehensive education as including cognitive (knowing and thinking), psychomotor (doing and skills) and affective (social and cultural, or “being”). Unfortunately, much modern education at all levels focuses more on the quantitative and cognitive or academic aspects of learning at the expense of the application and social intangible aspects (Robinson & Aronica, 2016). This generates graduates who can answer theoretical questions well, but are not necessarily adept at applying the theories, or confident to engage with other people to

242  Research handbook on project performance resolve unknown challenges. The missing application and social capabilities are significant life success skills that need to be developed somewhere. Whilst alternative, more comprehensive, education approaches continue to be published over time, there are relatively few that are widely adopted, and even fewer that combine aspects from all such approaches (OECD, 2018). Project-based social learning provides opportunity to accelerate the trend toward more comprehensive learning experiences, by combining the positive aspects of the many experiential approaches mentioned above. One key insight from these experiential and practical approaches is that learners are able to explore in socially connected ways with divergent approaches. They aim to generate a range of options for future challenges, instead of just remembering facts they were told (Hayden & McIntosh, 2018; Downes, 2018; Lim et al., 2019; Shelley, 2021). A positive outcome of combining aspects of these approaches into Applied Social Learning Ecosystems (ASLE) (Shelley & Goodwin, 2018) is that the educational experiences are facilitated in an inclusive, constructive project environment. This provides the learners an opportunity to adapt and reapply their learning more effectively across different future contexts (Baker et al., 2002; Alvarez-Alvarez et al., 2019; Shelley, 2021). This chapter describes insights from one approach that embeds the best elements of many of these learning approaches into a single project-based learning experience, leveraging real projects.

RESEARCH METHODOLOGY This research combines 11 cycles of action research in project-based learning programs facilitated over four years. During each learning program, feedback was gathered from stakeholders about the learning experiences and activities, to inform design adjustments to implement for the next cycle. Program participants (on average 24 in each cycle) were assigned to project teams (3–5 people) to address real business challenges for business project owners. In each cycle, an average of five different projects were worked on, which collectively covered government, education, start-up, large and small corporations and not for profit. Each project team worked on one project and with visibility of what was happening in the other projects. Teams proceeded through a series of guided workshop activities that first deconstructed the client challenge and then assembled options emerging from the conversations around the challenge and the desired tangible outputs and the intangible outcomes. The structured approach ensured that all teams were working in parallel through some creative approaches to projects, rather than them simply applying what they already know. This deliberate approach to introducing new concepts is an important part of the design to optimize learning, while still delivering real project outputs. The principles of ASLE (Shelley and Goodwin, 2018) and Reverse Bloom Learning Framework(RBLF) (Shelley, 2020a) were embedded into the design of blended learning experiences, conducted over a period of 4 to 12 weeks (varied with different program offerings). Data for the research analysis was generated by the learners in a series of activities supported by a combination of online tools (MS Teams, Google Sites, discussion forums and online collaboration boards). The learners were familiar with each other as they had been in the same program for some time. This is a significant factor in the way they interacted with each other as they already had a relationship as co-learners.

Projects as vehicles of learning  243 Table 17.1

The flow of activities in the weekly cycles of the learning program

Activity/role

Sunday

Monday

Tuesday

Wednesday

Thursday

Friday

Saturday

Conversation

Slide deck

 

 

Weekly

 

 

 

 

Participate in team meetings as self-organized

starter

and video

Learner

Watch/read

Participate in

Reflect and

engagement

announcement Reflections

Collaborate around themes and elements

share Apply the concepts and elements and reflect on experiences and outcomes of their client

 

challenge Learning facilitator

 

Facilitate

 

engagement

Load

Engage in team meetings as requested

announcement

session Client and

Engage in team meetings as requested

mentor Learners’

Share perspectives of the insights from the application of ideas in different contexts (in

community

discussion forums)

 

Ask questions about their client challenge project in the discussion forums

Notes: Conversation starters are all loaded before the program begins to encourage pre-reading and early activities. Announcements are loaded during the program to regularly stimulate engagement between participants.

A generic overview of the program interactions is shown in Table 17.1. Each week relevant content in the form of “Conversation Starters” (digital files shared to stimulate engagement about that phase of the project) was shared for reading and reflection. The learners read the materials and then interacted with each other about their perceptions of them in a discussion forum (asynchronous text posts and replies). After the online dialogue was completed, a weekly engagement session was facilitated as a videoconference to discuss the contributions and questions the learners had about the range of contributions. Parallel to these engagements, the learners were applying the ideas to their team “Client Project Challenge”. The client challenge is a complex problem they research and develop options for, on behalf of a real industry client. The learner teams engage with the clients as consultants through the four-week course. Groups interacted with their client through an initial briefing session, email, social media, informal videoconference conversations, a formal pitch of their recommendations and finally producing a formal business proposal report. Discussion forum posts, video conversations and artifacts in the collaboration tools (MS Teams, Google Sites, shared Google Docs and Miro) are all rich data sources to draw upon to observe how the learners interacted and support their efforts to produce a professional level set of outcomes for the client. The completed assignments, feedback on the formal peer review and informal conversations with the learners about the challenges they face also provided insights. Conversations between the researcher and the client, and the team mentors (an independent industry support professional for each group), added alternative sources of insights. All data sources were analyzed for common themes and insights about the learning experiences of the learners and the impacts these had on their learning experiences. Insights in the results section draw on the main themes emerging across the full cohort of learners. Lifelong learning and cocreative and collaborative learning were dominant topics of discussion with the learners throughout the course. The RBLF and ALSE were discussed in the initial engagement session and one of the discussion theme forums. This was included to ensure the learners were conscious of the course design and its intent; that is, not content

244  Research handbook on project performance Table 17.2

Learning themes and their elements covered in the project-based learning experience

Theme

Primary elements associated with this theme

Why ethical consulting?

Performance, leadership, ethics, innovation, trusted advisor, reputation, professionalism

Who starts conversations for sensemaking?

Emergence, culture, narrative, sensemaking

What are 3Rs? Robust Relevant Research

Critical thinking, data analysis, decision-making

Where do reflective insights come from?

Reflective practice, storytelling, conversation, knowledge cocreation

Situational cocreation of new knowledge When is value created?

Value, people, capability development, learning

How to achieve success through behavior?

Succession, learning organization, behavior, attitude

Reviewing your consulting project. Constructively

Knowledge transfer, design thinking, project management, impact,

challenging perspectives

quality

Understanding the consulting industry

Mentor, coach, challenge, sustainability, consult

Knowing, doing, being … and becoming

Security, role models, relationships, opportunity

Persuading through effective language

Influence, language, engagement, stakeholders, emotional intelligence, belonging, identity

Changing mindsets for ownership: shifting from “what

Perspective, ideas, creativity, humour,

is?” to “what is possible!”

outcomes, outputs, benefits, beneficiaries, risks

Sharing your client recommendations

Change, pitch, insights, ownership, performance!

delivery based, but collaborative socialization of concepts, based in real business challenges to cocreate options that are unique to the clients’ requirements. The concepts being applied in the programs were reinforced by the 12 themes and the 60 elements being covered in the discussion forums (Table 17.2). The themes and elements were selected to emphasize the role of soft skills in the influence and advisors of others. This is why consulting was chosen as the title of the course, as all successful professionals consult and are consulted on a range of matters in their career. This applies to internal consulting as much as it does to being an external consultant and a respected professional generally in any field. Although the perspectives differ across contexts and fields of practice, the capabilities for professional success remain largely behavioral and cultural. Collectively the activities, discussions, themes and elements address eight of the top 10 Future Skills addressed by the World Economic Forum (WEF, 2020a). The assumptions being made in this approach are that social cocreation of new insights in uncertainty is the ideal way to develop the balanced professional capabilities across knowledge, skills and behavior, or “knowing, doing and being” (Shelley, 2017). Equally important is that the environment places the learners just outside their comfort zone, yet remaining psychologically safe. This stimulates their creativity and ability to cocreate new options, instead of relying on what is already known. The aim of this research is to elicit insights on the effectiveness of this developmental approach from the learners’ perspectives and assess their connection between this and ongoing development of future capabilities.

ANALYSIS AND DISCUSSION There was a consistent strong sense of support for this style of project-based learning throughout the 11 cohorts of learners. This was evident in all aspects of the program, through the high levels of participation and engagement and the quality of the outputs the learners generated for

Projects as vehicles of learning  245 their project clients. Examples to support these statements are provided in learner comments drawn from the engagement sessions, discussion forums and peer review listed in Table 17.3. Table 17.3

Examples of feedback from learners about the learning approach

Learner comments in peer reviews or discussion forums (anonymized) The course was facilitated in the most interactive way. We got to do many readings and discussion in the class … we get to work with real client/real business and that is very differentiated and help to engage us stronger and build our capability and provide strong connection with our real life experiences. Thank you. There was of course additional pressure as we were consulting real clients, but overall it led to significantly more learning outcomes. The course is facilitated on the way to let people learn from each other, rather than just listen to professor. It is good to have practical sharing from all people based on their experience. Working on the real case also made me feel that the solution, which we provide, must be practical, because in real life people do not care much about great idea that does not apply for their business. And we also can learn about mistake that consultant can make in real life. This program provided great scaffolding for different learner levels, covering BOTH how to learn, and where/who/what learners are striving to become. Each learner was able to adapt the support materials to match their level and desired development elements. There are clear socio-contextual structures and frameworks for communicative success, which are critically important for all learners. Different approaches such as “Conversation Starters”, discussion, storytelling and sensemaking enabled people to participate and share professional/cultural contexts. The collaborative conversations spiral encompassing adaptive human behaviour, knowledge co-creation, mutual value, etc was a unique feature that was fantastic for learner orientation and inclusion. This gives me big motivation to keep exploring more, the knowledge won’t become mine until I deliberately practiced and keep building examples. I feel beneficial a lot when applying what I learnt in real life. Every day, we are engaging the people surrounding us through sense-making conversations to influence others, this brings me great fulfilment when turning things in an effective way which is mutually beneficial. Real project is amazing. Nothing can make a medical intern feel more excited than giving them a real patient! All our learnings finally can be applied, where potentially can generate significant impact to client’s business. The bigger the responsibility is the higher engagement we are. Thank you for the great efforts to build the project cases, enable the best practice on the ground. Interesting project in real consulting process and practical initiatives. This is the best course in the program. Though there is more demand than usual, the course is really helpful. I learnt a lot. It is well organized in course content, well-designed pace though there is time limitation. Many extra information is shared for students to read after course. I like the collaborative learning experience, we join the discussion board and Google Sites. There is a 1 hour session each week to make the scholars keep updated and in touch. I admire the time management, and everything is delivered on time with quality, especially during the discussion part that our lecture could politely and skillfully proceed the process without making anyone feel uncomfortable. As I shared in our last engagement session, it is indeed “save the best for last”. I have really enjoyed all engagement sessions, and how we worked together during the intensives. We are impressed in the way the programme structure is organized, the knowledge of consulting, the tips and techniques for delivering consulting pitches and reports, and more importantly, the dedication of transferring the knowledge to us, and help us build our lifelong learning attitude. In my view, this is one of top 3 excellent courses of the program due to some following reasons: 1.

The dedication and knowledge from Professor as well as the structure and new tool of experience he did invest into this course. Impressive.

2.

The time management with superb and discipline, I love it so much.

3.

The presentation and discussion among the cohort are very good. Thanks.

Make it on campus class rather than online as we wish to have more time and face-to-face discussion with teacher and our client. This course is the best one I have completed. All assignments and materials have been given in a way that expose us to practical situation. I felt kind of pressure, and at the same time kind of excitement as I worked during the course.

246  Research handbook on project performance The positive responses were despite the learners being under considerable time pressure, as they were all working in professional roles during the program and subjected to a time pressured intensive format.

CHALLENGES OF SHORT INTENSIVE FORMAT LEARNING All cohorts of learners were involved in blended learning (face-to-face and virtual interactions) that involved both a three-day intensive and ongoing remote interactions. For some cohorts, the total duration of the program was 12 weeks, and for others the whole program was completed in four weeks. Feedback about the time constraints was consistent across cohorts, as seen in the example comments in Table 17.4. However, the impact of this was more prominent in the four-week version of the program. This is a real challenge for lifestyle learning (Shelley & Goodwin, 2018) in the modern era, where there is an expectation that formal learning occurs in parallel with a challenging career. As professionals try to achieve more career impact faster, and at the same time accelerate their development, lifestyle balance is challenged. Prioritizing time becomes more challenging as the duration of programs are reduced to fit in the busy lives of professionals. Everyone wants a full learning experience that is rich and applicable, but in shorter timeframes. The heuristic time requirement for a Master’s-level course (Australian Qualifications Framework Committee, 2013) is approximately 144 hours for an average learner to achieve an average grade. When this time is allocated over a normal semester of 12 weeks, it is achievable with discipline. However, achieving the same quality level of learning at AQF 9, condensed into intensive formats, places huge time pressures on learners. This inevitably creates a conflict between the convenience of intensives and the ability to get deep learning experiences completed in such short timeframes. Managing these expectations is a challenge for learning facilitators, who wish to optimize the outcomes for the learners, whilst acknowledging the time pressures they place on themselves. Table 17.4

Examples of comments from learners about time pressures of intensive formats

Learner comments from emails, peer reviews, MS Teams chats and discussion forums Considering the teaching mode advertised for the whole program, the intensity of class activities could be a bit burden on some days. However, as we always shared in class, that only 4 weeks for a consulting project is not the ideal way of delivering it. Because of time limitation, it also creates a limit on new knowledge. For example, what will happen after we provide solution to client, they apply but they have challenge when they apply in real life, even though we know they agree with the solution at the beginning but what should we do at that case. It should be longer, perhaps time allocated for the course should be double. More time to work on the Global Consulting Project. I wish I had more time :) to absorb the most from the course as content is rich and demand is high. Extend the course for a few weeks to get the feedback from client if any of our solution can really help them. And from that we can learn more why our proposal is not practical in real life, what we should do better. I would suggest increase the course timetable to give students more time to digest and prepare for the last consulting project. Since this is a last milestone course, it is possible to design this course from 1 month to 1 semester, so that the students have enough to present what we have learnt from our previous courses and the new learnt consulting skills and knowledge. As a consultant, we are accountable for helping client achieve their goal through mentoring, however we cannot help them to execute the plan and build every single resources. It’s important to develop the debate thinking skills when aligning the core execution plans. I felt each hour of our very limited time together was carefully considered and I received maximum value for my money.

Projects as vehicles of learning  247

INSIGHTS FOR FUTURE DEVELOPMENT OF EXPERIENTIAL LEARNING Feedback from the learners and other parties associated with this approach highlights that the opportunity to further embed socialization into the experiential learning activities is worth pursuing. This learning experience was so powerful for the learners because of the range of projects that were included over the four years and because the interactions continued to evolve for the participant feedback with each of the 11 cycles. Optimal learning experiences prepare learners with the capabilities (knowing, doing and being elements) to prepare them for unknown future challenges – not focusing on what is already known (which may or may not be relevant to future contexts). The program structure is largely the same. It benefits from refining activities around the participant feedback to provide ways of including emerging aspects that were not already there. As new aspects were incorporated into the program, the experience was richer and more powerful. This does not mean adding more content; it was quite the opposite. Content volume decreased whilst the essence of new insights was incorporated into the relevant structured activities, often as a probing question or short video. This encouraged the learners to socialize these “conversation starters” into the context of their project. Some of the key features of the design changes are listed in the next section.

INSIGHTS FROM THE CLIENTS AND MENTORS IN THE PROGRAM Clients and mentors are an important part of this program design, as they add a level of reality and more diversity of perspectives to the conversations. The learners recognize the importance of this, as seen in the typical comments shared below. Thank you team. Through your hard work, you’ve opened our eyes to the value of consulting services & strategic analysis while providing great objective, data-driven recommendations along with several innovative ideas. I really appreciated the team’s strategic thinking and firm apprehension of our business despite the few exchanges we’ve had. I’m truly inspired – please know that your report will have great significance in the future of Papillon’s growth. It will be my personal responsibility as a stakeholder in this business to see that these valuable insights and plans get implemented. I am a very happy client and I wish you all the best in your future endeavors! (Challenge Project Client) The practical recommendations from the cohort were aligned with our own direction but added cohesive, actionable steps for our company implementation. What was even more valuable were the challenging and new perspectives provided by the students. I look forward to discussing with our Top Management! (Challenge Project Client) I have been a team mentor on several occasions in this program and enjoy the interactions with the students and project clients very much. Although the role of the team mentor is there to challenge the team to be at their best, I always learn a lot from how they interact and the ideas they bring to the project from their diverse professional experiences. (Project Team Mentor)

248  Research handbook on project performance

HOW WOULD THE LEARNERS SHARE THEIR INSIGHTS ABOUT THE PROJECT-BASED LEARNING EXPERIENCE? The most important success measure about anything is customer feedback. As part of the anonymous peer review activity, learners were asked what advice they would give to a friend who was considering doing this program. The feedback is provided exactly as stated by the participants, except for adjustments to ensure anonymity. This does not need to be discussed further here, as the learners’ own words speak for themselves (Table 17.5). The answers are sorted in order of those mainly about the structure and experiences of the program, followed by those about the general applicability of the capabilities to ongoing professional activity. The evidence and insights shared in this chapter highlight how engaging learners in real-world, project-based learning activities creates deeper engagement and more meaningful learning outcomes. Learners’ feedback shows that real client projects were a motivating Table 17.5

Feedback from learners on whether friends should engage in this approach

Comments as stated (adjusted to anonymize where relevant) The program embodies everything that is great about professional learning. It provides the students the opportunity to apply numerous skills and experience gained over the previous courses in a real-life context. Make sure to read through each of the twelve themes and additional topics before the intensive and take the time to explore other additional resources online. I particularly enjoyed learning more about the key skills and challenges of a consultant from current and previous experts that are also translatable to all professional fields. Please bring one or two of your core values or strengths into class, in return you will bring back 20+ other values or even cocreated new values exchanged through joint learning efforts. This course is not going to teach or repeated the materials where you can search from Google or books. You should expect a psychological approach and behavior influencing experiments, through the learning and practice. You will also experience fun games, the OrgZoo animal characteristic and behavior analysis, which gives insights into how critical the impact behaviour is in teams. During the course, you can freely raise your questions, share your opinions, answers come even faster than Google, and always providing an integrated answer which beyond my expectation. You will have the chance to test your learning effectiveness on well-prepared real challenges to excise our practice, which is the only criterion for testing knowledge. Last but not least, you will receive constructive feedback after your pitch, you may not hear those perspectives during your work, as you’ve been too comfortable with what you were repeatedly doing and missing the mindfulness. Practical and interesting course. There are a lot of new things and a new approach. You need to prepare for the new learning method and tools as well, but you will have a chance to propose some actions which can help people to apply in real life to solve their problem. It is really a good way of putting together all the knowledge we have learnt from the previous courses into a project and learned additional new consulting skills. Even though you might not work in the consulting industry, the skills are needed in all aspects of our professional career. Interesting and high-level of interactions with various forms such as discussion, presentation, debate, examples, essay with practical application. This is the best courses that we participated in. Besides your rich experiences related to consulting business, the way you deliver and touched upon Miro, Google Sites, different topics for assignment and get cohorts to involve deeply in the course. This is a collaborative learning course. Everyone will have the opportunity to contribute to the experience. If you are great at speech, there are lots of opportunity for you to share your ideas. If you feel stronger in writing, you can also post your ideas in discussion session and Google Sites. Great course to take, very interactive and real project to work on. Consulting is the necessary skill-set not only for consultant but for a business manager, and in day-to-day life. Be ready for some new learning mode such as Google Sites. You may find it is a little bit confusing in the beginning, but just spend one hour on it, you will be fine.

Projects as vehicles of learning  249 factor that led to a higher level of investment of effort to generate high-quality outcomes. This better prepares learners for the application of their newly developed capabilities in their ongoing workplace and increases their awareness of the importance of being adaptable in our current professional world (Shelley, 2021). The social, collaborative and cocreative nature of the project-based learning generates deeper reflections, as well as a wider scope of applied aspects of learning. This happens because instead of 24 learners learning from a single source, 36 people (students, clients, mentors and the learning facilitator) learn from each other. Combining their diversity of experiences and perspectives across the themes and elements as they apply to different project contexts, they individually and collectively become aware of a wider set of possibilities. Combining learning before, during and after group interactions reinforces the superior depth and scope of learning. The main limitation of the current research is that this a relatively small study. Future examples of how these learning concepts can be applied, across wider cohorts of learners and project contexts, will further build support for the value of the approach. In time, as the approaches of ASLE and RBLF are facilitated across more programs and more cultures, a larger body of evidence to support how and why they work will be developed. Longitudinal studies will also show the longer-term impacts of learning in the workplace and provide new insights to enhance them further. Such studies can be developed through research and education partnerships between industry, universities and facilitating philanthropic foundations.

DESIGN INSIGHTS ON WHY THIS PROJECT-BASED APPROACH TO LEARNING IS OPTIMAL In each iteration of the program, constructive feedback on the project-based learning experience was gathered to refine the approach and create a more an interactive collaborative learning ecosystem (Shelley & Goodwin, 2018). There were some consistent patterns in the feedback that highlighted the success criteria from the learners’ perspectives. The list below summarizes why this project-based learning experience provides a special experience for the learners. To the author’s knowledge, there is no other learning experience that achieves all these aspects anywhere in the world: It is a genuine interactive project-based learning experience from which the findings will be applied by a project owner. The fact that the learners need to face the project owner and advise them what to do next places a strong reality to the context, one that a case study can never provide. (2) Learners engage in semiautonomous cocreation of new knowledge for a real client challenge and are required to deliver a practical set of recommendations within the constraints of the client. (3) Whilst there are extensive support materials provided across the 12 themes and 60 elements, including brief video introduction for each theme, the key content is created by the learners themselves, within the context of their client project. (4) Learning is stimulated by creating an “ASLE” (Shelley & Goodwin, 2018). This conducive environment supports socialization of ideas to encourage sensemaking, reflection and collaboration to support insights and emergence of options. (1)

250  Research handbook on project performance (5) Client and project challenge selection are critical. All accepted clients genuinely want options for their challenges (not “the answer”). The projects are assessed for suitable complexity and for which there is no simple copy and paste option. Only those for which the client does not yet know how to resolve it are selected. The client commitment and the challenge uncertainty are critical ingredients to achieve the exploratory learning. (6) The learning is iterative through phases that build on each other within the context of the challenges. This involves a reversal of the traditional learning approach, through a new approach RBLF (Shelley, 2020a). (7) The approach deliberately encompasses all three domains of learning; cognitive (knowing), psychomotor (doing) and affective (social, cultural – being) in an inclusive, interdependent way. This requires the learners to engage with each other in a series of collaborative conversations (Shelley, 2021), which switch between divergent and convergent thinking. (8) The formal assessments are 40% individual, 60% team based. The high level of team-based assessment reinforces collaboration across the team members and building the trust. The peer review process further reinforces the teamwork element of performance. (9) There are proactive interventions on how the teams are progressing via an anonymous peer review process (which also solicits anonymous feedback on the course experience) and regular conversations with the team mentor. (10) The practical experiences of the learning facilitator and the industry mentors bring a balance of pragmatic application and academic rigor. (11) The individual assignment is open and collaborative. Each learner researches a different topic and must relate it to the context of complex projects with practical insights, personal reflections and academic rigor. Participants collectively cocreate a database of insights on the topics that will inform decision-making on their client projects. Participants are expected to hyperlink their assignment to others to demonstrate the interdependencies. This creates rich learning and highlights the complexity of human projects and highlights the power of a collaborative working culture, aspects that contribute to high performance in future projects. (12) Extensive feedback is provided on the assignments, including a paragraph on what they did well (how they achieved the mark given) and one on what they could have added to achieve a higher mark. This is all done within the context of a previously shared rubric, detailing expectations for each grade across each criterion. This is supplemented with a short video summary and in-text comments in their submitted document. Providing all of these aspects in a single project requires significant design, planning and discipline. Many people studying at this level are highly experienced and capable professionals. As such, they have deep knowledge and confidence to act on their knowledge. This brings with it the benefits of mutual social learning, but also the challenge of influencing competent, capable learners to open their minds to alternative options. Traditional education (and PM) rewards efficiency (time and cost delivery) more than effectiveness (scope and quality delivery). The Project Management Body of Knowledge traditionally reinforced control of projects more than adaptability and agility. However, the recently released seventh edition has shifted to emphasize principles and pays closer attention to the human aspects and outcomes of project success (PMI, 2021). This rebalancing the way the industry perceives projects, and they value

Projects as vehicles of learning  251 they generate, is a positive change. Shifting mindsets to make more balanced considerations and investing in more inclusive conversations about possibilities is a significant part of the learning in this approach. This is an important aspect of the learning experience. It is why “knowing, doing and being” are all emphasized together to ensure the principles, intangible aspects and soft skills are developed along with the technical and logistical aspects of projects. The author suggests that projects based on principles and a balance of knowing, doing and being make excellent vehicles for professional development across all professions. Designing professional development in this manner ensures that projects are not just about delivery of a thing – they also deliver more capable professionals, collaborative teams and greater potential for future performance.

CONCLUSIONS The evidence in this research highlights the benefits of using real business projects to support learner development. In particular, since the COVID pandemic, experiences collaborating through a series of virtual activities, facilitated using online collaboration tools, have elevated confidence in working remotely in project environments. Confidently engaging and leading in virtual project environments has become an essential future skill. Engaging learners in projects for which solutions do not yet exist, and for which the recommendations will be implemented by business owners, places a different perspective on the learning activities. This generates a different learning mindset, with increased ownership of the recommendations. It also increases the motivation to engage deeper in learning activities. When teams deconstruct the client challenge and then assemble options emerging from the conversations, they are part of the solution. This stimulates them more than just implementing someone else’s answer. The structured, but flexible, workshop-based “learning by doing” approach engaged participants to cocreate novel options that applied well to the future challenges faced by the business clients. This chapter also highlights some important andragogical aspects of this approach that may not be immediately apparent for project professionals, including why these are important aspects of project outcomes generally. In particular, the learning impacts of dealing with a real complex challenge for a client that is yet to be resolved shifts the mindset from delivering a predefined solution to creating a range of prioritized options. Focusing on learning aspects of a project does not compromise achieving results; it amplifies the benefits and prepares learners to be higher-performing team members on future projects. Opening the minds of the team members to creative possibilities and encouraging more exploration of novel ideas generated superior results (outputs and outcomes) for both the team members and the project owners. Developing the capabilities across knowing, doing and being in balance generates not just good project outputs for that project; it creates strong function-connected teams for future project performance. Projects are not just vehicles of development, innovation and change – appropriately designed and facilitated, projects can be strategic vehicles of learning too.

252  Research handbook on project performance

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18. Impact of Industry 4.0 on agile project management Vijaya Dixit and Upasna A. Agarwal

1. INTRODUCTION Industry 4.0 is defined as a combined terminology for technologies such as the Internet of Things (IoT), big data, autonomous robots, simulation, additive manufacturing, augmented reality, virtual reality, and cloud computing. The main features of Industry 4.0 are horizontal and vertical integration. These aspects ensure internal collaboration of subsystems that create flexible, agile, and adaptable systems capable of offering customization in their product/ service offerings (Lin, Nagalingam, Kuik, and Murata, 2012). The fourth industrial revolution due to Industry 4.0 has brought profound and lasting changes in the economy and society, which in turn has resulted in the evolution of Project Management 4.0. In the new version, the entire project lifecycle right from project initiation, planning, execution, monitoring, and control is performed by utilizing Industry 4.0 technologies. Project Management 4.0 is characterized by digitization, virtualization, transnationalization, professionalization, and agile (Simion, Popa, and Albu, 2018). Because of these transformations, the project environment has become more complex and dynamic, which on one hand will cause disruptive effects on the traditional project management (Ribeiro, Amaral, and Barros, 2021), whereas, on the other hand, it will also greatly expand the collection of automation tools and technologies available to project managers to facilitate effective project planning, monitoring, and control (Simion et al., 2018). Recently, the concepts of Industry 4.0 have been successfully applied in the manufacturing industry by multiple researchers (Frank, Dalenogare, and Ayala, 2019; Qin, Liu, and Grosvenor, 2016). However, no study has reported the application of Industry 4.0 concepts in agile project management context. Like Industry 4.0, the horizontal integration across project entities (client, contractor, suppliers, subcontractors, statutory bodies, etc.) and the vertical integration of a project team inside the project organization are the two fundamental aspects of project management as well. In this study, the technologies of Industry 4.0 are studied from the perspective of their application in various knowledge areas of agile project management. Section 2 of this chapter discusses the impact of Industry 4.0 on project management and the role of agile project management. Section 3 focuses on the impact of Industry 4.0 on project human resource management (HRM). Section 4 proposes new research direction and Section 5 presents conclusions and future directions.

254

Impact of Industry 4.0 on agile project management  255

2.

IMPACT OF INDUSTRY 4.0 ON AGILE PROJECT MANAGEMENT

Projects have unique customized requirements and are carried out in highly uncertain and changing environments. Because of these characteristics, changes in project scope are inevitable. For highly dynamic projects where precise scope definition is not possible, agile project management approach is preferable. Agile project management comprises self-managed adaptable teams that continuously take inputs from customer-oriented feedback loops to iteratively adjust the scope and performance of the project. The key capabilities of agile project management are that it is able to handle the complexity of the projects and address uncertain environments and resultant changes (Scholz, Sieckmann, and Kohl, 2020). The important principles of agile as reported by Raji and Rossi (2019) are: ● ● ● ● ● ● ● ● ●

AP 1: Centralized planning using a collaborative approach AP 2: Frequent introduction of new innovative products AP 3: Speedy response to customer requests AP 4: Leveraging IT for integration and coordination among design and development activities AP 5: Leveraging IT for integration and coordination among manufacturing/company activities AP 6: Flexibility of suppliers in terms of delivery time and orders AP 7: Leveraging IT for integration and coordination among procurement activities AP 8: Flexible product mix through flexible equipment AP 9: Enhanced offering for product customization.

Large companies operate mostly in uncertain environments. As such, uncertainty is becoming the norm in the present global economy that operates on a free market philosophy. Arnold, Veile, and Voigt (2018) indicated that such uncertainty could bring additional challenges for the organization during its attempt to adopt Industry 4.0. Yanık and Işıklı (2019) stated that the agile approach, due to its key characteristics of responsiveness and speedy decision-making, can play a pivotal role in digital transformations of the companies, especially when the companies are executing large-scale projects full with uncertainties. Marnewick and Marnewick (2019) stated that the new environment in the era of the fourth industrial revolution requires shortening the development and innovation, as agile is more successful and quicker in implementing new products than the traditional project management. The aforementioned requirement can be fulfilled by adopting the agile approach for the faster development and implementation of innovations. Ghani at al. (2015) stated that agile methodologies enhance project quality, customer satisfaction, and flexibility for incorporating variations and complications. The altering environment created by the fourth industrial revolution requires cautious explanation of the shifting production prerequisites, and it is intensely linked to agile methodologies and where implementation of solutions is done in an agile way (Marnewick and Marnewick, 2019; Elnagar, Weistroffer, and Thomas, 2018). Simion et al. (2018) suggested that digitization will help organizations perform virtual simulation of project execution before real-time execution, which will lead to better project scope management and risk management. The availability of a large volume of data from continuous monitoring through sensors and application of data analytics tools on this data will provide early warning signals. The results of simulation and big data analytics will make project man-

256  Research handbook on project performance agers conscious of the probable risks that may be encountered during different stages of the project life cycle. This will facilitate better project risk and response management. Smart algorithms available can provide foresight of cost and schedule of projects better than expert assessments. Continuous data collection through sensors, machine-to-machine communication, and smart appliances will provide updated real-time cost and schedule progress indicators and automated quality control of deliverables (Simion et al., 2018; Cakmakci, 2019). This will enable better project monitoring and control through earned value analysis. Simion et al. (2018) stated that digitization will facilitate globalization of companies by allowing them to execute projects simultaneously in different parts of the world. E-social networking platforms can be used to involve stakeholders to provide feedback on project deliverables, which can be used for improving project performance. Using virtual platforms in procurement processes will help in sharing knowledge about purchases. E-procurement platforms can enable smart contracts and smart sourcing. Ribeiro et al. (2021) and Simion et al. (2018) forecasted that physical communication will slowly be replaced by internet connectivity and use of human–machine and machine–machine communication. Virtual telepathy will become predominant in the communication process and the use of big data analytics will permit the flow of a huge amount of information, rapidly, through a broader spectrum of communication such as 5G. The resulting virtualization will accelerate the communication processes and make it more dynamic within projects that will allow an extension of virtual teams spread across different parts of the world. Marnewick and Marnewick (2019) suggested that as robots and machines will become part of the project team, digital communication feedback needs to be integrated in collaborations to include nonhuman input and feedback. Simion et al. (2018) opined that technological interventions resulting from Industry 4.0 will lead to enhanced complexity of the projects as the number of components to be tracked will increase. This will create additional challenges for project integration management. However, the focus of Industry 4.0 is on technologies such as blockchain, the IoT, and cyber-physical systems (CPSs), and the integration of different technologies will enable information technology ecosystems to function in an intelligent and autonomous way. This will facilitate integration management of project data by sharing of common information to all stakeholders, enabling independent decision-making (artificial intelligence), agility, interoperability, flexibility, and efficiency (Marnewick and Marnewick, 2019). Table 18.1 presents the various Industry 4.0 technologies, their application in a project context, and the project management knowledge areas and agile principles affected by each technology.

 

Impact of Industry 4.0 on agile project management  257 Table 18.1 Industry 4.0

Application of Industry 4.0 technologies in a project management context Application

technology

Project

Agile project Author

management

management

knowledge area aspect Additive

Additive manufacturing technology is used to

manufacturing manufacture personalized goods and complex parts

Scope,

AP2; AP3;

Rane, Potdar, and Rane

schedule, cost,

AP5; AP8;

(2019); Ivanov, Dolgui,

AP9

and Sokolov (2019);

with lower production costs, energy consumption, and risk material wastage. It minimizes inventory by allowing

Franco and Behrens

demand-based production, and shortens the lead times

(2019)

by eliminating long supply chains. In new product development projects financial and operational risks are higher due to innovative designing. Additive manufacturing can create product prototypes for feasibility check and design validation and minimize Autonomous

the risk associated with new product development Robots will gradually become part of project teams,

Resource, cost,

robots

working side by side with people comfortably, and

schedule

AP3; AP5

Franco and Behrens (2019)

communicating with them. These robots are more autonomous, more versatile, and more cooperative. The use of the autonomous robots at the construction sites will eliminate the risks associated with human health and safety, and they can complete the repetitive tasks with more efficiency and less cost and time Big data

Big data analytics uses computerized algorithms

analytics

in large databases to identify trends, interactions,

Risks, quality

AP1; AP3;

Rane et al. (2019);

AP4

Haddud and Khare

and correlations that can reveal useful information.

(2018); Ribeiro et

It helps in improving the accuracy of forecasting,

al. (2021); Franco

traceability, visibility, and efficiency. The insights

and Behrens (2019);

drawn from big data analytics assist in solving

Cakmakci (2019); Raji

complex network problems leading to improved

and Rossi (2019)

network responsiveness. Big data analytics helps in forecasting the different risks involved in a construction project, such as vague design specifics and requirements, loose subcontractor control, Blockchain

financial risk, etc. Blockchain allows non-tamperable, time-stamped

Stakeholder,

AP1; AP6;

Rane et al. (2019);

records accessible to all stakeholders across the

integration,

AP7

Simion et al. (2018)

network reducing conflicts and better integration

procurement

across project stakeholders. It enables rapid and automatic payments between parties via smart contracts, which assists in managing multiple suppliers within the project

258  Research handbook on project performance Industry 4.0

Application

technology

Project

Agile project Author

management

management

knowledge area aspect Cloud

Project networks comprise several entities including

Integration,

AP1; AP3;

Rane et al. (2019);

computing

suppliers, contractors, client, consultants, and

cost

AP4; AP5;

Haddud and Khare

AP6; AP7

(2018); Ribeiro et

regulatory agencies that are located at different locations. Cloud computing technology allows

al. (2021); Franco

data storage in a single source cloud, which can be

and Behrens (2019);

accessed by any stakeholder of the project. This leads

Cakmakci (2019); Raji

to better integration management by real-time and

and Rossi (2019)

symmetrical information sharing across all entities and across all geographical locations. As the cloud is a shared resource, it does not incur acquisition and maintenance costs. This reduces the operational costs Cyber-

of the project, leading to savings CPSs ensure integration of the physical world with

Integration,

AP1; AP3;

Zhong, Xu, Klotz,

physical

the computing/virtual world. These interconnections

resource

AP4; AP5;

and Newman (2017);

systems

within CPSs guarantee real-time data and information

AP7

Oztemel and Gursev

sharing, leading to a high level of coordination,

(2020); Elnagar et

regulation, transparency, and efficacy

al. (2018); Cakmakci (2019); Raji and Rossi

IoT

In a project, different kinds of resources are deployed

Monitoring

AP1; AP3;

(2019) Rane et al. (2019);

such as equipment, workers, robots, etc. Workers’

and control,

AP4; AP5;

Ribeiro et al. (2021);

activities and health conditions can be tracked using

communication, AP7

Franco and Behrens

smart clothing and smart helmets. All aforementioned

integration

(2019); Cakmakci

resources in the production site can be connected

(2019); Raji and Rossi

via embedded software, sensors, and electronic and

(2019)

network devices through internet technology, leading to integrated and intelligent project systems. This will increase the quality and efficacy of data collection in real time, thus facilitating earned value analysis for better project monitoring and control

Impact of Industry 4.0 on agile project management  259 Industry 4.0

Application

technology

Project

Agile project Author

management

management

knowledge area aspect Simulation

Simulation exploits real-time data to replicate the

Schedule, risk,

AP1; AP2;

Rane et al. (2019);

physical world in a virtual environment, which may

cost

AP3; AP8

Ribeiro et al. (2021);

include computers, items, and humans. It offers

Franco and Behrens

a virtual system analysis and optimization framework

(2019)

that can help to reduce the project schedule, new product development time, and expense. The simulation can also be used for risk analysis in projects for architecture, scheduling, planning, and development domains Augmented

AR can be used for visualization/walking through,

Monitoring and AP1; AP2;

Edirisinghe (2018);

reality

knowledge recovery, on-site assembly, and

control, risk

AP3; AP8;

Ribeiro et al. (2021);

AP9

Franco and Behrens

way-finding. An AR smart helmet can generate a location-specific AR overview when it is combined

(2019); Raji and Rossi

with sensor and imaging technology. Golparvar-Fard,

(2019)

Peña-Mora, and Savarese (2012) invented a method for tracking progress by image processing. Photographs taken on-site are used in this process to create an “as-built” 3D model, and this is compared to the “as-planned” model. AR can be used for a protection strategy that produces alerts to discourage employees from entering dangerous areas (where the area’s spatial coordinates are predefined), such as when there is a high probability of overhead items dropping in the construction field

3.

HUMAN RESOURCE MANAGEMENT IN INDUSTRY 4.0

An important knowledge area of project management that is affected by Industry 4.0 is project resource management. It involves identification, acquisition, and management of human resources required to execute a project successfully. HRM has been a challenging task even without Industry 4.0. Once the organization decides to implement Industry 4.0, it will force project managers to rethink current practices and processes around HRM. Marnewick and Marnewick (2019) and Sony and Naik (2019) opined that the top management’s commitment and full-fledged involvement and the adaptableness of employees are important for Industry 4.0 adoption. With digitization being implemented, project managers are reorganizing projects’ internal structures using digital products in order to adapt to the changing requirements of Industry 4.0 (Cakmakci, 2019). Nowadays, the human members of the project team are being replaced by robots and full automations, particularly for repetitive tasks. This makes monitoring and controlling easier as much information is now available in real time. However, the aforementioned changes require robust initiation and planning processes so that the tasks assigned to the robot and the machine must be designed in such a way that they align with the digitization aspect of the job crafting (Ribeiro et al., 2021). Leadership Bushuyeva, Bushuiev, and Bushuieva (2019) stated that as the world transforms rapidly during the fourth industrial revolution, a new generation of leaders is necessary.

260  Research handbook on project performance These leaders need to be technologically competent so that they can respond to innovations, thereby creating new businesses and technological opportunities for project implementation. Jermsittiparsert (2020) revealed that leadership style and Industry 4.0 together significantly impact organizational performance. The fourth industrial revolution has a disruptive impact on the way organizations work. In this context, an agile mind-set needs to be adopted to implement Industry 4.0 technologies as continuous change is brought about by the introduction of these new technologies (Marnewick and Marnewick, 2019). Project managers are the main actors in this industrialization change process, therefore they need to have the prerequisite technological skills and knowledge about technologies such as artificial intelligence, machine learning, CPSs, and big data analytics (Ribeiro et al., 2021). Project teams need to be agile and swift. This cannot be achieved through a “command and control” leadership style. The authoritativeness of project managers will depend on their ability to manage the overall flow at a holistic level as well as at a component level. Project managers need to adopt servant-leadership qualities to lead such agile teams (Parker, Holesgrove, and Pathak, 2015). Team: The implication of adoption of Industry 4.0 for project teams is that they have to continuously upgrade their skills and competency with respect to new technologies (Marnewick and Marnewick, 2019). This will result in a major change that has to be accomplished in an agile way. Thomas, Bellin, Jules, and Lynton (2012) stated that teams that are high-performing are agile in their thinking and always play an important role in the decision-making process. Simion et al. (2018) identified that digitization will create a globalization opportunity for companies to have virtual teams with members from different parts of the world. The cultural diversity in such teams on one hand will create an opportunity for new learnings, but on the other hand will lead to new challenges of cultural differences between the members of the project team. A major change brought about by Industry 4.0 will be in team composition, which will have a direct impact on individual team members and their mutual interactions (Marnewick and Marnewick, 2019). Future, virtual project teams will comprise two or more team members, both human and nonhuman, such as robots and smart machines. This will result in collective intelligence of both humans and computers. Robots will perform the repetitive tasks and the role of human staff will be concentrated on the creative, planning, non-repetitive aspects of the project. Such role revisions will lead to the disappearance of some professions and the evolution of new ones to change the team composition (Marnewick and Marnewick, 2021). The technical skills and competencies of team members will become important to manage emerging technologies such as AI and robotics. Effective training of the virtual teams can be performed using gamification or augmented reality. Furthermore, the flexibility of the project team will be enhanced with respect to response to work schedule, customer requirements, ability, and changes in the project environment. Ribeiro et al. (2021) stated that in the Industry 4.0 context, the traditional hierarchical organizational structure will be progressively altered to a flat structure wherein project team members will be independent professional figures full of creativity and freedom. At the end of the day, irrespective of the team’s composition, teams should be agile as this provides them with the capability to adjust their way of thinking and working. Teams should also be ahead of the learning curve and apply new skills and knowledge in order to function optimally in Industry 4.0.

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4.

DISCUSSION AND FUTURE AREAS OF RESEARCH

Agility has become an important dimension for organizational survival and thriving strategy. As Denning (2016) suggests, “agile management is now a vast global movement that is transforming the world of work. Most remarkably, the five largest organizations on the planet in terms of market capitalization—Amazon, Apple, Facebook, Google and Microsoft—are recognizably agile”. These organizations balance dynamism and adaptability, are nonlinear and organic, and are quick to adapt to change in a dynamic and unpredictable environment. Burgeoning interest in agile human resource (HR) and the implications of Industry 4.0 on HR mirrors a global trend toward new HR practices. The online publication of the Agile HR Manifesto with over 300 signatories (https://​www​.agilehrmanifesto​.org) is an indication of increasing interest in developing agile HR. However, while there is accelerating interest and relevance in the industry with regards to agile HR, scholarly research on individuals and team behavior-related issues of Industry 4.0 implementation with agile context implementation is sparse, fragmented, and therefore a possible area of future investigation (McMackin and Heffernan, 2021). For future research, we propose the need to undertake focused investigations of the micro, meso, and macro aspects of agile teams under the fourth industrial revolution. We elaborate these thoughts in the following paragraphs. Micro Level A possible area of intervention by studies in the future could be examining the HRM value chain in the context of agile projects in the fourth industrial revolution by using the ability–motivation–opportunity (AMO) model (Appelbaum et al., 2000). According to this model, in the HRM system there are three directions that are concomitantly worked on: ability, which facilitates employees’ knowledge, skills, and abilities (KSA); motivation factors (motivation-enhancing dimension); and extending working opportunities (opportunity-enhancing dimension) (Appelbaum, Bailey, Berg and Kalleberg, 2000; Boxall and Macky, 2009; Jiang, Lepak, Hu and Baer, 2012). The option of new Industry 4.0 technologies using agile teams can be well supported by the three AMO dimensions by creating synergies across the value chain. Traditional and agile organizations are fundamentally different in the way they approach and solve business problems. Understandably, therefore, the expectations from individuals as well as their dispositions, knowledge, skill, and attitudes in an agile organization differ from those in a traditional organization. Employees in agile teams are expected to have stronger tolerance to ambiguity and risk tolerance as well as planning and self-drive and organizing capabilities (Crowder and Friess, 2015). Employees in the Industry 4.0 context are required to have hard-core technical competencies. A possible area that needs intervention could be exploring best cases used for selecting or training the right people or talent (or both) in agile project teams. Extensions of this study may include training, compensation, and career development aspects of teams. Meso Level Agile teams: Organizations are making focused efforts to develop their products using agile methods (Stavru, 2014). Learning in agile teams is an iterative process and employees

262  Research handbook on project performance work cross-functionally to achieve common goals. Using agile principles, the teams work on specific projects and have high-quality deliverables. Typically, they take one project at a time. Even though an increasing number of organizations strive to implement agile teams, efforts need to be made to examine strategies of organizations transitioning from bureaucratic systems to agile (Moe et al., 2010; Nerur, Mahapatra and Mangalaraj, 2005). The interpersonal relationships and dynamics of an agile team could be unique. For instance, Project Aristotle of Google found team trust and psychological safety to be critical aspects for productivity among agile teams. Examining the process for creating trust and psychological safety in teams could be a promising area of future investigations. Macro Level Agile leadership: For any project success, leadership plays a key role. Transitioning from traditional to agile organizations may involve a new organizational flat hierarchy and empower teams. Examining the right leadership skills and styles could be an important area of investigation. We also need to investigate the nature of leadership in agile organizations from the perspective of professionals who identify as agile leaders. What does this new way of working require of leaders? There are a few essential leadership questions that need to be delved into more deeply.

5. CONCLUSION In today’s era, project management has become one of the vital fields in evaluating the success of a project. However, the implementation of a project is a very complex process. It has become crucial to forgo traditional project management techniques and adopt modern tools and technologies due to the intense competition between companies to enhance the efficiency and productivity of their processes. To achieve this, it is essential to reduce the project risks involved and to make more in less time. Industry 4.0 is revolutionizing the traditional methods with advancements in technologies and automation. As shown in Table 18.1, Industry 4.0 technologies will impact all knowledge areas of project management and enhance the application of agile aspects. Simulation of project execution will lead to better project scope management and risk management. Continuous data collection will enable better project monitoring and control through earned value analysis. E-procurement platforms can enable smart contracts and smart sourcing. Robots and machines will become part of the project team, which will integrate digital communication and facilitate integration management. Overall, the trade-off of cost, quality, schedule, and scope faced by traditional project management will be overcome to a large extent by application of these technologies, leading to enhanced project performance.

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264  Research handbook on project performance Nerur, S., Mahapatra, R., & Mangalaraj, G. (2005). Challenges of migrating to agile methodologies. Communications of the ACM, 48(5), 72–78. Oztemel, E., & Gursev, S. (2020). Literature review of Industry 4.0 and related technologies. Journal of Intelligent Manufacturing, 31(1), 127–182. Parker, D. W., Holesgrove, M., & Pathak, R. (2015). Improving productivity with self-organised teams and agile leadership. International Journal of Productivity and Performance Management, 6(1), 112–128. Qin, J., Liu, Y., & Grosvenor, R. (2016). A categorical framework of manufacturing for Industry 4.0 and beyond. Procedia CIRP, 52, 173–178. Raji, I. O., & Rossi, T. (2019, October). Exploring Industry 4.0 technologies as drivers of lean and agile supply chain strategies. In Proceedings of the International Conference on Industrial Engineering and Operations Management, Toronto, ON, Canada (pp. 23–25). Rane, S. B., Potdar, P. R., & Rane, S. (2019). Development of project risk management framework based on Industry 4.0 technologies. Benchmarking: An International Journal, 28(5), 31. Ribeiro, A., Amaral, A., & Barros, T. (2021). Project manager competencies in the context of the Industry 4.0. Procedia Computer Science, 181, 803–810. Scholz, J. A., Sieckmann, F., & Kohl, H. (2020). Implementation with agile project management approaches: Case study of an Industry 4.0 learning factory in China. Procedia Manufacturing, 45, 234–239. Simion, C. P., Popa, S. C., & Albu, C. (2018, November). Project management 4.0: Project management in the digital era. In 12th International Management Conference. Editura ASE, Bucharest (pp. 93–100). Sony, M., & Naik, S. (2019). Key ingredients for evaluating Industry 4.0 readiness for organizations: A literature review. Benchmarking: An International Journal, 27(7), 2213–2232. Stavru, S. (2014). A critical examination of recent industrial surveys on agile method usage. Journal of Systems and Software, 94, 87–97. Thomas, R. J., Bellin, J., Jules, C., & Lynton, N. (2012). Global leadership teams: Diagnosing three essential qualities. Strategy Leadership, 40(3), 25–29. Yanık, S., & Işıklı, E. (2019). An ANP approach for prioritizing the agile project management criteria in Industry 4.0 transition. In Agile Approaches for Successfully Managing and Executing Projects in the Fourth Industrial Revolution (pp. 165–187). IGI Global. Zhong, R. Y., Xu, X., Klotz, E., & Newman, S. T. (2017). Intelligent manufacturing in the context of Industry 4.0: A review. Engineering, 3(5), 616–630.

19. Performance management in public–private partnership projects: a perspective from the Indian road sector Dhruv Agarwal, Sagar Deshmukh, and Ganesh Devkar

INTRODUCTION India is reported to have the second-largest road network in the world, with a total length of 62.16 lakh kilometres, comprising national highways/expressways, state highways, and other roads. India now has the global record for building 34 kilometres of national highways every day, with plans to increase this to more than 100 kilometres per day (Roads and Highways/ Make in India, 2022). India’s road sector has gradually improved connectivity between major cities, towns, and remote areas over the past few years. MoRTH (the Ministry of Road Transport and Highways) is responsible for the planning, development, and maintenance of India’s national highways. Until June 2020, MoRTH reportedly built only 1,681 kilometres of roadway, with a significant jump in the process in the following year, which resulted in the construction of 2,284 kilometres of national highways by June 2021, bringing the total length of road construction in India to 13,298 kilometres. This has led to an increase in compound annual growth rate of about 17% compared to that of 2016. The goal is to bring the total roadway in India to 65,000 kilometres by 2022 at a cost of Rs. 5.35 lakh crores, and 23 national highways by 2025 (IBEF, 2022). Formerly, public sector entities were solely responsible for the planning, design, construction, and operation of roads in India. The role of the private sector was confined only to the construction phase of road projects and in a fragmented manner. To incentivise the involvement of private sector in India, the government brought in the public–private partnership (PPP) model. This led to a huge boom in the industry with the emergence of the private sector as a key player. The PPP model introduced provisions like innovative technology, better risk distribution, superior quality of work, private investment, timesaving, and better operational efficiency. India has emerged as one of the largest road sectors that has embraced the PPP model. According to the PPP database of India, as of December 2019, the Government of India (GOI) had implemented a total of 1,824 PPP projects across different sectors and invested ₹2,495,539 crores for their execution and implementation. Of the 1,824 projects, 1,015 projects were in the transportation sector, and 1,824 in the road and bridges category. The GOI has, so far, invested a large share of ₹3,02,388 crores in national highway projects, the largest share within the transportation sector (Department of Economic Affairs, 2021). While the PPP model had a large footprint in terms of numbers of projects and quantum of investment, the performance of PPP road projects has been far from satisfactory. Several PPP road projects in India have run into issues like cost overrun, schedule overrun, land acquisition issues, and government clearance problems that have impeded project performance 265

266  Research handbook on project performance (Gopalkrishna & Karnam, 2015; Love et al., 2015). PPP research tends to focus on various topics, but there continues to be a gap in research in the evaluation of the performance of PPP projects in the road sector from a process life cycle perspective (Liu et al., 2018; Liu et al., 2015; Yuan et al., 2012). Past studies have evaluated project success, but they do not provide insights into the process involved (Yuan et al., 2012). Process evaluation is important for favourable outcomes, both at organisation level and project level. It helps control and improve all parts of a project life cycle as it proceeds, thereby enabling holistic performance evaluation of the project. Thus, process management is critical for the performance of a PPP project (Haponava & Al-Jibouri, 2012; Kagioglou et al., 2001). In the Indian context, there has been little research on measuring the performance of PPP projects pertaining to the road sector. This research develops a conceptual framework for analysing the performance of PPPs in road sector projects. It also analyses the present performance indicators used in road sector PPP projects and recommends areas for improvement. The following are the objectives of this study: (1) To identify the existing methods and parameters adopted for performance measurement of PPP road sector projects. (2) To arrive at the key performance measurement indicators. The scope of the study is entirely focused on road sector projects in India.

LITERATURE STUDY Several definitions of PPPs are available in the literature today. For example, the reference guide for PPP published by the World Bank, Asian Development Bank (ADB et al. 2014), defines PPPs as “A long-term contract between a private party and a government entity, for providing a public asset or service, in which the private party bears significant risk and management responsibility, and remuneration is linked to performance”. There are multiple definitions for the PPP model with the specifics changing across nations. There are various types of PPP models adopted in the road sector, such as BOT (Toll), BOT (Annuity), Hybrid Annuity Model (HAM), and Toll-Operate-Transfer (TOT). The benefits of PPPs include risk sharing, reducing public sector administrative costs, innovation, integrating the private sector’s knowledge, skills, and resources into construction and operating efficiencies, and boosting service quality (DEA, 2016; Yuan et al., 2009; Zhang, 2006). The complex long-term contract among PPP participants makes it different from the traditional infrastructure delivery system. In the past few decades, PPP research has focused on topics like (1) critical success factors (CSFs), (2) efficiency/effectiveness of project implementation, (3) risk management, (4) concessionaire selection, (5) roles and responsibilities of the government sector, and (6) PPP finance. However, there has been a paucity in research to assess the PPP project’s success from a process life cycle perspective (Liu et al., 2018; Liu et al., 2015; Yuan et al., 2012).

Performance management in public–private partnership projects  267 Background of Performance Measurement Performance measurement is a process of evaluating the effectiveness and efficiency of the steps followed to achieve the objective of the project, organisation, or stakeholder (Yang et al., 2010). It is a challenging process as it involves high risk and financial commitments from the private sector, long-term concession periods, and multiple stakeholder involvement. Without performance measurements, the project would produce sub-optimal service quality. Various performance measurement frameworks have been proposed by researchers. One of the most frequently used performance assessment frameworks was the balanced scorecard introduced by Kaplan and Norton (1992). Its drawback was its inability to measure performance against multiple stakeholders’ environments (Neely et al., 2001). Neely et al. (2001) introduced a new system called performance prism that focuses on five facets, viz., stakeholder satisfaction, strategies, processes, capabilities, and stakeholder contribution, all of which are inter-linked. This framework was criticised for its complexity in the implementation process and its focus only on the product, which leads to unsuitability to process improvement. A new framework – the key performance indicator (KPI) system – was then proposed by Liu et al. (2015), which enabled performance measurement of projects throughout their life cycles. This framework evaluates the process in terms of effectiveness and efficiency to achieve project objectives. KPIs can include both quantitative and qualitative indicators of performance evaluation. They are not the direct measures of performance evaluation but are targets or milestones that alert the user about the progress of the process. Performance measures are defined to quantify and understand the outcomes of the indicator. Project performance can only be measured if the key indicators and performance measures are defined and monitored (Villalba-Romero & Liyanage, 2016; FHWA, 2011). Performance Evaluation in the Execution Phase In project management, the performance of a construction project is traditionally measured using the iron triangle factors of time, cost, and quality, while the measurement of the operation and maintenance phase is based on KPIs defined by the stakeholders. (Villalba-Romero & Liyanage, 2016; Liu et al., 2015). Kagioglou et al. (2001) argued that the traditional performance measurement systems (PMSs) are insufficient to assess project success. In order to get a bigger picture, various other indicators of project success such as health and safety, profitability, technical performance, financial performance, productivity, environmental sustainability, stakeholder satisfaction, project duration, dispute resolution, transfer of technology, material management, etc. were proposed in various studies conducted from the project perspective (Ali et al., 2013; Chan & Chan, 2004; Cox et al., 2003; Luu et al., 2008; Radujković et al., 2010; Tripathi & Jha, 2018). All of the above-mentioned indicators focus on the construction phases of the project and evaluate based on product perspective. The productive perspective means the outcome of the construction project. This means that all the frameworks are designed to evaluate the project’s performance at the end. This product-oriented evaluation cannot provide insights into the performance of the processes carried out (Liu et al., 2015). Researchers felt that process-based evaluation is ideal as product-oriented evaluation cannot help project managers in improving the implementation process. Therefore, a new framework is required that can evaluate the dynamic life cycle of a project in a process-oriented perspective.

268  Research handbook on project performance Performance Evaluation of PPP Projects Evaluating PPP projects is a complex process because of its dynamic nature, long-term contractual agreement, and multiple stakeholder involvement over the project life cycle. Yuan et al. (2009) proposed a unique KPI framework for PPP projects, in which indicators can be used to evaluate the project’s performance based on five components, namely: (1) project’s physical characteristics, (2) innovation and learning indicators, (3) process indicators, (4) financing and marketing indicators, and (5) stakeholder indicators. Several shortcomings were identified in the framework, such as a disagreement between the aims of various stakeholders. Therefore, Yuan et al. conducted another study (2012) and analysed the framework using the Confirmatory Factor Analysis (CFA) model to check the relationships between the performance indicators and performance packages. Cong and Ma (2018) developed a measurement system based on the 4E theory (Efficiency, Economic, Effectiveness, Equity) and used the Ordered Weighted Averaging (OWA) model to rank the identified indicators. Hossain et al. (2019) determined the performance indicators and weighted them using the Analytical Hierarchical Process (AHP). These systems followed the product evaluation process perspective. Performance Evaluation of PPP Road Projects Villalba-Romero and Liyanage (2016) created a step-by-step PMS for PPP road projects, which included nine KPIs and 29 performance measures derived from Qualitative Content Analysis (QCA). Direct scoring approach and weighing scoring assessment approach were used for evaluation. The National Highway Authority of India (NHAI) has developed a vendor PMS to monitor the performance of various stakeholders/vendors in NHAI projects (CW Construction World, 2020). The aim is to generate a transparent and comprehensive performance rating system for its stakeholders (consultants, contractors, etc.). Based on this system, vendors are rated after multi-level reviews. Suitable amendments would be made in the contract documents to incorporate the ratings of vendors as one of the qualification criteria. This is aimed at achieving higher accountability of vendors and thereby improved quality of highways. Evaluation from a Process Life cycle Perspective All the studies mentioned in the above sections evaluate the PPP project’s life cycle performance at the end of the project, which is a product-oriented way of evaluation. Liu et al. (2015) challenged this mode of evaluation because of its focus on the product alone, which results in a myopic viewpoint to the project itself. It ignores the process involved in the development of the PPP project. Process life cycle performance measurements, on the other hand, evaluate each phase/stage of the PPP project and can address the concerns and opinions of all stakeholders involved across the entire project life cycle. Liu et al. (2015) developed a KPI framework using the performance prism system. The KPIs in this framework were categorised into three phases, namely (1) initiation and planning, (2) procurement, and (3) partnership. This framework was refined by including five evaluation nodes in the PPP project life cycle opposed to the two evaluation nodes that were conventionally used, to effectively and efficiently control the projects deployment process. The nodes were at the start of the initiation

Performance management in public–private partnership projects  269 phase, between the pre-tendering and bidding phases, the contract and design phases, the end of the execution phase, and the end of maintenance and handover phases. Budayan et al. (2020) developed a conceptual life cycle PMS based on stage-level KPIs for performance measurement of BOT projects in Turkey. This study suggests that the stage-level KPIs must be used instead of phase-level KPIs for performance measurement because in phase-level evaluation, parties must deal with many KPIs, which could be a cumbersome process. It also suggests that KPIs must be measured and reported regularly for continuous improvement. All the studies mentioned above have looked at KPIs from a life cycle perspective but with different strategies; they have proposed performance evaluations based on phase-level KPIs. This strategy focused on phase evaluation and overlooked the performance of stages. The evaluation of multiple stages must be performed at the end of each phase, which could be difficult as measuring, monitoring, and analysing multiple KPIs would require extra resources.

RESEARCH METHODOLOGY For this research, a mixed-method approach was adopted wherein both qualitative and quantitative data were collected to establish a problem-centred knowledge claim. The effective definition of the research problem entails collecting data both simultaneously and sequentially. Of the four knowledge claim areas, viz., postpositivism, constructivism, advocacy/ participatory and pragmatism, pragmatism was used for this research as it allows a choice of multiple methods, techniques, and procedures. Three methods were finalised for data collection: semi-structured interviews, questionnaire survey, and case study, which were chosen to achieve the research objective. The flowchart in Figure 19.1 presents a snapshot of the research methodology.

Figure 19.1

Research methodology flowchart

270  Research handbook on project performance

DATA COLLECTION Identifying the Key Performance Indicators The performance evaluation framework for PPP projects was drawn by identifying potential KPIs from various literature. The literature referred were related to stage-wise evaluation and phase-wise evaluation frameworks for PPP projects. A few studies have focused on the process life cycle perspective for PPP road projects (Villalba-Romero & Liyanage, 2016). Along with this, best practice guidelines for performance measurement for PPP projects have been reported (Budayan et al., 2020; Cong & Ma, 2018; Villalba-Romero & Liyanage, 2016; FHWA, 2011; Hossain et al., 2019; Liu et al., 2018; Liu et al., 2015, 2016; Love et al., 2015; Mladenovic et al., 2013; Okudan et al., 2020; PPP Cell DEA, 2015; PPP Toolkit, 2011; Yuan et al., 2009, 2012). After identification of all KPIs, the first step was to list them and categorise them into six different project life cycle stages. A total of 168 KPIs were identified, and they were divided into six stages, namely (1) feasibility stage, (2) PPP preparation stage, (3) evaluation and award stage, (4) design stage, (5) construction stage, and (6) operation and maintenance stage (PPP Toolkit, 2011). Similar KPIs were grouped and rephrased. Finally, a list of 65 KPIs was prepared that covered the entire project process life cycle. Semi-Structured Interviews Semi-structured interviews were conducted to face-validate the identified KPIs and to understand the current system followed in India for performance evaluation of road sector PPP projects. The interview questions for the interaction with experts were developed based on the understanding of literature reviews. The questions were aimed at understanding the performance of road sector projects in India, validity of KPIs, areas of improvement in performance measurement, projects that suffered from lack of performance measurement, and the main challenges in projects and difficulties in implementing the performance measurement framework. The experts interviewed included government and private sector officials with more than 15 years of experience working on PPP road projects. Eight interviews were conducted through in-person meetings or Google Meet. Each interview lasted from 45 minutes to 90 minutes. This helped in understanding the industry perspective on the performance evaluation. Questionnaire Survey After completion of the face-validation process, based on the expert’s recommendations, the list of KPIs was updated. For further content validation of the KPIs, a questionnaire survey was conducted. In this, the respondent was asked to rate the KPIs based on a Likert scale of 1 to 4, depending upon the degree of relevance as per their perspective in PPP road projects. According to Yusoff (2019), the minimum number of experts for content validation should be six and not exceed ten. The criteria for selecting experts were (1) the respondents must have managerial experience in BOT road projects, (2) they must be working with clients, consultants, or contracting firms, and (3) they must have a minimum of 10 years of experience in PPP road projects. The questionnaire was shared with ten experts fulfilling the criteria and six responses were received in the given time.

Performance management in public–private partnership projects  271 The second round of questionnaire-based survey was conducted after validating the list of KPIs. The second round was conducted to understand the relative significance of each KPI. The respondents were asked to rate the KPIs based on a Likert scale 1 to 5 depending upon the degree of importance of each KPI. They were asked to highlight the KPIs that they thought needed to be monitored continuously throughout the project stages. The questionnaire was sent to 130 people working in various government, consulting, and contracting firms working on PPP road projects. A total of 47 responses were received with the response rate of 36%. A similar survey was conducted by Yuan et al. (2012), who obtained a response rate of 13.02%. The respondents had different years of experience: 19% of respondents had five years of experience, 9% of respondents had 5–10 years of experience, 19% of respondents had 11–15 years of experience, 21% of respondents had 16–20 years of experience, and a maximum 32% of respondents had more than 20 years of experience. Case Studies Case study analysis aims to shed light on a decision or a group of decisions, including why they were made, how they were made, how they were implemented, and the outcomes (Yin, 2009). Cross-case analysis helps elucidate the similarities and differences in the actions, events, and processes for different case studies. Here cross-case analysis was conducted to understand the project performance and to identify the evidence for each indicator and comparing the three PPP projects. Actual challenges faced in each project were identified by conducting interviews with project stakeholders and studying the case study reports available on public portals. Elaborate data collection was done for all the three case studies and an overview of them is given in Table 19A.1.

DATA ANALYSIS AND RESULTS Data analysis was done to interpret the data collected to achieve the research objective. Semi-Structured Interviews Currently, there is no clear framework to evaluate the performance of PPP road projects from a process life cycle perspective. Available frameworks focus only on the project’s construction phase or operation and maintenance phase or from stakeholder perspective. Performance monitoring is done based on the set guidelines or parameters mentioned by the client in the contract document. Eight interviews were conducted with the experts. The most important parameters that directly impact the performance of the project were identified as (1) land acquisition, (2) permits and approvals, (3) financial modelling, (4) public support, (5) traffic projections, (6) contractor’s technical experience, (7) contractor’s financial capacity, and (8) the project management parameters included cost, time, quality, risk, etc. During the semi-structured interviews, the experts reviewed the identified KPIs list and suggested that a few KPIs were not directly linked to the performance of the project, and were irrelevant in the Indian context. A total of 20 KPIs were removed from the list of 65 KPIs. The list of eliminated KPIs is shown in Table 19.1.

272  Research handbook on project performance Table 19.1

List of eliminated KPIs

Sr. no.

Project stage

Eliminated KPIs

1

Feasibility stage

Stable and favourable legal environment

2 3

Comprehensiveness of feasibility study PPP preparation stage

Innovation for strategic planning and process design

4

Contract with enough flexibility

5

Appropriateness of tender stages with terms and conditions

6 7

Appropriateness of timeline of tender procedure Evaluation and award stage

Private contractors’ willingness to participate in the project

8

Shareholders’ willingness to participate in the project

9

Creditors’ willingness to participate in the project

10 11

Appropriateness of negotiation framework Construction stage

Subcontractors’ performance

12

Vendors’ performance

13

Environmental safety

14

Prime contractor’s satisfaction

15

Subcontractors’ satisfaction

16

Vendors’ satisfaction

17

Relationship among stakeholders

18

Effective communication and responsiveness

19

Operation and maintenance

Health and safety management

20

stage

Creditor’s satisfaction

A total of 46 KPIs were finalised after eliminating the above-mentioned indicators through a face-validation process. Content Validity Analysis The content validity process was conducted to check the degree of relevance of each item concerning the framework. Based on the received responses, the content validity index (CVI) values were calculated (Yusoff, 2019). There are two forms of CVI values: item content validity index (I-CVI) and scale content validity index (S-CVI). Based on the calculations, the CVI values should be equal to or greater than 0.83 for six responses as recommended by Yusoff (2019). All KPIs with CVI values above 0.83 were accepted, except three KPIs, of which two KPIs had a CVI value of 0.67 and one KPI had a CVI value of 0.50. These three KPIs were eliminated from the performance evaluation framework. The eliminated KPIs were political stability, interface management, and end-user satisfaction. This gave a final conceptual framework of 43 KPIs responsible for performance evaluation, which is shown in Table 19A.2. Ranking of Key Performance Indicators After the finalisation of the conceptual framework, a second round of questionnaire surveys was conducted to understand the relative importance of the indicators. The data collected from questionnaire surveys was tested for internal consistency and the ranks of the most important indicators were identified using the relative importance index (RII) method.

Performance management in public–private partnership projects  273 Reliability test A reliability test was performed to determine internal consistency. For this study, Cronbach’s alpha technique was used (Saunders et al., 2007). The Cronbach alpha coefficient for this study was 0.85, which indicates very good reliability of the data variable (Chawla & Sondhi, 2011). Relative Importance Index (RII) The data collected was analysed using the RII as reported in El-Sawalhi and Hammad (2015) and Pandit et al. (2015). The KPIs identified in this study had varying degrees of influence on the performance measures of the PPP road projects. Therefore, the RII of each KPI was calculated based on the following formula: RII 

W 1n1 2n 2  3n3 4n4  5n5  AxN 5N

where ∑W = total weightage given to each element by the respondents, and varied from 1 to 5 (n1, n2, n3, n4, n5 = Likert scale response rating); A = highest weightage, N = total number of respondents. The higher value of RII indicates a higher importance of KPI towards the project performance evaluation. Ranks were considered based on the priority basis. Standard deviation was used to rank the indicators with the same RII values. The lower the standard deviation value, the stronger was the consistency of the respondents. Yuan et al. (2012) used mean and standard deviation to rank the variables in their study. Table 19A.2 shows the ranking of KPIs. Case Study Analysis Case study analysis was conducted to understand the concept of performance evaluation for the selected case studies of PPP road projects. The challenges faced in each project were identified by conducting interviews with project stakeholders and studying the case study reports available in public portals. This study used a case study comparison of highway projects developed under the BOT model. The projects were selected such that they had all completed construction stages and were in operation and maintenance stages for at least 5–6 years. The evidence for these case studies was collected from multiple secondary sources like feasibility study, environmental clearance report, and interviews conducted with stakeholders associated with the project such as officials from the client organisation, independent engineer, concessionaire, and consultants. These interviews helped in documenting their experience and challenges they faced during implementation. Based on the interviews and secondary data, the stories for all case studies were prepared and are presented in the following section. This research compared three BOT road sector projects and mapped the evidence for each KPI. Cross-Case Analysis Cross-case analysis gives a comparative view of evidence with respect to each KPI. The evidence for case studies was tabulated for each indicator, showing the overview of evidence indicators for each case study along with the ranks obtained from RII analysis.

274  Research handbook on project performance The stages considered for PPP project life cycle were feasibility stage, PPP preparation stage, evaluation and award stage, design stage, construction stage, and operation and maintenance stage. The case study evidence with regards to the 43 KPIs is discussed with reference to these stages. Feasibility Stage This stage comprised ten KPIs to comprehensively analyse the processes. Technical feasibility, financial feasibility, and environmental study were evidenced in all the three case studies as the client engaged feasibility consultants to perform these studies. All three case projects were technically feasible, whereas in terms of financial feasibility, only cases A and B were viable based on traffic modelling, but case C was not viable as per analysis because of low traffic demand, therefore it was proposed to be implemented on a viability gap funding scheme under the BOT model. Environmental studies for all three cases were successfully done and the best suitable alignments were chosen in each case, such that there was the least environmental impact. In case C, major multiple bypasses were proposed to avoid any resettlement. In terms of project needs and desired outcomes, cases A and B were part of a master infrastructure plan proposed by the relevant state government, whereas case C was proposed under the state hsighway project scheme. All three cases aimed at upgrading existing two-lane to four-lane toll roads. Economic study was effectively conducted for cases B and C, whereas no evidence was found for case A. Evidence for permits, approvals, and land acquisition for all three cases clearly shows that the required processes were carried out efficiently but, in case A, there were issues related to land acquisition because the local public were against the development of the road as they were expecting huge returns for their land parcels. The value for money assessment and client’s expertise in PPP projects was successfully evidenced. An effective risk management plan is one of the most important indicators in this stage as per the RII analysis. Various risks were not addressed in the case studies, which impacted the performances of the projects. In case B, risks related to design, approvals, policy, and revenue were not clearly predicted and were not allocated to appropriate partners. Case C lacked in predicting risk related to policy change and the development of alternative routes and traffic-related risk was not considered effectively in cases A and B. PPP Preparation Stage This stage consisted of indicators related to governance framework, procurement innovation, preparation of detailed contract document, suitability of concession period, and deciding the criteria for selecting concessionaire. For all three cases, the selection criteria for procurement of concessionaire were important. For cases A and B, the selection criteria were the lowest price offered by the bidder, whereas for case C, the bidding parameter was to quote the minimum grant or highest premium for a fixed concession period and fixed user fees. The contract document was prepared as per the standards; i.e., Asian Development Bank and World Bank guidelines for all three case studies. The concession agreement for cases A and B was used as a model agreement for other projects. It was evident that the suitability of concession period is important as the concession period for all three cases fell within the limits of World Bank guidelines, which is less than 30 years. Evidence regarding the procurement innovation

Performance management in public–private partnership projects  275 was strongly witnessed in cases A and B as these were the first projects that were implemented on the BOOT model and the case C project was proposed under the Viability Gap Funding (VGF) scheme. The governance framework for all three cases was properly established and the roles and responsibilities for all stakeholders were clearly defined. Evaluation and Award Stage All indicators in this phase were evidenced for all three case studies except realistic schedule of investment and revenue, effectiveness of financial close, and appropriateness of financing options. The concessionaire’s technical and financial proposal was evaluated as it is an important step to select any concessionaire. Evaluation was done as per the clauses mentioned in the contract document. Cases A and B were among the initial projects that were carried out under PPP mode and hence the concessionaire had no prior experience of PPP projects, whereas in case C, the concessionaire gained sufficient experience to execute the project successfully. In terms of transparency and competitive tendering procedure, very few private players participated in the bidding process for the selection of the concessionaire, which shows poor competitiveness. In case C, only three players participated in the bidding process for selection of the concessionaire. The indicator related to appropriateness of toll tariffs was evidenced in all three cases; the toll tariff was calculated based on the fixed formula recommended by the ministry and inflation was considered based on the Whole Price Index (WPI). Design Stage No evidence was obtained for KPIs like technology transfer ability, technology innovation, and design management. In this stage, much importance was given to design quality as per RII analysis and necessary measures were taken to maintain quality. For example, in case A, the Engineering, Procurement and Construction (EPC) contractor proposed an alternative design to reduce the cost, which the Special Purpose Vehicle (SPV) overruled because of quality issues. Construction Stage The construction stage had ten KPIs to monitor the construction process. An independent engineer was appointed in all three case studies, which helped monitor the cost, time, quality, contractor’s performance, and Environment, Health and Safety (EHS) standards for the project. In terms of the contractor’s performance, an independent engineer supervised the contractor’s performance for all cases. In case A, it was observed that the contractor assigned a part of work to the subcontractor, which was against the contractual conditions. During the execution, the subcontractor damaged the utility lines and affected the project performance. The independent engineer was responsible for supervision of the work, and he identified this issue followed by resolution of the same, which shows that the contractor’s performance was monitored. It was also seen that cost and time management was done properly in cases A and B as projects were finished within the time limit and budget. In case A, the project was estimated to be completed in 39 months whereas it was finished in 31 months, 8 months ahead of schedule. For case C, only minor time delays were identified. In terms of quality, no major issues were encountered in any case study. Similarly, no major issues were recorded related to EHS expect

276  Research handbook on project performance Table 19.2

Suggestions

Sr. no

KPI

Suggestions

1

Financial

Financial models failed due to inaccurate traffic projections. A third-party organisation or expert

feasibility

institute is suggested to be appointed for vetting the consultant’s feasibility studies.

2

Risk management

It is recommended that the risk management strategy be developed during the project’s inception phase, emphasising risk linked to traffic forecasts, design, approvals, policy changes, revenue model, and alternative route development.

3

Land acquisition

100% of the land acquisition process must be completed during the feasibility stage. Contractor must be hired only after land acquisition process is completed effectively. Public consultation must be conducted in advance to avoid any hassle during execution works.

4

Contractor’s

Usually, the prime contractor sublets work to a subcontractor. In some cases, the subcontractor

performance

is not qualified enough to execute the job. To overcome this issue, there must be provision of

End-user’s

It is suggested to have an in-depth public conversation to know the requirements of the end-users

willingness to

and avoid any difficulty in future. Processes related to land acquisition must be initiated prior to the

support the project

award of contract.

a third-party agency to monitor the overall performance of the project. 5

in case A where clearances related to tree cutting were encountered. This shows the proper management of quality and EHS standards by the independent engineer in all three cases. No evidence was found for KPIs like contract management, resource management, advance technology, and equipment for the construction process. Strong evidence was obtained for the end-user’s willingness to support the project. In case A, locals were against the development of the project as they were expecting large returns in exchange for their properties, which was then resolved by paying them the demanded returns, whereas in cases B and C the local public were supportive and their issues were also taken into consideration. Operation and Maintenance Stage Currently all projects are in the operations stage and each case faces issues related to project profitability. During the initial years of operations, projects faced issues related to insufficient traffic, which impacted revenue collection. Cases A and B suffered because of the service road proposed along the highway. In case C, a major drop was seen because of the proposal of upgradation of an alternative highway, which resulted in traffic shift. This impacted the project profitability and operational efficiency. After the construction of the asset, the client was satisfied with the quality of work delivered. However, client satisfaction is also linked to user satisfaction, and it was analysed based on user experience, travel time, etc. No evidence was obtained for indicators like effective cost management, time management, transfer management, and asset condition monitoring. Based on the above observations, the suggestions in Table 19.2 are made to overcome such problems in the future.

CONCLUSION This research identified the KPIs responsible for the success of a project. Through a literature review, a list of 168 indicators were identified. Similar factors were merged and categorised into six different stages of PPP projects and 65 KPIs were finalised.

Performance management in public–private partnership projects  277 To validate the identified indicators, face validation and content validity analysis were performed. In face validation, semi-structured interviews were conducted to understand the suitability of the 65 KPIs in the Indian context. Based on expert opinions, a few KPIs were rephrased and 20 KPIs were eliminated. A conceptual framework of 46 KPIs was finalised during expert discussions. Further, the recommended indicators were tested using a questionnaire survey to check the relevance of the indicators. The data obtained from this survey was tested by content validity analysis. In this analysis, CVI values were calculated for all the indicators. As per the analysis, all the indicators were valid except three indicators that showed CVI values less than 0.83, leading to direct elimination. This validation process gave a final framework for performance evaluation with 43 KPIs categorised into six different stages. After the finalisation of the conceptual framework, a second round of questionnaire surveys was conducted to understand the importance of indicators. The RII method was used to determine the ranking of the indicators. Later, cross-case analysis was carried out to understand the overall performance for different projects. Evidence was obtained as per the framework for each case study. From case studies, it was seen that each project faced multiple challenges during the implementation. Suggestions are provided to overcome such challenges in future projects. This research helped in formulating a conceptual framework for performance evaluation of PPP projects and it was validated by all the domain experts working in government and private sectors. This framework helps the various stakeholders involved in a PPP project, such as the government body, concessionaire, contractors, independent engineers, consultants, facility managers, etc., keep track of the KPIs and monitor project performance with respect to the KPIs to prevent problems and bottlenecks. Table 19A.1 shows the framework. Some of the identified limitations of the study are as follows. In the cross-case analysis, only three case studies were taken up for analysis because of time restrictions. Evidence for the cross-case analysis was not collected effectively because of insufficient contacts. Data collection issues arose due to the changes in multiple stakeholders, transference of officials to other projects, and poor sharing of information due to confidentiality clauses. The future scope of the research is to develop this framework further by identifying the performance measures and designing a rating scale to evaluate these KPIs for PPP road projects. More case studies and evidence can be obtained for cross-case analysis.

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280  Research handbook on project performance

APPENDIX Table 19A.1

Project details

Project details

Case A

Case B

Case C

Project authority

Provincial public authority

Provincial public authority

Provincial public authority

Type of PPP contract

Build Own Operate Transfer

Build Own Operate Transfer

Build Operate Transfer (BOT)

(BOOT)

(BOOT)

Concession period

30 years

Project cost (as per agreement) 306.00 crores

30 years

20 years

175 crores

498.81 crores

Project cost (actual)

342.24 crores

160.83 crores

1,422.00 crores

Length of project

53.0 KM

32.0 KM

173.0 KM

Signing of concession

12 May 1999

17 October 1998

17 September 2008

March 1999

–

15 September 2000

30 April 2012

agreement Commencement of construction May 2000 work Completion of construction

20 November 2002

work Commercial operation date

20 February 2003

24 October 2000

26 June 2012

Current status

Operation and maintenance

Operation and maintenance

Operation and maintenance

stage

stage

stage

analysis)

approvals

Land acquisition

Permits and

KPI 9 4

in PPP projects

Client’s expertise

management plan

Effective risk

assessment

Value for money

feasibility

Economic

impact analysis

Environmental

desired outcomes

Project needs and

feasibility

Financial

KPI 1 15

KPI 8 39

KPI 7 6

KPI 6 12

KPI 5 26

KPI 4 29

KPI 3 3

KPI 2 3

and maintainability

constructability

(including project

feasibility

P

P

P

P

P

X

P

P

P

P

P

P

P

P

P

P

P

P

P

P

P

P

P

P

P

P

P

P

P

P

   

 

Y

 

 

Y

 

 

Y

 

Y

 

 

Y

 

 

Y

 

 

Y

 

 

 

 

Y

Y

 

 

 

 

Y

Y

Y

Y

Y

 

Y

 

 

 

 

 

 

 

 

Y

 

 

 

Y

 

Y

Y

Y

 

 

 

 

Y

 

Y

Y

Y

 

Y

 

 

 

Y

 

Y

Y

Y

 

Y

Y

(2016) Y

Y

Technical

 

 

 

 

 

 

 

 

 

 

 

 

 

Y

Y

 

 

Y

 

 

 

 

Y

Y

Y

 

Y

Y

Y

Y

 

 

 

 

 

 

 

 

 

 

(2015)

 

 

 

 

 

 

 

 

 

 

 

Y

 

 

 

 

Y

 

 

 

(2011)

Toolkit

DEA

(2020)

(2019)

Y

KPI 1 1

(2018)

Liyanage

(2018)

et al.

(2016)

(2015)

and

(2015)

(2012)

(2009)

3

2

(2011)

1

PPP

FHWA

Cell

et al.

and Ma et al.

Liu

et al.

et al.

Romero

et al. (2013) et al.

et al.

et al.

Study

Study

Hossain Okudan PPP

Cong

H. J.

J. Liu

Villalba- J. Liu

Mladenovic Love

Yuan

Yuan

Case

Case

Study

Literatures

Case

Cross-case analysis

1

Rank KPIs

Framework with KPIs, rankings, evidence, and literature references

Stage Rank Feasibility stage

no.

Sr.

Table 19A.2

Performance management in public–private partnership projects  281

18

KPI

17

KPI

23

18

technical proposal

concessionaires’

Evaluation of

procedure

tendering

and competitive

Transparent

PPPs

knowledge of

Concessionaire’s

KPI

34

award stage

3

16

Evaluation and

Stage  

concessionaire

selecting

Criteria for

15

KPI

9

specifications

Suitability of

concession period

16

14

KPI

technical, financial

draft with

Detailed contract

2

KPI

13

innovation

Procurement

41

12

KPI

Governance

KPI

framework

stage

11

PPP preparation

2

38

Rank KPIs

Stage  

no.

Sr.

P

P

P

 

P

P

P

P

P

 

P

P

P

 

P

P

P

P

P

 

P

P

P

 

P

P

P

P

P

 

Cross-case analysis

 

Y

Y

 

 

Y

 

 

 

 

 

Y

Y

 

 

Y

 

 

 

 

Literatures

 

Y

Y

 

 

 

 

 

 

 

 

 

 

 

Y

Y

 

 

 

 

 

Y

 

 

 

 

Y

 

 

 

 

 

 

 

Y

Y

 

Y

Y

 

 

 

 

 

Y

Y

 

Y

Y

 

 

 

 

 

Y

Y

 

Y

 

 

 

 

 

 

 

 

 

 

 

 

 

Y

Y

 

Y

 

 

 

 

 

 

Y

Y

 

Y

Y

Y

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

282  Research handbook on project performance

13

5

Stage  

Construction stage

skill

management and

Prominent design

24

KPI

27

innovation

26

Technology

Technology

quality)

process (design

KPI

4

Proper design and

efficient design

transfer ability

43

7

Design stage

revenue

of investment and

25

KPI

24

KPI

4

Stage  

23

Realistic schedule

Effectiveness of

KPI

33

adjustment

 

X

X

X

P

 

X

X

Appropriateness of P financing options

financial close

22

27

22

KPI

21

KPI

P

 

X

X

X

P

 

X

X

P

P

P

 

X

X

X

P

 

X

X

P

P

P

Cross-case analysis

Appropriateness of P tariff/tolls or price

financial proposal

concessionaires’

Evaluation of

Rank KPIs

KPI 2 32

19

KPI

no.

Sr.

 

Y

Y

Y

 

 

Y

 

 

 

 

 

Y

Y

Y

 

 

Y

 

 

 

 

Literatures

 

 

Y

 

 

 

 

 

 

 

 

 

 

 

 

Y

 

 

 

Y

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Y

Y

Y

 

 

Y

Y

 

 

 

 

Y

Y

Y

 

 

Y

Y

 

 

 

 

Y

Y

Y

 

 

Y

Y

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Y

 

 

 

 

 

Y

Y

Y

 

Y

Y

 

 

 

 

 

 

 

Y

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Y

 

 

 

Performance management in public–private partnership projects  283

process

maintenance stage

6

support the project

willingness to

End-users’

Operation and

36

Stage  

36

KPI

construction

equipment for

technology and

Advance

42

KPI

35

management

Effective resource

34

KPI

31

management

Effective contract

management

21

health, and safety

environmental,

33

KPI

35

Effective

32

KPI

Effective time

management

1

management

Effective cost

management

quality control

31

KPI

KPI 3 11

5

Effective

29

KPI

Contractor’s

performance

8

Rank KPIs

28

KPI

no.

Sr.

 

P

X

P

P

P

P

P

P

P

 

P

X

X

X

P

P

P

P

P

 

P

X

X

X

P

P

P

P

P

Cross-case analysis

 

 

Y

Y

Y

 

Y

Y

Y

 

 

 

Y

Y

Y

 

Y

Y

Y

 

Literatures

 

 

 

 

 

 

Y

 

 

 

 

 

 

 

Y

 

Y

Y

 

 

 

 

 

 

 

 

Y

Y

 

 

 

 

Y

 

Y

 

Y

Y

Y

Y

 

 

Y

 

Y

 

Y

Y

Y

Y

 

 

Y

 

Y

 

Y

Y

Y

Y

 

 

 

 

 

 

Y

Y

Y

 

 

 

 

 

 

 

 

 

Y

 

 

 

 

Y

Y

 

Y

Y

Y

 

 

 

 

 

 

 

Y

 

Y

 

 

 

 

 

Y

 

Y

 

Y

 

 

 

 

 

 

 

Y

 

Y

 

284  Research handbook on project performance

maintenance

monitoring

Asset condition

17

KPI

43

management

Effective transfer

37

42

KPI

Project

profitability

19

41

KPI

management

Effective time

KPI 4 28

Effective cost

management

25

management and

39

KPI

14

Operations

38

KPI

Client’s

satisfaction

2

Rank KPIs

37

KPI

no.

Sr.

X

X

P

X

X

P

P

X

X

P

X

X

P

P

X

X

P

X

X

P

P

Cross-case analysis

Y

 

 

Y

Y

 

Y

Y

 

 

Y

Y

 

Y

Literatures

Y

 

 

Y

 

 

 

Y

 

 

Y

Y

Y

 

 

 

 

Y

Y

Y

 

 

 

 

Y

Y

Y

Y

 

 

 

Y

Y

Y

Y

 

 

 

Y

Y

Y

Y

 

 

 

Y

Y

 

Y

 

 

 

 

 

Y

Y

Y

 

 

Y

Y

Y

Y

 

 

 

Y

 

Y

 

 

 

 

Y

 

Y

Y

 

 

 

Y

 

Y

 

Performance management in public–private partnership projects  285

Index

Abdel-Alim, A. M.  92 Abd El-Karim, M. S. B. A.  92 ability–motivation–opportunity (AMO) model 261 absorptive capacity  236 academic-dependent relationship  162 accident risk  97 Ackoff, R.L.  41 activity-based costing theory  12 actual spending (AC) values  68 adaptive performance management approach 201 principles 202 Adeleke, A. Q.  92 Adler, M.J.  241 Aeronautical Development Agency (ADA)  154 Agarwal 9 Agarwal, Dhruv  9 agency contractual relationship  49 agency theory and project governance  49 Agile approach  151, 152, 155 Agile business environments  200 Agile life-cycle models  117 Agile methods  29 Agile principles  262 Agile project frameworks  24 Agile project management  49 Industry 4.0 on  254 techniques 24 Agile scaling frameworks  24 Agile software development frameworks  24 Agile work management frameworks  24 agility/flexibility in project management approach 80 Ahmed, Riaz  2 aircraft electric system  155 Ajmal, M. M.  218 Al-Momani, A. H.  96 alternative performance management model  201 analytical hierarchy process (AHP)  116, 126, 141, 268 Anantatmula, V. S.  6 Angelo, W.J.  96 annual budgeting 200 Applied Social Learning Ecosystems (ALSE)  242, 243, 249 appreciative inquiry  233

Aristotle 120 Arnold, C.  255 array projects  136 artificial intelligence (AI) chatbots  23 Asbury, S.  216 assembly projects  135 asset development metrics  18 Association for Project Management (APM)  94, 215 ATLAS.ti. Codes  205 Augmented Reality (AR)  259 Australian Securities Exchange  119 autonomous robots  257 average matrix Z  99, 101, 102 of effects  105 aviation project  152 Backlund, F.  235 Baker, B. N.  178 Bakker, R. M.  236 “balanced scorecard”  17 Banerjee, A.V.  116, 121 Bartsch, V.  235 Bashir, H.  142 Bayesian network (BN)  145 behavioral critical success factors (CSFs)  80 Bellin J.  260 “Belt-and-Road” infrastructure initiative  82 benefits management  40, 43 benefits realization practices  80 Berger, G.S.  94 “bet team”  29 beyond budgeting  198, 199, 201, 202, 203, 207, 208, 209, 210, 211 advantages of  202, 203 challenges of  203 principles of  202 reasons for  209 summary and research question  203 Bhattacharya, S.  115 Bhoola, V.  96 Big Data analytics  257 blockchain 257 Bloom et al (1956)  241 BMG Research  219 Bogsnes, B.  200 Bon-Gang, H.  93 Bougie, R.  59

286

Index  287 Bourmistrov, A.  200 Bratianu, C.  95 Bresnen, M.  235 Briscoe, Jon P.  129 British Association for Project Management (APM) 80 Brunet, Maude  6 Bryde, D.  97 Budayan, C.  269 budget allocation  198 budgeting 200 definition of  200 process  199, 200, 207 build–operate–transfer (BOT) model  273, 274 projects 269 road sector projects  273 Bushuyeva, N.  259 Cakmakci, M.  256 capacity-based metrics  12 capstone course  158, 159, 160, 161, 162, 164, 166, 167, 169, 170, 173 capstone projects  161, 162, 164, 167, 169, 170, 171, 172, 173 Carbone, T. A.  93 care management systems  190 Carlo (2014)  95 causal group  104, 106, 109 cause-and-effect relationship  98 diagram  100, 103 Change Control Board (CCB)  73 role of ‘monitoring’ to  71, 72 traditional role of  70, 71 change control process  67, 70, 71 charge-out model  208 Chbaly, Hafsa  6 Chen, P.  56 Chinowsky, P. S.  130 Chronéer, D.  235 Clarke (2018)  159, 160 Clarke, M.  159 classical operational management theories  42 classic contingency theory  80 classic performance models  39 Cleland, D. I.  217 “Client Project Challenge”  243 clients and mentors  247 client satisfaction  276 cloud computing technology  258 Coase, Ronald  128 codes and themes  205 cognition analysis  121 collaborative mindset  133 ‘command and control’ type of leadership style  260

community of practice (COP)  235 company vision to value-driven portfolio  27, 28, 29, 30 complex adaptive system (CAS)  26 theory of  50 complex aviation project, managing risk in  152 complexification gap  82 complex projects  17 complex systems  39 comprehensive education  241 comprehensive project performance framework 18 computer-mediated communication tools  224 conditional probability  145 conductive organizational culture  217 Confirmatory Factor Analysis (CFA) model  268 conflicts/disputes 97 Cong, X.  268 construction and demolition waste (CDW)  4, 55, 65 clause, respondent opinions on recycling  63, 64 management  56, 57 recycling 57 respondents’ perception of recycling  63 construction industry  55, 65, 92, 93, 96, 97, 101 risk in  93 risk management in  94, 110 Construction Industry Development Board (CIDB)  59, 65 construction projects  61, 92, 93, 94, 96, 129 recycling CDW in  62 construction stage  275, 276 constructive project environment  242 content validity analysis  277 content validity index (CVI)  272, 277 context gap  82 contingency theory  77 continual refinement process  205 continuous data collection  256 control charts  69, 70 controllability engineering theory  12 conventional non-participative practices  188 conventional versus Lean-led design approaches 194 “Conversation Starters”  243 co-occurrence matrices  205 Cooper, D. R.  219 corporate budget  201 corporate or organizational culture  216 cost and financial performances  14 cost and time performance  14 cost overrun  96, 97 cost performance  14, 15 cost to company (CTC)  197

288  Research handbook on project performance course learning outcomes  170 course-related knowledge and skills  168 Covid-19 vaccine  40, 48 Crawford, L.  237 Creswell, J.  163 critical success factors (CSFs)  69, 76, 77, 80, 81, 88 complexification gap  82 context gap  82 external environmental impact gap  83 success factors to success conditions  83, 84, 86, 88 temporal conflation gap  81, 82 underperformance gap  81 Cronbach’s alpha 59, 273 cross-case analysis  271, 273, 274, 275, 276, 277 cross-cultural integration  7 data analysis & visualization  222, 223 implications for theory and practice  223, 224 key terminologies  214, 215, 216, 217 literature review and synthesis  217, 218, 219 notable anecdotes  223 participant’s demographics  220 research methodology  219, 220 cross cultural project management  224 cross-disciplinary product teams  36 cultural diversity  260 “cultural industries”  217 cultural management  225 cultural variables  7 culture in information systems  216 Cunningham, W. S.  204 customer lifetime value (CLTV)  31 customer-oriented feedback loops  255 customer satisfaction  17, 178, 184 Cyber Physical System (CPS)  258 cyber-physical systems (CPSs)  256 Dainty, A. R. J.  129 Dalcher, D.  84 Dandage, R. V.  96 Daniel, Pierre  3 data collection process  59 data-driven models  140 data driven quantitative techniques  145 data integrity  70, 72 project monitoring and  73 data integrity problem  4 Daum, J. H.  201 Dayal, A.  129 de-biasing project estimates  80 decision making, models of  120 fallacies, assumptions and challenges  120, 121 hope as capability in managing projects  121, 122

decision-making process  117, 172, 191, 192, 260 Decision Making Trial & Evaluation Laboratory (DEMATEL) method  5, 98, 99, 100, 101, 104, 106, 109, 143, 144 decision theories  46 Delhi Metro 116, 129 delphi technique  137, 142 demand-driven planning  211 de Miranda Mota, C. M.  216 demolition waste  56 den Haak, Bart  3 dependency effect  149 “design funnel”  46 “design performance gap”  6, 188, 190, 193, 194 design stage  275 Diamond Typology framework  135 digital environments  26 digital technologies  224 rapid normalization of  224 Dinsmore 214 directed acyclic graph (DAG)  145 diversity of experience, designing for  169, 170 Dixit 9 documentation-based lessons learned  235 Donnelly, J.  84, 86 Drouin, N.  122 Duflo, E.  116, 121, 130 Dvir, D.  80 dynamic project environment  118 Dynamic Systems Development Method (DSDM) 24 earned value (EV)  68, 69, 72 as project monitoring  68 metrics 72 effect group  104, 109 effective communication  179 effective project performance  2 effective project portfolio management  179 effective risk management  5, 94 challenges to  118 plan 274 effective standards development of  16 effective training of virtual teams  260 EHS standards  275, 276 Ekholm, B.-G.  200 Eliassen, R.  56 Elizar 57 El-Sawalhi, N. I.  273 emergent performance, model of innovation in projects  44, 45, 46 instability in operations design  46, 47 systemic interactions of projects and operations  47, 48, 49

Index  289 Emery, F.E.  41 Engwall, M. 82 Enshassi, A.  96 environmental issues  57 respondents’ concerns about  61, 62 Eppler, M. J.  235, 236 E-procurement platforms  256, 262 Eriksson, P. E.  235 E-social networking platforms  256 evaluation and award stage  275 “ex-ante” approach  69 execution phase, performance evaluation in  267 experiential learning  152, 232, 247 exploitative learning processes  235 exploratory learning  250 external client factors  177 external environment  80, 83 external environmental impact gap  83 externally-funded projects  176 external project risk factors  117 external risk  92 familiar groups  166 Farr-Wharton, R.  95 feasibility stage  274 Federal Transit Administration  75 Fellows, R.  219 file sharing platform  165 financial benefit  16 financial metrics  17 financial performance measurements  17 financial profitability of projects  40 financial ROI  40 Fisher, D.  178 fixed capacity  7, 197, 198, 199, 205, 206, 207, 210, 211 approach  205, 206 benefits of  205, 206 budget 210 challenges of  206 model 198 rationale of  197 flexible sense-and-respond mechanisms  201 flow capacity  199 Flyvbjerg B.  96, 115, 118, 120, 122 Fontela, E.  98 formal cost management practices  10 formal education  241 formal learning  246 formal project management processes  9, 184 Foucault, Michel  120 Fourth Industrial Revolution  254, 255, 259, 260, 261 free market philosophy  255 French vaccination campaign  40

Fuzzy MCDM  141 Gabus, A.  98 Galileo 116 Gamble, N.  159 Gandhi, Mahatma  115, 116 Gemünden, H.G.  80 Gilbert, G.  161 Gilbert, Guinevere  6 globalization 133 global mindset  133 Goldratt, Eli  25 Goode, M.  200 “good human behavior practices”  129 governance organizational practices  50 group behaviour, equilibrium model of  171 Gupta, Ruchita  5 HAL 155 Hall, Douglas T.  129 Hammad, S.  273 Harvey, J. B.  128, 130 healthcare facilities, complexities of defining needs in  189 Henisz, W.  129 Henrie, M.  218 Heskett, J. L.  216 heterogeneous group of students  169 Hethero Terminal 5  134 hierarchical-operative groups  214 Hillage, J.  159 Hirschman, A.O.  84 Hobbs, B.  217 Hoegl, M.  80 Hofstede, G.  218, 219 holistic education  241 benefits of  241 Honolulu rail project  76, 86 hope model  130 hospital megaproject  7 hospital projects  189 Hossain, M.  268 human resource management (HRM)  259, 260, 261 Hyväri, I.  81 Ikaa, Lavagnon A.  4 Ika, L.A.  84, 86, 88 Impact-Relation Map (IRM)  98 inadequate performance indicators  14 independent risk  152 Indian construction industry  116, 117, 124, 128 Indian construction projects  117, 129 case method  122, 123, 124, 125, 126, 127 challenges to effective risk management  118 hope model  130

290  Research handbook on project performance industry environment  117 models of decision making  120, 121, 122 power in projects and managing social risks 120 risk and governance  118, 119 risk management  117, 118 social risks and political risks  119 success in Indian projects  116 Indian projects  115, 116, 117, 128 public sector projects  116 road sector case studies  271 case study analysis  273, 274, 275, 276 content validity analysis  272 identifying key performance indicators 270 performance evaluation in execution phase  267 of PPP project  268 of PPP road project  268 performance measurement  267 process lifecycle perspective  268, 269 questionnaire survey  270, 271 ranking of key performance indicators 272 research methodology  269 semi-structured interviews  270, 271, 272 Indian Space Research Organization (ISRO)  134 industrialisation change process  260 Industry 4.0 on Agile project management  9, 255, 256, 257, 258, 259 human resource management in  259, 260 macro level  262 meso level  261, 262 micro level  261 industry environment  117 information and communication technologies (ICTs) 216 information technology ecosystems  256 infrastructure development projects  115 infrastructure industry  116 infrastructure projects  128 initial direct-relation matrix  99 “initiative team”  29 innovation mindset  133 innovation performance  14 innovation projects  140 input–process–output (IPO) model  41, 43 instability in operations design  46, 47 Institute of International Finance (IIF)  95 integrated risk management mitigation  172 integration management  46, 170, 171 integration milestone  68 interactive collaborative learning ecosystem  249

interactive project-based learning experience  249 intercultural communication effectiveness  219 internal project risk factors  117 International Council for Building (CIB) Performance 18 International Journal of Project Management  236 internet culture  217 Internet-of-Things (IOT)  256, 258 Interpretive Structural Modelling (ISM)  143, 144 inter-project learnings  235 interview questionnaire  181 interviews  204, 205 intra-and inter-project learning  235 intraorganizational social ties  235 iron triangle  13, 14, 83 Işıklı, E.  255 Ives, M.  218 Iyer, K.C.  115, 117, 129 Iyyunni, Chakradhar  5, 117 Jain, Karuna  5 Japp, K. P.  119 Jermsittiparsert, K.  260 Jha, K.N.  115, 117, 129 Johannesburg Stock Exchange (JSE)  204 Judgev, K.  8, 178, 214, 216, 217, 235 Jules C.  260 Julian, J.  235, 236 Kaarbøe, K.  200 Kagioglou, M.  267 Kahneman, D.  115, 120, 121, 124, 125 Kaivo-oja, J.R.L.  133 Kamara, J.  190 Kanri, Hoshin  28 Kaplan, R.S.  11, 17 kernel culture  219 key performance indicators (KPIs)  3, 18, 42, 69, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277 Kharbanda, O. P.  216 Koestalam, P.  57 Koskinen, K. U.  218, 235, 236 Kotnour, T.  235 Kotter, J. P.  216 Ku, H.-B.  204 Kumar, Sunil  5 Kusche, I.  119 Kwok, J. Y.-c.  204 Lai, Y.  56 Laufer, A.  129 Lauraeus, I.T.  133 leadership influence of  223 principles 201

Index  291 Leal-Rodríguez, A. L.  236 Lean-led Design 7 bridging  191, 192, 193, 194 complexities of defining needs in healthcare facilities 189 using traditional practices  189, 190 Lean OKRs  24, 28, 31, 32, 33 approach 30 cycle  34, 35, 36 framework   37 lean production environment  197 lean software development  198 lean thinking  28 “learning by doing” approach  251 learning themes and their elements  244 Lee, Chia-Kuang  5 Lee, L.  235 Lee, Y.  56 lessons learned process  232, 233, 234, 235, 236, 237 Lifestyle Learning  246 Light Combat Aircraft (LCA)  152, 153, 154, 155 lightweight governance model  35, 36 Likert rating scale for impact and probability  140 Lim, C. S.  215 line replacement units (LRU)  155 Ling, F.Y.Y.  12 Liu, A. M. M.  219 Liu, J.  267, 268 logical framework analysis techniques  40 London Stock Exchange  118 Loosemore, M.  129 Lovallo, D.  120, 121, 124, 125 low-quality projects  16 low risk management 5,  94 accident risk  97 conflicts/disputes 97 cost overrun  96, 97 Decision Making Trial & Evaluation Laboratory (DEMATEL) method  98, 99, 100, 101 demographic profile  101 effects of  93, 104, 105, 106, 108, 109 failure to meet desired quality and requirements 97 lack of knowledge in risk management implementation 95 lack of managerial support and communication  94, 95 lack of resources  95 low risk attitude  95, 104 poor risk culture in organization  95, 96 project delay/time overrun  96 resistance to change  94 risk in construction industry  93 systematic review  98

Lundy, V.  94 Lutchman, C.  129 Lynton N.  260 machine learning tools  152 MacKay, J.  129 Mainga, W.  236 maintenance efficiency metrics  18 Ma, L.  268 mal-adaptive risk behaviors  115 Malaysian construction industry  56, 62, 63 Malaysian waste management  55 Malik, A.  200 “management of project management”  80 managerial support and communication, lack of  94, 95 Mantel, S. J.  216 Mantha, S. S.  96 March, J.  120, 121 Marion 4 market capitalization  261 Marnewick, A. L.  255, 256, 259 Marnewick, C.  255, 256, 259 Mars Orbiter Mission (MoM)  134 Mason, M.  220 Matějka, M.  203 Mathur, G.  235 matured organizations  176 maturity path  207 McClory, S.  235 Ménard, P. M.  217 Meng, J.  94 mentors  162, 163, 166, 167, 168 role, aligning expectations of  172, 173 mentor-student relationship  173 Merx, S.  160, 170 Messner, W.  219 Millennials and Digital Natives generations  217 Miller, R.  115 Mitchell 166 mitigation strategies  97 modern quality management systems  69 Mohamed, M. Z.  215 Monte Carlo analysis  116 Monte Carlo simulation  120, 125, 147 Morin, P.P.  94 Mosa El Nawawy, O. A.  92 Mueller, J.  217 Müller R.  178 multi-criteria decision making (MCDM)  141, 152 multicultural delights  222 Murphy, D. C.  178 mutually exclusive, collectively exhaustive (MECE) 31

292  Research handbook on project performance mutual social learning  250 Naik, S.  259 national culture  216 National Highway Authority of India (NHAI) 268 Neely, A.D.  11, 18, 200, 267 negative risks  92 New Complexe Hospital (NCH) project  190, 191, 192, 193 non-favourable effect  149 non-profit organization’s approach  176 normalized direct-relation matrix  99, 102, 105, 107 Norton, D.P.  17 novelty, technology, complexity, and pace (NTCP)  80, 135, 136, 153, 154 Objectives and Key Results (OKRs)  28, 33, 34, 35 oil refinery construction project  137 Oliveira (2017)  92 Olsson, R.  93, 95 “one and done” attitude  82 online communities group  224 online data collection  59 online questionnaires  59 Opera House  216 operational management  49 theories 41 operational outcomes, from project outputs to  39, 40 operational project models and analyses  50 operational system’s mission  42 operational value chains  40, 41, 42, 43, 50 operation and maintenance 18, 276 operations strategy theories  47 optimal learning experiences  247 Ordered Weighted Averaging (OWA) model  268 organizational agility principles of  49 organizational commitment  236 organizational culture  118, 216 organizational decision making  70 organizational guidance  203 organizational learning  235, 236 in project management environments  235 organizational project management maturity  176 organization and management metrics  18 organization culture  180 pair-wise comparison  126 Pandit, D.  273 Peach, D.  159 Peer Review process  250 people-readiness model  129

“perceived employability”  159, 170 performance criteria  13 performance dimensions  14 performance evaluation in execution phase  267 of PPP project  268 of PPP road project  268 performance frameworks of projects  18 performance indexes  69 performance information  13 performance management  18, 202 performance measurement matrix  17 performance measurement systems (PMSs)  267, 268 performance measures  11, 13, 14, 18 performance metrics  11, 12, 18 performance models  18, 39 and frameworks  49, 50 performance monitoring  271 performance objectives for project  18 performance prism system  268 pessimistic explanatory style  122 Petit 7 Pfizer vaccine  48 phase-specific performance measures  18 Pinnington, A. H.  217 Pinto, Jeffrey K.  4 Pinto, J. K.  216 Pinto, J.K.  83 Plan–Do–Check–Adjust (PDCA)  35 planned value (PV)  72 Planning Fallacy principle  80 ‘plan progress management’  73 PMI 215 political risks  119 Pollard, E.  159 poor risk culture in organization  95, 96 portfolio funnel  32 portfolio management  179, 184 Portfolio Management Office (PMO)  36 Posterior Risk  149 Power, D.  217 Priemus, H.  120, 122 PRINCE2 24 principal–agent relationship  49 private sector, role of  265 proactive risk assessment approach  154 proactive risk management  152 probability distribution functions  147 probability impact matrix  139 problem-centred knowledge claim  269 process-based evaluation  267 process-based lessons learned  235 process life cycle performance measurements 268

Index  293 process principles  201 product development plan  27 product development practices  46 product management  27 product-oriented evaluation  267 product-related decision-making  16 project autonomy  80 project-based approach  249, 250, 251 project-based learning  244 activities 248 experience  244, 248, 249 programs 242 project-based organizations  235 project-based social learning  242 project-based work  76 project behavior  77 project benefits and outcomes  3 project constraints, impact of flow on  199 project critical success factors frameworks of  78 project culture  217, 223 project definition process  191, 193 project definition stages  190 project delay/time overrun  96 project development cycles  45 project development model  81 project-driven approach  198 project environment  254 project execution efficiency  83 projectification of society  39 project initiation phase  16 project integration management  256 project learning process  235 project life cycle  154 stages 270 project management  13, 14, 23, 28, 36, 37, 39, 67, 69, 76, 88, 172, 215, 217, 240, 262, 267 approach, agility/flexibility in  80 best practices, influence of  223 capstone projects  161, 174 courses 215 culture 214 degree  162, 164, 168, 170 factors 181 field 50 frameworks 24 fundamental role of  42 literature  11, 13, 76, 77 maturity 6 methodology 215 methods 27 metrics 12 model  28, 36 practices  176, 179, 183, 184 principles  176, 224

profession 2 program  163, 169, 171 research  83, 84, 86 skills  6, 158, 161, 162 strategies 12 success  2, 16, 177, 178, 179 techniques 23 theory  43, 76, 88 tools  16, 170 traditional 24 university program  170 visualization of  43 Project Management 4.0  9, 254 Project Management Body of Knowledge Guide (PMBOK® Guide)  8, 14, 24, 93, 118, 215, 225, 231, 232, 233, 234, 237, 240, 250 Project Management Institute (PMI)  6, 11, 93, 118, 158, 164, 171, 231, 232, 234 Project Management Journal  236 project management lessons learned  231 analysis of two sets of methodologies  236, 237 content analysis of  232, 233, 234 journal abstracts reviewed on  234, 235, 236 project management maturity role on project performance  176, 177, 179, 180 case study method  181, 184 factors 179 project success and project management success  177, 178, 179 research method  180 survey questionnaire  180, 181 project management research methodologies  122 project management team  134 project management tools  16 project manager leadership role  2 project metrics  12 project monitoring and data integrity  67 baseline 67 control charts  69, 70 critical success factors and key performance indicators as  69 earned value as project monitoring  68 efficacy 73 implementation considerations  72, 73 project progress data  70 rearview mirror approach  68, 69 role of ‘monitoring’ to the Change Control Board (CCB)  71, 72 system 4 traditional role of Change Control Board (CCB)  70, 71 Project Myopia  24

294  Research handbook on project performance project performance  2, 8, 11, 39, 76, 176, 177, 178, 223 analyzing challenges of  16, 17 conceptualization of  11 dimensions of  13, 14, 15 evaluation 273 factors  179, 180, 181, 184 framework  17, 18, 19 management 40 measures of  12, 13, 14 metrics of  12, 14 multi-level framework of  40, 41, 42, 43 outcomes 18 planning tools  9 project management maturity role on  176 scope of  50 project portfolio management function  181 project progress data  70 project-related employment  168 project-related skills and knowledge  170 project reports  68 project resilience  80 project risk management  152 course 170 project risks  93, 94, 96 management  94, 95 Project’s Change Control Board  4 project scope management process  198 project’s mismanagement  76 project’s performance  80 project sponsorship  80 project status  72 project success  2, 5, 76, 77, 80, 81, 82, 83, 84, 86, 88, 133, 177, 178, 179 failures  134, 135 project dimension  135, 136 project in VUCA environment  133 qualitative models and techniques for risk identification and assessment  137, 139 quantitative models using analytics for risk assessment 140 risk management process  136, 137 risk monitoring and control  150, 151 risk response strategies  147, 148, 149, 150 project supervision  80 project team management  116 psychological sanctuary  122 public-private partnerships (PPPs)  9, 75, 265, 266 benefits of  266 database of India  265 preparation stage  274, 275 projects  266, 268, 270, 274, 276, 277 road projects  265, 268, 270, 271, 273, 277 types of  266

public sector entities  265 Qualitative Content Analysis (QCA)  268 qualitative research method  8 qualitative risk analysis  139 quality performance  14 quantifiable and non-quantifiable skills  171, 172 quantitative analysis  208, 209 quantitative models Monte Carlo simulation  147 risk interaction techniques  141, 142, 143, 145 risk prioritization techniques  140, 141 quantitative research approach  58 quantitative research design  58 quantitative risk analysis  116 questionnaire-based survey  271 questionnaire survey  58, 59, 272, 277 rail project  75 Raisinghani, Mahesh S.  7 Raji, I. O.  255 Ramos, P. A.  216 random sampling method  59 Rane, S. B.  96 Rankin, J.  12 Rauzana, A.  97 rearview mirror approach  68, 69 recall versus integration  170, 171 recycling CDW clause  63, 64 “red light learning”  236 reduction of costs  210 Rees-Caldwell, K.  217 “registration system”  46 Reina, P.  96 Reiter, Karin  119 relational learning  236 Relative Importance Index (RII)  273, 274, 277 reliability of data  59 reliability test  273 Remington, K.  117 research framework  58 resistance to change  94, 104, 108, 109 resource allocation  197, 208 respondents’ demographic profile  101 Reverse Bloom Learning Framework (RBLF)  242, 243, 249, 250 Ribeiro, A.  256, 260 Richardson 4 Rickards, R. C.  203 risk adaptation strategy  148 risk analytics  140 risk and governance  118, 119 risk appetite curve, digitization of  123 risk assessment  140 Monte Carlo simulation  147 risk interaction techniques  141, 142, 143, 145 risk prioritization techniques   140, 141

Index  295 risk attitude  95 risk aversion  121 risk-based activities  118 risk-based communication  115 risk behavior  115 risk breakdown structure (RBS)  137, 138 risk culture  96, 118 risk dependencies  149, 151, 152 response strategy  149 risk identification and assessment, qualitative models and techniques for  137, 139 process 97 techniques  137, 139 risk interaction techniques  141, 142, 143, 145 risk management  92, 93, 97, 109, 117, 118, 119, 172 adoption 5 aspects 6 framework 115 function 115 implementation  93, 94, 95 in construction industry  94, 110 in construction projects  109 in projects  5 methodology 155 process  134, 136, 137 program 118 session 126 strategies  147, 151, 154 risk mitigation strategy  148 risk monitoring and control  150, 151 risk network, visualization of  142 risk prevention  148 risk prioritization techniques  140, 141 risk register  152 risk response actions  152 risk response planning  147 risk response strategies  147, 148, 149, 150 risk score  140 risk structure matrix  142 risks, types of  119 robotic systems  189 Rockart, J.F.  84 Rossi, T.  255 RSM Robson Rhodes LLP  118 rules of thumb  70 Sabariyah, D.  97 SAFe  7, 204 sample interview questions  163 sample scales for quantitative probability and impact 140 Samset K.  115 Sanofi vaccine  48

Sanyal, S.  117 scaled agile environment  197, 210 beyond budgeting  201 fixed capacity  198, 199 framework 204 planning in  197 research methodology  203, 204, 205 results  205, 206, 207, 208, 209 traditional budgeting  200, 201 schedule performance  14 Schein, E. H.  216 Schindler, M.  235, 236 Seiden, Joshua “Outcomes over Output”  26, 34 Sekaran, U.  59 Sekar, G.  14 self-belief 159 self-control 130 Semantic Network Analysis (SNA)  142, 143 semi-structured interviews  204, 219, 271 semi-structured questionnaire  220 sensitive defence technologies  153 Shapira, Z.  120, 121 She, L.-Y.  128 Shenhar, A.J.  80, 117 Shepherd, D. A.  236 Shohet, I.M.  18 Shore, B.  219 short intensive format learning 246 Simion, C. P.  255, 256, 260 Simon, Herbert  128 simulations 259 Singh, Dhruv Pratap  7 Sisodia, R.  129 situated learning 235 Slevin, D.P.  83 Smircich, L.  218 Smith, C.  160, 163 social capital  235 social learning ecosystems  242 social risks and political risks  119 managing 120 socio-technical systems  46 approach 42 operations as  41, 42 theory of  50 software-intensive system development  68 software product companies  24, 28, 30, 36 software project management  81 Sony, M.  259 sound business case  80 Sousa-Poza, A.  218 Spencer, J.  216

296  Research handbook on project performance stage gate approach  47 stage-theories of group development  171 stakeholder behavior  5 stakeholder engagement  116, 118 standard deviation  273 standard form of contracts  4, 55, 57, 58, 63, 64, 65 standardized risk management practices  135 standard operation procedure (SOP)  56 State Highway project scheme  274 state-of-the-art technologies  152 statistical analysis  59 Statistical Package for the Social Science (SPSS) 59 strategic management  215 cycle of operations  47 of organizations  40 stress fundamental managerial segments  216 structured decision-making  117 structured project management  179 student 163 success conditions  77, 83, 84, 86, 88 Sundarajan, S.  97 Sung, P.  56 super-high-tech projects  136 supportive learning environment  236 survey questionnaire  6, 177, 180, 181 “sustainability by the project” 81 Swarup, L.  12 Sweis, G.  96 Sydney Opera House  216 systemic projects 39, 135 TACTILE model  129 tangible project  68 Taylorism 24 Tchobanogious, G.  56 team leadership  130 teamwork quality  80 temporal ambidexterity  81 temporal conflation gap  81, 82 Theisen, R.  56 theory of constraints  25 Thomas R. J.  260 Thomke, S.  42 Thomsett, R.  216 threshold value  100, 103, 104 Tippett, D. D.  93 total-influence matrix  99, 100 total relation matrix  102, 105, 107 traditional and agile organizations  261 traditional budgeting  199, 200, 201, 203, 208, 209, 211 traditional education  250 traditional hierarchical organizational structure 260

traditional infrastructure delivery system  266 traditional iron triangle of project management 23 traditional learning approach  250 traditional management approach  201 traditional MCDM techniques  141 traditional practices decisions  194 traditional project analysis practices  50 traditional project definition practices  192 traditional project management  23, 36, 254, 255, 262 bets 31 company-level goal(s)  30, 31 false beliefs of  24, 26 from company vision to value-driven portfolio  27, 28, 29, 30 initiatives 31 Lean OKRs  33 Lean OKRs cycle  34, 35, 36 outcomes over output  26 portfolio funnel  32 products and outcomes  26, 27 Taylorism 24 traffic congestion  75 “triple loop of learning”  235 Trist, E.L.  41 Turner, J. R.  219 Turner, Michelle  6 Turner, R.  84 Tversky, A.  115, 120 uncertainty management  45 practices 50 process 46 theories of  43 under budget  68 underperformance gap  81 unfamiliar groups  166 United Nations Sustainability Goal  161 university capstone project case study aligning expectations of the mentor’s role  172, 173 collaboration versus task allocation  164, 165 confidence  167, 168 course knowledge and skills  168, 169 designing for diversity of experience  169, 170 developing employability  159, 160 examining curriculum  160, 161 group conflict  166, 167 impact of familiarity  165, 166 integrating quantifiable and non-quantifiable skills  171, 172 mentor’s role  169 method  161, 162, 163 participants  163, 164

Index  297 recall versus integration  170, 171 right person in the right job  158, 159 skills gap identification  167 themes 164 unjustified preferential partnerships  115 unstable operational systems  46 unsuitable working environment  188 UN Sustainable Development Goals  76 “vaccinate” operational system  46 vaccination campaign  40, 46 Valuckas, D.  202, 203 value chain operations  40, 41 Value Creation Model (VCM)  3, 24, 27, 28, 30, 31, 32, 33, 35, 36 value-driven portfolio, company vision to  27, 28, 29, 30 Vanhercke, D.  159, 170 VCM Ambassador Team  36 Veile, J.  255 Vendor PMS  268 Verma, V.K.  97 viability gap funding scheme  274 Vierlboeck, M.  200 virtual mindset  133 virtual project environments  251, 260 virtual telepathy  256 visualization tools and techniques  192 Voigt, K. I.  255 volatile, uncertain, complex and ambiguous (VUCA) environment  5, 117, 133, 152, 240

Wagner, D. B.  216 Wallin, J.  200 Wang, T.  80 Ward, L. R.  215 waterfall approach  81, 199 Water Infrastructure projects  130 Watson, T.  94 Whole Price Index (WPI)  275 Wibowo, M. A.  57 Wijngaards-de Meij, L.  160, 170 Willard, B. K.  217 Wingrove, D.  161 work breakdown structure (WBS)  136 work management system  24 World Economic Forum (WEF)  244 World Health Organization  189 Yang, J. B.  100 Yang, R.J.  142 Yanık, S.  255 Yeh, L  56 Yuan, J.  142, 268, 271, 273 Yusoff, M. S. B.  270 Zahidy, A.-H.  97 Zainudin, Nurhaizan Mohd  4 Zarei, B.  142 Zavadskas, E. K.  92, 93