Leadership and Digital Change: The Digitalization Paradox [1° ed.] 0367275015, 9780367275013

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Leadership and Digital Change

Digitalization is on everyone’s lips as new technology changes business landscapes and conventional companies are outperformed by younger digital and agile contestants. In this volatile environment it seems more relevant than ever before to understand the aspects and business logic behind the elusive phenomenon called “digitalization”. Never before have there been such great opportunities to unleash the full potential of technology within organizations to create long-standing competitive advantage. This book explains the strategy and practice of how to lead and control the people side of digital change in a dynamic world of uncertainty and social complexity, and as such the book snares the elusive phenomena of digitalization. Digitalization drives behavioral change and calls for a new way of thinking among senior executives. In practice, reaping the benefits of digital technology is not as easy as it first appears to be. This book provides a map to navigate in the volatile business landscape where change occurs continuously because of digital technology. It provides an historical frame of the evolution of digital technology, decodes digitalization’s negative influence on the external aspects of customer satisfaction, discusses and explains the strategic and leadership consequences of different forms of digital change, and finally demonstrates how leading digital change can be put into practice. Illustrative case studies and examples are provided throughout, as well as models and frameworks. This is a valuable resource for researchers, academics, and students in the fields of organizational studies, organizational change, technology and innovation management, and digitalization. Einar Iveroth is Associate Professor in Business Studies at Uppsala University, Sweden. Jacob Hallencreutz, Ph.D., is Group CEO of EPSI Rating Group, Stockholm, Sweden.

Routledge Studies in Organizational Change & Development Series Editor: Bernard Burnes

Reconsidering Change Management Applying Evidence-Based Insights in Change Management Practice Steven ten Have, Wouter ten Have, Anne-Bregje Huijsmans, and Maarten Otto Rethinking Culture Embodied Cognition and the Origin of Culture in Organizations David G. White, Jr Academic Practitioner Research Partnerships Developments, Complexities and Opportunities Edited by Jean Bartunek and Jane McKenzie The Social Psychology of Change Management Theories and an Evidence-Based Perspective on Social and Organizational Beings Steven ten Have, John Rijsman, Wouter ten Have and Joris Westhof Organization Development and Society Theory and Practice of Organization Development Consulting Baruch Shimoni Reshaping Change: A Processual Perspective, 2nd Edition Patrick Dawson Changing Change Management: Strategy, Power and Resistance Darren McCabe Leadership and Digital Change The Digitalization Paradox Einar Iveroth and Jacob Hallencreutz For more information about this series, please visit: www.routledge.com/ Routledge-Studies-in-Organizational-Change-Development/book-series/ SE0690

Leadership and Digital Change The Digitalization Paradox Einar Iveroth and Jacob Hallencreutz

First published 2021 by Routledge 52 Vanderbilt Avenue, New York, NY 10017 and by Routledge 2 Park Square, Milton Park, Abingdon, Oxon, OX14 4RN Routledge is an imprint of the Taylor & Francis Group, an informa business © 2021 Taylor & Francis The right of Einar Iveroth and Jacob Hallencreutz to be identified as author of this work has been asserted by them in accordance with sections 77 and 78 of the Copyright, Designs and Patents Act 1988. All rights reserved. No part of this book may be reprinted or reproduced or utilised in any form or by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying and recording, or in any information storage or retrieval system, without permission in writing from the publishers. Trademark notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. Library of Congress Cataloging-in-Publication Data A catalog record for this book has been requested ISBN: 978-0-367-27501-3 (hbk) ISBN: 978-0-429-29642-0 (ebk) Typeset in Sabon by Apex CoVantage, LLC

Contents

List of Figures and Tablesvi Acknowledgmentsvii Prefaceviii 1 Introduction

1

2 Putting Digitalization in Perspective

9

3 Understanding the Customer Side of Digital Change

43

4 The Swedish Potato: A Story of a Transformation

69

5 Strategic Aspects of Digital Change

81

6 The Employee Side of the Digital Change

105

7 Summary and Final End Notes

135

Index140

Figures and Tables

Figures 2.1 2.2 3.1 3.2 3.3

Six Stages of Organizational Learning 14 Four Waves of Organizational Learning 17 General Customer Satisfaction Trend 45 The EPSI Model 54 The Latent Variables’ Relative Importance on Customer Satisfaction Over Time 56 5.1 The Digitalization Map89 5.2 The Strategic Continuum of Digital Change 97

Tables 1.1 Major Digital Change Challenges 5 2.1 Models of Creative Accumulation and Creative Destruction28 3.1 Items From Questionnaire Connected to the EPSI Model 67 6.1 The Commonality Framework for Digital Change 108 6.2 Hard and Soft Factors of Digital Change 122 6.3 The Framework Applied to the Potato Story 126

Acknowledgments

We are grateful to FEI Research Institute for their keen interest in our research, as well as their financial support. Also, this book would not have been possible without our continuous discussions we have had with colleagues and their respective organizations over recent years. Therefore, we are deeply indebted to our friends and colleagues at Uppsala University, CASIP, Swedish Institute for Quality (SIQ), and EPSI Rating Group, especially our Chief Analyst Dr. Johan Parmler. The greatest and most loving thanks to our families, especially Jeanette, Sofie, Eije, and Dorothea. Thank you for putting up with us, especially since the finalizing of the book took place during a very chaotic time due to the Coronavirus. Without you, none of this would have happened. Finally, a special acknowledgment and love to Sofie, who in an apartment in Dalston in London came up with the innovative idea of connecting digital change to something as rudimentary as a potato!

Preface

After finalizing our previous Routledge book, Effective Organizational change (2015), we have been out there researching and lecturing about how to prevail in a time of uncertainty and rapid change. The audience has been both students, research fellows, consultants, and leaders from different industries. The change challenges are many, but over the last years it has been obvious to us that the word digitalization is on everyone’s lips. And this is understandable. The development of digital services has skyrocketed during that last five years. Services from almost all societal sectors and industries are today available around the clock via digital platforms, literally just a smartphone away. Changed internal as well as external demands, needs, and expectations have come consequently. Therefore, it is fair to say that handling digital change is one of today’s great management challenges. Yet many leaders fumble in the dark when going from theory to practice. To reap the full benefits of digital technology is not that easy as it first appears to be. There are for sure textbooks that cover models, concepts, and ideas about how to master digital change, but real life has always been less clear cut. Far too many digital change initiatives go awry despite good intentions and plans. During our meetings, seminars, and discussions with friends we have shared many experiences from our craft of doing research and lead change in practice. In our conversations one notion has been standing out; society as we know it is on the brink of a transformation that will change almost everything: what we do, how we do it, and what to do— due to digitalization. It is fair to say that organizations in all industries and societal sectors across the globe struggle with digital change. But the word digitalization as such is too often used as a label for almost any change initiative, project, or undertaking where computers and information technology to some extent are involved. When looking closer there seems to be no clear-cut definition of the word and what it means in practice. Rather, digitalization is used to describe a wide range of change challenges, from disruptive transformations of whole industrial sectors to simple launches of apps, web applications, or internal process adjustments. There seems to be widespread confusion, and we

Preface ix feel that digitalization is used as a remedy for almost any internal or external development need. Moreover, the customers’ perceptions of the outgrowth of all these new digital services are not always positive. We call this development the emergence of the digitalization paradox— digital services have come closer and are available around the clock, but personal relations seem to have gone astray in the process. Therefore, it is more relevant than ever before to understand the aspects, as well as business logic, behind the elusive phenomenon that everyone talks about. There is a plethora of books on how to go about digitalization challenges, mainly written from a technology perspective. But successful digital change is less about technology per se and more about people and new ways of thinking, feeling, and doing. Success lies in the people side of change. And that is what this book is about. Leadership and Digital Change: The Digitalization Paradox uncovers what it is that leaders actually do when they lead digital change. By doing so, the book provides the frontline of digitalization research for researchers and graduate students, while at the same time informing leaders of what they can do to excel in their digital change efforts. The book combines a theoretical overview, models, and conceptual discussions with rich cases from the field. Most importantly, the book extends earlier work by presenting the Digitalization Map and the Commonality Framework of Digital Change. But  .  .  . having written all these nice words, we feel obliged to add a final personal note. During the finalization of this work, the Covid19 pandemic hit the world and the gap between a textbook and reality suddenly became painfully clear. We are now in the middle of a societal change that cannot be fully grasped. There is also an awkward irony to this crisis; Covid-19 is right now accelerating digital change in many societies, when physical interactions in haste turn digital in all corners of the world. So, in a somewhat uncomfortable sense, this book is more relevant than ever. Take care of each other, wherever you are.

1 Introduction

One night in January, we were having yet another discussion about the design of this book. The debate took place in Jacob’s kitchen and was quite tiresome. To get a breath of fresh air and hopefully find some clarity we decided to take a walk around the lake (Jacob lives in Mölnbo, a small rural village about 60 km southwest of Stockholm). Halfway around the lake, we decided to stop at the farm Bergholm and say hello to Mauritz and Sanne, Jacob’s neighbors and close friends. Einar was getting cold and perhaps they could offer some warm refreshments. And yes, they were welcoming as always. While sipping on our drinks (now in their kitchen), we all noticed a small truck that entered the farm and parked in Mauritz and Sanne’s courtyard. Time was about 8 pm and it was pitch black outside. Who was that? Burglars? Mauritz looked out the window and said relaxed “oh . . . the food is coming”. The intruder turned out to be their weekly delivery of groceries from one of the internet supermarkets. While Mauritz collected the bags and chitchatted with the driver, Sanne explained: We buy almost all foodstuffs online. So handy and convenient. As you can see, they deliver literally at our doorstep and we don’t have to spend time at shopping malls or supermarkets just to get our weekly need of groceries. So easy, just a couple of clicks away. And the drivers are usually nice and service minded. They even find the way out here in the lonely woods. Of course, they know nothing about the details of the stuff they deliver so, if something is missing, or if some foodstuffs have a poor quality it is a drawback. That is of course easier to handle face to face in a supermarket. We looked at each other and nodded. Ok, here was our introduction to the book. This short vignette is merely one example of how the delivery of products and services has changed significantly during the last decades due to advances in technology, and information technology in particular. For some, such a delivery of goods and services might seem as a simple

2  Introduction transaction performed in another way compared to earlier. Nothing more. However, behind all this lies a great organizational challenge both from an external perspective concerning the on-going relationship with customers, and from an internal perspective when it comes to changing organizational structures, processes, and people. More specifically, we find that this vignette from everyday life touches upon many of the key aspects of this book. Externally, the experience in Mauritz and Sanne’s kitchen underlines the notion that for many new technology has become something that is just taken for granted—smartphones, apps, and good connectivity are no-brainers. The technology is simply not important for the end-user; instead the prime focus is the services that are available and enabled by digital technology. For an organization, this translates into external challenges to establish, uphold, and improve the customer relationship and satisfaction through different forms of digital interfaces and channels, as well as through the less digital truck driver. Internally, the vignette shows that new technology transforms organizations, industries, and societal sectors (in this example the logistic implications for the value chain of grocery shopping) from the customer interface through ordering, packaging, and distribution. The shelves in the shop are substituted by a webpage and a warehouse. The cashier in the supermarket is substituted by a truck driver. For an organization, this translates into internal challenges of making sure that the correct strategic decisions are aligned with the continuous development of digital technology and assure that technology is used in the organization in the right way, at the right time, and for the right purposes. On top of this, the internal and external challenges influence each other, as customer feedback should drive the development of digital technology as well as organizational change. More broadly, the story visualizes that digitalization in practice often is about down to earth behavioral change for both the customer as well as for employees. The option to buy groceries online triggers new customer behavior, and demand for new ways of working within the retail industry come consequently. The story also touches a phenomenon that we call the digitalization paradox: services come closer and are available around the clock, but at the same time the distance to personal and customized relations increases. And to complicate things further, digital services available from one industry are soon expected from other totally different industries, so this expectation spillover accelerates societal change. Digitalization breeds changes to industries, complete systems, and society at large. In this way, digitalization—which is what this is all about—comprises individual, organizational, social, and societal change that organizations and their leaders must manage and control. Looking around we see that the word digitalization is on everyone’s lips. And this is understandable. Services from almost all societal sectors are available around the clock via digital platforms and are literally just a

Introduction 3 smartphone away. New customer interfaces, combinations of goods and services, and internal as well as external demands, needs, and expectations come in the wake. Never have service providers had the potential to be close to customers and users via new digital interfaces. Big data create opportunities to understand and meet different needs with customized services. And never have there been such great opportunities to unleash the full potential of technology within organizations to create long-standing competitive advantage. Yet many organizations and leaders fumble in the dark when going from such rhetoric to reality. In practice, reaping the full benefits of digital technology is not that easy as it first appears. In our dialogues with senior managers, there is often a notion that society as we know it is standing on the brink of a major transformation that literally will change almost everything: what we do, how we do it, and what to do—due to digital technology. The extent to which such opinions (about the real and future transformational nature of technology) are true or not is too early to tell. What we can say, however, is that we are now experiencing a societal change at large. And this profound societal change is not only about new technology. Political instability, barriers to trade, nationalism, and protectionism seem to characterize the global agenda, and the collective capacity of the international community to address fundamental societal problems has become weaker, and the global world as such seems fragile. This also applies to organizational life. A stressful working life reduces well-being and job health and produces work environment challenges in several social sectors. Add to this a public conversation and discourse where alternative facts and “fake news” have almost become a new norm. Who should you believe in? Who is right? How to do everything? Technology has since industrialization been a driver for societal development and the birth of new products and services. Through history, new technology has created customer value on its own merits. However, today intangible organizational assets such immaterial, intellectual, and human capital are becoming increasingly important for organizational performance in the eyes of the customers. It is fair to say that organizations in all industries and societal sectors across the globe struggle with digital change. And the word digitalization is nowadays used as a label for almost any change initiative, project, or undertaking where computers and information technology to some extent are involved. However, when looking closer there seems to be no clear-cut definition of the word and what it means in practice. Rather, digitalization is used to describe a wide range of change challenges—from disruptive transformations of whole industrial sectors to simple launches of apps, web applications, or internal process adjustments. While writing this book, it has become clear to us that there is a widespread confusion that digitalization these days is used as a remedy for almost any internal or external development need. Therefore, it is more relevant than ever

4  Introduction before to understand the aspects, as well as business logic, behind the elusive phenomenon that everyone talks about. There is a plethora of books on how to go about digitalization challenges, mainly written from a technology perspective. But successful digital change is less about technology per se and more about people and new ways of thinking, feeling and doing. Success lies in the people side of change. And that is what this book is about. To clarify from the start: our guiding definition in this book is that digitalization is a transformational term that refers to the individual, social, organizational, and societal implications that come out of the diffusion and adoption of new information technology (Iveroth et  al., 2018). And this rapid development is not just affecting service organizations. Manufacturing companies nowadays need to offer additional services, or integrated product-service solutions, in addition to, or instead of, their traditional offerings in order to stay innovative and meet demands, needs, and expectations posed by competition from lower cost economies (Lightfoot et al., 2013; Oliva and Kallenberg, 2003; Stauss et al., 2010). This change is often in the literature referred to as servitization, a term coined in 1988 by Vandermerwe and Rada (1988). Servitization has been described as “a business-model change and organizational transformation from selling goods to selling an integrated combination of goods and services” (Bustinza et al., 2015, p. 53). In this way, the environment in which both private and public organizations are operating is changing at an accelerating speed, with trends such as servitization and digitalization at the forefront (Coreynen et al., 2017). As a response to changes in the external environment and an attempt to increase the understanding of customer behavior, concepts such as customer journey (Richardson, 2010) and co-creation of value (Lenka et al., 2017; Payne et  al., 2008) have been adopted to understand customers perception of a particular product, service, or brand. In service industries and service research fields, these external, customer-focused concepts have been discussed for years (Galvagno and Dalli, 2014; Halvorsrud et al., 2016). Manufacturing organization and industries were late adopters but have today more attentiveness towards these elusive customer-focused concepts by offering services and integrated product-service solutions triggered by both digital technology and customer demand (often having consequences for their whole organization and business model). There is also a growing interest within the public sector to focus on “services-tocustomers” and get feedback from different societal stakeholders. And all this is catalyzed and accelerated by new digital technology. As we hinted in the beginning of this chapter, the overarching digitalization challenge is twofold: there are both external customer challenges as well as internal organizational challenges to consider. When approaching the external customer side of digitalization, we should first digest one crucial observation from our own research: customer satisfaction in

Introduction 5 Swedish industries has decreased since 2010 (Hallencreutz and Parmler, 2019). This research will be thoroughly discussed in Chapter 3, but what we see is that digitalization affects consumer behavior and customers’ demand, needs, and expectations. And customers’ perception of this outburst of new digital services is not always positive. This is linked to what we earlier referred to as the digitalization paradox—digital services come closer and are available around the clock, but personal relations seem to go astray in the process. And this paradox is a critical aspect to consider, since our recent research also shows that the ability to provide personal and proactive service is a much stronger driver for customer satisfaction compared to product features. Our conclusion is that we—managers, consultants, and researchers—must be much more aware of the organizational consequences of these somewhat paradoxical collective changes in customer behavior that have emerged through digitalization. However, when approaching the internal organizational and employee side of digitalization, we see other challenges. The management of the relationship and interaction between the customer and the organization breeds and translates into encounters that lie inside the organization. If we are set out to abridge the digitalization paradox, then we must not only understand the digitalization process connected to relationships with customers but also understand how to lead, manage, and control digital technology within the organization. This is crucial since these internal processes provide the very foundation of delivering the value proposition to the customer in the first place. This is by no means trivial, and in fact, this has less to do with technology per se and more about how to change our own behavior. For example, IBM (2008; Jørgensen et al., 2009) conducted a study of digital change projects based on faceto-face interviews and surveys with over 1500 practitioners worldwide. Their research suggests that the soft factors are becoming increasingly important. More precisely, and as Table 1.1 illustrates, the study shows Table 1.1 Major Digital Change Challenges Changing mindsets and attitudes (soft factor) Corporate culture (soft factor) Complexity is underestimated (soft factor) Shortage of resources (hard factor) Lack of commitment of higher management (soft factor) Lack of change know how (hard factor) Lack of transparency because of missing or wrong information (hard factor) Lack of motivation of involved employees (soft factor) Change of process (hard factor) Change of IT systems (hard factor) Technology barriers (hard factor) Source: Adapted from IBM, 2008, p. 12; Jørgensen et al., 2009, p. 40

58% 49% 35% 33% 32% 20% 18% 16% 15% 12% 8%

6  Introduction that in digital change projects, hard and tangible issues of digital technology are not the main concern (such as change of IT-systems and dealing with technological barriers). These are not the winning criteria in managing digital change. Instead, it is the soft factors of managing people and their behavior, motivation, attitude, culture, and mindset. These factors are also the most difficult to get right. The IBM study also concluded that a common denominator among successful organizations is that they distinguish themselves by treating the management of digital related change as a core competence and nurture it as a professional discipline. These companies have developed tools, models, and processes for managing the soft issues of organizational change. More recent studies (see, e.g.: Cascio and Montealegre, 2016; Södergren, 2018; World Economic Forum, 2016) not only confirm such notions but also contend that stronger focus on soft factors might be even more important today and in the near future. For example, the comprehensive report from World Economic Forum (2016, p. 22) in Davos about the effects of digitalization argues that: Overall, social skills—such as persuasion, emotional intelligence and teaching others—will be in higher demand across industries than narrow technical skills, such as programming or equipment operation and control. . . . Cognitive abilities (such as creativity and mathematical reasoning) and process skills (such as active listening and critical thinking) will be a growing part of the core skills requirements for many industries. We might offer world class technical solutions and flawless internal change processes, but if we fail in handling the soft immaterial aspects from the customers perspective, we will leave the customer with an awkward feeling of being neglected, forgotten, and perhaps not seen as important. And if we have blind faith towards structures and technology without acknowledging employees and their behavior, the digital change will go astray and ultimately fail. Overall, our guiding principle in this work is that there is a tension between technology, organization, and customer as their development is out of step with each other. Roughly put, it takes a while for the organization and its people to catch up with technological changes, while customers might embrace the new much faster and put pressure on from the outside. One of the purposes and contributions of this book is to illustrate these tensions and discuss how we can synchronize them and make them work and develop in tandem. This book focuses on the people side of digitalization. The idea behind it is that organizations in general should improve their ability to understand, lead, manage, and empower people in such ways that they at least to some extent keep up with the perceived societal changes out there, catalyzed by digitalization. We start this journey with the subsequent

Introduction 7 chapter that provides an historical overview of the evolution of information technology (IT) during the last 60 years as well as examine the different ways technology and organization have been studied. The purpose is to provide a frame and background for later arguments and discussions. Then in Chapter 3, we will approach the current digital change from the outside by discussing the on-going transformation of customer demands, needs, expectations, and behaviors, supported by results from decades of quantitative market research. After this we will travel back to 18th-century Sweden in the subsequent Chapter 4. There we will visit the Andersson family, who is struggling with potato cultivation. This chapter is composed of a fictional story about how potato production transformed the lives of a family in a small parish in Småland. This historical odyssey visualizes how a new revolutionary farming technology once changed the world and functions as an analogy for technological change. The later chapters of the book will refer back to the story in order to highlight different important facets of change and explain the plethora of its adjacent leadership and management choices, activities, and strategies. Then in Chapter 5 we will move back to current times and go inside the organization and discuss different strategic approaches to digital change. This includes The Digitalization Map that explains that there are four different kinds of digital changes that necessitates their respective ways to strategies, control, communicate, and lead. Then the following Chapter  6 will be more practice oriented as the chapter explains what it is that leaders actually do when they lead employees and the whole organization through a digital change. This will be done by presenting The Commonality Framework for Digital Change that communicates the different activities, leadership roles, and resources that are at play during such a change. We finish off with a last chapter that wraps up and summarizes the main points of the book. Now let us in the next chapter begin by looking in the rearview mirror and see how digitalization has developed across time and what we can learn from this. We do so because the understanding of current digital challenges can become deeper if we understand the legacy of digitalization, and the historical lessons that it yields, and such insights of the past can translate into better decisions, choices, and actions.

References Bustinza, Bigdeli, Baines & Elliot (2015). Servitization and competitive advantage: The importance of organizational structure and value chain position, Research-Technology Management, 58(5), pp. 53–60. Cascio & Montealegre (2016). How technology is changing work and organizations, Annual Review of Organizational Psychology and Organizational Behavior, 3(March), pp. 349–375.

8  Introduction Coreynen, Matthyssens & Van Bockhaven (2017). Boosting servitization through digitization: Pathways and dynamic resource configurations for manufacturers, Industrial Marketing Management, 60(January), pp. 42–53. Galvagno & Dalli (2014). Theory of value co-creation: A systematic literature review, Managing Service Quality, 24(6), pp. 643–683. Hallencreutz  & Parmler (2019). Important drivers for customer satisfaction— from product focus to image and service quality, Total Quality Management & Business Excellence (March), pp. 1–10. Halvorsrud, Kvale & Følstad (2016). Improving service quality through customer journey analysis, Journal of Service Theory and Practice, 26(6), pp. 840–867. IBM (2008). Making change work. Continuing the enterprise of the future conversation (IBM: IBM Global Services). Iveroth, Magnusson  & Lindvall (2018). Digitalisering och styrning (Lund: Studentlitteratur). Jørgensen, Owen & Neus (2009). Stop improvising change management! Strategy & Leadership, 37(2), pp. 38–44. Lenka, Parida & Wincent (2017). Digitalization capabilities as enablers of value co-creation in servitizing firms, Psychology & Marketing, 34(1), pp. 92–100. Lightfoot, Baines & Smart (2013). The servitization of manufacturing: A systematic literature review of interdependent trends, International Journal of Operations & Production Management, 33(11–12), pp. 1408–1434. Oliva & Kallenberg (2003). Managing the transition from products to services, International Journal of Service Industry Management, 14(2), pp. 160–172. Payne, Storbacka & Frow (2008). Managing the co-creation of value, Journal of the Academy of Marketing Science, 36(1), pp. 83–96. Richardson (2010). Using customer journey maps to improve customer experience, Harvard Business Review, 15(1), pp. 2–5. Södergren (2018). Förändringsförmåga, in: Iveroth, Lindvall & Magnusson (Eds) Digitalisering och styrning, pp. 383–409 (Lund: Studentlitteratur). Stauss, Nordin  & Kowalkowski (2010). Solutions offerings: A  critical review and reconceptualisation, Journal of Service Management, 21(4), pp. 441–459. Vandermerwe & Rada (1988). Servitization of business: Adding value by adding services, European Management Journal, 6(4), pp. 314–324. World Economic Forum (2016). Global challenge insight report: The future of jobs employment, skills and workforce strategy for the fourth industrial revolution. Available from: http://www3.weforum.org/docs/WEF_Future_of_Jobs. pdf [Accessed 2020–02–24].

2 Putting Digitalization in Perspective

Introduction This chapter provides an historical and theoretical background to the evolution and adoption of information technology (IT)1 that gives a context and frame for later parts of this book. The historical background starts by defining and conceptualizing digitalization—a word often used without a clear meaning. Then follows and historical overview where we first reflect upon older forms of IT and then explain six forms of organizational learning that an organization goes through when appropriating digital technology. The later parts of the historical background are composed of a description of four waves of digitalization from the middle of the last century until today. These different waves explain how digital technologies have evolved from being large and standalone units that enabled automation to the more present forms that have the potential to transform organizations, markets, and societies. Particular attention is paid to organizational consequences of the advancement of digitalization as well as discussion of current trends. The second part of the chapter explores the three different types of theoretical streams that have been used in studies of technology and organizing during the last 60  years: Technology imperative, Organizational imperative, and Entanglement-in-practice perspective. These three different theoretical lenses afford three different rationales of how technology influences change and organizing. Now let us begin by exploring the main theme of the book: digitalization.2

Conceptualizing Digitalization The words “digit” and “digitization” come from the Latin term “digitus”, which means finger or toe. Originally this was connected to figures and the activity of counting numbers, as a hand or a foot can come in handy in such actions (Cöster and Westelius, 2017; Ong, 1995). Today the term Digitization has a similar connotation since it refers to the

10  Putting Digitalization in Perspective conversation process of transforming analog data3 into digital data.4 Google books’ scanning of physical into digital books is an illustrative example of this process. Digitalization, however, is a more transformational term as it refers to the individual and social, organizational, and societal implications that come out of digitization (Iveroth et al., 2018b). Since computers and digital systems are now increasingly interconnected, it opens for transformational change at all the three levels—individual, organizational, and societal. Historically, technology-enabled change that influences these three levels is nothing new. There have been a number of dominant technologies across time that have had a similar transformational effect and have amounted into different industrial revolutions: • • •

The first industrial revolution took place in late 18th century and was the outcome of steam and waterpower and mechanical production. The second revolution was in the late 19th century propelled by electricity, mass production, and division of labor. The third industrial revolution of the 1960s was enabled by electronics, IT, and automated production.

Currently there are many that argue that we are now facing a fourth industrial revolution (also referred to as industry 4.0) because of digitalization (see, e.g.: Archibugi, 2017; Brynjolfsson and McAfee, 2017; Iveroth et al., 2018b; Lasi et al., 2014; Schwab, 2015; World Economic Forum, 2016). There are, and has been for some time, several aspects that have contributed to this development. For instance, Lasi and his colleagues (2014) argue that there are both pull and push triggers that lie in the foreground of the Fourth Industrial Revolution (4IR): The pulling triggers include demands for shortened development and innovation periods in organizations; increased individualization where the customer sets higher demands for tailored products and services (“batch one size”); new customer demand, needs, and expectations; higher flexibility in organizations and production; quicker decision making processes through decentralization and flattened organizational structures; and finally, resource efficiency because of shortage, ecological, and sustainability factors. The push triggers are composed of the development of now commonly used technologies such as computers, smartphones, software applications, and 3-D printers. On a higher level the push triggers also include: increased automation and mechanization that enables robots to support physical work; “smart factories” or “autonomous manufacturing cells” where work and decisions are decentralized to computers and robots; miniaturization of computers into a small number of cubical centimeters.

Putting Digitalization in Perspective 11 At the same time, there are arguments raised that digitalization is more of a hyperbole with little effect in comparison to earlier industrial revolutions (for further discussion and examples, see, e.g.: Boyd and Holton, 2018; Cetri Magazine, 2017; Peters, 2017; Poole, 2017). One argument is, for example, that digitalization is just a natural extension of the third industrial revolution that was enabled by IT and electronics. One strong advocate for the 4IR is the economist Klaus Schwab (2016, p. 3), founder and Executive Chairman of the World Economic Forum. According to him, there are three distinct reasons for why digitalization is indeed a new industrial revolution: Velocity: Contrary to the previous industrial revolutions, this one is evolving at an exponential rather than linear pace. This is the result of the multifaceted, deeply interconnected world we live in and the fact that new technology begets newer and ever more capable technology. Breadth and depth: It builds on the digital revolution and combines multiple technologies that are leading to unprecedented paradigm shifts in the economy, business, society, and individually. It is not only changing the “what” and the “how” of doing things but also “who” we are. Systems Impact: It involves the transformation of entire systems, across (and within) countries, companies, industries and society as a whole. We concur with Schwab and similar arguments—undeniably digitalization will have profound effect on all levels of society. However, if you reflect over Schwab’s text (2016) you will notice a somewhat simplistic tone at the same time as he ignores making reference to other work being done on the same or similar subject within most scientific disciplines. One good reason for doing so is that from a historical point of view the 4IR can give great “promise or potential peril” (Schwab, 2016, p.  8) for nation-states, organizations, and human kind as such. Most likely Schwab’s intention was to communicate such a message in a clear and easy way in order to create a new mindset and increased awareness for policy makers, governments, business leaders, and civil society. This becomes clearer if we consider later work (Schwab and Davis, 2018) where there are a more grounded connection to a variety of 4IR’s complexities and challenges, such as security, integrity, medical applications, lack of political will, asymmetrical distribution of power, inadequate institutions, and so forth. Schwab’s worries are warranted. On the one hand, and with the right mindset, knowledge, and empowerment, 4IR has the potential to significantly improve for example working conditions, company growth, income levels, all aspects of sustainability, and quality of life for

12  Putting Digitalization in Perspective humanity. On the other hand, there are a great number of inherent risks with 4IR. For instance, the revolution can create significant inequality if only a selected few companies and governments master the innovations and technology of 4IR. Another possible scenario is that a large part of the lower-skilled working force is replaced by automation and robotics. In addition, unemployment can also increase because the new jobs that 4IR do create may require higher levels of education and specialization skills. What can also happen is that the mix of increased global internet connection and increased unemployment and inequality creates fragmented societies, extremism, and civil disorder and unrest. Such a negative spiral of development can also be propelled forward by fake news and deliberate disinformation. The outcome of the 4IR and how it will affect nations, organizations, and people is too early to tell, and many questions will remain unanswered for quite some time. However, what we do know is that what happens tomorrow, and how 4IR will play itself out connects directly to the decisions and actions made today.

Historical Overview of Digitalization Earlier Forms of IT One important departure point for describing the historical development of digitalization is to shortly reflect over its core and foundation: IT. Originally, we developed this technology to help us managing and dealing with all sorts of information and data. Generally, IT has the main purpose of facilitating us with: writing down and decontextualize information, storing the information, (often) transporting the information, and then finally decoding it in such a way that it is comprehendible at the other end in order to make some sort of a decision. Therefore, IT is by no means a new thing, and most civilizations across history have had their own way of dealing with this problem. About 5000 years ago the Sumerians had their cuneiform that was written down on clay tablets, the Incas had their khipu that was knots on a string, the Egyptians had their hieroglyphs, and different forms of tally sticks were used in the UK and other places in Europe. In most cases these forms of technologies were developed for the purpose of keeping track of records, taxes, military information, and calendrical information (Cöster and Westelius, 2017). Other examples of information technology inventions that made a stronger imprint on our own society are the alphabet, Morse code, and the telegraph. These forms of IT have across time struggled with the same problem: contextualization. All of them have tried to develop different systems, standards, routines, educational systems, and so forth to make sure that information is encoded on the one end, and that it is decoded on the

Putting Digitalization in Perspective 13 other end in as much similar manner as possible. Modern forms of IT are no exceptions, as Kallinikos notes (2001, p. 62): The information that computer-based systems generate is often decontextualised, i.e., it has been taken away from the context that it now describes or refers to. However, in order to be interpreted, information must be re-contextualised, i.e., the context to which it refers must be reconstructed in the minds of the people that deal with this information. Even in our globalized world, the management issues that arise are in many cases not necessarily connected to technological problems. Instead, management and control problems with digital technology are often about making sure that the context at both the sender and receiver end are similar. As Brown and Duguid (2001, p.  204) elegantly explain: as technologies increasingly allow people to communicate across space and time, as knowledge is disembedded in one place to be reembedded in another, the critical question concerns the degree to which the embedding conditions at both ends of the communication are similar. To the extent that they are, then communication and coordination are likely to be successful. To the extent that they differ, communication and coordination are likely to break down. One notable difference with more modern forms of IT is that it has transcended limitations of space and time in an increasing rate. For example, Morse code, together with the telegraph, enabled information to be transported with the speed of eight words per minute from the U.S. to the UK in the late 19th century. This revolutionary technology enabled companies to be dispersed across the globe; for example Morse code and the telegraph was one of the cornerstones in the British Empire. Eventually the telegraph was replaced by other IT innovations such as the telephone and radio that opened for transmitting information even quicker and across greater geographical distances. Such forms of technology were based on analog and mechanicalelectronic technology, and it was not until the 1950s that research and experimentation with digital based technology began. The military and larger organizations (e.g., IBM and Bell Labs) and universities primarily drove this research forward. However, these early attempts of digitization were performed in isolation as they did not have any major influence on society at large. And it is not until recently that digitalization has had a more profound effect on individuals, organization, wider systems, and society.

14  Putting Digitalization in Perspective But let us stay in the middle of the last century to see if we can make some historical lessons from earlier attempts of digitalization. One way to do so is through Richard Nolan’s stages theory of IT and organizational learning (Nolan, 1973, 1979, 2000).5 This is a normative geared theory but suits us well here since it illustrates how IT and digitalization have developed across the last 60 years and how such development influences organizations and organizing. The theory serves several insights that can be of value for discussion and understanding of the current problems and opportunities of digitalization. Six Stages of Organizational Learning

ORGANIZATIONAL LEARNING

The stage theory proposes that since the 1950s, the assimilation of IT in the organization can be illustrated as six stages of organizational learning that together forms an S-curve—see Figure 2.1. These stages are composed of: Initiation, Contagion, Control, Integration, Data Administration, and finally Maturity—see Figure 2.1.6 According to the

Contagion Initiation

Integration

Control TIME

Data Administration

Maturity

Figure 2.1  Six Stages of Organizational Learning Source: Adapted from Friedman, 1994, p. 137; King and Kraemer, 1984, p. 467; Lyytinen, 1991, p. 94; Nolan, 1973, p. 401

Putting Digitalization in Perspective 15 theory, organizations go through these stages when they try to adopt a new technology. In the first stage of Initiation the organization is, with caution, making limited investment in a new technology. Controlled experiments and trials are performed, and the aim is to prove and understand its potential value for the organization. In most cases, the experiments are performed by one or a few departments or functional areas, senior management is less involved, and there is a lack of clear connection to overall direction or strategy. The second stage is termed Contagion, and here there is a higher degree of organizational learning compared to the earlier stage (given that the organization has not abandon the new technology altogether in the Initiation stage). Trials and experiments are performed in an uncontrolled manner, technology is used ineffectively, and there is a high degree of slack. Senior management is now fully dedicated to the new technology as they promote its use and incorporate it in the organization’s strategy. There is great demand for the new technology and there is a widespread fear that the organization will be outmatched by competitors if they do not master the technology as soon as possible (and hence the label contagion). The stage often ends with a crisis with runaway budgets and users as well as managers being less happy, frustrated, and exhausted (Grégoire and Lustman, 1993). The uncontrolled growth and ultimately inefficiency in the Contagion stage amounts into a situation where management tries to gain greater control of the developments before it escalates (Nolan, 2000)—and this is the third stage of Control. In this stage growth, organizational learning, and slack decrease and efficiency and control increase. The new technology is centralized and formalized and problems with technical malfunctions as well as overspending from earlier stage are addressed. There are also efforts of standardization, and more attentiveness is paid to the people working with the technology rather than the technology itself (by, e.g., professionalization). In the fourth stage of Integration, there is a balance between control and growth, and different independent and disparate systems are integrated. The technology is now more reliable and delivers a high-quality service to its users. The standardization process that began in earlier stages continues even further. The accumulated learning from earlier stages results in users being more knowledgeable than earlier and capable of using the technology. Therefore they also become the main driving force for development instead of technology-specialist (Friedman, 1994). As illustrated in Figure 2.1, it is in this stage that a competing technology often is introduced, as there is an overlap of S-curves.7 The next stage is referred to as Data administration, and here attention is paid towards the data and information that comes out of the

16  Putting Digitalization in Perspective technology rather than the technology in itself. Data and information are considered being a greater strategic resource compared to earlier. In this phase, the use of the technology becomes more seamless and is one important enabler for many processes within the organization. There is also tight control of the resources spent on the technology, and controlling and steering committees are often used. Top management are actively involved and they view the technology as one central part for achieving strategic objectives by, for example, integrating suppliers and customers (Favaretto, 2015). At the same time, and as illustrated by overlaps of S-curves in Table  2.1, another technology (or several technologies battling dominance?) is on the rise. In the last stage of Maturity, the technology mirrors the organization and its information flows, and the IT is embedded in every part of the organization. The technology is matured and contributes significantly to the effectiveness and efficiency of the organization. The technology is increasingly being used for forecasting and future planning and the management control is used to its full extent. The role of the technology shifts from being one part of achieving strategic objectives into being a significant key-enabler for attaining full competitive advantage. Overall, central to all the six stages of organizational learning is the notion of resource slack. Across time there is often a high degree of resource slack in the first three faces (i.e., Initiation, Contagion, and Control) and a stronger degree of control in the remaining stages where the users are to a greater extent held accountable for technology expenditure (Lyytinen, 1991; Mahmood and Becker, 1985). When there is a slack of resources, this often translates into learning and experimentation activities that nurture innovation. However, such activities are actively discouraged and restricted in the later stages. The willingness to invest in the current technology is limited in later stages but at the same time organization that aims to progress to the next S-curve have to provide resource and slack to the emerging technology (i.e., the overlap of the different S-curves in Figure 2.2). Four Waves of Digitalization So, the six stages (that amounts into an S-curve) constitute the different phases of learning that the organization goes through when adopting a new technology. Now, if we zoom out and examine the development of digital technology since the 1960s, there have been four different S-curves: Data Processing (DP) wave, Desktop wave, Network wave (the first three waves are mainly based on the work of Nolan, 2000; Nolan and Bennigson, 2003), and Cyber-physical wave, as illustrated in Figure 2.2. Let us start with going through the first DP wave.

Putting Digitalization in Perspective 17

ORGANIZATIONAL LEARNING

Cyber-Physical wave

1960

Network wave Desktop wave DP wave

1975

1980

1995

2010

2015

Figure 2.2  Four Waves of Organizational Learning Source: Extended and adapted from Favaretto, 2015, p. 25; Nolan, 2000, p. 332; Nolan and Bennigson, 2003, p. 3

DP Wave The DP wave started approximately in the beginning of the 1960s and ended around the 1980s. During this time, the dominating technology was mainly composed of centralized standalone mainframe computers, and the organizations often had a multidivisional functional hierarchical structure. Roughly put, centralized big computers aiding big and centralized organizations. The users of IT were in most cases engineers or scientist that used the technology for scientific purposes or managers and administrators that used IT for commercial purposes. In this wave technology played an automating role (Zuboff, 1988) by automating advanced mathematical calculations for scientists, for instance. Or aiding managers and administrators in running of their large organizations more efficiently by, e.g., automating payrolls and attentiveness of customer payments. The technology was viewed as “big and large machines”, and this was mostly because that was what they were: you went to a large room where the machine was located and there you put in information in the form of a punched card to enable advanced calculations. The control and management of the DP computers was handled by a so-called DP manager. These individuals were often seen as having a command-and-control style of managing and exercising a “benevolent dictatorship” (Nolan, 2000, p. 346). With the support of higher management their main purpose was to use the technology to support the organization current and traditional way of doing business—avoiding experimenting

18  Putting Digitalization in Perspective with the technology to explore new innovative ways to do business (Nolan, 2000; Nolan and Croson, 1995). One important actor in this wave was IBM. In the early 1950s the company started to produce computers for commercial use. For example, in the 1950s you could lease the successful IBM 650 for about $3250 that could help you with programming, modulation, and calculation (Nolan, 2000). For several decades, IBM became a dominant driving force in digitalization by continuously introducing innovations and establishing standards and having a strong position and influence on digitalization as a whole. Indeed, they can be compared with current digital and bigger companies such as Facebook, Google, and Amazon—for better or worse (Lindvall and Osowski, 2018). Desktop Wave Close to the end of the DP, people began to understand that greater computer capacity could be achieved by connecting several computers, and this marks the transition into the Desktop wave. This period started about 1980 and lasted until 1994 (Nolan, 2000; Nolan and Croson, 1995). In this wave, the technical infrastructure was characterized by centralized mainframe computers (for formal use) and decentralized microcomputers (for informal use). This situation emerged by the introduction of Apple’s microcomputer in the late 1970s and with IBM’s Personal Computer (PC) in the early 1980s (with a Microsoft operating system and parts of the hardware from Intel). Over time PC became the most dominant technology that enabled, e.g., word processing for secretaries and administrative personal, graphical systems for desktop publishing and arts departments, and spreadsheets for finance and accounting employees. The microcomputers were not only more user friendly because of their graphical interface (compared to the DP computers), but they were also relatively cheap. Another significant driver for change was that PC vendors sold directly to single departments or end-users, often without any direct approval from the DP managers. Organizational learning increased when the PC was formally accepted. People began to experiment with, e.g., connecting and integrating computers and different ways to analyze and present the information that the computers produced. There were also some demands for a flatter organization structure compared to the multidivisional and functional hierarchical structure of the DP wave. An organizational structure that embraced risk-taking, teamwork, networking, analytical work, and flexibility, and less of a command-and-control approach. However, such demands would not translate into any larger organizational changes until the next wave. Overall, and on a more aggregated level, the IT industry

Putting Digitalization in Perspective 19 began to transform and open-up for new actors, increased price competition, and horizontal integration. Furthermore, in this wave technology played a political role as the microcomputers threatened the position of the DP manager and use of DP based technology. Both IBM’s and Apple’s computers were attractive for individual customers who began to buy and use them. At the same time, the very same organization were using DP machines. As a result, there were perceived risk connected to security and data integrity. In addition, whose figures should you trust and base your decisions on: information from the microcomputers or information from the DP machines? And in extension, if you choose to base your decision on information from microcomputers, there were numerous microcomputers giving you different numbers. Because of such situations, the role and term Chief Information Officer (CIO) was introduced in the early 1980s who was supposed to bring some order to the chaotic situation. This introduction of the term CIO illustrates a changed perspective towards technology. Now IT necessitates a new form of leadership, and information is considered an important key resource. In addition, employees are beginning to be referred to as “knowledge workers”, and IT is no longer viewed as an “industrial like machine” and is viewed instead as a technology that can provide information and knowledge. Overall, the purpose of IT went from automating existing business processes into informing decision making and aiding the process of analyzing and presenting data: a shift of using IT to “automate” into “informate” (Zuboff, 1988). Network Wave Now we move into the third S-curve of the Network wave that starts in 1995 and ends around 2015. This period is characterized by wide use of the internet and intranets that required less of the earlier control oriented approach and more organizational acceptance for open-standards and common platforms (Nolan and Bennigson, 2003). Here the so-called dotcom bubble emerged as a result of overrated dot-com companies. We also see a worldwide worry for the millennium bug (Y2K problem). In this wave, the challenge of the CIO was to coordinate rather than control the IT, as there were numerous computers interconnected via intranet, that was interconnected with numerous computers outside the organization through the internet—and on top of this things changed continuously. For example, IT was increasingly being used to communicate and interact with both customers and suppliers outside the organization that could “self-serve” themselves through using web-browsers. As such, the borders of the organization became more ambiguous than ever

20  Putting Digitalization in Perspective before as the internal information architecture became more and more connected and integrated with the computer systems of actors such as suppliers, partners, and customers. Just in the same way as the DP wave’s IT architecture mirrored the organizational structure of multidivisional functional hierarchical structure, this wave had an IT architecture that mirrored a network organizational structure that was more flexible, dynamic, and organic (Nolan, 2000). Significant investments in IT were made in this wave to the extent that many questioned if such investments would actually translate into any productivity gains. The so-called Solow Paradox or Productivity Paradox illustrates this from the early days of the rising Network wave (when the Desktop wave still was dominant): “you can see the computer age everywhere but in the productivity statistics” (Solow, 1987, p.  36; we will return to this paradox later in this chapter). Indeed, there were many examples of failed IT initiatives and investments (e.g. the dot-com bubble). One of the consequences was, for example, that the CIO, who in earlier periods was considered being a “star”, was now often perceived as a scapegoat of IT failures (with importance and status of the CIO diminishing accordingly). It is in this wave that IT to a larger extent than earlier contributes to transforming parts of the organization and its processes. For example, Amazon sold books through the internet with minimal inventory, and Levi-Strauss used data from retail stores and geo-demographic data to match supply and demand in different regions (Nolan, 2000). In many ways, IT propelled a development from “make-and-sell-strategy” to “sense-and-respond-strategy”. Earlier, the organization would make a product and store the offer in an inventory until a customer bought it through a transaction. Now in this wave, IT enables the organization to listen to the customer’s wants and needs, produce the product accordingly, sell it to the customer, and subsequently continue the relationship and communication with the customer. This shift is still continuous until today and has increased in recent years as the next chapter will illustrate, where we will visualize the transition from make-and-sell to sense-andrespond through several examples and results from our extensive market research. Overall, the network period was also composed of many followers that were less proactive and who struggled with keeping up with the change from the outside world that sometimes took them off-guard. As Nolan notes (2000, p. 374): More often than not, however, a particular IT breakthrough surprised companies, and they found themselves in a position of strategic jeopardy—that is, the breakthrough forced a company to match a competitor’s IT initiative just to keep their customers.

Putting Digitalization in Perspective 21 It was also in this wave that organizations began to change their approach to IT from managing a technology that produces information into a view of technology that in itself can create competitive advantage by enabling new ways of doing business and adding value to products and services for both customers and suppliers. In other words, a shift “from managing technology to managing information resources enabled by IT” (Nolan, 2000, p. 383). Cyber-Physical Wave The original stage theory only covers the first three waves (Nolan, 2000), but if we move beyond this we can with some certainty argue that the core technology of the new wave is not composed of one technology but instead composed of several technologies that are interconnected into a Cyber-Physical System (CPS; Borgia, 2014; Lasi et al., 2014; Poovendran et al., 2011). Such a system is composed of software that is embedded in tangible products and artifacts that share data and information with other systems to achieve a function or influence a physical process. In short, the physical and the digital world become intersected. Or more specifically explained: The notion of CPS [Cyber Physical Systems] refers to a next generation of embedded ICT systems [i.e., Information Communication Systems] where computation and networking are integrated with physical processes and they control and manage their dynamics and make them more efficient, reliable, adaptable and secure . . . Information about physical processes, for example gathered through sensors, are transferred, processed, and used in the digital world, but they may also affect physical processes through feedback loops. The influence of CPS system on our daily lives is suggested to increase significantly once the internet-of-things and 5G networks become more established. CPS systems exists today and include, for example: selfdriving cars and collision avoidance, military drones, control systems for airplane and car traffic, artificial heart pacemakers, and remote robotic surgery. A commonplace, future, and somewhat rough example of a CPS system is a “smart bed”. Imagine that you wake up one morning, having slept quite badly. The sensors in the bed will have picked up on this during the night and have therefore lowered the temperature by interacting with the software in the heating system of the apartment. However, since this was apparently not enough the bed has concluded that you need a new pillow and that there is too much light in the bedroom. Therefore, the “bed” has contacted a number of curtain and pillow vendors with data about your

22  Putting Digitalization in Perspective size and weight of your head and window measures. Offers from these are now in your mailbox. And finally, since you have woken up the bed tells the coffee-machine to start working on your morning coffee. We are indeed in a new wave, however to what extent we should refer to this current period as the Cyber-physical wave remains to be seen. In fact, there are signs that we might be in the contagion stage given that there is such focus, discussion, and organizational resources spent on exploring technologies where CPS-system is central: artificial intelligence, smart factories, big data and business analytics, eye-tracking devices, industrial sensors, speech and facial recognition, drones, robots—just to name a few. Being located in the contagion phase of the current wave can be exemplified by Murray (2015, p. 6), who proclaims that “Together these innovations are hurtling us toward a new industrial revolution. Savvy corporate leaders know they have to either figure out how these technologies will transform their businesses or face disruption by others who figure it out first” (also noted by: Cascio and Montealegre, 2016). However, exploring different future trajectories and scenarios is outside the purpose and scope of this book (and no one can predict the future), but we can make some remarks regarding the current developments. In general, the development factors and triggers of the 4IR that was presented earlier in this chapter are even more relevant today compared to over five years ago (Lasi et al., 2014): shortened development and innovation periods in organizations; “batch one size” concept and increased individualization where the customer sets higher demands for tailored offerings; higher flexibility and agility in organizations and production; quicker decision making processes through decentralization and flattened organizational structures; and finally, resources efficiency because of shortage, ecological, and sustainability factors. Many of the developments that began in the network wave has in the Cyber-physical wave come to almost full force. In the earlier wave IT, and the information that it provided, it was seen as an important part of realizing organizational strategies and processes. Now however, digital technology is progressively a central part of the whole organization and its business. Put differently, if digital technology would suddenly disappear then almost all companies would be out of business since digital technology is deeply embedded in most organizations and its processes. In extension, such a situation also provides greater risks, as most things are, or will be, connected to everything. The movement of from make-and-sell towards sense-and-respond (that began in the earlier wave) has intensified. There is a development towards mass customization and economies of scope (i.e., instead of volume, cost savings are done through producing several products with greater variety that are similar yet different), where customer segmentation and

Putting Digitalization in Perspective 23 knowledge about customer needs and wants becomes critical. Now more than earlier it becomes important to listen to customers, analyze their data, understand them, and respond by producing a tailored offering. In other words, a swing from strong industrial and mass-market production delivered through transaction towards to a knowledge society focusing more on customer service and values where offerings are offered through continuous interaction with consumers. Overall in a management control perspective the movement towards a sense-and-respond strategy translates into a shift from cost control and command-and-control to greater empowerment of employees, from product to service, from cost to value, from being reactive to being proactive (Björkdahl and Holmén, 2019; Lindvall and Iveroth, 2018). We will show in the subsequent chapter how this overall movement also has had a negative effect on customer relationships and customer satisfaction during the last decade. The subtle and not always conscious move from an instrumental “make-and-sell” business logic to a more organic “sense-and-respond” logic has triggered changed customer behaviors as well as new demand and expectations. As a result, the digitalization paradox has emerged: digital services have come closer and are literally just a smartphone away, but the distance to personal, human relations seems to be increasing. This challenge will be thoroughly discussed in our next chapter. Moving on, another pattern of the development in this wave is that value creation is to a greater extent than earlier performed in connection to the environment in which the organization is situated. Traditionally value creation was first and foremost performed inside the organization, but now products and services are often developed and distributed in deep collaboration with both suppliers and customers, and consequently the borders between the organization and outside world become blurred. An example of this development is that both practitioners and researchers frequently refer to organizational context as an ecosystem or business ecology that is composed of actors such as suppliers, customers, distributors and intermediaries, competitors, financers, standardization organizations, authorities, regulating organizations, politicians, opinion leaders, and the general public. In this highly dynamic environment such actors “influence each other, enter into contractual relations, compete, imitate, constrain, merge, split, and absorb each other through acquisitions” (Cöster et al., 2020, p. 152). The myriad of actors change continuously over time and value creation and capturing is often performed in exploiting these various actors and their resources in different ways. For example, the current trend of servitization, driven by digitalization, is often delivered and developed in collaboration with different actors in the business ecology. Another example are digital based companies like Airbnb, Spotify, and Uber, which base a

24  Putting Digitalization in Perspective large part of their business on underutilized resources owned by actors in the business ecology. A final feature for the current wave is that digital technology is becoming permeated in almost everything—as the aforementioned examples of the Cyber-physical wave clearly illustrate. Indeed, technology seems to be what now many refer to as ubiquitous, meaning everywhere: digital technologies are almost everywhere and connected to almost anything (Yoo et  al., 2012). This influences not only social interaction but also work and organizing in a much larger extent than earlier (Cascio and Montealegre, 2016; Iveroth et al., 2018b). This empirical development is mirrored in research activities across disciplines. For example, technical and engineered geared sciences focus on what they refer to as “ubiquitous computing” (Abowd and Mynatt, 2000; Lyytinen and Yoo, 2002), where computing can be done by accessing almost any device and be in almost any format (in comparison to the more isolated activity of desktop computing). Similarly, social sciences focus on the concepts of “sociomateriality” within the Entanglement-in-practice perspective that is considered to be “the new black” (Jarzabkowski and Pinch, 2013) because it can “radically reconceptualise our notions of technology and reconfigure our understandings of contemporary organisational life” (Orlikowski, 2010, p.  128). This concept or theory argues that earlier social and material aspects of using technology where separated. Now, however, both social and material aspects are entangled and intertwined during on-going practice. Almost everything we do in practice is both social and material at the same time because of the pervasiveness of digital technology: “the social and the material are considered to be inextricably related—there is no social that is not also material, and no material that is not also social” (Orlikowski, 2007, p. 1437). We will return to the concepts of Entanglement-in-practice and sociomateriality in the end of the second part of this chapter that uncovers different theoretical streams in the studies of technology and organizing. Discussion One way to summarize the historical development digitalization that we just described is by the concept of automate, informate, and transformate (Iveroth et al., 2018b; Zuboff, 1988). In the DP wave, the main purpose of digital technologies was to automate simple work routines, such as handling invoices, payroll, and customer payments. Costs are reduced and efficiency is strengthened through standalone systems. Then we gradually began to understand that we could gain an increasingly amount of computer power by connecting the standalone units into a common system. By doing so, we could use the digital technology to informate work

Putting Digitalization in Perspective 25 that strengthened decision making through increased access to combined information (using systems that today are referred to as business intelligence). Now more than earlier, information could be combined, and physical work gradually became more virtual and analytical that facilitated learning. Finally, starting in the Network wave and continuing in the current Cyber-physical wave, digital technology has enabled us to transformate organizations and sometimes whole industries. Here, and to a much greater extent than earlier, value is created in interactions with and relations to actors outside the organization, and digital technologies open up for innovative business models (Cöster et al., 2020). Digital technology as such has become a transformational power that can change well-established structures and sometimes the very foundation of various industries. For example, digital based companies such as Spotify have transformed the music industry, Uber has changed the transportation industry, and Airbnb has influenced the hotel industry significantly. In this way, digital technology has the potential to offer new business models (or business areas), with new ways to produce, package, and deliver an offering to a market (Iveroth et al., 2018a). Nolan’s stage theory is well established, especially within the field of information systems as well as among practitioners since it is very intuitive and useful (Benbasat et al., 1984; Grégoire and Lustman, 1993; King and Kraemer, 1984; Lyytinen, 1991). However, empirical evidence for Nolan’s stage theory are mixed, and it remains invalidated (see, e.g.: Grégoire and Lustman, 1993; Li et al., 1994; Lucas Jr and Sutton, 1977). According to a review of Favaretto (2015), the mixed results are often due to problems with measuring the stages of growth in each stage and across time. Another significant problem is the operationalization of the model since the different key-terms and concepts are underspecified; therefore, researchers are forced to make their own interpretations. Nevertheless, such problems with validation are not uncommon to many other stage theories within business studies and information systems (see, e.g.: Debri and Bannister, 2015; Galliers and Sutherland, 1991; Kazanjian and Drazin, 1989). In addition, most of the critiques specifically target Nolan’s theories and to a large extent ignore other literature that has come to a similar description and analyses about how digitalization has evolved across time (see, e.g.: Applegate et  al., 2002; Beniger, 1986; Cash, 1994; Lindvall and Iveroth, 2018; McKenney et al., 1995). Overall, Nolan’s stage theory still provides a general, accepted description of organizational learning and growth, and most importantly, it shows the interconnection between digitalization and organizational and management issues. In a broader perspective, one of the most interesting and relevant issues of the development of digitalization across time are the “overlaps” between the different S-curves when there is a high amount of

26  Putting Digitalization in Perspective technological discontinuity (Christensen, 1997; Lepore, 2014). This is when there is a conflict between the further growth of the mature and ruling dominant technology and the new and often dynamic growth of the new digital technology. Proponents of the dominant technology are struggling to preserve power and knowledge against the people who argue for the new emerging technology (Nolan, 2000). Research focusing on times of technological discontinuity has recurrently shown that the organizations that succeed in mastering the new emerging technology often do so because they are willing to make necessary organizational changes required in order to reap the full benefits of the technology. For example, Nolan notes that late in the DP wave the DP managers “discovered that transaction processing could be integrated across the traditional functions: simultaneously, an order could be taken from a customer, inventory reserved, the order scheduled for production in the factory, and an invoice sent” (Nolan, 2000, p. 381). In other words, some managers understood that if they connected different standalone systems, they could improve business operations. However, such improvements would require significant organizational change such as new process, roles, activities, and structures, and this often resulted in disappointment and change resistance. Indeed, Nolan continuous “Failures to consummate the required organizational changes effectively resulted in less than optimal use of computers” (Nolan, 2000, p. 382). Similar arguments can be found throughout research connected to digitalization. For example, as we partly showed earlier, in the 1980s and 1990s many studies explored the so-called Solow’s productivity paradox that “you can see the computer age everywhere but in the productivity statistics” (Solow, 1987, p. 36). This productivity paradox argued that is almost impossible to identify and measure the outcome of information technology investments in terms of higher productivity (Brynjolfsson and Hitt, 1996; Kohli and Devaraj, 2003; Lucas, 1999). Numerous studies were done that aimed to prove the value of IT-investments, but many of these studies were inconclusive. One of the major reasons was that such studies used traditional measures of productivity. These measures were very aggregated and therefore missed the improvements that were located at a local level. The studies were performed mainly during the Desktop wave, and this is when computers often were standalone units that were less interconnected, and the information infrastructure was to a large extent decentralized. For example, the early use of Excel optimized local use and knowledge work (often connected to accounting) but did not have any larger effects on organizational productivity (Lindvall and Iveroth, 2018). It is only later, in the later stage of Network and the current Cyber-physical wave, when digital technology becomes increasingly more interconnected, and increasingly more transformational in nature, that the potential of technology becomes more apparent.

Putting Digitalization in Perspective 27 Also, and more importantly, the productivity studies conceptualized technology as a static and monolithic “tool” that could simply optimize current processes, and by doing so neglect viewing technology as something that can open up and enable change. For example, Dedrick and his colleagues performed a large review of productivity studies and concluded (2003, p. 27): At the firm level, the review further concludes that the wide range of performance of IT investments among different organizations can be explained by complementary investments in organizational capital such as decentralized decision-making systems, job training, and business process redesign. IT is not simply a tool for automating existing processes, but is more importantly an enabler of organizational changes that can lead to additional productivity gains. Likewise, another review concluded: importantly, our review of the literature shows that a narrow focus on “IT” is misguided and misleading. The focus should be on IT-dependent strategic initiatives of which IT represents a fundamental component because technology does not contribute to firm performance in isolation, but instead contributes as part of an activity system that fosters the creation and appropriation of economic value. (Piccoli and Ives, 2005, p. 766) If we move a couple of years ahead, we can find similar ideas about the connection between change and digitalization. For instance, Saunders and Brynjolfsson (2016) argue that the ones that reap the most of their digital investment spend about $9.00 on developing organization and skills and $1.00 on hardware and system. So, many neglect that technology only opens for changes that can lead to productivity gains and increased competitive advantage—but this potential is only realized for those organizations willing to truthfully engage in organizational change issues (and how an organization can go about doing so is partly what this book is about). Indeed, across time there is a recurrent pattern of what Nolan noted as “Failures to consummate the required organizational changes effectively”. One of the reasons for why this happens is that many have a rational perspective of digital technology, or as Piccoli and Ives puts it a “narrow focus on ‘IT’ ” (2005, p. 766). Such a rational perspective translates into a view of technology as a stable, robust, and reliable artifact that when implemented spreads easily in the organization, and subsequently employees simply and automatically adapt to the new circumstances. We will revisit this notion of

28  Putting Digitalization in Perspective technological rationality in later parts of this chapter as well as in Chapter 6, so keep this in mind. What is further relevant when it comes to the phases of technological discontinuity (the “overlaps” between the S-curves) is that they are composed of both disruption as well as continuity as there is both creative accumulation and creative destruction. As Archibugi explains (2017, p. 538): In the creative accumulation model, large firms systematically exploit new technological opportunities as a method to maintain their market shares and to keep outsiders out of business. In the creative destruction model, major innovations are introduced by small companies that become big precisely because they have won the bet on the potential of their new products and processes. It is not difficult to find examples in business history where successful companies prospered according to each of the two models. Table 2.1 illustrates this further. Both incumbents and new entrants are active and make their respective contributions to developments in different industries. Some incumbents realize that there is a change of paradigm going on and manages to mobilize resources, employees, and capital accordingly. Within the

Table 2.1 Models of Creative Accumulation and Creative Destruction Disruption and creative destruction

Continuity and creative accumulation

• Large incumbent organizations that drive innovation with the aim by formal research and exploitation of pre-existing capabilities. • The source of development comes from earlier innovations and accumulation of knowledge. • The innovation process focused on large number of incremental innovations. • High barriers to entry because of high cost of innovation as well as the relevant significance of accumulation of knowledge. • Oligopolistic market dominates. • Development of technology is path-dependent

• Small companies and new entrants that propels innovation forward using economic turbulence to gain market share from incumbent firms. • Exploration and search for new markets and opportunities • New organizational forms that facilitates innovation • Pathbreaking innovations and discontinuous technologies that has the potential to open-up new industries. • New industries with low barriers to entry • High amount entry and exit translates into low levels of concentration and increased competition.

Source: Adapted from Archibugi, p. 538

Putting Digitalization in Perspective 29 photographic film market, Eastman Kodak did not manage this very well, while Fujifilm did so, being one of the leaders within digital photography today. At the same time, there are small firms and new entrants that use pathbreaking innovation that generates growing markets and new opportunities—such as Microsoft (being a new entrant in the 1970s and 1980s), Google, Spotify, and others. In extension, the co-existence of creative accumulation and creative accumulation models suggest that, depending on context and time, organizations are facing different kinds of organizational changes. For some, digital driven change can involve a complete disruption—as in for Eastman Kodak—where change is sudden and dramatic and mainly triggered by outside forces. For others, change is merely an active strategic choice that has been built up and accumulated for quite some time. A new direction is set out by the firm in order to relocate and revive competitive advantage. For example, in 2004, IBM made the choice of a more service- and software-oriented strategy and sold its hardware-oriented PC business in 2004 to Lenovo. This was a radical choice since they have been the key actors in digitalization by developing hardware since the 19th century. They managed to do this because they had accumulated knowledge for some time. So, during technological discontinuity there are different organizations that are facing different types of changes that requires different types of managerial control, leadership, and strategy. Besides this, organizations are also handling change during the times when there is not any larger discontinuity at play. Roughly put, organizations need one type of organizational change during times of technological discontinuity and need another type of change during, e.g., the contagion or control phases of the S-curves. For example, an organization that already masters the digital technology might only need to fine tune, build, and improve their existing processes in order to accommodate to the latest digital developments. This whole notion of different types of strategic organizational changes is precisely what we will discuss and further explore in the strategic geared Chapter 5.

Historical Overview of Technology Geared Organizing Studies Within Management Absent Presence This section and subsections provides and overview of how technology has been studied and conceptualized in research over the last 60 years. This will be done by explaining three different streams of dominant research beginning with the Technology imperative, moving on to the Organizational imperative, and finally ending up in the most dominant current focus of the Entanglement-in-practice perspective (Barrett et al.,

30  Putting Digitalization in Perspective 2006; Markus and Robey, 1988).8 However, before doing so there is a need to acknowledge the point that technology and organizing studies has to a large extent been absent in management research. In fact, in many studies, technology is not brought to the center stage, and its role and influence on organization and management is unacknowledged. For example, Zammuto and his colleagues went through the articles published in three of the field’s top journals between 1996 and 2005 and found that only 2.8% explored the relationship between technology and organization. Similarly, Orlikowski and Scott (2008, p. 435) examined 2,027 articles in four highly ranked journals between 1997 and 2006, and concluded that only 4.9% addressed technology and organization: “Thus, over the past decade of management research, over 95% of the articles published in leading management journals do not consider or take into account the role and influence of technology in organizational life”. These examinations are not recent, and most likely the interest in the relationship between technology and organization has increased due to the general awareness of digitalization; nevertheless they provide some insights into how neglected technology has been over the years. Technology Imperative Since around the middle of the last century, the Technology imperative has been the most dominant stream, and it holds a deterministic view of technology (Hickson et al., 1969; Thompson, 1967). With this perspective, technology is viewed as an independent physical object with material properties that determines, for example, the organizational structure, degree of centralization, size, and individuals skills, complexity, and productivity (Orlikowski, 1992). With this standpoint technology is considered to be the independent variable, having causal influence on people and organizations (some also suggested moderating variables, see, e.g.: Jarvenpaa, 1989). In short, technology is the driver of change. The Technology imperative downplays the role of human agency and treats individuals as pawns who are passive to the external and deterministic forces of the wider context of the organization. In this way, the human aspects are neglected, and people are given limited possibilities to shape and influence technology and participate in change processes. Studies using a Technological imperative often have a variance approach to studying change (Gregor, 2006; Mohr, 1982), using a positivist approach with statistical techniques that seeks generalizing laws (Orlikowski, 2010). Studies using Technological imperative where dominant during the 1960s and 1970s, and the most prominent researchers within this field are often referred to as contingency theorists9 (Harvey, 1968; Perrow, 1967; Thompson, 1967; Woodward, 1958). In general, contingency theorists

Putting Digitalization in Perspective 31 argue that there is “no best way” to manage and design organizational structure. Instead, the effectiveness hinges on a number of contextual contingencies, often connected to technology, environment, historical aspects, and expectations. One of the main tasks of contingency theorists was to come up with different common principles about the connection between technology and organizational design and structure. For example, Woodward (1958) studied the relationship between the type of technology and organizational structure in British manufacturing firms. Woodward (p.  16) argued, for example, that “different technologies imposed different kinds of demands on individuals and organizations and that these demands had to be met through an appropriate organization form” (also noted by: Leonardi and Barley, 2010). Her work shows that different technological aspects need to be taken into account when designing and controlling an organization (Burnes, 2009). Similarly, the subsequent work of Perrow (1967) extended Woodward’s research by exploring the actual task of work and its connection to technology. Compared to Woodward, his research included non-manufacturing firms and knowledge connected to technology (instead of production technology). He developed a typology of four different technologies (routine, craft, engineering, or non-routine technology) that was connected to the degree of task being variable and predictable (i.e., if tasks done with technology amounted into exception from standard operating procedure), and to what extent tasks could be analyzed and categorized (i.e., routine way of dealing with exceptions). A final example of an influential contingency theorist is Thompson, who explored the link between technology and workflow. Besides downplaying human agency, one of the main problems with contingency theorists is their way to conceptualize technology as something abstract and aggregated. As Leonardi and Barley contends (2010, p. 162): In general, contingency theorists equated technology with what industrial engineers would call a production system, which is comprised of people, processes, and machines, all of which must be coordinated to transform inputs into outputs. Contingency theorists never concerned themselves with specific artifacts (like hardware or software) or artifacts’ identifiable material properties. Indeed, and overall, the Technological imperative suffers from a fixation with aggregated structure and materiality that amounts to what is often referred to as technical rationality that has been extensively been criticized (e.g.: Agarwal and Lucas Jr, 2005; Avgerou and McGrath, 2005; Ciborra, 2006; McGrath, 2006; Orlikowski, 2000; Walsham, 2001). Roughly put, technical rationality translates into a view of technology

32  Putting Digitalization in Perspective as a stable, robust, and reliable artifact that when implemented spreads easily in the organization, and subsequently employees simply and automatically adapt to the new circumstances. In short, IT will take care of itself. Using a metaphor to explain: IT works as a magical silver bullet that, almost by automation, transforms the organization and the work done by employees. Keep the concept of technical rationality in mind, as we will revisit it later in this book. Organizational Imperative The second major stream is the Organizational imperative, and the studies used within this perspective take an opposite view by downplaying the casual agency of technology (Fulk, 1993; Galbraith, 1977; Kling, 1991). Here the human agents are regarded as the prime drivers of change since they socially construct technology and subsequently make the direct choice of whether to use the technology or not. As Orlikowski explains (1992, p. 400): This perspective suggests that technology is not an external object, but a product of ongoing human action, design, and appropriation. The research foci within this perspective are discernible. One stream focuses on how a particular technology is physically constructed through the social interactions and political choices of human actors. Technology is here understood to be a dependent variable, contingent on other forces in the organization, most notably powerful human actors. . . . This perspective does not accept that technology is given or immutable, focusing attention instead on the manner in which technology is influenced by the context and strategies of technology decision makers and users. One influential researchers within the Organizational imperative is Child (1972). He was one of the proponents of the so called strategic choice school (Galbraith, 1977) that purports that technology is a tool that can be used for solving organizational difficulties and problems (Markus and Robey, 1988). More specifically, they argue that the organization should be seen as a social system that is contingent with its wider (open) environment. Problems should be resolved by scanning the wider environment for suitable technology and structure and then make a choice (Wilson, 1992). In this way, the quality of the strategic choice made by managers determines the success of the technological change. Studies using the agency lens were popular during late 1970s, 1980s, and 1990s, and many of the later studies focused on social constructivism. Such an approach argues that technology is a social object, and implementation “emerges out of an ongoing stream of social action in which people respond to the technology’s constraints and affordances, as

Putting Digitalization in Perspective 33 well as to each other” (Leonardi and Barley, 2010, p. 5). Social constructivists do not totally ignore technology and its causal agency. However, according to some critics, the social constructivist downplays the role of technology and treats it as a separate entity from the social. More specifically, critics claim that social constructivist based studies often neglect how technology and its materiality are entwined with the social during on-going practice (see, e.g.: Barrett et  al., 2006; Leonardi and Barley, 2010; Orlikowski and Scott, 2008; Orlikowski, 2010). Some well-referenced work using social constructivism is, for example, Bijker et al. (1987). They explored and argued that because of political aspects, norms, and values, people tend be “interpretive flexible” when it comes to how they view technology that influences how they design, implement, and use the technology. Similarly, Fulk (1993) explored the connection between email communication and sensemaking and showed how social aspects such as conformity influenced this process. Likewise, Kling and his associates (1980) showed how computer programs are the outcomes of a web of social relationships and political processes. Overall, many studies using the Organizational imperative perspective have been criticized for downplaying the role of materiality, physical characteristics, and the affordances that technology provides. Also, because of the perspectives’ pre-occupation with relational, social, interpretive, and highly situated aspects of technology, the wider political and societal consequences of technology get neglected (Orlikowski, 2010). The overall criticism is that the Organizational imperative ascribes too much agency to the human actor. Or roughly put, using a metaphor: technology functions as the chess pawn that people voluntarily choose to move and use or not to use—in order to enable some type of change. The individual is considered to have a direct choice of whether to use technology for the purpose of satisfying potential organizational needs for information. In other words, it is a perspective where human agents are the driver of change—downplaying casual agency of technology. Entanglement-in-Practice The Technological imperative and the Organizational imperative can be seen as reactions against each other, either attributing the causality of change to people or to technology and structure. Both are problematic. On the one hand, too much agency provides a voluntarist stance to change that purports that change is caused by the free will of independent individuals with limited constraints. On the other hand, too much structure yields a deterministic standpoint alleging that change is merely a result of technology and structures that alone determine the actions and fate of individuals.

34  Putting Digitalization in Perspective Precisely this aspect of the divide between agency and structure is a long-standing debate in social science (Archer, 1995; Ritzer, 2008). Structures provide temporary stability to everyday work and are commonly things like organizational structure, social structure, different forms of digital technology, culture, rules, and routines. Agency can be viewed as the source or capacity to change structure in which the concept of actor is an attribute of agency. Actor can be an individual, group, organization, or even an artifact that has the capacity to reproduce or to change structure (Iveroth and Hallencreutz, 2015; Scapens, 2006). Agency, actor, and structure are integral concepts of change (Caldwell, 2006), since an interplay between them is crucial in order to move change forward. Limited interaction between them often amounts to a cumbersome and problematic change process: on the one hand, an actor with agency but without structure amounts to no more than a sightless journey, whereas on the other hand, structure without the actor is little more than an abandoned ship drifting on its own accord. Or as Brown and Eisenhardt explains (1997, p. 29): “Too little structure makes it difficult to coordinate change. Too much structure makes it hard to move”.10 During the recent decades, studies of technology and change have increasingly had a more balanced view of actor and structure than the Technological and Organizational imperatives have offered, examples include: structuration theory (Barley, 1986; Giddens, 1984; Orlikowski, 1992), Actor-Network-Theory (ANT; Callon, 1986; Latour, 2005), mangling of practice (Jones and Symmetry, 1998; Pickering, 2010), and sociomateriality (Cecez-Kecmanovic et al., 2014; Orlikowski and Scott, 2008). The theories have their differences (see, e.g.: Leonardi and Barley, 2010; Orlikowski and Scott, 2008), but common to them all is that they avoid collapsing into a strong deterministic or voluntarist perspective. Such theories are similar in that they renounce the classical dichotomy of agency and structure; instead they are brought together into an interconnected perspective with the rationale that an interplay between agency and structure is imperative for change. Indeed, a common denominator is that they provide a more integrated, interactional, and balanced view of agency and structure than the Technology and Organizational imperatives have offered. Another similarity in many of these studies is the notion of “Entanglement-in-practice” that argues that technology and its materiality11 is an integral part of on-going actions and social relations.12 This suggests that technology and structure only come into being when they are combined with social activities during on-going practice (and vice versa). Orlikowski (2007) provides a simple example of a Google search to explain Entanglement-in-practice: a Google search is not entirely enabled by its materiality (being for example servers, databases, webpages, and algorithms). Neither is a Google search entirely social or human activity. The activity is instead composed of an intertwinement of both

Putting Digitalization in Perspective 35 the social and material aspects that is situated in time (e.g., a Google search today will not be the same as tomorrow) and space and is context dependent (e.g., a search is dependent on geographical location). This can be compared to how information searching was done before digitalization, involving activities such as visiting a library, talking to people in your personal network, going to conferences, visiting places, photocopying important information, etc. In such activities, there was a clearer separation of what was social and what was material and structural. In this way, the idea of Entanglement-in-practice suggests that if one wants to understand human activity this cannot be done unless material and structural aspects that are used in those activities are taken into consideration. And to understand structure and materiality one should understand it in relation to how it is used during on-going practice and the affordances that it provides. In a broader perspective, many argue that the concepts such as Entanglement-in-practice are highly relevant today since digitalization enforces technology and materiality to be permeated in almost all social activities we perform in organizations, as well as in our daily lives in general (Cecez-Kecmanovic et  al., 2014; Jones, 2014; Orlikowski, 2010). The current Cyber-physical wave that we discussed in this chapter is an example of this permeated nature of technology and materiality, and the later Commonality Framework of Digital Change in Chapter  6 is an example of a theoretical model that rests upon an Entanglement-ofpractice perspective. More precisely, Chapter 6 will uncover the entanglement of both structural-material and actor-social properties that together come into being during the continuous practice of leading digital change. The framework as such provides both a method and a lower-level theory that can work as a sensitizing device and help us understand digital change where technology is seen in its context, and where both technology and people are brought forth to center stage. Such an attempt can be seen as a contribution, since the Entanglement-of-practice perspective has been criticized for having “very little to offer the practitioner” (Cecez-Kecmanovic et  al., 2014, p.  826). However, the framework is situated in the later parts of the book, and before we dwell more upon these internal aspects of organization we are going to examine how the movement towards a “sense-and-respond” logic has influenced customer relationships and satisfaction, and what we can do about it.

Notes 1. In this book, we refer to IT in a broad point of view and by doing so we are referring not only to its material and to technological properties but more importantly we include IT’s social, organizational, and managerial consequence when we use the term. Some would prefer using the term “information systems”; however we do not want to overcomplicate things, and in addition it increases the risk of being misunderstood if both the terms IT and

36  Putting Digitalization in Perspective IS are used (on top of this, Information Communication Technology, ICT, could also be used to further complicate matters). 2. For a discussion about the general concept of technology, see Weick (1990). 3. Analog data is represented in a tangible and physical way such as sound, letters in a book, VHS cassette, or vinyl records. 4. Digital data is a numerical representation of data in binary form (numbers 1 and 0) that are stored in for example computers, mobile phones, and tablets. 5. Nolan’s theories were originally inspired by Greiner’s (1972) seminal article about organizational growth. 6. The original stage theory contained only the four first stages (Gibson and Nolan, 1974; Nolan, 1973), and later the extension of the theory included all six stages (Friedman, 1994; Nolan, 1979), and there have been attempts to include additional stages (Friedman, 1994; Mutsaers et al., 1998). 7. One interesting aspect about the first four stages is that they resemble the general characteristics of emotional elicitation and mood congruence that can be found in psychology literature. As Friedman (1994, p.  138) notes: “Stage 1 Caution when dealing with unfamiliar subsidiary issues. Stage 2 Optimism that follows success. Stage 3 Pessimism that follows disappointment. Stage 4 Balance that follows experience of variations”. 8. Groupings and discussions about streams of research connected to technology, organizing, and change can easily be made more complicated and nuanced. However, this is outside the scope of this book. For increased complexity, see, for example: Barley (1998); Leonardi and Barley (2010); Orlikowski and Scott (2008). 9. Another influential group of researcher within the Technology imperative perspective is the Aston group (Aldrich, 1972; Hickson et al., 1969). 10. We will come back to this notion in Chapter  6. However, for the sake of simplicity we will in Chapter 6 refer to agentic properties of change as soft factors and structural properties as hard factors. 11. Materiality is part of the tangible properties of structure, and the concept denotes the material nature of technology and, in particular, the functionality of the IT artifact. In other words, “precisely those tangible resources that provide people with the ability to do old things in new ways and to do things they could not do before” (Leonardi and Barley, 2008, p. 161). 12. Some recent research argues for using the concept of “imbrication” instead. This concept rests upon an ontology of separateness instead of a relational ontology. Imbrication suggests that materiality (structure) and social aspects are separated and have their own entities. However, they are also interdependent and influence each other as they are interlocked in an overlap (Leonardi, 2011, 2013).

References Abowd & Mynatt (2000). Charting past, present, and future research in ubiquitous computing, ACM Transactions on Computer-Human Interaction (TOCHI), 7(1), pp. 29–58. Agarwal & Lucas Jr (2005). The information systems identity crisis: Focusing on high-visibility and high-impact research, MIS Quarterly, 29(3), pp. 381–398. Aldrich (1972). Technology and organizational structure: A  reexamination of the findings of the Aston group, Administrative Science Quarterly, pp. 26–43. Applegate, Austin & Mcfarlan (2002). Creating business advantage in the information age (Boston, MA: McGraw-Hill).

Putting Digitalization in Perspective 37 Archer (1995). Realist social theory: The morphogenetic approach (Cambridge: Cambridge University Press). Archibugi (2017). Blade Runner economics: Will innovation lead the economic recovery? Research Policy, 46(3), pp. 535–543. Avgerou  & Mcgrath (2005). Rationalities and Emotions in IS innovation, in: D. Howcroft & E.M. Trauth (Eds) Handbook of critical information systems research: Theory and application, pp. 299–324 (Cheltenham: Edward Elgar). Barley (1986). Technology as an occasion for structuring: Evidence from observations of CT scanners and the social order of radiology departments, Administrative Science Quarterly, 31(1), pp. 78–108. Barley (1998). What can we learn from the history of technology? Journal of Engineering and Technology Management, 15(4), pp. 237–255. Barrett, Grant  & Wailes (2006). ICT and Organizational Change, Journal of Applied Behavioral Science, 42(1), pp. 6–22. Benbasat, Dexter, Drury  & Goldstein (1984). A  critque of the stage hypothesis: Theory and empirical evidence, Communications of the ACM, 27(5), pp. 476–485. Beniger (1986). The control revolution: Technological and economic origins of the information society (Cambridge, MA: Harvard University Press). Bijker, Hughes & Pinch (1987). The social construction of technological systems: New directions in the sociology and history of technology (Cambridge, MA: MIT Press). Björkdahl & Holmén (2019). Exploiting the control revolution by means of digitalization: Value creation, value capture, and downstream movements, Industrial and Corporate Change, 28(3), pp. 423–436. Borgia (2014). The Internet of Things vision: Key features, applications and open issues, Computer Communications, 54(December), pp. 1–31. Boyd & Holton (2018). Technology, innovation, employment and power: Does robotics and artificial intelligence really mean social transformation? Journal of Sociology, 54(3), pp. 331–345. Brown  & Duguid (2001). Knowledge and organization: A  social-practice perspective, Organization Science, 12(2), pp. 198–213. Brown & Eisenhardt (1997). The art of continuous change: Linking complexity theory and time-paced evolution in relentlessly shifting organizations, Administrative Science Quarterly, 42(1), pp. 1–34. Brynjolfsson & Hitt (1996). Paradox Lost? Firm-level Evidence on the Returns to Information Systems Spending, Management Science, 42(4), pp. 541–558. Brynjolfsson & Mcafee (2017). Machine, platform, crowd: Harnessing our digital future (New York: WW Norton & Company). Burnes (2009). Managing change: A strategic approach to organisational dynamics (Harlow: Financial Times Prentice Hall). Caldwell (2006). Agency and change: Rethinking change agency in organizations (London: Routledge). Callon (1986). Some elements of a sociology of translation: Domestication of the scallops and the fishermen of St Brieuc Bay, in: Law (Ed) Power, action and belief: A new sociology of knowledge, pp. 196–233 (London: Routledge & Kegan Paul). Cascio & Montealegre (2016). How technology is changing work and organizations, Annual Review of Organizational Psychology and Organizational Behavior, 3(March), pp. 349–375.

38  Putting Digitalization in Perspective Cash (1994). Building the information-age organization: Structure, control, and information technologies (Burr Ridge, IL: Irwin). Cecez-Kecmanovic, Galliers, Henfridsson, Newell  & Vidgen (2014). The sociomateriality of information systems: Current status, future directions, MIS Quarterly, 38(3), pp. 809–830. Cetri Magazine (2017). The fourth industrial revolution does not exist! Cetri Magazine, December  6. Available from: http://cetri-tires.org/press/2017/thefourth-industrial-revolution-does-not-exist/?lang=en [Accessed 2020–02–24]. Child (1972). Organizational structure, environment and performance: The role of strategic choice, Sociology, 6(1), pp. 1–22. Christensen (1997). The innovator’s dilemma: When new technologies cause great firms to fail (Boston, MA: Harvard Business School Press). Ciborra (2006). The mind or the heart? it depends on the (definition of) situation, Journal of Information Technology, 21(3), pp. 129–139. Cöster, Iveroth, Olve, Petri & Westelius (2020). Strategic and innovative pricing: Price models for a digital economy (Abingdon: Routledge). Cöster & Westelius (2017). Digitalisering (Stockholm: Liber). Debri  & Bannister (2015). E-government stage models: A  contextual critique, 2015 48th Hawaii International Conference on System Sciences, 2015(January), pp. 2222–2231. Dedrick, Gurbaxani & Kraemer (2003). Information technology and economic performance: A critical review of the empirical evidence, ACM Computing Surveys, 35(1), pp. 1–28. Favaretto (2015). Stage level measurement of information and communication technology in organizations (Doctoral dissertation CDU 62::007) Escola de Administração de Empresas de São Paulo. Friedman (1994). The stages model and the phases of the IS field, Journal of Information Technology, 9(2), pp. 137–148. Fulk (1993). Social construction of communication technology, Academy of Management Journal, 36(5), pp. 921–950. Galbraith (1977). Organizational design (Reading, MA: Addison-Wesley). Galliers  & Sutherland (1991). Information systems management and strategy formulation: The ‘stages of growth’model revisited, Information Systems Journal, 1(2), pp. 89–114. Gibson & Nolan (1974). Managing the four stages of EDP growth (Boston: Harvard Business Review). Giddens (1984). The constitution of society: Outline of the theory of structuration (Cambridge: Polity Press). Grégoire & Lustman (1993). The stage hypothesis revisited: An EDP professionals’ point of view, Information & Management, 24(5), pp. 237–245. Gregor (2006). The nature of theory in information systems, MIS Quarterly, 30(3), pp. 611–642. Greiner (1972). Evolution and revolution as organizations grow, Harvard Business Review, 37(July–August), pp. 37–46. Harvey (1968). Technology and the structure of organizations, American Sociological Review, 33(2), pp. 247–259. Hickson, Pugh  & Pheysey (1969). Operations technology and organization structure: An empirical reappraisal, Administrative Science Quarterly, 14(3), pp. 378–397.

Putting Digitalization in Perspective 39 Iveroth & Hallencreutz (2015). Effective organizational change: Leading through Sensemaking (London: Routledge). Iveroth, Lindvall & Magnusson (2018a). Introduktion, in: Iveroth, Lindvall & Magnusson (Eds) Digitalisering och styrning, pp. 17–35 (Lund: Studentlitteratur). Iveroth, Lindvall  & Magnusson (2018b). Digitalisering och styrning (Lund: Studentlitteratur). Jarvenpaa (1989). The effect of task demands and graphical format on information processing strategies, Management Science, 35(3), pp. 285–303. Jarzabkowski & Pinch (2013). Sociomateriality is ‘the New Black’: Accomplishing repurposing, reinscripting and repairing in context, M@ n@ gement, 16(5), pp. 579–592. Jones (2014). A matter of life and death, MIS Quarterly, 38(3), pp. 895–925. Jones & Symmetry (1998). Information systems and the double mangle: Steering a course between the Scylla of embedded structure and the Charybdis of strong symmetry, in: Larsen, Levine & DeGross (Eds) Information systems: Current issues and future challenges, pp. 287–302 (Laxenburg: International Federation for Information Processing). Kallinikos (2001). The age of flexibility: Managing organizations and technology (Lund: Academia adacta). Kazanjian & Drazin (1989). An empirical test of a stage of growth progression model, Management Science, 35(12), pp. 1489–1503. Kling (1980). Social analyses of computing: Theoretical perspectives in recent empirical research, ACM Computing Surveys (CSUR), 12(1), pp. 61–110. Kling (1991). Computerization and social transformations, Science, Technology, & Human Values, 16(3), pp. 342–367. King & Kraemer (1984). Evolution and organizational information systems: An assessment of Nolan’s stage model, Communications of the ACM, 27(5), pp. 466–475. Kohli  & Devaraj (2003). Measuring information technology payoff: A  metaanalysis of structural variables in firm-level empirical research, Information Systems Research, 14(2), pp. 127–145. Lasi, Fettke, Kemper, Feld & Hoffmann (2014). Industry 4.0, Business & Information Systems Engineering, 6(4), pp. 239–242. Latour (2005). Reassembling the social: An introduction to actor-network-theory (Oxford: Oxford University Press). Leonardi (2011). When flexible routines meet flexible technologies: Affordance, constraint, and the imbrication of human and material agencies, MIS quarterly, 35(1), pp. 147–167. Leonardi (2013). Theoretical foundations for the study of sociomateriality, Information and Organization, 23(2), pp. 59–76. Leonardi & Barley (2008). Materiality and change: Challenges to building better theory about technology and organizing, Information & Organization, 18(3), pp. 159–176. Leonardi & Barley (2010). What’s under construction here? Social action, materiality, and power in constructivist studies of technology and organizing, The Academy of Management Annals, 4(1), pp. 1–51. Lepore (2014). The disruption machine, The New Yorker, 23(June), pp. 30–36. Li, Rogers & Chang (1994). An empirical reassessment of the measure of information system sophistication, Information Resources Management Journal (IRMJ), 7(3), pp. 3–20.

40  Putting Digitalization in Perspective Lindvall & Iveroth (2018). Struktur: Digitalisering och organisering, in: Iveroth, Lindvall & Magnusson (Eds) Digitalisering och styrning, pp. 183–211 (Lund: Studentlitteratur). Lindvall & Osowski (2018). Teknik: från stor fysisk hårdvara till små osynliga tjänster, in: Iveroth, Lindvall & Magnusson (Eds) Digitalisering och Styrning, pp. 87–114 (Lund: Studentlitteratur). Lucas (1999). Information technology and the productivity paradox: Assessing the value of investing in IT (Oxford: Oxford University Press). Lucas Jr & Sutton (1977). The stage hypothesis and the s-curve: Some contradictory evidence, Communications of the ACM, 20(4), pp. 254–259. Lyytinen (1991). Penetration of information technology in organizations a comparative study using stage models and transaction costs, Scandinavian Journal of Information Systems, 3(1), pp. 87–109. Lyytinen & Yoo (2002). Ubiquitous computing, Communications of the ACM, 45(12), pp. 63–96. Mahmood & Becker (1985). Effect of organizational maturity on end-users’ satisfaction with information systems, Journal of Management Information Systems, 2(3), pp. 37–64. Markus  & Robey (1988). Information technology and organizational change: Causal structure in theory and research, Management Science, 34(5), pp. 583–598. Mcgrath (2006). Affection not affliction: The role of emotions in information systems and organizational change, Information & Organization, 16(4), pp. 277–303. Mckenney, Copeland  & Mason (1995). Waves of change: Business evolution through information technology (Boston, MA: Harvard Business School Press). Mohr (1982). Explaining organizational behavior (San Francisco: Jossey-Bass). Murray (2015). The new industrial revolution (And Our Giga-Good Fortune), Fortune, 171(6), pp. 6–6. Mutsaers, Van Der Zee & Giertz (1998). The evolution of information technology, Information Management & Computer Security, 6(3), pp. 115–126. Nolan (1973). Managing the computer resource: A stage hypothesis, Communications of the ACM, 16(7), pp. 399–405. Nolan (1979). Managing the crisis in data processing, Harvard Business Review, 57(2), pp. 115–126. Nolan (2000). Information technology management since 1960, in: Chandler & Cortada (Eds) A nation transformed by information: How information has shaped the United States from colonial times to the present, pp.  217–256 (Oxford: Oxford University Press). Nolan & Bennigson (2003). Information technology consulting (Working paper: 03–069) (Boston: Harvard Business School). Nolan & Croson (1995). Creative destruction: A six-stage process for transforming the organization (Boston, MA: Harvard Business School Press). Ong (1995). Hermeneutic forever: Voice, text, digitization, and the” I”, Oral Tradition, 10(1), pp. 3–26. Orlikowski (1992). The duality of technology: Rethinking the concept of technology in organizations, Organization Science, 3(3), pp. 398–427. Orlikowski (2000). Using technology and constituting structures: A  practice lens for studying technology in organizations, Organization Science, 11(4), pp. 404–428.

Putting Digitalization in Perspective 41 Orlikowski (2007). Sociomaterial practices: Exploring technology at work, Organization Studies, 28(9), pp. 1435–1448. Orlikowski (2010). The sociomateriality of organisational life: Considering technology in management research, Cambridge Journal of Economics, 34(1), pp. 125–141. Orlikowski & Scott (2008). Chapter 10: Sociomateriality: Challenging the separation of technology, work and organization, The Academy of Management Annals, 2(1), pp. 433–474. Perrow (1967). A  framework for the comparative analysis of organizations, American Sociological Review, 32(2), pp. 194–208. Peters (2017). Technological unemployment: Educating for the fourth industrial revolution, Journal of Self-Governance and Management Economics, 5(1), pp. 25–33. Piccoli & Ives (2005). IT-dependent strategic initiatives and sustained competitive advantage: A review and synthesis of the literature, MIS Quarterly, 29(4), pp. 747–776. Pickering (2010). The mangle of practice: Time, agency, and science (Chicago: University of Chicago Press). Poole (2017). The fourth industrial revolution review—adapt to new technology or perish, The Guardian, January 6. Available from: https://www.theguard ian.com/books/2017/jan/06/the-fourth-industrial-revolution-by-klaus-schwabreview [Accessed 2020–02–24]. Poovendran, Sampigethaya, Gupta, Lee, Prasad, Corman  & Paunicka (2011). Special issue on cyber-physical systems, Proceedings of the IEEE, 100(1), pp. 6–12. Ritzer (2008). Modern sociological theory (Boston: McGraw-Hill). Saunders & Brynjolfsson (2016). Valuing information technology related intangible assets, MIS Quarterly, 40(1), pp. 83–110. Scapens (2006). Understanding management accounting practices: A  personal journey, The British Accounting Review, 38(1), pp. 1–30. Schwab (2015). The fourth industrial revolution: What it means and how to respond, Foreign Affairs, December 12. Available from: https://www.weforum. org/agenda/2016/01/the-fourth-industrial-revolution-what-it-means-and-howto-respond/ [Accessed 2020–02–24]. Schwab (2016). The fourth industrial revolution (New York: Crown Business). Schwab & Davis (2018). Shaping the future of the fourth industrial revolution: A guide to building a better world (New York: Currency). Solow (1987). We’d better watch out, New York Times Book Review, July(12), p. 36. Thompson (1967). Organizations in action: Social science bases of administrative theory (New York: McGraw-Hill). Walsham (2001). Making a world of difference: IT in a global context (Chichester: Wiley). Weick (1990). Technology as equivoque: Sensemaking in new technologies, in: Goodman & Sproull (Eds) Technology and organizations, pp. 1–44 (San Francisco: Jossey-Bass). Wilson (1992). A strategy of change: Concepts and controversies in the management of change (London: Routledge). Woodward (1958). Management and technology (London: HMSO).

42  Putting Digitalization in Perspective World Economic Forum (2016). Global challenge insight report: The future of jobs employment, skills and workforce strategy for the fourth industrial revolution. Available from: http://www3.weforum.org/docs/WEF_Future_of_Jobs. pdf [Accessed 2020–02–24]. Yoo, Boland Jr, Lyytinen & Majchrzak (2012). Organizing for innovation in the digitized world, Organization Science, 23(5), pp. 1398–1408. Zuboff (1988). In the age of the smart machine: The future of work and power (Oxford: Heinemann Professional).

3 Understanding the Customer Side of Digital Change

Introduction After having explored digitalization historically and discussed earlier studies in technology, we have now arrived at one of the core aspects of this book: how digitalization changes customers’ perceptions, preferences, expectations, and behaviors. We commenced the introduction of this book by visiting Sanne and Mauritz in Mölnbo. Their testimonial about how they changed shopping behavior showed in a down to earth way the digital and behavioral change that has taken place with accelerating speed during the last two decades. And their shift of habit—from traditional grocery shopping in a supermarket to online ditto—is merely one story out of numerous out there. We think it is fair to say that few of us have been unaffected by digitalization. We have changed as consumers. We do business differently. And new demands, needs, and expectations come consequently. We also stated in the introduction to this book that digitalization is twofold—internal and external. In this chapter we will focus on the external fold and scientifically show through our extensive market research how customer behavior, demands, needs, and expectations have evolved over time due to digitalization. We begin this journey by showing the evolutionary development of customer perceptions across time together with illustrative case studies and examples. Then in the subsequent section, we explore the most important methodological aspects that lie behind the quantitative data that is the base of this chapter. This understanding is a requirement for exploring the drivers behind the digitalization paradox that we discuss in the proceeding section. We end the chapter by discussing different ways in which leaders can tackle and manage the digitalization paradox. However, before moving into things let’s revisit some of our key points previously presented. One crucial point is that customer satisfaction has decreased since the last decade. One of the reasons for this is what we call the digitalization paradox: digital services have come closer and closer but personal relations seem to go astray in the process. More specifically, our recent

44  Understanding the Customer Side research suggests that the gap between product and/or service providers and customers has never been perceived as wide as today (Hallencreutz and Parmler, 2019). At the same time, during the last decade digitalization has become a crucial factor for the execution of most of the interactions with customers as well as overall organizational strategies. However, and as we will show you in this chapter, many digitalization efforts seem to have a negative effect on customer satisfaction—it rather seems to boost dissatisfaction since digital functionality nowadays is taken for granted and something more is expected. New digital technology changes business landscapes, and this evolution has affected customer satisfaction and expectations negatively in many industries and countries during the last decade. We argue that the root cause is that all these new digital interfaces often lack a human sense. Roughly put, human-human relations have been lost in the process. Automated services may offer swift functional solutions, but there is an absence of real social interaction. And this digitalization paradox must be handled to regain devoted customers, but to understand how to do so we should first look back and examine the evolution of customer satisfaction.

The Evolution of Customer Satisfaction Aspects of customer focus and satisfaction has been widely discussed and regarded as fundamental building blocks of different management concepts for decades (Bergman and Klefsjö, 2010). The term customer focus has been used to describe the desired starting point of organizations’ improvement efforts (Hellsten and Klefsjö, 2000; Sousa, 2003). In most quality management theories, customer focus practices involve “the establishment of links between customer needs and satisfaction and internal processes” (Sousa, 2003, p. 2). In Sweden, research on customer satisfaction began to intensify in the late 1980s, when different organization began to measure customer perception (and we will return to this later in this chapter as part of the data presented originates from this research). By then, it is fair to say that there still was a wide gap between the rhetoric and the reality. Customer focus and satisfaction meant little in practice. However, by examining longitudinal data spanning over three decades, we may capture something about the evolution of consumer behavior at least within a northern European context. In the Nordics, with some differences between the countries, the 1990s was a period of deregulation and liberalization of several industries and societal sectors. From a customer perspective this meant new opportunities and freedom of choice. Consequently, product offerings and value propositions became an important part of the customer experience. Customer satisfaction was no longer merely about perceived value for money. During this decade, the general level of customer satisfaction increased. From a digitalization perspective it is also relevant to note that the internet is widely diffused and adopted during this decade. There is an overflow of

Understanding the Customer Side 45 affordable “Home computers”. Technology becomes a crucial part of the changing of customer-firm relationships from transactional to relational as we partly described in Chapter 2 (Oliva and Kallenberg, 2003). This trend of increased customer satisfaction is strengthened during the first decade of the new millennium (the Y2K bug apparently did not crash everything). New technologies enable new services close to the customers through faster and more reliable internet connections. “Do it yourself” becomes a selling point—you can now order things, pay things, book things, monitor things, find information, and suddenly administer many aspects of your everyday life at the screen. Social media explodes and enables consumers to communicate and share positive and negative experiences. The birth of the smartphone makes the platforms mobile. Digitalization breeds customer satisfaction during these years between 2000 and 2010. Apps are sexy, iPhone is the thing. But scrutinizing our empirical data also tells us that during this period soft immaterial aspects such as brand image, trust, and human touch continue to be crucial customer satisfaction drivers. What we see here is the birth of the digitalization paradox. Services have now come closer, but many customers start to grow an awkward feeling of being forgotten, abandoned, and taken for granted. The digitalization hey days seem to end around 2010, see Figure 3.1. Brand image and customer service becomes more important than technology.

Figure 3.1  General Customer Satisfaction Trend Source: Extended and adapted from Hallencreutz and Parmler, 2019, p. 6.

46  Understanding the Customer Side During the subsequent decade, our data tells us that technology no longer drives customer satisfaction. It rather makes customers feel distanced and alienated. Instead, technology is substituted by personal relations and customized service. We also see a growing (customer) focus on sustainability and social responsibility and declining customer satisfaction indices with polarization tendencies (i.e., consumers are either “very satisfied” or “very dissatisfied”—nothing in between). The digitalization paradox is now a harsh reality. The customer side of digital change therefore needs to be further analyzed and understood.

Deconstructing the Digitalization Paradox Within Different Industries From the historical odyssey of the earlier section, we can conclude that the evolution of the human-technology interplay has had a generally negative effect on customer satisfaction during the last decade. We see what we call a digitalization paradox. One way to further illustrate and explain the deconstruction of the paradox metaphor is to look closer at the banking industry from a customer perspective. One reason for doing so is that we have collected quantitative data and measured customer perception in the Scandinavian banking sector for three decades. Another reason is that the banking industry has for a long time deployed new customer interfaces through technology, starting with the cash machines in the late sixties. Yet another reason is that almost every one of us has a relation to a bank. We learn as children to save money for future dreams. Coins are put in moneyboxes and we experience the difference between saving and wasting. Also, already as children we often painfully learn gradually about the gap between rich and poor. Moreover, the bank is often involved in defining moments such as the first home, our own business, the dream vacation, the first car, and such. Thus, it is fair to say that we all can in some way relate to different customer experiences from the banking industry. When the internet was widely diffused in the mid-1990s in the Nordics, the banks were forerunners in offering swift banking services (such as payments and transactions) via web-based interfaces. These services were by then an appreciated and welcomed novelty and contributed to boost in trust and customer satisfaction in the industry. People seldom had to go to a certain banking branch or fill in forms to pay telephone bills or mortgages. Everyday banking life for many people was simplified through new digital technology. Through digitalization customers could take care of many practical banking services all by themselves, and there was no longer a need for manual handling of routine transactions through extensive branch networks. As the digitalization pushed the industry further, the use of cash was successively substituted by cards and online solutions,

Understanding the Customer Side 47 and costly and risky cash handling could be reduced. Consequently, in the beginning of the millennium many banks actively started to dismantle their cash handling processes, and it was somewhat of a cultural revolution when bank branches stopped handling real money—by many seen as the very symbol of banking. As a final step in this process, branches with few physical visits and booked meetings were closed. Somewhere along this process many customers started to feel abandoned. The availability of local bank branches was significantly reduced and old fashioned (manual) services gone. In rural areas this development had a significant impact on local society and business life with even political implications. People felt let down. It had suddenly become an ordeal to get in contact with a living person behind all the neat (but anonymous) digital services. Frankly, new technology did not do the trick anymore. Instead a digitalization paradox had emerged. New technology had transformed a whole industry, but important service elements got lost in the process. Services had come close, but customers felt distanced. How could this evolution happen? One of the reasons is that the banks initially went about this industry transformation mainly from an inside out perspective. The core was to use digitalization primarily for rationalization purposes. Enhanced customer experience was not top of mind. For sure, new technology provided access to basic and practical banking services around the clock, but the added customer value soon faded. Instead internet banking became a commodity. This development also led to significantly fewer interactions with “real people” within the bank since the need to stop by your banker at the local branch to pay your ordinary bills had vanished. Instead new customer demands, needs, and expectations emerged. If your sole relation to the bank went through a webpage and the local branch was closed, who should you now call if you needed something extra? The answers from the industry were less often customer centric, and from a customer satisfaction perspective the technological evolution led to a backlash. This is also reflected in our customer satisfaction studies (Hallencreutz and Parmler, 2019). For example, ten years ago, satisfaction figures started to drop, catalyzed by the global financial crises starting with the fall of Lehman Brothers in 2008. And since 2010, our data uncovers that customer satisfaction and trust has decreased in the banking industry with a slight recovery in the last years. Hopefully, insightful executives in the banking industry have now realized that digital interfaces should be supplemented with local, personal, and customized services, which eventually will lead to a recovered customer satisfaction in the industry in the years to come. Another example illustrating how technology has transformed industry logic comes from the car industry and the classic Swedish brand Volvo (well, today Volvo is owned by the Chinese, but the brand identity is still very Swedish, and the production and product development is still

48  Understanding the Customer Side centered in Gothenburg). AB Volvo was formed in 1926 as a subsidiary of the Swedish ball bearing industry SKF with Assar Gabrielsson as CEO and Gustaf Larson as Deputy CEO and Technical Manager. They had worked together since 1924 on the planning and construction of the first Volvo car and in August 1926 they succeeded in convincing the management of SKF that the production of cars could be a profitable business and benefit the development and sale of ball bearings. The original plans for the Volvo brand (meaning “I  roll” in Latin) had been to use it for primarily a special series of ball bearings, intended for the U.S. automotive market, but that idea was abandoned. Instead the brand was used for the new car project. The first Volvo rolled out of the factory on April 14, 1927. The car and motorism radically changed the whole of our global society and our way of life since the mid-20th century. It linked people, products, and places in completely new ways. Vehicle traffic became an integral part of our everyday private and professional lives. The car was also for many decades an icon, a symbol of wealth, and a new modern society. However, a car was only until recently just a car. Basically, a means of transportation and a physical product that came in different brands, sizes, colors, exterior and interior designs, and technical specifications. Global competition around these product characteristics has been fierce through the decades after World War II, and the industry as such has contributed to many industrial innovations. At the same time, the automobile community has also contributed to the environmental and climate problems, which is one of our challenges today. The car industry is currently undergoing major changes, but this is a story of its own. Here we merely comment on the car industry from digitalization perspective since many of us can relate to cars from private endeavors on the road. Volvo flourished during the 1950s and 1960s and launched models that are still iconic, for instance the Volvo P 1800 was made world famous by Roger Moore in the 1960s television series The Saint. Roger Moore played the lead character, the infamous Simon Templar, and drove a white P1800 in all the 118 episodes from 1962 until 1969. Two other renowned models were the Volvo Amazon (1956–1970) and the 140/240 series in production for more than 25 years. These models were by all means analogue and mechanical, and it was not until in the 1980s that certain systems in the car were computerized. However, it did not primarily improve the customer (driver) experience. But things improved across the years. Early examples of digitalization from a customer perspective is the introduction of (fairly primitive) trip computers that could record, calculate, and display information to the driver on the road. Such information included remaining mileage on the current fuel volume, average and instant fuel consumption, temperature, average speed, and estimated

Understanding the Customer Side 49 arrival time. Volvo introduced this feature broadly when launching Volvo 850 in 1992. However, when the internet came into full force the purpose of a car became so much more than a means of transportation with some different features. Today, a car is an interconnected and large digital gadget and a part of everyday life with service functions and auxiliary services. Modern cars have integrated infotainment screens with functions to access all systems in the car, including safety systems, air conditioning, cruise control, door mirrors, media, navigation, cameras, and phone integration. Safety systems are also improved by new technology, such as collision warning, automatic brakes, pedestrian warning, sleep warning, lane assist, parking sensors and cameras, and active cruise control that constantly adjusts the speed to the car in front. In addition to this, there are what we now consider to be standard features such as, ABS, anti-slip, anti-spin, and airbags. In most cars many of these features can also be customized and adjusted to different drivers (or should we perhaps say “users”) individual preferences. And as such, the car is today a CPS-system (see Chapter 2) as most of these things are interconnected as well as connected to wider systems. This means that brands like Volvo today have an equally natural place at major electronics and mobile shows, as in the classic car showrooms, and that partnerships with Apple, Microsoft, and Ericsson and others are increasingly important (Cöster et al., 2020). This entry of digital services into the car means that car manufacturers and car users now mutually experience a totally different set of relations and interactions compared to just a couple of years ago. And new customer expectations come consequently. For instance, in 2011, Volvo introduced the “Volvo On Call” app for smartphones. Suddenly, the Volvo brand enters a new arena and starts to compete with other app services. Figuratively speaking, the car now crowds with the bank, children’s school, the supermarket, and other downloaded services in the same screen. With this Volvo app the user remotely can monitor the car’s GPS position, check if doors or windows are open, lock or unlock the car, control fuel consumption and trip meter position, as well as various sensors, turn on engine heaters, and export detailed travel logs. In later editions Volvo also offers “in car deliveries” where you can order various products and have them delivered directly to the car. Parallel to these servitization efforts, Volvo has launched new alternative ways to provide the actual vehicles. “Care by Volvo” is a subscription service and through car sharing services like “Sunfleet” Volvo tries to challenge traditional ways of usage, pricing, financing, and ownership. Other car manufacturers provide similar solutions. Yet another illustrative is the growth of online shopping during the last 20 something years—that we also illustrated in the first chapter with the short story of Mauritz and Sanne’s weekly deliveries of groceries.

50  Understanding the Customer Side In the old days, a consumer went to a physical shop, picked and chose from available goods on the shelves, made a purchase, and brought the product home. The customer perception was affected by one single customer-provider interaction and the shop controlled most of the whole process. Today, the consumer can be anywhere. He or she may browse the net and compare products and offerings via different websites. The first interaction, or touch point, is via the interface on the shopping site. Eventually the product is delivered through the mail or via some collect point which can be at a postal office, a supermarket or a logistics center. This is another customer touch point. Then the product is unpacked, checked, and hopefully compliant with the specifications on the net. Yet another touch point. Finally, the price of the goods and services should be paid. From being a one-off event in a shop, a simple digital purchase of a commodity will now involve multiple providers, touch points, and brands all affecting the customers’ perception of the purchasing experience. In summary, these three examples of banking, manufacturing, and online shopping all have their respective evolutionary experiences with digital change. The bank industry went from an industry logic based on manual services provided by clerks at bank branches combined with giro services to digital around the clock “do-it-yourself” transactions and advanced services provided by advisors. The car industry, illustrated through Volvo, has experienced a gradual drift towards servitization, since the product offering today is so much more than just a car. In addition, Volvo serves as a good illustration of the shift from a make-and-sell strategy to a sense-and-response strategy that we brought up in Chapter 2. Namely that this car manufacturer has moved from merely selling a standardized product with certain fixed features to offering a customized, interconnected digital gadget with service functions and auxiliary services. Finally, the short example from online shopping illustrates how the industry is under a (quite painful) transformation from traditional analog shopping to online shopping. All these three examples have in common that traditional human-human interplay have been substituted or supplemented by digital interfaces. The digital development in these three industries has led to a plethora of services but at the same time the interaction with “real people” has almost vanished. For sure, a car can still get a flat tire (if you are lucky your car still has a spare) and still needs regular (physical) services. But the car may also lose connection to the internet, get problems with internal systems, get glitches in the app software and so forth. And that is the new deal; the car as such might run flawlessly but if the added digital gadgets malfunction, it may ruin the customer experience in seconds. Digital technology is good when it works, but if you lack swift customer service functions you are bound to fall into the trap of the digitalization

Understanding the Customer Side 51 paradox if it fails. Thus, when embracing the customer side of digital change there are a lot of aspects to consider. Transforming the customer experience should form the core of digital change. Social media enables organizations to instantly capture the voice of the customer, mobile interfaces engage customers on the move, and bring the customer interaction to their physical location. And smart analytics help in making better use of data to customize and personalize products and services. But, despite all these possible advantages something fundamental seems to get lost in the process of digitalization. Root causes are complex, but based on our research we see four overarching challenges related to the digitalization paradox: •

•

Consumer consciousness—During the last decade the use of the internet and social media has rocketed. In a time when “news” (fake or true) are globally spread by milliseconds through these formal and informal networks, it can be assumed that consumers have become more conscious, critical, cautious, and demanding. This implies that leaders in general need to understand and embrace this new volatile environment. Much more effort should be put in the care of the brand image. For instance, we see strong correlations between customers’ perception of a certain brand and their level of satisfaction. If a customer perceives a brand as trusted, it is likely that that specific customer also will be satisfied with the products and services provided by that brand. This consumer consciousness seems to have very little to do with the quality of the deliveries as such if the brand lives up to certain standards or principles in the eyes of the customer. The brand image is strengthened by both external communication efforts (you could call it traditional “marketing), but even more through the conduct of the people within the organization. How are executives cited and referred to in media? Is social media buzz swiftly handled? Is the staff personal, polite, and friendly? Are there profound core values that actually reach all the way to the customers? Is the brand identity signaling purpose and meaning? A plethora of questions will be asked by a new conscious customer collective. Falling faith—As a consequence of the digitalization paradox, we also see that trust and confidence in companies and institutions seem to have weakened since the financial crisis in 2009–2010 (nota bene, not only in the financial sector). More than before, questions about sustainability, social commitment, and business ethics influence the choice of conscious customers. Our data also unravels that organizations that are perceived as sustainable, socially responsible, local, and personal gain a more positive customer feedback regardless of actual deliveries. While brands associated with for instance greed, fraud, or perhaps pollution, exploitation, or child labor, struggle and

52  Understanding the Customer Side

•

•

will eventually perish (even if they might provide high quality products and services). Digital dichotomization—our research also uncovers that customers’ purchasing behaviors change as social media interaction and digital networking grows. The digital world seems to come without nuances. We either like or unlike, compare, try, shop around, or tell the world about our experiences often in black or white. This means that the digital customer relation is shaky and holds inherent risks, especially if there is an absence of human interaction. We see in our data that customers in general tend to be more binary and polarized. You are pleased until you are displeased; there is nothing in between. From a practitioner’s point of view, this means that a customer who has previously been very satisfied all of a sudden and without warning may just turn grumpy and leave. This dichotomized behavior is strongest in digital business environments with multiple providers without personal relations. Limping loyalty—The new restless and dichotomized business environment also makes consumers of today “unfaithful”. We may be satisfied with a product or service delivery but try other options anyway. This implicates that a satisfied customer not necessarily is loyal in a traditional sense. There is also a new restlessness. Customers might say “I have been loyal to you a whole year . . . when do I get my loyalty bonus?”. Surely, there are still customer segments who prefer long-term relations with one single brand, but they are on the verge of extinction. More common is the jumpy restless customer types who might stay for a while but shop around and try others. The key to a profound loyalty is to make customers emotionally attached to the purpose and values of the brand identity. This can be achieved through candid external communication and close personal customer relations. The trick is to be both “digital” and “local”.

Our contention is that digitalization has made customer relations more polarized and volatile. And new technology does not by default seem to drive satisfaction. To understand the variables behind this development, we must understand in depth how customer perceptions can be measured and analyzed.

Measuring Customer Perceptions Economic and social benefits of digital change should be evaluated from various perspectives. Digitalization combined with increasingly complex customer requirements have resulted in a growing need for processes which can gather and use customer feedback in order to improve products and services (Edvardsson et al., 2014). Organizations can no longer

Understanding the Customer Side 53 rely solely on financial performance indicators, as these do not adequately capture the value of crucial intangible non-financial assets such as brand awareness, customer satisfaction, and loyalty (Birch-Jensen et al., 2018). There is a smorgasbord of automated customer feedback collected during the customers’ digital service usage, which often is readily available for the providing organizations (Porter and Heppelmann, 2014). During the last few years there has also been an increasing use of customer satisfaction measurements. This development is enhanced by trends such as digitalization, globalization, and servitization (Arvidsson, 2011; BirchJensen et al., 2018; Bititci et al., 2012). Thus, organizations, researchers, and consultants are scrambling to understand how to make use of this codified customer feedback in order to increase customers’ service experience (Mcafee et al., 2012; Ostrom et al., 2015), which in turn has the potential to increase customer satisfaction and the firm’s financial performance (Eklof et al., 2017). In an era when many customer interactions turn digital these “soft” aspects are even more important—as we also touched upon in the first chapter but from another perspective. Changing customer behaviors push organizations to implement additional non-financial performance measurements with the ability to capture past, present, as well as future performance (Bititci et al., 2012; Taticchi et al., 2010). A high level of customer satisfaction lead to sustained financial performance, stronger company image, protection of current market share, increased customer loyalty, and decreased customer complaints. But this new landscape also holds inherent risks. A  poor service delivery may go viral, and social media can ruin a brand image in seconds. Therefore, customer satisfaction measurements are recognized as an important indicator for future financial importance and has become the non-financial performance indicator that is the most widespread (Bititci et  al., 2012; Eskildsen et  al., 2003; Fornell et al., 1996; Stern, 2006). The aspect of customer centricity when leading change is certainly not new. Questions about the importance of value creation for customers and other stakeholders have long been widely discussed in the academic domain (Birch-Jensen et  al., 2018). It is fair to say that most management theories state that customer focus and customer satisfaction are core organizational aspects and success factors in all industries and societal sectors. As such, it needs to be understood, measured, and managed. In the new digital landscape this is becoming a matter of life and death. Rapid change with disruptive elements driven by technology has become the “new normal” and needs to be understood and managed accordingly. The understanding on how customer satisfaction evolves over time should therefore be seen as an urgent non-financial performance indicator when leading digital change. According to Eklöf et al. (2017, 2018), customer-based measures are also useful as indicators of companies’

54  Understanding the Customer Side future performance and should be incorporated even more into corporate decision-making processes, especially during times of change. Trustworthy and manageable customer satisfaction measurements require robust measurement systems, and different concepts have evolved during the last decades. In this chapter, we build our reasoning on longitudinal studies based on the Extended Performance Satisfaction Index Model (the EPSI model). This is the main customer satisfaction index in Sweden, and when it was established in 19891 (based on research conducted by Stockholm School of Economics), it was the world’s first nationwide index.2 Since then, the EPSI model has also been applied and used in a number of countries (e.g., Norway, Denmark, the US) and is well established within the scientific community (see, e.g.: Eklöf and Westlund, 2002; Fornell, 1992; Fornell et  al., 1996; Kristensen et  al., 2000; Kristensen and Westlund, 2003). The EPSI model is composed of five latent or “hidden” variables that influence perceived value and customer satisfaction, which in turn is (hopefully) transformed into customer loyalty (and this can take some time). This is shown in Figure 3.2, where the latent variables are on the left-hand side and the main causal relationships are indicated by the arrows.3 Also, a set of manifest variables is associated with each of the latent variables, and these can be found in the appendix. The different components of the EPSI-model are as follows: • •

Image relates to the brand name and what kind of associations the customers get from the product/brand/company. Customer expectations relate to the prior anticipations of the said product in the eyes of the customer. Such expectations are the result

Figure 3.2  The EPSI Model Source: Adapted from Eklöf and Westlund, 2002, p. 1103; Hallencreutz and Parmler, 2019, p. 3

Understanding the Customer Side 55 of active company/product promotion as well as hearsay and prior experience from the product/provider. • The perceived quality concept includes two parts: product quality and service quality. “Product quality” is the quality of the product as such (in the eyes of the customer), while “service quality” relates to associated services like guarantees given, after sale service provision, availability, engagement, reception, etc. • Perceived value concerns the “value-for-money” aspect as experienced by the customer. It is here seen to be affected by perceived quality as well as by expectations. • Customer satisfaction is measured by three standard items: overall satisfaction, fulfilment of expectations, and how well you think “your provider” compares with your ideal provider. • Perceived loyalty relates to repurchase, word-of-mouth, and recommendation. When deploying the model, data collection is done mainly through computer assisted telephone interviews or web surveys based on a structural questionnaire as outlined in Table 5.1 in the appendix. Respondents are asked to rate all variables between 1–10. The model then transforms the output to index values between 0 and 100. A customer satisfaction score above 75 indicates a high level of satisfaction, while a score below 60 indicates customer dissatisfaction. Respondents may also leave open comments for further text analysis. The data presented in this chapter was collected from Svenskt Kvalitetsindex and is composed of a total of approximately 1.3  million customer interviews that were conducted between 1989 and 2019 (data from all the latent variables were included) and covered organizations within the industries of banking, insurance (life and non-life), telecom (mobile operators, broadband and Pay-tv), and energy (trade, distribution and heating). Now we have earlier unraveled that the longitudinal customer satisfaction trend is falling in Sweden, and in this section we have explained how customer satisfaction can be understood through latent variables. In the next section we will look closer at these latent variables and analyze them in connection to each other and how they together influence customer satisfaction in the context of digitalization. And as you will see, some very interesting insights and findings emerge.

Understanding the Drivers Behind the Digitalization Paradox Earlier we described how the evolution of digitalization has created a digitalization paradox. Digital services have come closer, but personal relations seem to have gone astray in the process. The gap between service providers and customers has never been perceived as wide as today

56  Understanding the Customer Side since new digital interfaces often lack a human sense. Swift functional solutions are available around the clock, but real social interaction is scarce. Something is missing in many digital value propositions because far too often digitalization initiatives turn technology centric instead of customer centric—and as we described in Chapter 2, such an overemphasis on technology has been very common in both practice and research for the last 60 years (and we will also readdress this issue of technology rationality in later chapters). So far, we have stated that digital technology changes, business landscapes, and classic theories about governance, management control, and effectiveness of private and public organizations seem less relevant today. Now, it is crucial to understand in-depth how customer perception evolves over time to be able to handle the digitalization paradox. A first step of doing so is to make a closer examination of the EPSI data and the customer satisfaction drivers in the EPSI measurement model. Figure  3.3 unravels the relative importance of the latent variables (drivers) on customer satisfaction across time. Let us go through them one by one. The latent variable Image denotes the awareness of a brand identity, which is the key element that affects how people perceive an

0

.1

.2

.3

.4

.5

Importance of latent variables on CSI over time

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

Year

Image −> CSI Product quality −> CSI Perceived value −> CSI

Expectations −> CSI Service −> CSI

Figure 3.3 The Latent Variables’ Relative Importance on Customer Satisfaction Over Time Source: Extended and adapted from Hallencreutz and Parmler, 2019, p. 7

Understanding the Customer Side 57 organization over time. This signifies what kind of associations the customers get from the product, brand or organization. The brand identity is the very soul of a brand and is difficult to change, at least not without major losses in time and money. Image should therefore be seen as an intangible asset that evolves over time. This variable has been the most important satisfaction driver in the EPSI model. As stated earlier in this chapter, customers do not only buy a product or a service, but they also buy the perception of a brand. As depicted in Figure 3.3, the trend (of the variable Image influence on customer satisfaction) in recent years is relatively stable and high regarding its impact on customer satisfaction. Thus, we can conclude that the importance of an organization’s image is sustained and remains strong over time. Intangible assets such as brand identity, trust, and reputation do have a significant impact on customer’s perception—positively as well as negatively. As mentioned, consumers are enlightened, conscious, and purposeful. Aspects such as social responsibility, sustainability, ethics, and conduct are critical and have been so for a long time. In a digital world, the average customer is also strongly affected and influenced by word of mouth and (social) media newsfeeds about different brands. We “like” and “unlike”. Although the tendency is that we are both critical and appreciative, it is fair to say that today, bad publicity may ruin a brand in seconds. In a digital world, it is important to safeguard the brand image. A final note is that certain fluctuations in the relative impact can be observed, for instance the Image peak in 2015. This was the result of an intense public debate about three aspects that together affected customer satisfaction negatively: coal production’s influence on large brands in the energy sector, a broad-based lack of trust in the banking sector due to certain “scandals”, and bribery in the telecom sector. Smaller and similar and fluctuations can also be identified in our data (but that is another story beyond the focus of this book). Deconstructing the EPSI data further, we note that the latent variable Product quality was stable until 2010, but since then the importance of this latent variable has been reduced significantly. Product specifications and quality aspects have less impact on customer satisfaction, according to our research. New technology does not seem to catalyze customer satisfaction the way it used to do in previous decades. This diminishing importance of product quality (as a driver for satisfaction) is an important and critical research finding when we seek to understand the customer side of digital change from a practitioner’s viewpoint. Product quality is substituted by Service quality (they cross each other in Figure 3.3 around 2012), covering “softer” aspects such as customer relations, availability, engagement, and reception. This research finding could perhaps serve as a wake-up call for many organizations, focusing mainly on product characteristics and technology investments in the era of digitalization,

58  Understanding the Customer Side instead of servitization and customer relations. New products, gadgets, special features, cool apps, advanced internet interfaces, or “things” in general seem to have a very volatile effect on customer satisfaction. In fact, we advocate that new digital technology in many cases actually drives dissatisfaction. It has become a “hygiene factor” and should just be there and work. No one rejoices over new apps or internet interfaces anymore (or talking fridges, intelligent washing machines, or connected cars); that time has passed. In this respect, digital technology has become a commodity. Instead, the effect on customer satisfaction from the latent variable Service quality has increased significantly over the last ten years and is now almost equally strong as Image (see the highest two lines in year 2017 in Figure  3.3). Customer service breeds customer satisfaction, and this variable has a significantly greater impact on customer satisfaction today than the variable Product quality. The shift took place in 2011—just as the general level of satisfaction started to shrink in Sweden—and since then the gap has widened, as depicted in Figure 3.3. Thus, it is reasonable to assume that the digitalization paradox has affected customer satisfaction negatively. Open comments from respondents (in the questionnaires) about service quality strengthen such a hypothesis by stressing the absence of “closeness” and personal relations. Further examination of these open comments yields a picture that tells us that being close to customers’ needs, being personal and local (geographically close), and being close to customers’ core values profoundly drive customer satisfaction. Another fundamental, and perhaps obvious, service quality aspect is to proactively provide swift responses to shifting customer needs, demands, and expectations. Moreover, as technology streamlines many services, the elusive phenomenon of “being different” stands out as an important customer satisfaction enhancer. Consequently, to achieve digital mastery it is crucial to zoom in on the customer end of the supply chain rather than just focusing on technology. Finally, the variable Perceived value has been low on the importance scale but has increased slightly over the last two years mainly due to the occurrence of several price comparison sites. But the effect on customer satisfaction from a digitalization perspective is negligible. A general conclusion based on this data is that expectations, price, and Perceived value are interrelated to other quality aspects and do not per se have a significant impact on customer satisfaction and loyalty. Thus, a low price is not necessarily a competitive advantage. In conclusion, our longitudinal data on customer satisfaction shows a paradigm shift in the studied industries during the last decade—product quality is substituted by service quality as one of the most crucial drivers for customer satisfaction. This calls for a shift of focus, especially in a time of rapid change driven by globalization and new digital technology.

Understanding the Customer Side 59 However, such a shift from product deliveries to service deliveries holds new challenges. Services from all societal sectors are available around the clock via digital platforms, but many consumers still perceive digitalization as something sterile and anonymous rather than personal. Therefore, service providers have never been perceived as “distant” as today. The digital customer interfaces are available 24/7, but the sense of a personal relationship seems to be lacking. This is a true digitalization paradox: services come closer, but the gap to personal (human) interfaces widens. All these findings call for new principles, practices, and tools to urgently enhance customer centricity. A shift towards a more balanced integrated approach recognizing the increasing value deriving from firms’ intangible assets such as brand image and customer perception seems to be a way forward in times of digital change. This book may hopefully provide some useful insights on how to go about doing so. Digital technology is for sure an enabler, and digitalization is without a doubt a brute force in all societal sectors. But it does not seem to automatically sustain customer satisfaction and loyalty. To prosper in this new environment, we should instead profoundly understand the latent satisfaction drivers and learn to handle the digitalization paradox.

How to Manage the Digitalization Paradox From a Customer Perspective Once again, most organizations face paramount challenges when leading digital change. Employee change resistance, lack of internal expertise, hindering organizational structures, political aspects, budget constraints, and a general lack of an overall digitization and change strategy are common internal pitfalls. As we will describe in detail in Chapter  6, such pitfalls can be significantly reduced by a balanced interplay between soft and human factors on the one hand, and hard and technology/structure factors on the other hand. One without the other will not cut it. The digital change will bring along a myriad of technical challenges, and the right people need to be on board. Our own research findings show that difficulties with digital change is very seldom about the functionality or availability of technology (as we also brought up in Chapters 1 and 2). Instead, embracing the people side is crucial. Adding the customer perspective to this discussion makes digital change an even greater undertaking, especially if you are facing a change of great complexity and magnitude. How do you cope with the societal change and different stakeholders’ needs and expectations while our own platform is burning? How do you strengthen brand image and service quality when we are busy handling internal strategic, structural, and cultural ordeals?

60  Understanding the Customer Side The core of the digitalization paradox is the gap between perceived Service quality and perceived Product quality—as depicted in Figure 3.3. A  fundamental service quality aspect is to provide swift responses to shifting customer needs, demands, and expectations. Our data discloses the need for close and personal relations, enabled through sincere human interactions. Being a trusted business partner, being personal and local, and being close to customers’ core values profoundly drive customer satisfaction. Core service aspects needed to be able to close the paradox gap can be summarized as follows: •

•

•

Simplicity—A plethora of streamlined digital services confuse customers in a stressful environment. Smartphones of today are crowded with colorful apps that are more or less useful. Therefore, easy access and first-time right are important guidelines when handling the digitalization paradox. When developing a new digital service, substituting a manual (analogue) service, or adding a digital service to a physical product, it is crucial to validate the usefulness through the eyes of customers. Your intended end-users probably already have a myriad of similar apps with similar functionality in their smartphones. These apps will be benchmarked, and expectation spill over will likely occur (features and functions will be compared). So critically ask yourself, in what way will your digital service stand out and add value in a wider context? Customization—Customers want to feel important and acknowledged. Standardized digital products and services might be rational, swift, and easy to access but not always user friendly. A  customer imperative in this new environment is “know me and show me!” Instant is the new expected and perceived individual solutions are a “must-have”. But offerings generated through algorithms based on internet and social media traffic are not appreciated by the vast majority of consumers out there—this is not seen as a “serious” customization. In fact, these automated processes quite often are counterproductive. Instead, we advocate that managers should put much more effort into encouraging their organizations to literally treat every customer interaction as an opportunity for recognition and get to know each customer a little better. The machines could do a lot but not this job. Profound social interaction is still a human thing. Proactivity—A recurrent pattern in our data is the importance of proactivity. In the digital environment people feel lost and abandoned by their service providers. Common customer comments are: “I wish someone cared”. The organizations that successfully bridge the paradox gap listen to the unspoken needs and wants and are the first ones to reach out. In practice, they act on customers’ unexpressed demands, needs, and expectations. Proactivity is not about

Understanding the Customer Side 61 being clairvoyant but rather a mindset among engaged employees with a sincere interest in “walking the extra mile”. If you grow close customer relations and know your customers consumption patterns and preferences, you can come up with timely and tailored offerings to different customer segments. But let us repeat: the solution is not to spam customers with auto generated newsletters or seasonal offerings based on internet traffic. According to Westerman and his colleagues (2014), there are several key differences between leaders and laggards when it comes to the implementation of digital technologies. Those who are successful in mastering the digitalization paradox share some key attributes. They know how to use technology to get close to customers, empower their employees, and fully understand both the customer and employee side of digital change. Moreover, leaders of these organizations know how to drive effective organizational change (more about this in Chapter  5 and particularly Chapter 6). They have a clarity about how and where to invest in digitalization and have articulated a vision. Strong leadership capabilities also make new digital initiatives easier and less risky. Unfortunately, here many leaders go astray. Successful digital change should focus on the people side of change. And “people” in this context means both employees and customers. Handling the customer side of digital change means in practice that digital customer processes should be transformed through a combination of a series of down to earth interventions: •

•

Lead through sensemaking and sensegiving—Leaders may be unable to completely erase doubt and uncertainty from employees’ minds, but one can certainly alleviate them (as we will explain in the upcoming chapter). Being consistent and transparent is key. Keep employees informed and involved through the whole process. Empower them and paint them a future they can all work towards. Engaged and motivated employees are by far the best service providers and brand identity enhancers and may boost customer satisfaction through times of change by being friendly, personal, and available. In our earlier work we have presented more precisely how leaders can go about when they lead change through such sensemaking and sensegiving processes (see: Iveroth and Hallencreutz, 2015). Know your customers—Organizations that are successful in coping with the digitalization paradox also invest more effort in understanding customer behavior. They observe how customers behave before, during, and after interactions and then design the digital customer experience based on this information. Making the employees customer focused is key. This can be achieved through transparent information about customer satisfaction and candid conversations

62  Understanding the Customer Side

•

•

about positive as well as negative customer feedback. For example, our research shows that organizations that have a high customer satisfaction score and that use such measures actively have a clear customer strategy, processes for measuring, processes for follow-up, and a customer oriented culture (Birch-Jensen et al., 2018). Zoom in on image and service—Another success factor is to admit and address image and service challenges and be transparent, humble, and honest in this effort. Avoid self-deception and fight organizational habits claiming that “we know our market and our customers”. To understand and handle critical customer interactions is crucial. The brand is built both from outside-in (market communication) and inside-out (personal customer service). Swift and candid complaints handling and service recovery processes can also be good means to improve customer perception. Personal and informal customer relations and initiatives should also be noticed and encouraged by management—in times when everyone looks alike it gives a competitive edge to be different. Focus on parallel stakeholders—Customers and employees of today are enlightened, conscious, and purposeful. Aspects such as social responsibility, sustainability, ethics, and conduct are critical. Therefore, digital masters use all available channels to improve customer reach and engagement and get closer to both customers and employees as well as other interested parties in an intertwined and interconnected environment. Personal relations should always be nourished. Today’s contender could be tomorrow’s business partner.

Finally, successful digital change requires good use of customer data and a scientific approach to decision making. The risk of suffocating from data drowning is always present, especially since most organizations these days experience an overload of information. However, agile change leaders understand the importance of harnessing the huge volumes of unstructured data coming from surveys, customer usage, and social media. They filter out the trivia and integrate data to gain insights, make better decisions, and increase the quality of the customer experience in times of change. In summary, this chapter has addressed the customer side of digital change and how digitalization affect consumer behavior and customers’ demands, needs, and expectations in literally all corners of our modern society. We have shown that new digital technology has changed customer perceptions and behaviors during the last decades in many industries. We have also established that the main reason for the decline of customer satisfaction is the failure in the ability to transform technological achievements into customer value.

Understanding the Customer Side 63 Moreover, we have discussed the need for proactive change strategies. Instead of taking initiative, far too many organizations have drifted along and adopted reactive digitalization strategies. Looking ahead and trying to make prophecies about the future is always bound to fail. But we will try anyway. If we take our longitudinal customer perception data from three decades and flip the perspective to 30 years ahead, what patterns do we then see? We believe the following five overarching tendencies will be sustained: •

•

•

•

•

Digital is natural—The digitalization troubles we discuss in this book and elsewhere will soon be “the new normal”. For sure, new innovative gadgets and applications that we today cannot dream about will be launched. Some will probably revolution our everyday life, and some will be buried and forgotten. Most likely technology will have “human sense” built in, but genuine and sincere human relations will always beat technology. Trust is everything—We believe that the importance of genuine core values will be strengthened in the decades to come, where trust and trustworthiness stand out as critical intangible assets (as an opposite to “fake”). Brand identities built on trust are bound to prosper. Sustainability is for real—The global attention on economic, social, and environmental issues will accelerate and soon be a core aspect of any organization’s operation. Policy statements and beautiful words on websites will no longer be accepted by a young, conscious, and angry generation of consumers. Closeness is key—When embedded technology has become “normal”, the ability to offer and deliver local, personal, and customized products and services will be a competitive advantage. Customers will choose providers with trusted brands, core values close to their own, and genuine value propositions. Satisfaction and loyalty will be built on close customer relations where technology will play a subordinate part. Critical thinking is back—We foresee that people (hopefully in a near future) will take a step back and start to critically scrutinize the continuous flow of information out there. Sources, references, and factual review will be modern again. This will of course affect consumer preferences.

This chapter have explored how digitalization influences consumer behavior and customers’ demand, needs, and expectations. More specifically, we have shown that new technology has blurred the boundaries between industries and societal sectors. Customers no longer benchmark functionality and digital services within a specific industry; they go beyond and expect the same level of functionality from everyone—we

64  Understanding the Customer Side call this expectation spillover. We also see that customers demand personalized solutions and offerings. And, perhaps the most crucial finding, the emergence of new digital services has led to a growing need for personal relations. This is the very core of the digitalization paradox: technology drives a need for human interaction. No one can predict the future, but we strongly believe that understanding the customer side of digital change very much is a matter of understanding human behavior. The digitalization paradox is for real. We also know that the new connected society under construction will be a complex adaptive system and needs to be managed accordingly. Digitalization per se enhances this complexity and calls for new management models as well as new ways of thinking. The technological aspect of transformational and sometimes disruptive digital change should align and harmonize with the organic, emergent, and evolutionary characteristics of behavioral change. However, the people side of change is always a challenge—as we will now colorfully illustrate with an historical story about transformational change in the subsequent chapter.

Notes 1. Other nations which have developed national indices are Norway (Wallin Andreassen and Lindestad, 1998), Denmark (Kristensen et  al., 2000), and the US, with the American Customer Satisfaction Index (ACSI) (Fornell et al., 1996). The European Performance Satisfaction Index (today known as the EPSI Rating initiative) was first initialized in 1997 by the EC (European Commission) and the Pan-European quality organizations EFQM (European Foundation for Quality Management), EOQ (European Organisation for Quality), and IFCF (International Foundation of Customer Focus) (International Foundation of Customer Focus; Eklöf and Westlund, 2002). 2. One might wonder why market research from a small country in the outskirts of northern Europe is relevant, but these findings about a decrease of customer satisfaction are congruent with similar studies in Europe. Furthermore, it should be noted that Sweden scores top three (after the US and China) in the IMD World Digital Competitiveness Ranking (IMD, 2018), and overall the Nordics are often seen as progressive when it comes to digitalization and innovation. Bearing these aspects in mind we find it relevant to learn more why customer satisfaction seems to have decreased during the last decade with Sweden and the Nordics as a starting point. 3. The EPSI Model is built on Structural Equation Models (SEM; Bollen, 1989; Kaplan, 2000). SEMs include a number of statistical methodologies meant to estimate a network of causal relationships, defined according to a theoretical model, linking two or more latent complex concepts, each measured through a number of observable indicators. The basic idea is that complexity inside a system can be studied considering a causality network among latent concepts, called latent variables, each measured by several observed indicators usually defined as manifest variables. Within SEMs, the EPSI-model relies on the Partial Least Squares (PLS; also known as PLS Path Modelling, PLS-PM) and this has been proposed as a component-based estimation procedure different from the classical covariance-based LISREL-type approach (Tenenhaus,

Understanding the Customer Side 65 2008). PLS Path Modelling aims to estimate the relationships among blocks of variables, which are expressions of unobservable constructs. Essentially, PLS-PM is made of a system of interdependent equations based on simple and multiple regressions. Such a system estimates the network of relations among the latent variables as well as the links between the manifest variables and their own latent variables (for further details on the methods connected to the EPSI model, see, e.g.: Eklof, Hellstrom et al., 2017; Eklof, Podkorytova et al., 2018; Eskildsen et al., 2003; Fornell, 1992; Fornell et al., 1996; Kristensen and Westlund, 2003).

References Arvidsson (2011). Disclosure of non-financial information in the annual report: A  management-team perspective, Journal of Intellectual Capital, 12(2), pp. 277–300. Bergman & Klefsjö (2010). Quality: From customer needs to customer satisfaction (Lund: Studentlitteratur). Birch-Jensen, Gremyr, Hallencreutz & Rönnbäck (2018). Use of customer satisfaction measurements to drive improvements, Total Quality Management & Business Excellence), pp. 1–14. Bititci, Garengo, Dörfler  & Nudurupati (2012). Performance measurement: Challenges for tomorrow, International Journal of Management Reviews, 14(3), pp. 305–327. Bollen (1989). Structural equations with latent variables (New York: Wiley). Cöster, Iveroth, Olve, Petri & Westelius (2020). Strategic and innovative pricing: Price models for a digital economy (Abingdon: Routledge). Edvardsson, Gustafsson, Olsen & Witell (2014). Turning customer satisfaction measurements into action, Journal of Service Management, 25(4), pp. 556–571. Eklof, Hellstrom, Malova, Parmler & Podkorytova (2017). Customer perception measures driving financial performance: Theoretical and empirical work for a large decentralized banking group, Measuring Business Excellence, 21(3), pp. 239–249. Eklof, Podkorytova & Malova (2018). Linking customer satisfaction with financial performance: An empirical study of Scandinavian banks, Total Quality Management & Business Excellence), pp. 1–19. Eklöf  & Westlund (2002). The pan-European customer satisfaction index programme—current work and the way ahead, Total Quality Management, 13(8), pp. 1099–1106. Eskildsen, Westlund & Kristensen (2003). The predictive power of intangibles, Measuring Business Excellence, 7(2), pp. 46–54. Fornell (1992). A national customer satisfaction barometer: The Swedish experience, Journal of Marketing, 56(1), pp. 6–21. Fornell, Johnson, Anderson, Cha & Bryant (1996). The American customer satisfaction index: Nature, purpose, and findings, Journal of Marketing, 60(4), pp. 7–18. Hallencreutz  & Parmler (2019). Important drivers for customer satisfaction— from product focus to image and service quality, Total Quality Management & Business Excellence), pp. 1–10.

66  Understanding the Customer Side Hellsten & Klefsjö (2000). TQM as a management system consisting of values, techniques and tools, The TQM Magazine, 12(4), pp. 238–244. IMD (2018). The IMD world digital competitiveness ranking 2018 results, IMD world competitiveness center. Available from: www.imd.org/wcc/world-com petitiveness-center-rankings/world-digital-competitiveness-rankings-2018/ [Accessed 2020–03–24]. Iveroth & Hallencreutz (2015). Effective organizational change: Leading through sensemaking (London: Routledge). Kaplan (2000). Structural equation modeling: Foundations and extensions (Thousand Oaks, CA: Sage). Kristensen, Martensen & Gronholdt (2000). Customer satisfaction measurement at post Denmark: Results of application of the European customer satisfaction index methodology, Total Quality Management, 11(7), pp. 1007–1015. Kristensen & Westlund (2003). Valid and reliable measurements for sustainable non-financial reporting, Total Quality Management  & Business Excellence, 14(2), pp. 161–170. Mcafee, Brynjolfsson, Davenport, Patil & Barton (2012). Big data: The management revolution, Harvard Business Review, 90(10), pp. 60–68. Oliva & Kallenberg (2003). Managing the transition from products to services, International journal of Service Industry Management, 14(2), pp. 160–172. Ostrom, Parasuraman, Bowen, Patrício & Voss (2015). Service research priorities in a rapidly changing context, Journal of Service Research, 18(2), pp. 127–159. Porter & Heppelmann (2014). How smart, connected products are transforming competition, Harvard Business Review, 92(11), pp. 64–88. Sousa (2003). Linking quality management to manufacturing strategy: An empirical investigation of customer focus practices, Journal of Operations Management, 21(1), pp. 1–18. Stern (2006). A guide to global acquisitions (Palo Alto, CA: Fultus Corporation). Taticchi, Tonelli  & Cagnazzo (2010). Performance measurement and management: A literature review and a research agenda, Measuring Business Excellence, 14(1), pp. 4–18. Tenenhaus (2008). Component-based structural equation modelling, Total Quality Management, 19(7–8), pp. 871–886. Wallin Andreassen & Lindestad (1998). Customer loyalty and complex services: The impact of corporate image on quality, customer satisfaction and loyalty for customers with varying degrees of service expertise, International Journal of Service Industry Management, 9(1), pp. 7–23. Westerman, Bonnet & Mcafee (2014). Leading digital: Turning technology into business transformation (Boston, MA: Harvard Business Review Press).

Appendix

Table 3.1  Items From Questionnaire Connected to the EPSI Model Latent variables

Manifest variables

Image

• • • • • •

Customer Expectations

• • Perceived Product Quality

• • • •

Perceived Service Quality

• • •

Perceived Value

• •

Customer Satisfaction

• • •

It can be trusted in what it says and does It is stable and firmly established It has a social contribution for the society It is concerned with customers It is innovative and forward looking Expectations for the overall quality of “your provider” at the moment you became customer of this provider Expectations for “your provider” to provide products and services to meet your personal need How often did you expect that things could go wrong at “your provider” Overall perceived quality Technical quality Range of services and products offered Reliability and accuracy of the products and services provided Customer service and personal advice offered Quality of the services you use Clarity and transparency of information provided Given the quality of the products and services how would you rate the fees and prices that you pay for them? Given the fees and prices that you pay, how would you rate the quality of the products and services offered? Overall satisfaction Fulfilment of expectations How well do you think “your provider” compares with your ideal provider? (Continued)

68  Understanding the Customer Side Table 3.1 (Continued) Latent variables

Manifest variables

Customer Loyalty

• If you would need to choose a provider how likely is it that you would choose “your provider” again? • How to you usually talk about your provider. In a negative or positive way? • If a friend or colleague asks you for advice, how likely is it that you would recommend “your provider”?

4 The Swedish Potato A Story of a Transformation

Introduction Individual, organizational, and societal change that comes out of different technological conquests is nothing new. In this chapter, we will illustrate this through a story about the introduction of potato cultivation in 18th-century Sweden. The vignette communicates certain strategic aspects of technology-induced change, but most importantly it uncovers the behavioral dimension of such change. Then later in the proceeding Chapters 5 and 6, we will revisit this story to underline and clarify key points and rationales in a colorful way. We have chosen to communicate parts of this book in this way because learning in many cases comes not from aggregated metaphors, figures, and models, and neither from atomic details of the empirical world, but rather from the stories that are crafted in between these two extremes. In this way, successful learning in many cases lies in the stories that are weaved from both high and low aggregation. The anticipation of such an approach is, by the words of McCloskey (1990, p. vii), that leaders, consultants and researcher that ride on the hyperbole of digitalization should “stop selling snake oil and . . . come back into the conversation of humankind. That is where they belong, back where we can watch them”.1 So let’s start: the potato began its development as a tuber in human service already about 10,000 years ago in South and Central America, but it took thousands of years before the potato reached Europe via the Spaniards during the 16th century (Brown, 1993; Hawkes and FranciscoOrtega, 1993; Hougas, 1956). This new farming technology meant a major transformation for literally the whole of Europe, in a time when farmers cultivated barley, oats, rye, flax, and turnips, and bad harvests and malnutrition were common. This is a fictional story, but many details are true and based on historical research.

Prologue The year is 1752. September is chilly and grey. The lush green of summer is fading away and farmer Jacob Andersson is desperate. Again. The

70  The Swedish Potato harvest has failed, and his family is facing another winter of hunger. He feels miserable and useless. What to say to his wife and two daughters? He leans on his pitchfork and sighs. Something radical must happen. Some kind of miracle. This simply cannot go on. The scene is from Småland in Sweden, in an era when farmers were severely undernourished and struggling. Crop failure was very common, there was an almost constant shortage of grain. Every year large amounts had to be imported from abroad. Because of these harsh conditions, the Royal Swedish Academy of Sciences2 made different attempts (in cooperation with the state authorities in Sweden) to encourage Swedish farmers to change parts of their crop over to production of the more nutritious potato. In a European perspective, Sweden was a late adopter of potato as they started doing attempts in late 18th century, and by then Italy, Spain, France, and the UK had already used the potato in cultivation since the late 16th century, and what is now known as Germany had experience of this crop from the beginning of the 17th century (Hawkes and FranciscoOrtega, 1993). However, the worn out farmer Jacob Andersson knows nothing about all this. He is just desperate and hungry. And he prays for a miracle. One of the attempts to encourage potato production was made by the scientist Jonas Alströmer, who published writings about this new crop and the cultivating and harvesting technology behind it (Alströmer, 1777, 1992). He was also involved in Royal Swedish Academy of Sciences efforts spreading a leaflet in the form of a “potato manual” to farmers in Sweden (this actually still exists; see: Kungliga Tryckeriet, 1749)—similar attempts were made elsewhere in Europe by, for example, Frederick the Great (Frederick II) in Prussia (Hougas, 1956). However, there was initially strong resistance to the change, since many farmers could not understand how potatoes should be grown, harvested, and eaten. In other words, they misunderstood the technological and organizational changes needed to succeed with potato production. In addition, the potato was connected to strong feelings, fears, and prejudices, as this story soon will unravel.

Scene One The Andersson family has barely survived winter, but now spring is coming with new hopes. And . . . surprise! One early morning Jacob Andersson receives a strange package from the governmental authorities in the far distant city of Stockholm. Andersson has never been to the capital or had any direct contact with these governmental bodies, so it all feels weird and outlandish. He opens the package and inside he finds a letter, a book, and a copy of Jonas Alströmers’s manual about how to grow potatoes and a couple of seed potatoes.

The Swedish Potato 71 Andersson scratches his head and tries to decipher the letter. What on earth is all this about?! The deciphering turns out to be a tough challenge. Both the letter and the book are written in a type of language that is seldom spoken in these rural areas. The writing is so artistic and unfamiliar that the poor farmer finds it hard to even distinguish different letters. He is more used to reading the bible. Despite these difficulties, he finally manages to understand the core of the message. Apparently, these so-called authorities are deeply worried about the fact that people are starving in Sweden and they now offer a solution to this problem. They want farmers like Andersson to start growing a new exotic crop called potato. In other words, and as far as he could understand, they ask him to change the way he has been working for decades and start cultivating potatoes. Then there was gabble about a vision of a well-nourished and healthy Swedish people. Andersson feels cross and irritated. Why should a bunch of high street people in Stockholm know better than himself about farming? He cannot relate to their vision because the way he has done things by growing wheat and barley has worked for his family for generations. If they really wanted to help, they should do something about the Swedish weather! Send a fancy letter to god instead! He frowns and throws the piece of paper away. He then picks up this weird manual about growing potatoes. This text is even worse than the letter. He cannot comprehend or in any way relate to the abstract descriptions of farming practices, noble language, and the strange combination of Swedish and Latin terms. He feels awkward—both insulted and stupid at the same time. Deep inside, he realizes that he cannot go on like before. This last winter literally almost buried his family. But a major change feels overwhelming. What if everything goes wrong?! The content of the package feels very alien for Andersson, but he decides to be progressive and try these new lumps called seed potatoes. OK, I will try to do this but never mind all this detailed gibberish, I will just do what I always do. Just plant these and eat whatever comes out of the earth, Andersson thinks to himself.3 Accordingly, he plants the potato seeds, waits for about two months, things begin to grow, and all of the sudden just before midsummer the plants are shedding their blossoms. Now he does what he has done all his life; he reaps and eats whatever comes out of the ground. There seem to be some nice leaves and haulm—they could work as an alternative to lettuce. Also, there are beautiful green berries4—I am sure my wife can make a good jam out of them. Perhaps these new tubers weren’t so bad after all. As the summer goes by the righteous Andersson, his wife and daughters do what he thinks the authorities wants them to do: they eat the potato haulm and berries for lunch and dinner. This has evidently disastrous effects. Not only is it almost inedible, it also causes diarrhea,

72  The Swedish Potato headaches, and cramps. As a result, he stops cultivating potatoes. Fortunately, he has only used a small part of his precious land for growing this new poison, and there is enough barley and wheat to keep them through the rest of the year. Andersson is furious with the authorities in Stockholm. He is also suspicious and wonders if a larger conspiracy is behind all this. He decides to keep quiet about this debacle and instructs his family to say nothing to anyone. He looks back at this strange potato ordeal with an awkward feeling—why did the authorities try to poison his family? Does the state try to extinct poor people?! Or is it an act of the Devil?! Is this perhaps some kind of punishment? He promises himself to never ever again listen to advice from foreigners or abandon old habits and working methods. This effort nearly killed them.

Scene Two About a year later, his neighbor, the somewhat bumptious herbalist and gardener Einar Carlsson, stops by the Andersson family. Carlsson is a successful gardener in the parish and sells ordinary as well as exotic crops to a wide range of customers. Carlsson notices that his old neighbor Jacob looks thinner than ever after yet another hard winter. Einar says: My dearest friend, you have seen better days. Have you tried this new exotic crop called the potato? It is magical and does wonders—you should really try it out. It would do you and your family good. Andersson replies fiercely: No way! I tried it last year and it turned out to be toxic. Then Carlsson hears all about the troubles that Andersson went through, as well as his theories about a covert state extinction program staged by a rough official called Allstrom or something like that. Andersson lowers his voice and whispers; between us, I think the church has something to do with all this. As Andersson babbles on, Carlsson gets more and more concerned about his old friend. He says with a friendly voice: No, you got it all wrong my friend. Your failure had nothing to do with evil men from Stockholm. You should eat the root of the plant and not the leaves and berries. You must change the way you do things when you are growing potatoes. It is a whole new way of thinking, working and farming. Andersson listens suspiciously. His eyes blacken: I  knew it  .  .  . you too . . . Einar . . . you too are a part of all this. Andersson turns away and walks back to his cottage. His clothes hang like rags over his thin body.

The Swedish Potato 73 A week later they meet again. Carlsson notices that Andersson is even more weary and pale and decides to use another tactic: Jacob, this cannot go on. Now, let me tell you my story. Andersson shrugs. Then Carlsson tells Andersson all about the practices and procedures behind successful potato cultivation. He admits that he also was a little cautious in the beginning but was convinced when he realized all the benefits. Carlsson then brings Andersson to the field and explains the potatoes sensitivity to sunlight. Jointly they plant some seed potatoes and Carlsson demonstrates how they later should be harvested. They even take a walk to Carlsson’s farm and Carlsson shows Andersson his own cellar, where he describes how to store potato in the best way. Carlsson even say that Andersson can store his potatoes in Carlsson’s cellar. They then take a walk back to Andersson’s farm and there with a grin Carlsson reveals that in his backpack he happens to have a couple of delicious potatoes. Andersson feels miserable. He and his family are tormented by hunger, but it would be such a defeat to admit to everyone that he has been a fool and that he almost killed his family by ignorance. Reluctantly they go to Andersson’s kitchen and together they make potato mash. Andersson, as well as his wife and daughters, enjoy the meal tremendously (and they feel satisfied for the first time in ages). Carlsson is very pleased. He has translated this alien tuber into something attractive through words, language, gestures, and demonstrations that Andersson and his family can understand. This translation was successful because Carlsson is an herbalist and therefore an expert on these matters. In addition, Carlsson is also good with people and good at explaining complicated matters because he has his own store and green house where he sells exotic crops like potatoes to uninformed customers. As a result, of the translation, Andersson begins to reflect and learn. He begins to understand what it really means to be a potato farmer.

Scene Three Although Andersson enjoyed the mashed potatoes he is not yet fully convinced. Carlsson is very eager and pushy. Sure, they have been friends for long but old Carlsson is also known in the neighborhood for being just a little too good to be true. Some people even call him manipulative and greedy. So, when Carlsson suggests that he could supply Andersson with seed potatoes and storage capacity if he could get a fair share of the harvest, Andersson backs away: Sure, but why should I bother? Why should I care? I might as well continue with wheat and barley. They have worked fine for me and my family for generations. We have just had a couple of bad

74  The Swedish Potato years lately due to circumstances out of my control. It all lies in the hands of God almighty. Then Carlsson starts to line up arguments: Well you could do that, but you have to realize that the potato produces one-third and sometimes even one-half times more crop compared to wheat and barley. If you for example plant potato on one square meter and plant wheat or barley on another square meter, you will get more out of the square meter where you planted your potato. You and your family will have twice as much to eat! This must surely be important to you since you do not have that much land to grow your crops. We have known each other for a long time, and I am sure we could settle a fair potato deal. I will help you all the way. Andersson is still not convinced. Carlsson preaches: Not only that, but the potato has immense nutritional value compared to other crops. If you start growing and eating the potato, your family will be better off and better nourished. Also, the potatoes are buried beneath the earth so they will be protected from pilferage. You know as well as I that since people in the area are starving, they have started to steal crop from each other. This will not become a problem for you if you start with potato production and store the outcome in my cellar. Another thing you should also consider is that the potato is very easy to prepare and cook. It will take your wife less time and energy to transform the potato into a nice meal compared to wheat or barley. On top of this I am not suggesting that you should stop using wheat and barley all together. I am just saying that you should vary that crop that you have. If there is a bad harvest for the barley you can fall back on the potatoes—and the other way around. Andersson feels emotional: Still I don’t think I can manage this all by myself, I don’t have that much of land to use for this wild experiment, and it seems so complicated. I don’t think I have what it takes. And the most important of all is that the stakes are really high: if I fail my family will starve another winter. Carlsson reassures and coaches: Oh, don’t you worry. I am an expert on this matter, and I have grown the potato for some years now. You and I live close by and we meet regularly so I will be able to help you and give you support as you are

The Swedish Potato 75 testing this new crop. In addition, my business is booming so if things go wrong your family are always welcome to eat at our place—I am sure you can compensate me when you overcome your initial problems. Don’t you worry about that now. Andersson expresses deeper emotions and the common belief about the potato in the parish: Oh that’s really nice of you, but I am afraid that people will make fun of us and reject us if we start growing this weird lump. You have always been successful, but I know that people talk behind my back. . . “look there goes that stupid Andersson who almost killed his family”. The potato is murky, shady and earthy. This must surely be proof of the devilish nature of this weird root-crop. People in the valley also tell me that it causes leprosy and can be used as an aphrodisiac: this must surely be the work of the devil. You must also remember that I have two daughters soon ready to be married. If people in this parish find out that we are using this devilry then I think that we will be expelled from the community. The girls might even be seen as witches. And you know as well as I about the consequences of being rejected from the parish. We might even be punished by being put in the pillories. So . . . I must admit that the mash was delicious but think I decline your generous offer after all. (these different forms of prejudices connected to the potato was common and one of the reasons for why it took so long before potato cultivation was established, see, e.g.: Brown, 1993) Carlsson is persistent: Yes, yes, yes I  am aware of the gossip and the foolishness spreading in the parish. But these are ideas of very ignorant minds from people that are afraid of change. Don’t listen to them. Surely you are better than that. I know that this is not true at all, since I have grown the potato myself for years and as you know—I am still doing fine. Do you see any horns in my forehead? Do I have a tail? Is my tongue black? Of course not! These rumors are just stupid ideas. In fact, even the priest of this parish grows the potato and he strongly believes that the potato is not the work of the devil but on the contrary a gift from god. Carlsson explains his relationship with the priest: I am actually a very good and close friend of the priest and we have a mutually beneficial collaboration. We both share a passion for

76  The Swedish Potato gardening, and he has gardening as a hobby and spends his spare time growing root-crops like the potato. I  humbly assist him with some good advice every now and then, and he gives me and my family an extra blessing in the evening prayer in return. He understands these matters and the prejudice that surrounds the potato. We have been thinking about this situation and the bad consequence that it brings for quite some time now. Carlsson presents a change and political plan: Actually, we have a plan how we can get rid of all these foolish and false ideas. On the church service every Sunday for the future month or two he will deliver a sermon with the message that the potato is indeed a gift from god. He will also strengthen this message by informally talking to people when he socializes before and after the church service to make sure to get the message across. By the end of the month people will begin to understand the word of mouth and appreciate the true nature of this wonderful new crop. Indeed, the priest and I have set out to get rid of all these rumors and prejudices once and for all. Therefore, I  don’t think people will bother your family. I have also volunteered to provide seed potatoes for everyone in the parish. It feels so good to save lost souls. Almost like a divine act. And I will ask for very little in return, just a minor fraction of their future harvests. After some weeks of more persuasion, Andersson finally accepts the challenge and Carlsson gives Andersson some seed tubers. Just before leaving, Carlsson reinforces the message by saying: Oh, by the way, did you know that the potato has such a beautiful flower that even King Louis XVI of France wears it in his buttonhole and the queen Marie Antoinette wears it in her hair? (this is true according to Hougas, 1956).

Scene Four Time went by and Andersson ultimately followed Carlsson’s advice and started growing potatoes. Since Carlsson was eager to follow the progress of his investments, he was sincerely interested in making sure that Andersson and many others in the parish had actually changed their mindset and attitude towards this new crop and had started to produce this gift from God. Therefore, every second week on Mondays during Carlsson’s spring and summer morning walks, he stops by Andersson’s potato fields and counts the number of potato plants and the number being harvested. He also from time to time chats with

The Swedish Potato 77 Andersson about how it is going. Carlsson also peeks into Andersson’s garbage hill to see if there are any potato peels there. This last and small activity is important for Carlsson, and he thinks to himself: there is a big difference between what one says one does and what one does in the end. The same process is repeated at other farms along his morning trail— farm’s that Carlsson has been nudging with seed tubers, fertilizer, and good advice. He calls these farmers his personal “disciples” and reports regularly to the priest about their progress. He makes mental notes about his observations—his indicators—and reminds himself to ask the priest to perhaps praise him a little extra at the sermon the upcoming Sunday. Pleased, he summarizes that due to this new farming technology and his own profound goodness the parish is now prospering, and his pocketbook is becoming thicker. A divine combination, he concludes, as he hums through the valley on his way home.

Epilogue Andersson’s attempts of transformation into potato cultivation were eventually successful, thanks to Carlsson, and he and his family did not need to go hungry anymore, and their health increased tremendously. In fact, he and his family served as a good example and symbol for the rest of the parish. After some time had passed, the rumors spread in the parish and neighboring villages about Carlsson and Andersson’s activities, and more and more farmers picked up on potato production. Many of these suddenly realized that everybody else was “doing it” and therefore adapted to this new way of cultivation. However, there were also those in the parish that were persistent and wanted to preserve the old way of doing things and that shared Andersson’s earlier prejudice about the potato. This was very unfortunate, as there were crop failure in later years that amounted into starvation and many people died. The farmers that were late adopters were not only inspired by the discussion and activities that were taking place between Carlsson, Andersson, and the priest, but they also began to notice a number of activities that emerged: various people from different parts of the parish began to collaborate and experiment with all sorts of stuff that was connected to this new crop. Gradually, a potato became so much more than just food as it opened up for new ways of making a living and new ways of making a buck. Here are some examples of this. Since Einar Carlsson was an innovative herbalist, he started to fine tune potato cultivation and developed potatoes seeds that was more accustomed to the cold and harsh climate of the Nordics. In addition, he began selling new alternative roots such as the Jerusalem artichoke,

78  The Swedish Potato renova, kohlrabi, parsnip, and celeriac. Einar also diversified his business and started to collaborate with carpenters and blacksmiths delivering tools tailored for potato production. He joined up with his neighbor Jan Svensson, who supplied fertilizer—together they sold a start kit with seed potatoes and fertilizer. Moreover, surprisingly enough after the bumpy start, Jacob Andersson’s youngest daughter Beda had taken the potato to heart and started to experiment with new cooking methods such as grilling, roasting, and frying. She also developed new dishes such as the potato gratin and “Andersson’s temptation”—a special gratin made from potatoes, onions, and sprat (decades later renamed “Jansson’s Temptation” after a Swedish opera singer). She became so successful that she later in life could open a small inn named “The Golden Root” and offered gratins, mashed potatoes, potato wedges, roasted potatoes, potato chips, and potato pancakes, together with different side orders. People soon rushed to her restaurant and spread the word about these new dishes. Beda had five children that all engaged in the restaurant business and eventually they expanded beyond Småland and brought in new potato influences from continental Europe. She lived a prosperous life and could give her father Jacob a good old age.

What Actually Happened (for Those That Are Interested) In the 1770s, a series of bad harvests led to a more nationwide spread of the potato, but it took a while into the 19th century before it was found on most Swedish dining tables (partly also because it turned out that you could produce vodka from it). This coincided with effects of a land reform that were gradually implemented in Sweden, which meant that each farm got larger pieces of arable land instead of small scattered patches (this had already been taken place in many other places in Europe). It was also during this period that the concept of crop rotation was introduced to a larger extent. To switch between different crops year by year gave more nutritious soils, better harvests, and reduced the risk of disease infestation on the crops. New refined potato varieties that were tastier and better adapted to Northern European conditions also made farmers more interested. From now on, the cultivation of potatoes left the garden plots and took over the fields. New food trends come and go, as time goes by. The potato hey-days are over, and this lifesaver no longer has the same crucial role in people’s diet. In the second half of the 20th century, the potato was challenged by, for example, pasta and rice. Today, potatoes are cultivated on merely 1% of arable land in Sweden. About two-thirds of the Swedish commercially grown potatoes are food potatoes, and the rest are so-called factory potatoes used for starch, and industrial potatoes used as raw materials

The Swedish Potato 79 in the food industry for the manufacture of chips, French fries, and powdered mash. Although the potato has lost a little bit of its glory, it is still considered to be an important staple food and has its given place both in history and in global food culture. Now, after this historical odyssey, we will return to the world of digital change, and we will do so in the next chapter by going inside the organization and discuss strategic aspects of such change. We will revisit the potato story in the remaining parts of the book as it snares many underlying key issues of strategizing, leading, and controlling digital change.

Notes 1. There has been, for some time, a discussion and call for a narration approach when it comes to communicating research within several scientific disciplines, such as economics (Klamer et  al., 1988; McCloskey, 1990), organizational theory (Czarniawska, 1998), management (Dumez and Jeunemaitre, 2006), and organizational change (Buchanan and Dawson, 2007). 2. The very same organization that today are responsible for awarding the Nobel Prizes in chemistry and physics, and the Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel 3. In reality, some people grew turn turnips and other ground fruits in the 18thcentury Sweden. However, Andersson was not aware of this type of practice and crop. 4. Back then the potato plant produced more berries than it does today, and these are toxic.

References Alströmer (1777). Potaters plantering, grundad på rön och försök (Stockholm: Svenska vetenskapsakademiens handlingar: 38). Alströmer (1992). Får och potatis: Jonas Alströmers två skrifter från 1727 och 1732 (Veberöd: Blå ankan). Brown (1993). Origin and history of the potato. Proceedings of the symposium past, present and future uses of potatoes, American Journal of Potato Research, 70(5), pp. 363–373. Buchanan  & Dawson (2007). Discourse and audience: Organizational change as multi-story process, Journal of Management Studies, 44(5), pp. 669–686. Czarniawska (1998). A narrative approach to organization studies (Thousand Oaks, CA: Sage). Dumez  & Jeunemaitre (2006). Reviving narratives in economics and management: Towards an integrated perspective of modelling, statistical inference and narratives, European Management Review, 3(1), pp. 32–43. Hawkes & Francisco-Ortega (1993). The early history of the potato in Europe, Euphytica, 70(1), pp. 1–7. Hougas (1956). Foreign potatoes, their introduction and importance, American Journal of Potato Research, 33(6), pp. 190–198. Klamer, Mccloskey  & Solow (1988). The consequences of economic rhetoric (Cambridge: Cambridge University Press).

80  The Swedish Potato Kungliga Tryckeriet (1749). Underrättelse om jord-pärons plantering, nytta och bruk, af kongl. maj:ts och riksens commerce collegio utgifwen och til trycket befordrad år 1749. Cum gratia & privilegio s:æ r:æ maj:tis. Available from: http://weburn.kb.se/eod/6760/NLS14A016760.pdf [Accessed 2020–03–12] (Stockholm: kongl. tryckeriet). McCloskey (1990). If you’re so smart: The narrative of economic expertise (Chicago: University of Chicago Press).

5 Strategic Aspects of Digital Change

Introduction We stated already in the introductory chapter that digitalization is a transformational term that refers to the individual, social, organizational, and societal implications that come out of the diffusion and adoption of new information technology. At the same time, we also noted that the word digitalization is used by both researchers and practitioners to describe a wide range of change challenges—from disruptive transformations of whole industrial sectors to simple launches of apps, web applications, or internal process adjustments—and that most organizations seem to struggle with these challenges. From a managerial perspective, we argued that the overarching digitalization challenge are twofold. There are both external and internal aspects to consider when leading digital change. Considering all these aspects and their underlying connotations, there is a multi-layer mosaic of interconnected internal and external variables to decode, understand, and control to be able to navigate successfully in the emerging new business landscape during the current Cyber-physical wave. A common mistake in such navigation is that leaders tend to slide into a change process without making thorough assessments of what types of change the organization is facing and how such changes can be managed and controlled (Hallencreutz, 2012). Our notion is that it is even more so when it comes to digital change. While writing this book we have noticed that many leaders are fumbling in the dark here. The extra dimension of technology seems to hamper many executives. These days, every organization appears to have an urge to “turn digital”, but when interviewing senior executives about their strategic motives to digitalize, the responses are surprisingly often blurry and inconsistent. Our contention is that this strategic inconsistency turns many digitalization efforts technology centric instead of value and people centric. Questions such as “What type of digital change are we approaching, and what are the consequences for how we communicate, strategize, control and lead the change?” often remains unanswered or partly answered at best.

82  Strategic Aspects of Digital Change As mentioned, the word digitalization is used as a label for almost any change initiative, project or undertaking where computers and information technology to some extent are involved. This is problematic, since the way we talk and communicate influence how we think that eventually influence how we consciously or unconsciously act (Marshak, 2002; Pettigrew et al., 2001). And if many people facing the same change have different views of what type of challenge they are facing, and the consequences that it brings, they will act, move, and drive the change in different directions and end up at different places. Add to this the conundrum that yet after half a century, executives and business managers still have problems speaking the language of the “IT-department” and vice versa. Indeed, different perspectives of change breed different kinds of thinking and acting. For example, in the potato story in the earlier chapter, Andersson misjudged the nature of the change and believed that it only required minor corrections of earlier farming practices. In his mind, he could cultivate, harvest, and make use of the potato much in the same way as he had before—it was just a minor tune-up. The governmental authorities on the other hand understood that this was a major change. Maybe not completely transformational (as it later turned out to be) but radical enough that they decided to spend resources on strategic (oneway) communication. If they instead would have realized that they should have treated people’s feelings, habits, and poor knowledge differently, they might have considered more of a two-way communication strategy, engaged active use of change agents, political influences, and so on. But alas . . . the concept of organizational change was perhaps not top of mind of the nobility in Stockholm at that time. Similarly, it is said the King of Prussia, King Frederick William, used a more radical and forceful change strategy than the Swedes (Hougas, 1956). In the middle of 17th century, he realized that the potato could be a savior when the grain harvest failed, so he declared a royal edict that potato should be cultivated and to “cut the ears and nose” of those farmers who resisted and refused. This strategy was less successful. Nevertheless, about 100  years later, Frederick the Great extended this policy with distributing free seed tubers, information about potato cultivation and storage as well as recipes— a more cunning change strategy with a more prosperous outcome. Einar Carlsson, our innovative herbalist and gardener, did understand that his change was indeed discontinuous and radical in nature and required a completely new behavior. Therefore, he embraced the new and acted as a change agent by trying to change Andersson’s practices of cultivating and harvesting. In the end of the story (i.e., epilogue), he made use of the true potential of the change from a business perspective, since he saw the emergence of new customer needs. This opened further experimentation as well as new business opportunities. For example, Carlsson started to sell Jerusalem artichoke, kohlrabi, parsnip, and celeriac,

Strategic Aspects of Digital Change 83 and he began collaboration with carpenters and blacksmiths to produce tools that was could be used for all these kinds of new innovative crops. The laggard Andersson was a much slower starter (but not a strong late adopter as many in the parish) but finally embraced the new thanks to his ambitious friend Carlsson. Eventually Jacob Andersson and his family also reaped the benefits of the new farming technology. Altogether, these unfolding changes was due to the very same potato. Yet it yielded different actions, decisions, and doings depending on time and circumstances. In this way, different interpretations of individual and organizational change yields different actions and strategies, and if we can make sure to have the same—or at least similar—interpretations, then the change will have a better chance to succeed. Therefore, it is vital for leaders to both have a clear strategic direction and a rich vocabulary of different kinds of organizational change, which enable them to have in-depth discussions about change consequences that altogether feeds into their strategic decisions. A  rich vocabulary and common understanding will in turn influence the congruence and alignment of how change is communicated, controlled, and led across the organization. This seems to be even more crucial when it comes to digital change, since the level of complexity usually is very high. This chapter offers such a vocabulary of digital change and their respective consequences. We start with explaining two different ways to define change in the next two sections. Then we will use these different definitions to construct a model in the form of The Digitalization Map that visualizes four different kinds of change together with rich examples.

Sorting Change by Its Magnitude The first type of categorization is the magnitude of change in relation to the impact on the strategy of the organization and the behavior of its employees. More specifically it is concerned with: to which extent does the change affect core aspects of the organization’s strategy and structure and to what extent does the change translate into behavioral change? One of the most referenced examples of such a classification is Dunphy and Stace (1993; Balogun et al., 2016; Iveroth and Hallencreutz, 2015) who categorized the magnitude of change as follows: •

•

Fine-tuning change refers to refining policies and processes and matching people with strategies and structures and process and is usually performed at the divisional or departmental level. This type of change is mainly incremental, emergent, and realigning, and the impact of the whole organization is small, if any. Incremental adjustments incorporate distinct alterations to processes and strategies. This is change of a greater magnitude but still mainly

84  Strategic Aspects of Digital Change

•

•

incremental and inside the existing framework and way of thinking. It may, however, affect core aspects of operations. Modular transformation is a change with significant magnitude that focuses on parts of the organizations such as several departments and refers to changes that are prompted by a radical shift of one or several divisions. This could be transformational to its nature and outside the existing framework Corporate transformation is about company-wide changes such as radical alterations to strategy, structure, and people. Such a change often also includes significant alterations to core values, value offering, and business model and is therefore disruptive and revolutionary in nature with high magnitude and impact.

Another way of portraying the magnitude of change is to examine the extent to which the change translates into behavioral alterations. For example, change can produce first-order, second-order, or thirdorder change of behavior (Bartunek and Moch, 1987, 1994; Davidson, 2006; Tsoukas and Papoulias, 2005). In first-order, people alter their current schemata and cognitive structures that results in, e.g., new skills and empowered decision making. These kinds of changes rests upon already taken-for-granted assumptions, beliefs, and understanding in the organization as a whole. Current behavior and way of doing things are extended and “bent” (Weick and Quinn, 1999). Second-order change is one step further, as it replaces existing cognitive structures with a new one, such as changing organizational culture. This type of change involves lateral thinking, obstruction of status-quo, and the questioning of, e.g., current assumption, values, routines, and control structures. Second-order change is often (but not always) deliberately triggered and directed by management and current behavior, and the way of doing things is “broken” and replaced with a new behavior. Finally, in third-order change the employees themselves question their own underlying assumptions and behavior, and by doing so they analyze and identify weaknesses of their current schemata and cognitive structures. Leaders often play a teaching role, and stakeholders are often involved in discussing and negotiating different alternatives way of doing things as well as trying to establish a new common meaning and understanding. Here the change is more explorative, since less is known about how to move ahead and how new behavior can solve current problems. Third-order change also distinguishes itself from second-order change by being more triggered by developments in the external institutional environment and business ecology in which the organization is situated (Tsoukas and Papoulias, 2005)—for example, a shift towards a new dominant technology.

Strategic Aspects of Digital Change 85 Combined and simplified, the magnitude of change (connected to both organizational and behavioral change) can be portrayed by two ends of a continuum: (1) change that is done within the existing strategy, structure, and culture, and (2) change that is done outside existing strategy, structure, or culture. We will return to this continuum in a later section, as it will be included in The Digitalization Map, but before we do so we are going to examine how change can be classified according to its tempo.

Sorting Change by Its Tempo Change can also be distinguished by its tempo and how often it occurs. Whether the change is individual, organizational or societal the tempo or rate of change always varies across time. For example, Hayes notes that organizational change and development of industries (2002, p. 3): follows a sigmoidal (s-shaped) curve with a slow beginning (lag phase) associated with experimentation and slow market penetration, a middle period of rapid growth (log phase) as the product gains acceptance and as dominant designs emerge, and finally a tapering off as more advanced or completely different products attract consumers’ attention. Hayes continues to explain that this is followed by another S-curve. Broadly, this follows the same rationale that can be depicted in the S-curves in Figures 2.1 and 2.2 in Chapter 2 about organizational learning and the four different eras. These notions of S-curves show that the rate and tempo of which change occurs varies as there are periods of sudden and dramatic change at the same time as there are periods with slower more step-by-step changes. Earlier research have used different (and often confusing) key terms about this phenomena, such as discontinuous or continuous, bumpy change or smooth change, evolutionary or revolutionary, radical or incremental, episodic or continuous flow, and transformational or transactional (Burke, 2008; By, 2005). There are some variations between them, but generally, the concepts want to convey the same thing: change is either discontinuous in nature by moving ahead through sudden and dramatic moves, or change is continuous in nature driven forward by small steps and adjustments. Discontinuous change often includes dramatic alteration of whole operations, which affects core aspects of the organization’s strategy, structure, and people, and seldom occurs. This type of change is characterized by a “swing” between long periods of stability with almost no greater change that is then dramatically replaced by shorter periods of revolutionary change that abrupt the status-quo (Gersick, 1991; Greenwood and

86  Strategic Aspects of Digital Change Hinings, 1996; Tushman and Romanelli, 1985). Discontinuous change has during the last decades often been triggered by new disruptive and innovative technologies (for instance internet applications, smartphones, printing, payments, streaming services, digital photography, and such), redesign of processes (e.g., Business Process Re-engineering), or profound changes to policies and regulations (e.g., the deregulation of the telecommunications market in the 1980s in parts of Europe). Another example of this are the “overlap” between the S-curves in Chapter two. According to Gersick (1991, p. 15), central to discontinuous change is the notion of “deep structure”: Deep structure is a network of fundamental, interdependent “choices,” of the basic configuration into which a system’s units are organized, and the activities that maintain both this configuration and the system’s resource exchange with the environment. Deep structure in human systems is largely implicit. Examples of deep structures are organizational culture, control systems, and organizational design. Discontinuous change can also be identified in scientific fields that can only be broken through a “paradigmatic shift”, or the discontinuous change that occurs with parenthood, or group development: “Groups do not develop in a linear set of stages, rather, they proceed with not much happening and then recognize (almost suddenly) a need to move forward rapidly in a new way” (Burke, 2008, p. 66). Like this, there are discontinuous changes in many different forms of change. Deep structures create path-dependency and are very resistant to change as they are upheld by feedback-loops and networks of interaction: “it generates a strong inertia, first to prevent the system from generating alternatives outside its own boundaries, then to pull any deviations that do occur back into line” (Gersick, 1991, p. 19). However, most of the time there are equilibrium periods that are composed of very few significant changes, and if changes do occur, they almost never influence the deep structures. Sooner or later (but rarely) there is a “jolt” to the system that results in a revolutionary period when the deep structures are altered. This often happens when there is a significant misalignment between the external environment and the deep structures of a system. Gersick use a sports analogy to explain deep structures and equilibrium periods: the deep structures are composed of the rules of playing soccer, and such rules are rarely changed. Using the same analogy, the equilibrium periods are the soccer game in play that can experience minor changes due to situated activities of players and coaches that together influence the effectiveness of the soccer game. However, such activities usually stay within the rules, standards, and design of the game.

Strategic Aspects of Digital Change 87 Nevertheless, almost all changes are not discontinuous and revolutionary but continuous and evolutionary—according to Burke (2008, p. 65), “No doubt, more than 95 per cent”. This is even more so today compared to earlier, as the current wave of digitalization affords a volatile and ever-changing business landscape and environment. Often, change is not a “big bang” but rather takes the form of many small steps and iterations which together lead to a change of a wider system, and such processes rarely stop. After every incremental step, there are feedback loops to determine if the change step was in the right direction. If not, then attempts will be made to improve the incremental change. Typical examples include Japanese practices such as Kaizen or Kaikaku, continuous improvement, and agile IT development concepts. Theories that are labeled continuous often make the connection between the nature of organizational change and the nature of living systems and biology: firms are like all living organisms that evolve across time in an continuous fashion and with a constant struggle for survival (Morgan, 2006; Van De Ven and Poole, 1995). Orlikowski (1996, p. 66) provides an illustrative description of continuous change: Each variation of a given form is not an abrupt or discrete event, neither is it, by itself, discontinuous. Rather, through a series of ongoing and situated accommodations, adaption, and alterations (that draw on previous variations and mediate future ones), sufficient modifications may be enacted over time that fundamental changes are achieved. There is no deliberate orchestration of change here, no technological inevitability, no dramatic discontinuity, just recurrent and reciprocal variations in practice over time. Each shift in practice creates the conditions for further breakdowns, unanticipated outcomes, and innovations, which in their turn are responded to with more variations. And such variations are ongoing; there is no beginning or end point in this change process. According to Orlikowski, many small modifications and small changes can together produce more fundamental changes. Weick and Quinn (1999) communicate a similar idea. They argue that if continuous changes are performed at different departments that are tightly coupled and interdependent, they can cumulate and evolve into more system-wide and significant changes. However, if there are looser interdependencies and coupling, then the changes will remain in the different departments and becoming isolated “pockets” of innovation without any larger system change. Still, the extent to which continuous change over time can produce revolutionary change is debated: there are those who argue that almost the only way to produce change

88  Strategic Aspects of Digital Change is a “jolt” and a change to the deep structure of an organization (see, e.g.: Burke, 2008, p. 70). Altogether, this whole discussion provides a very dichotomous perspective. Change is either discontinuous or and continuous, nothing in between. However, in real life there are often different degrees of discontinuous and continuous change, and an organization needs both (often at the same time) to move forward. We must also take into consideration that digital change is twofold and can trigger different external and internal change tempos. It can take time for an organization and its people to catch up with technological changes, while customers might embrace the new much faster and apply pressure from the outside. The main challenges for leaders are first to be aware about the varieties of these changes and then get the ability and means to identify different types of change and finally to adjust strategy, leadership, and control accordingly. Or as Pascale and his collogues (2000, p. 38) puts it: “The trick is to clearly identify the nature of the challenge and then use the right tool for the right task”. The Digitalization Map presented in the next section offers a model that can aid in such activities.

The Digitalization Map Taking the two earlier classifications of change (magnitude and tempo) and placing them together, we get a map of different kinds of digital change, see Figure  5.1.1 This map is an extension of our earlier work (Iveroth and Hallencreutz, 2015) as well as others (see, e.g.: Balogun et  al., 2016; Greiner, 1972; Marshak, 2002; Nadler et  al., 1995) and is mainly distinguished by being applied to digital change. The combination of different degrees of magnitude (x-axis) on the one hand, and tempo (y-axis) on the other, gives us four different types of digital change: Digital Adaption, Digital Tuning, Digital Transformation, and Digital Disruption. We will now go through each of the different types, starting with Digital Adaption in the upper left corner. Digital Adaption: “Everyone else is doing it . . .” In this corner of the map, change is mainly discontinuous and often triggered by technological advancements in the surrounding environment. The reason for the change is often a stagnated organization and a gap between the organization and the wider environment and industry that is further developed. These adaptive changes happen less often and are radical, with impact on vital aspects of many organizations, but they are not necessarily challenging core strategies, structures, or processes. Thus, one can say that changes are done mainly within the existing organizational context (or “inside the box”) and are not transformational for the whole organization. A Digital Adaption is usually a response to external

DIGITAL TRANSFORMATION

Magnitude

DIGITAL DISRUPTION

Continuous change through small steps and adjustments

DIGITAL TUNING

Figure 5.1  The Digitalization Map

Within the existing strategy, structure, and culture

DIGITAL ADAPTION

Z

Tempo

Discontinuous change through sudden and dramatic moves

Outside the existing strategy, structure, or culture

Strategic Aspects of Digital Change 89

90  Strategic Aspects of Digital Change (often unforeseen) triggers such as new competition from digital services which lead to reactive adjustments and alignments of products, services, and internal processes. An organization situated in this part of the map is a follower, not a leader, and probably lacks a proactive digitalization strategy. Accordingly, the leadership in this area is often reactive. Change agents will most likely focus on pragmatic change reactions of information from outside of the organization but at the same time argue for preserving things as they are as soon as things have been implemented. “If it isn’t broke, don’t fix it” is a prevailing approach. Many mature organizations of all sorts could be sorted under Digital Adaption. In fact, it is here that you most likely will end up if you lack a deliberate and proactive digitalization strategy. One can even say that this place today is quite crowded since our view is that most organizations lack such a digitalization strategy. And if the outside pressure continues to increase, and management still being unaware, these organizations might well be pushed into more disruptive and unpleasant changes in the rectangle area next door to the right (Digital Disruption) where the intensity of change is much higher and time to act less. Let us illustrate with a concrete example from the public sector: education. The Swedish educational system has for many years struggled with the implementation of interactive digital learning management platforms. The idea has been to enable for stakeholders such as headmasters, teachers, students, and parents to plan, schedule, document, and communicate through one common interface. In 2017, the Swedish government decided on a national digitization strategy for the school system. Thus, a discontinuous external pressure of digital change came from the top. However, the direction from the authorities has not been cogent and consequently the implementation has been scattered and reactive. Some schools have embraced this development wholeheartedly (and should today be found in the Digital Tuning area) while others have lagged and are still struggling with basic functionalities. For many stakeholders this type of change happens occasionally (but not that often), and at the same time it does not completely change their main core activities of teaching but alters, e.g., documentation, student feedback, and communication with parents. As such, this broader change could be placed in the lower middle area of Digital Adaption. We should of course also visit our potato farmers in Småland and apply The Digitalization Map on their ordeals. In doing so, we could argue that Andersson’s neighbors as well as most of the farmers in neighboring villages were late adopters and thus could be placed in the Digital Adaption rectangle area (see epilogue in Chapter 4). These farmers could well have been forerunners like Carlsson but started to pick up on potato production when they suddenly realized that most villages around them were doing so, and in addition they heard that the local blacksmith and

Strategic Aspects of Digital Change 91 carpenter were doing stuff connected to this new crop. For many of these farmers, the change was discontinuous change (e.g., change perceived as something radical, different, and unusual and happened less often), and therefore their late change could be argued for being located in the upper parts of the tempo scale (Y-axis) within the adaption rectangle area. At the same time, since potato cultivation for these famers were very different from the usual way of doing things (but not completely different since so many others were doing it) the change is positioned far to the right within the Digital Adaption rectangle area (X-axis). Digital Tuning: “Let’s continue improving and push it up a notch” Moving from the upper left corner to the lower left corner in The Digitalization Map we enter the rectangle area of Digital Tuning. This type of digital change could be described as a deliberate and proactive approach to digitalization, where change management is executed on a continuous basis through small steps and alterations within the existing framework. The aim here is to strengthen existing practices and services through on-going operational improvements with new technology. Therefore, in many cases (but not all) the outcome of the digital change is an add-on to current value proposition that the organizations already offer and, at least in a short-term perspective, the change often do not challenge competitors’ business models. Changes that can be positioned here are in many cases parts of a deliberate long-term change strategy that has a strong continuous improvement approach to managing operations and business opportunities. Both structure and culture indicate that this type of organization often has a proactive rather than a reactive strategy and approach to change. Here the role of the leader is often to create safe-zones for experimentation and testing things out, and they therefore often exercise a supporting, coaching, and guiding leadership style. Leaders also play a vital part in facilitating teamwork and team learning, and less time is spent (compared to the other types of changes) on arguing and negotiating for change since it, to a large extent, comes natural for many employees. An agile and resilient organization strives to be in this corner, where we find, for instance, the renowned Swedish brand IKEA. This company strives to make the brand more attractive to consumers in the digital era with services and products designed to match the lifestyle and needs of the future consumer. Many of these change initiatives indicate that IKEA is striving to slowly transform into a company at the forefront. Through a continuous Digital Tuning, the IKEA leadership demonstrates an awareness that digitalization is what it takes to remain relevant and competitive in the future (Marr, 2018). By constantly developing, improving, and

92  Strategic Aspects of Digital Change refining, the company can be better adapted to new accelerated expectations. In a press release, Jesper Brodin, CEO of IKEA, explained the company’s new technical investments by: “As urbanization and Digital Transformation continue to challenge retail concepts, we need to develop business faster and in a more flexible way” (Budds, 2017). From a potato perspective, we can argue that Jacob Andersson’s first attempts of potato cultivation in scene one can be labelled as a failed Digital Tuning attempt. This attempt would be positioned in the very bottom left and lower corner (at the end of the both axis) since he (wrongly) argued that growing and cultivating and eating potatoes were pretty much the same as what he would do with wheat and barley. But he was both ignorant and nonchalant and totally underestimated the complexity of the change. Therefore, he failed completely. One can also argue that Einar Carlsson later in the story proactively fine-tuned potato cultivation at large as he developed new seeds, offered alternative ground fruits, developed a kit with seed potatoes and fertilizer, collaborated with the carpenter and blacksmith to produce new tools—this could also be seen as an approach situated in the lower left of the map. Digital Transformation: “Let’s revive and go beyond . . .” In the lower right in the map, we find Digital Transformation. Here the digital change is the outcome of a planned approach and deliberate choices made by management. The intention is often to set out a completely new direction of the organization in order to relocate and revive the competitive advantage. This type of change is transformational in nature because the scope and magnitude lie outside the existing framework. This often includes lateral thinking and approaches that go beyond current schemata of most employees and the current way of doing things. Digital Transformation strives to reposition the organization by changes to its culture, structure, and business processes, as well as to revive and relocate the competitive advantage through on-going alteration to products, services, capabilities, and resources through digitalization. The change is not completely discontinuous because the source of the change (as well its on-going refinement) often comes from earlier innovations, accumulation of knowledge, and exploitation of pre-existing capabilities. In this way, there is no complete break with the past. Compared to tuning and adaption, this change necessitates more of a perceived visionary leader (with a team behind the scenes) that provides a trusting direction for the future. One important activity is to help people to let go of the past, creating time for grieving, and then make them embrace the new. Leaders here are also very active as sense givers and sense makers by having candid conversations with employees as well as senior managers, being ready to redraw some change plans and improvise if needed (Iveroth and Hallencreutz, 2015).

Strategic Aspects of Digital Change 93 Common examples in this part of the map often (but not always) originate from leading tech companies that have their hallmark of developing innovations that transform organizations and industries beyond fine tuning and increase quality and value creation—for example, technology change initiatives coming from Apple, Amazon, IBM, Microsoft (in its hey-days), and Spotify. However, for such companies the change initiative is not completely disruptive and discontinuous as it rests upon a strategic choice, relatively clear plans, and knowledge and capabilities that have been developed for quite some time. At the same time, their innovations and change initiatives often trigger digital changes in other organizations that are disruptive (and is therefore a Digital Disruption). A short example from Chapter 2 can illustrate this. In the end of the DP wave (overlapping with the emergence of the Desktop wave), IBM, Apple, and Microsoft were main actors developing desktop computers. These companies had been thinking, experimenting, and planning the development for years. However, and as we explained, this innovative digital technology triggered disruptive changes in many other organizations that had political consequences and amounted to radical changes to business processes and structure and that threatened whole systems of information infrastructures within and across industries. We can also find actors in the potato story that could be argued having experienced Digital Transformation. These are the characters and actors that were introduced late in the story (see epilogue in earlier chapter): the carpenter, the blacksmith, Jan Svensson, and Andersson’s daughter Beda. Because of the now almost widespread use of the potatoes, the carpenter and blacksmith offered and sold new tools for potato cultivation, Jan Svensson developed tailored fertilizers, and Beda developed new potato dishes as well as her own business. These changes were proactive choices outside their traditional way of working and thinking. And this offered new value propositions and modifications and reviving of their respective “business models”. Potato cultivation opened opportunities to sell new tools, seed potatoes and fertilizers to new customers, as well as for Beda to open her small inn “The Golden Root”. At the same time, the changes as such were not completely discontinuous as they were built on knowledge and resources that was acquired earlier but now modified and extended. For instance, the carpenter still used his skills in carpeting but focusing on new types of tools, and Beda used her old cooking skills but developed new cooking methods as well as recipes and dishes. Digital Disruption: “We are facing a revolution . . .” Finally, in the upper right corner, Digital Disruption is situated. This type of radical and often revolutionary transformational change aims

94  Strategic Aspects of Digital Change to release the organization from its current position and recreate what the company does by fundamental changes to its strategy, structure, and processes. It is a dramatic and often disruptive change affecting the “spinal cord” of the organization—in other words, alterations to the core structures of the organization. A transformation like this is often accelerated by unexpected external developments and requires a high degree of thinking outside the box and bold and decisive leadership. For instance, new dominant technology has influenced many mature industries such as photography, telecom, and media, where the business logic has faced new ways of thinking and new agile contestants have outperformed some of the traditional organizations. Of course, the overlap between the S-curves in Chapter 2 is an example of such events (where technology and change are discontinuous and disruptive). As we also described in the same chapter, during these times of shifts from one dominant technology to another (being most accentuated in the Cyber-physical wave), there are in many cases a myriad of actors in the business ecology, and value propositions are often developed in deep collaborations with these actors. Such activities are also common in change located far up the y-axis in the Digital Transformation rectangle area (at the border to Digital Disruption, as the examples from the potato story in the earlier section demonstrated). Overall, in Digital Disruption, competition is fierce, intensity is higher, and competitive advantage and business models are not modified and revived but totally re-created. Some actors prevail, while others perish depending on their strategic choices. When leading disruptive change, the change pressure and level-ofurgency are extremely high. Therefore, forceful and decisive leadership is often needed as well as intense communication about the “burningplatform”. Leaders in this situation must be bold, holistic, humble, and honest. They should be willing to take risks, trust their gut feeling, and make swift decisions based on incomplete facts. Visionary and transformational leadership from a few key individuals is needed, but at the same time, it is important to have deep discussions and get support from a knowledgeable and experienced guiding team. Our experience tells us that leaders who manage to guide their organizations through disruptive changes are hardheaded to the change objectives but softhearted to the people. A well told case story is when the successful Nordic telecom industry underestimated the brute force of the smartphones. In just a year both Nokia’s and Ericsson’s products were outperformed by new pathbreaking technology. Or rather, the products from the Nordic producers were actually very good, but the customers’ preferences changed much swifter than any forecaster could have expected, which triggered an industry wide change of high intensity and speed. Back in 2007, Nokia’s global dominance of the cell phone market

Strategic Aspects of Digital Change 95 seemed unassailable, but just in a couple of months the market changed. Eventually, the leadership in Nokia and Ericsson awakened, but needed changes came too late and were ineffective partly due to internal cultural resistance. Do we find this kind of disruptive change in the potato story? Here the most obvious example is Jacob Andersson in the later parts of the story. In the beginning, he misjudged the magnitude of the change as well as its tempo—he simply used the wrong strategy in the bottom lower left part of The Digitalization Map. However, as the story unfolded, he began to realize that he and his family were facing a major transformation. He gradually understood that this required very new behaviors and that this was for him something truly radical and discontinuous. He admitted that he had to abandon habits, procedures, and techniques used by his family for generations. Old truths about farming were overthrown. But thanks to support from Carlsson, he triumphed. Not only did the change translate into a completely new way of farming, but it also inspired his daughter Beda to use the potato as a steppingstone to a new career as a chef and restaurant keeper. In this way, Jacob Andersson’s change moved slowly from the bottom lower left corner of Digital Tuning to the upper right corner of Digital Disruption. But not everyone was successful. The farmers in the region who stubbornly clinged on to the old, refused to accept the devilish potato, waited too long, or were simply too slow and eventually perished. They literally did not survive.

Implications and Discussions Overall, and as we noted in the introduction to this chapter, the four types of change displayed in The Digitalization Map offer a way to make sense of the myriad of types of change that exist. Such a classification can be of value because terms like organizational change and digitalization often mean different things to different people. In fact, practitioners and researchers often talk past each other when conversing about digitalization and the consequences that it brings. We have observed that the term digitalization is used to describe both disruptive transformations of whole industrial sectors as well as simple launches of apps, web applications, or internal process adjustments. Since many of us actors in the corporate theatre often suffer from having a limited vocabulary for these different types of changes, we tend to use the same words but ascribe different things, proceeding actions, and consequences to the concepts used. That is where The Digitalization Map can contribute with at least some element of clarity. Misinterpretations translate into different actions and communication and different ways of managing and controlling the change. As a result, and over time, the

96  Strategic Aspects of Digital Change change wander of in different directions and ultimately become less successful. Therefore, the very first thing to do is to answer the core question: Where in The Digitalization Map is our digital change positioned and what are the consequences? Or even simpler, What type of digital change is my organization facing? Different types of digital change yield different kinds of situations that necessitate different approaches of strategizing, leading, and controlling the change. As The Strategic Continuum of Digital Change in Figure 5.2 illustrates (inspired by: Kotter and Schlesinger, 1979; Nadler and Tushman, 1995), digital fine tuning translates into a situation where the digital change: (1) has low intensity, time, and external pressure, (2) has room for errors and corrections, (3) is based upon path-dependent technology development, (4) is rational and a-political to its nature, (5) employees are invited to be involved and empowered, and (6) there is a low resistance to change. On the other end of the continuum, Digital Disruption requires a change strategy geared more towards a situation when there is great urgency, time and external pressure, less room for errors and corrections, pathbreaking technology development, change being emotional and political, having fewer involved and empowered employees, and finally high resistance to change. And in between these two extremes we find Digital Adaption and Digital Transformation. If we accordingly apply Figure 5.1 to Figure 5.2, then the continuum would transform to a “Z” that is flipped 90 degrees to the left—see the flipped “Z” in the middle of Figure 5.1. If we follow this “Z” in the center of the figure then the continuum would start in Digital Tuning, then move to Digital Adaption, moving on to Digital Transformation, and finally the continuum would end in Digital Disruption in the upper right corner. In this manner, different kinds of change require different approaches. This is the starting point for strategic discussions on how to proceed with a digital change and what consequences this breeds for the communication, control, and leadership of the change. To complicate things further, an analysis of the change consequences for the whole organization might result in there being different consequences depending on departments, people’s skills and tasks, and their earlier respective experience with digital technology. Shortly put, for some, the digital change might just be a fine-tuning, while for others the same change can be more disruptive or transformational in nature. In extension, this means that one type of communication, control, and leadership will be needed for a certain part of the organization, and another type of communication, control, and leadership is required for another part of the organization. Yes, this might sound messy, but reality is not linear or sequential but parallel and multi-dimensional.

Low intensity, time, and external pressure Room for errors and corrections Path-dependent technology development Rational and a-political Involved and empowered employees Low resistance to change

Digital Adaption

Figure 5.2  The Strategic Continuum of Digital Change

• • • • • •

Digital Tuning Digital Transformation

• • • • • •

High intensity, time, and external pressure Less room for errors and corrections Path-breaking technology development Emotional and political Less involved and empowered employees High resistance to change

Digital Disruption

Strategic Aspects of Digital Change 97

98  Strategic Aspects of Digital Change When lecturing about this complex reality, we sometimes use the Russian Babushka doll as a metaphor for organizational change. The Babushka is a hollow wooden doll shaped like an old traditional Russian woman (babushka  meaning “grandmother” or “old woman” in Russian). But the doll is in fact a set of wooden dolls of decreasing size placed one inside another. The hollow wooden figures can be separated at the middle (at the waist), to reveal a smaller figure of the same sort inside, which has, in turn, another figure inside of it, and so on. The smallest doll is a metaphor for individual change, the slightly bigger doll is the closest team, yet the bigger dolls symbolize different organizational layers, and the biggest doll covering all the rest represents society as a whole. All the dolls are interconnected but can face different change challenges. To understand the complexity, we must see, understand, and deconstruct the different layers and stakeholders involved (we must open the dolls until we get to the final one). Besides this notion that different types of change breed different kinds of strategies, leadership, and control, there are four other important aspects to note. First, as we have previously advocated, when digitalization is discussed most people are talking about a change that is disruptive in nature, but in reality such change is very rare. The Digitalization Map as such communicates that digitalization efforts are not by default discontinuous, revolutionary, or transformational. It depends. In fact, quite few organizations, business processes, or business models are in a real need for (or running the risk of) disruptive digital change. As Andriole argues (2017, p. 21) most need for digitalization comes from “ ‘conventional’ operational and strategic technology—not from emerging or so-called ‘disruptive’ technology”. In real life, societal digitalization in general is continuous and emergent to its nature and has been so for decades. Not all old truths need to be overthrown. Not everything should be digitalized. In extension, research shows that approximately half of the jobs out there will most likely not be substituted by new digital technology (Stiftelsen för Strategisk Forskning, 2014). AI and robots will most likely not take over the world and kill us all while we sleep. With a broader and historical perspective, industrial revolutions have translated into loss of jobs as well as extinctions of some professions. But at the same time revolutions have created new professions and often higher-skilled work—for example, many farriers lost their jobs when automobiles where introduced, but new jobs of building and selling automobiles were created (Cascio and Montealegre, 2016). But do not forget our potato friends in the 18th century. There are, however, some voices raised that things might be different in the current fourth industrial revolution (Brynjolfsson and McAfee, 2014; Cascio and Montealegre, 2016), but it is far too early to tell. In any case,

Strategic Aspects of Digital Change 99 we concur with McAfee, who in an interview communicated that (Kirkland, 2014): I’ve still never seen a piece of technology that could negotiate effectively. Or motivate and lead a team. Or figure out what’s going on in a rich social situation or what motivates people and how you get them to move in the direction you want. These are human abilities. They’re going to stick around. Digitalization will certainly lead to jobs being replaced by technology and some professions will have less importance. But altogether, the main focus of the discussion should be on the jobs and professions that can be created, or old ones that can be extended and modified due to the interaction between people and digital technology. Indeed, as Lindvall (2017) notes, discussions about digital technology should not solely be about “replacement” but should instead focus on how such technology can reinforce what people see, what they remember, and how they analyze. The trick is to figure out how we can interact with technology in such a way that it improves our business processes and organizations as well as developing new jobs and professions—which is similar to challenges during earlier industrial revolutions, but we have yet to figure this out. Second, modern organizations are complex systems operating in a complex ever-changing environment, where focus and output is determined by the needs and expectations of multiple stakeholders. The organizational life of today is often a combination of slow, robust, and linear events and blurry, rapid, irregular, and emergent events, which often should be led, managed, and controlled at the same time. In practice, this means that management structures should be able to handle both robust and slow-moving industrial systems (sometimes constructed perhaps 50–100  years ago) and simultaneously meet all the new demands, needs, and expectations that digitalization brings to the table. This will challenge old truths about industrial management, product development, project portfolios, funding, control procedures, and traditional quality management. A current example is the European railway sector where the infrastructure is more than 100  years old. In this sector new customer demands and deregulations force the industry to modernize its infrastructure at the same time as developing new digital interfaces, ticket handling, and booking systems to improve customer experience. This means that they should handle different kinds of changes that are situated in different parts of The Digitalization Map at the same time. A common term for practitioners for such an approach is bimodality, or ambidexterity, which is frequently used by researchers (meaning

100  Strategic Aspects of Digital Change the ability to use both hands with equal facility). Both terms refer to a similar point: exploiting current businesses at the same time as the organization explores new areas of tomorrow (Gibson and Birkinshaw, 2004; March, 1991; Raisch and Birkinshaw, 2008). And in today’s volatile business environment, there is an urgent need for both the exploitation of existing organizational capabilities and exploration for new capabilities. In extension, this translates into leading parallel change process with different types of logics. For instance, leaders should, to a greater extent, appreciate and promote different views and potentially contradictory behaviors rather than calling for uniformity. Learning, experimentation, and pilot testing should be encouraged and facilitated but without jeopardizing core aspects of current processes, operations, and businesses. Turning back to the railway sector with a rough example, it might be less wise to use the same change logic and approach for different types of development needs. It is perhaps not recommendable to encourage agile exploration and experimenting with signal systems and train brakes while it can be a useful approach when developing digital booking apps, onboard services, and timetable information systems. Third, The Digitalization Map is composed of two different scales: one magnitude scale and one tempo scale. Therefore, a change can be situated at different position within the four different rectangle areas. This depends on a myriad of factors and is hard (if not impossible) to assess for an outsider. We illustrated some positions in the earlier sections when we connected parts of the potato story to some clear positions in The Digitalization Map. Let’s take another example: IBM. This one originates from Chapter 2, and as you might recall, in 2004, IBM made the choice of a more software and service-oriented strategy and sold its hardware oriented business to Lenovo. This was a strategic and deliberate choice made by management, and the knowledge and capabilities for this new value proposition of service and software had been accumulated for many years. Therefore, the change as such was not a complete “jolt” to the organizational system, and it did not have significant effect on the deep structure of IBM. Accordingly (and given that we are correct as outside observers), this change is positioned far up on the tempo scale (Y-axis) within the Digital Transformation rectangle area (only close to the border to Digital Disruption). Still the magnitude of the change was high for many employees within IBM, since IBM had mainly focused on producing hardware technology for over 100  years—and therefore the change was located to the right on the magnitude scale (X-axis) in Figure 5.1. However, we cannot judge and determine the exact position of the IBM change (or any other general example), as you need to have indepth and inside knowledge of both the change and the organization.

Strategic Aspects of Digital Change 101 Another way to put it, you need to be deeply familiar with every doll (layer) in the Russian Babushka. As readers with a keen eye for details can notice, this example is from 2004, and IBM would most certainly be positioned at other places today. This highlights the fourth and final aspect that we want to draw attention to: The Digitalization Map is historically sensitive, meaning that one type of technological change can in one point in time be situated in one part of the map, while later it might be relocated to another part of the map. The potato production may once again serve as a simple example. In the beginning of the story (and as noted earlier), potato cultivation was for Jacob Andersson merely a fine-tuning exercise that had disastrous consequences. However, later the change was for him truly disruptive. Through the different scenes of the story, the change “travelled” from the bottom lower left corner of Digital Tuning to the upper right corner of Digital Disruption. Another way to illustrate the same point: in the 18th century this was for Jacob Andersson (and for many others) a disruptive change, however today different forms of technology development related to potato cultivation is most certainly a fine-tuning thing. Nota bene, the potato evolution took a century. The global diffusion of smartphones took less than a decade. In this way, a certain technology induced change can across time “travel” through different parts of the map. At the same time, this also highlights the fact that technologies that once enabled significant change rarely become completely obsolete (as potato cultivation), and are in one way or the other often present in our world today. Archibugi (2017, p. 537) illustrates this very well when he writes: The innovations introduced in the first industrial revolution continue to be with us and it is difficult to imagine our life without simple technological artefacts such as the myriad of mechanical devices that came to the fore during the Enlightenment. Of course, several products and services were replaced by alternatives that have become more popular: steam power has been substituted by the combustion engine and the combustion engine will, one hopes, be replaced in due course by solar power. The rate of change has been even faster in communications: pigeon-post has been substituted by telegrams and telegrams by email. There is no implication, of course, that the last method is superior to the previous one and some very progressive societies have occasionally returned to techniques previously considered obsolete. Cities like Amsterdam and Copenhagen, for example, are fighting to bring back bicycles and trams in order to get rid of automobiles. Who knows, soon the potato might be chic again.

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Note 1. The informed and reflective reader with a keen eye for detail might argue that The Digitalization Map (and some of the points made in this chapter) suffer from similar weaknesses as the strategic choice school (see Chapter 2). However, we argue that digital change as well as technology and organizing are complex phenomena that require multiple theoretical lenses and models that aid our understanding (Morgan, 2006). Indeed, such an approach functions like a kaleidoscope that reveals different facets of reality.

References Andriole (2017). Five myths about digital transformation, MIT Sloan Management Review, 58(3; Spring). Available from: http://ilp.mit.edu/media/news_ articles/smr/2017/58317.pdf [Accessed 2020–03–24]. Archibugi (2017). Blade runner economics: Will innovation lead the economic recovery? Research Policy, 46(3), pp. 535–543. Balogun, Hope Hailey  & Gustafsson (2016). Exploring strategic change (Harlow: Pearson). Bartunek & Moch (1987). First-order, second-order, and third-order change and organization development interventions: A  cognitive approach, Journal of Applied Behavioral Science, 23(4), pp. 483–500. Bartunek  & Moch (1994). Third-order organizational change and the Western mystical tradition, Journal of Organizational Change Management, 7(1), pp. 24–41. Brynjolfsson  & Mcafee (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies (New York: WW Norton  & Company). Budds (2017). Why ikea is buying a tech company. Ikea is moving from a youdo-it-all approach to a tech-does-it-all approach, Fast Company, 17–09–29. Available from: www.fastcompany.com/90144872/why-ikea-just-bought-atech-company [Accessed 2020–03–24]. Burke (2008). Organization change: Theory and practice (Thousand Oaks, CA: Sage Publications). By (2005). Organisational change management: A  critical review, Journal of Change Management, 5(4), pp. 369–380. Cascio & Montealegre (2016). How technology is changing work and organizations, Annual Review of Organizational Psychology and Organizational Behavior, 3(March), pp. 349–375. Davidson (2006). A  technological frames perspective on information technology and organizational change, Journal of Applied Behavioral Science, 42(1), pp. 23–39. Dunphy & Stace (1993). The strategic management of corporate change, Human Relations, 46(8), pp. 905–920. Gersick (1991). Revolutionary change theories: A multilevel exploration of the punctuated equilibrium paradigm, Academy of Management Review, 16(1), pp. 10–36. Gibson  & Birkinshaw (2004). The antecedents, consequences, and mediating role of organizational ambidexterity, Academy of Management Journal, 47(2), pp. 209–226.

Strategic Aspects of Digital Change 103 Greenwood  & Hinings (1996). Understanding radical organizational change: Bringing together the old and the new institutionalism, The Academy of Management Review, 21(4), pp. 1022–1054. Greiner (1972). Evolution and revolution as organizations grow, Harvard Business Review, 37(July–August), pp. 37–46. Hallencreutz (2012). Under the skin of change meanings, models and management (Doctoral thesis. Luleå: Luleå University of Technology). Hayes (2002). The theory and practice of change (Basingstoke: Palgrave). Hougas (1956). Foreign potatoes, their introduction and importance, American Journal of Potato Research, 33(6), pp. 190–198. Iveroth & Hallencreutz (2015). Effective organizational change: Leading through sensemaking (London: Routledge). Kirkland (2014). Artificial intelligence meets the C-suite, September 2014. Available from: www.mckinsey.com/business-functions/strategy-and-corporate-finance/ our-insights/artificial-intelligence-meets-the-c-suite [Accessed 2020–03–10]. Kotter & Schlesinger (1979). Choosing strategies for change, Harvard Business Review, 57(2), pp. 106–114. Lindvall (2017). Den fjärde industriella revolutionen: Digitaliseringen skapar helt nya förutsättningar för informationshantering, Organisation & Samhälle, 2017(1), pp. 4–9. March (1991). Exploration and exploitation in organizational learning; Special issue: Organizational learning: Papers in Honor of (and by) James G. March, Organization Science, 2(1), pp. 71–87. Marr (2018). The digital transformation to keep IKEA relevant: Virtual reality, apps and self-driving cars, Forbes, 2018–10–19. Available from: www. forbes.com/sites/bernardmarr/2018/10/19/the-amazing-digital-transforma tion-of-ikea-virtual-reality-apps-self-driving-cars/#1b615ab176be [Accessed 2020–03–24]. Marshak (2002). Changing the language of change: How new contexts and concepts are challenging the ways we think and talk about organizational change, Strategic Change, 11(5), pp. 279–286. Morgan (2006). Images of organization (Thousand Oaks, CA: Sage). Nadler, Shaw & Walton (1995). Discontinuous change: Leading organizational transformation (San Francisco: Jossey-Bass). Nadler  & Tushman (1995). Types of organizational change: From incremental improvement to discontinuous transformation, in: Nadler, Shaw  & Walton (Eds) Discontinuous change: Leading organizational transformation, pp. 15–34 (San Francisco: Jossey-Bass). Orlikowski (1996). Improvising organizational transformation over time: A situated change perspective, Information Systems Research, 7(1), pp. 63–92. Pascale, Millemann & Gioja (2000). Surfing the edge of chaos: The laws of nature and the new laws of business (New York: Three Rivers Press). Pettigrew, Woodman  & Cameron (2001). Studying organizational change and development: Challenges for future research, Academy of Management Journal, 44(4), pp. 697–713. Raisch  & Birkinshaw (2008). Organizational ambidexterity: Antecedents, outcomes, and moderators, Journal of management, 34(3), pp. 375–409. Stiftelsen För Strategisk Forskning (2014). Vartannat jobb automatiseras inom 20 år—utmaningar för Sverige (Stockholm: Stiftelsen för Strategisk Forskning).

104  Strategic Aspects of Digital Change Tsoukas & Papoulias (2005). Managing third-order change: The case of the public power corporation in Greece, Long Range Planning, 38(1), pp. 79–95. Tushman  & Romanelli (1985). Organizational evolution: A  metamorphosis model of convergence and reorientation, Research in Organizational Behavior (7), pp. 171–222. Van De Ven & Poole (1995). Explaining development and change in organizations, Academy of Management Review, 20(3), pp. 510–540. Weick & Quinn (1999). Organizational change and development, Annual Review of Psychology, 50(1), pp. 361–386.

6 The Employee Side of the Digital Change

Introduction In the previous chapter we discussed four different types of digital change and their respective consequences. In this chapter, we deepen this discussion by going further inside the organization and explore what it is that leaders actually do when they lead employees and the whole organization through such digital changes. This will be done by presenting The Commonality Framework for Digital Change that displays the different activities, leadership roles, and resources that are at play during different kinds of change. The main focus is on internal organizational aspects of digitalization, but these aspects are also crucial in dealing with external aspects connected to customer relationships, customer perceptions, and the digitalization paradox. Remember Mauritz and Sanne from the introduction who got their weekly deliveries of groceries via online shopping. Behind that scene of such a smooth online service lies a great number of internal organizational challenges, such as implementation of technology that can enable this service, continuous development and refinement of the technology, new logistics processes and warehouses (that are digitally connected), drivers digitally interacting with internal processes, as well as customer interfaces. And maybe most important of all: making sure that technology is used by employees in the right way, at the right time, and for the right purposes. Making these things work seamlessly is vital since these internal processes and activities provide the very foundation for delivering the value proposition to the customer. On top of this, internal processes and activities should be developed and aligned with the continuous feedback from customers as well as the industry. Leading such digital change is what we will focus on in this chapter. Equally important to remember from earlier parts of the book is that the digital technology will most likely become even more permeated in our organizations and working life in the future. For example, and as we discussed in Chapter 2, as we move further into the Cyber-physical wave our practices will become increasingly more sociomaterial and

106  The Employee Side of the Digital Change technology will become increasingly more ubiquitous—being everywhere. On a more aggregated level more organizations are moving from a “make-and-sell-strategy” to a “sense-and-respond-strategy”. In such a strategy shift, digital technology enables organizations to listen to the customer’s wants and needs, produce the product accordingly, provide it to the customer, and subsequently continue the relationship and communication with the customer. Therefore, being able to lead and manage digital change within the organization—the subject of this chapter—will become even more critical in times to come. This chapter also re-addresses a notion that we touched upon in Chapter 1: managing the soft factors is by far the greatest internal organizational challenge when developing digital technology. Indeed, digitalization, the fourth industrial revolution, and the digitalization paradox breed not only a need for increased social interaction in different ways but also a need to manage and lead such ambiguous processes (Iveroth et al., 2018). The IBM (2008, p.  19) study that we presented in the introduction of the book proclaim that the organizations that are able to do this and be successful in driving digital change treat organizational change as a “core competence at all levels [of the organization] and nurtured as a professional discipline, not an “art”” (there are also more recent research showing on similiar conclusion; see, e.g.: Södergren, 2018). The purpose of this chapter is to uncover and explain some of the strategic, leadership, and control activities connected this “core competence” and “professional discipline”. We will start doing so in the next section by presenting The Commonality Framework for Digital Change and explain its components and overall key aspects. The framework is composed of four different change dimensions that we subsequently will go through and explain the main activities, leadership roles, and resources pertaining to each dimension. After we have gone through the details of the framework we will zoom out and discuss the framework’s overall rationale as well as its contribution to theory and practice. This is then followed by a section that analyzes our potato story (Chapter 4) with the help of the framework. We will once again travel back to the 18th century with the purpose of understanding what social, technical, and structural aspects were at play and that together, and across time, amounted into the outcome of Andersson’s transformational journey. This will enable us to further understand the different aspects and nuances of the framework.

The Commonality Framework for Digital Change In our research, we have studied numerous change efforts triggered by technology in search of an underlying pattern concerning how such initiatives are led and controlled across time, and how people within the organization are engaged and affected. In this work, we have identified a

The Employee Side of the Digital Change 107 stable pattern across several contexts and industries. Namely, that digital change consists of four different levels of change complexity: common ground, common meaning, common interest, and common behavior— displayed in Table  6.1.1 As the table also shows, every dimension has a certain change activity (column two), a specific leadership role (column three), and certain resources (column four) that may be used to gain internal awareness, understanding, and finally activities and behaviors needed. Minor changes triggered by technology that require small or simple alterations to current practices might only require the first dimension of change, common ground. These kind of changes are often insignificant for the organization as a whole—for instance, the implementation of minimal changes to internal administrative routines that do not affect larger aspects—like renaming a digital document. Such changes are often unnoticed by others. However, if the change requires a more radical behavioral change it will most certainly require another change strategy that will include a more intense interplay between all four dimensions of the framework. We can use The Strategic Continuum of Digital Change (Figure  5.2) from the earlier chapter to illustrate this. As we move from the left to the right in the continuum, the interplay between all four dimensions becomes increasingly important. Mastering all four dimensions (often at the same time) is by no means an easy task, but the organizations that across time (and with numerous trial-and-errors) succeed in working actively with all dimensions are the ones that are more successful in coping with the people side of their digital change. We will return to this later in the chapter. In theory, every dimension strives for a higher degree of its respective commonality.2 However, in reality the different commonalities in every dimension can never be fully attained. The rationale of the framework is that an increase of the commonality in every dimension will translate into an increase of probability of a positive outcome and a more seamless transformation. What is also important to understand is that the framework consists of dimensions, and as any dimension—like the three dimensions of space: length, width, and depth—they co-exist. This means, for instance, that several of the dimensions of commonality can be at work at the same time in a specific point in time during a digital change. What is also important to take into consideration when understanding the framework is that when we refer to leaders or change agents we are pinpointing the formal or informal actors that drive the change forward. This could be a middle manager, the CEO, or simply an employee that is acting as a champion and “soul-of-fire” for the change (Stjernberg and Philips, 1993). For example, in the potato story in the earlier chapter, the herbalist and gardener Carlsson was just an ordinary villager that acted as an informal leader driving change forward. Please recall this aspect

108  The Employee Side of the Digital Change Table 6.1  The Commonality Framework for Digital Change Change Dimension

Change Activity

Change agent and leadership role

Examples of resources

Common Ground

Transactional activities such as the transfer of a change message between change agent and change recipient

Messenger

Common Meaning

Translational activities aimed at overcoming interpretive differences between actors through learning, reflection and sensemaking Relational activities, both political and supportive nature; the political activities align interests by negotiations and informal relationships, and the supportive activities manage feelings and emotions, and motivates change recipients. Stabilizing activities— consisting of monitoring, communicating, and intervening actions—which secure long-term and recurrent behavior aligned to the new digital technology

Expert and Translator

Functional digital technology, structure, manuals, vision, plans, goals, common culture, common language Experience-based knowledge, training, interpersonal skills, teaching skills, two-way communication

Common Interest

Common Behavior

Negotiator and Coach

Top management support; Networking, political, negotiating, socializing, coaching, emotional skills

Observer and Intervener

Key-performance indicators; systems for monitoring, rewards and feedback; structures for institutionalizing new behavior.

The Employee Side of the Digital Change 109 when reading about leadership and the role of the change agent in the remaining part of the chapter. Now let us go through the four dimensions of the framework and explain their respective rationale as well as change activity, leadership role, and resources. Dimension One: Common Ground The first dimension of complexity is called common ground, and the purpose here is to raise the shared awareness and understanding for all those that are influenced by the change: a greater common ground equals a smoother change process (but it will get more complicated as we will soon come to). The focus of change activities for leaders are transactional activities, like, for example, a one-way change message sent to the recipients (Armenakis and Harris, 2002; Bies, 2013; Campbell et al., 2015). If the form and message is adequate, if the recipients understand the message, and if the sender is seen as a trusted leader, then the receiver will embrace the need for change and willingly adapt accordingly. However, in a real-life context we must admit that these transmissions seldom are this seamless. More thorough sensemaking processes are often needed to reach intended change objectives. When a leader, acting as a change agent, is actively used in this dimension then the role of the leader is that of a trusted messenger that delivers the change message—for example, a manager that gives a one-way oral PowerPoint presentation to a large group of employees affected by the transformation. Failures in the common ground dimension are often due to an unsuccessful analytical transaction between the change agent and employee (recipient)—roughly put, people do not understand the message of change. If this happens the agent will try to repeat, increase, or modify the message of change (Lindvall, 2018; Shannon and Weaver, 1949). In this way, a common ground is analytically and cognitively oriented since it is dependent on the extent that people can comprehend and understand the message of change and adjacent discussions instrumentally. Therefore, the resources that can reinforce the common ground are resources that enable people to understand each other on the same terms. Such resources are often hard aspects that are structurally oriented such as functional digital technology, language, diagnostic tools, manuals, change plans, change messages, project model, and change goals. Resources of common ground can also be less formal and less explicit, as, for example, different forms of culture, routines, shared schemata, and cognitive structures (Bartunek and Moch, 1994; Davidson, 2006). Altogether, these types of recourses reduce organizational heterogeneity and support a unitary “work-language” and “ways-of-working” among the people of and organization.

110  The Employee Side of the Digital Change Or explained in other words, the resources are syntactically oriented by providing a shared and common “lexicon/syntax” and “work-logic” (Carlile, 2004; Foerderer et al., 2019; Rosenkranz et al., 2014), like people sharing the same jargon, acronyms, and vocabulary. If people share the same or similar “lexicon/syntax” and “work-logic” then transfer of change messages will be become less problematic. On the one hand, if these resources are strong then there is a high likelihood of a common ground and consequently a higher chance of success. Broadly speaking, the resources create a strong common ground that increase the probability that people will “walk in the same direction”. On the other hand, if these resources are fragmented, dispersed, or less consistent, then the digital change will be much more cumbersome, and people will talk, act, and walk in disparate ways. And you will most likely not win over people’s hearts and minds and get the awareness, understanding, and acceptance needed to succeed. In extension, this is also why there can be benefits from starting the digital change within one department, or focusing on one particular practice based culture within the organization (i.e., people that share a similar practice and communicate, analyze, and carry out work similarly, such as finance and accounting employees, doctors, nurses, engineers). That is, starting by initially focusing on one part of the organization where the common ground is already strongly established. Subsequently, when the digital change is firmly established, other parts of the organization can be targeted. When digital changes are instead driven across several departments or across different practice-based cultures at the same time—that has less of a common ground among them—there is an increase in complexity and a decrease of the likelihood of a smooth transformation process. One of our earlier research project, concerning a case study of a global organization within the telecom industry, illustrates the importance of common ground and stable lexicon/syntax and work-logic (Iveroth, 2012; Lindvall and Iveroth, 2011). This organization embarked on a digital change of the entire global organization. When they did so they had a considerable advantage when the employees used the same project approach and working model. When employees where spread across the globe and used the same practices and tools it facilitated the synchronization and coordination of strategic activities, events, and decisions across time and space. For example, their project model supported and strengthened people’s common ground and understanding of what phases different sub-projects of the change were in, actions being taken, and what kind of trials that lied ahead. One employee on one side of the globe could understand what was being done on another side of the globe. Similarly, strong and shared culture, vision, plans, and goals created a common ground by clarifying how, where, and why they were going in

The Employee Side of the Digital Change 111 a certain direction. Indeed, such structural tools and resources facilitated the management control and the ability to walk in the same path towards a common goal. Central to change of a common ground is that it anchors the more complicated changes that follow (i.e., common meaning, interest, and behavior) as it provides the necessary condition of a common ground among people. This is because when employees work with different things, use different language for their practice, and have different work logics, then changing the way they work becomes difficult. Digital changes that often fail do so because managers overemphasize the importance of this dimension. Or, rather, believe that a common ground is good enough to succeed. From an internal stakeholder perspective, there is often a strong belief that if the digital technology functions properly, and if the change is communicated (one-way), then alterations to the organization and the way employees work will automatically come about. Alternatively, an example from an external stakeholder perspective: a manager explaining an upcoming digital change to key customers and key suppliers through an email or postal letter (and not realizing the long-term consequences for, e.g., brand image and perceived closeness). And in doing so, underestimating the importance of the relation to the customer and the activities that goes into trying to handle the digitalization paradox. Such approaches are often less successful if the change is complicated, and it is well known (but easily forgotten) that many change initiatives fail because of the underestimation of the people side of change. Another way to explain this is that an over belief of common ground change often translates into technological rationality and a view of digital technology as a material thing that is monolithic, stable, and robust over time and space, and that can transform the organization like a “silver-bullet” (Agarwal and Lucas Jr, 2005; Avgerou and McGrath, 2007; Markus, 2004b; Markus and Benjamin, 1997). If you recall Chapter 2, we did not only discuss this concept of technological rationality but also the Technological imperative stream that has its prime focus on this dimension of digital change. To solely use Common ground as a strategy is not a viable approach to complex digital change. It may, however, be enough to enable minor Digital tuning and change projects that are situated close to the lower left corner of The Digitalization Map (Figure 5.1), such as alteration of certain internal work procedures that creates less change resistance. Or sometimes even minimal Digital Adaption changes situated in the lower left corner within the Digital Adaption rectangle area. If, however, the digital change is placed more the right of The Strategic Continuum of Digital Change (Figure  5.1), then too much focus on common ground will ultimately fail. In these situations, creating a

112  The Employee Side of the Digital Change common meaning is increasingly important, which is the subject of the next section. In summary, the common ground dimension is about trying to create a strong-shared understanding among the internal stakeholders. It is performed by means of different forms of transactional activities between management and employees, such as communicating a change message and a vision of a desired outcome. A change agent that has the role of being a messenger usually performs this activity. And the whole dimension is facilitated by structural resources that, to some extent, make people across the whole organization understand each other on the same terms. Dimension Two: Common Meaning When the complexity of the change increases—moving from the left side to the right side of the Strategic Continuum of Digital Change and change becomes more intense, emotional, political, and technology being pathbreaking—the change recipients will begin to interpret the change differently. Divergent sensemaking of the new technology throughout the organization will begin to arise. This is problematic since incompatible meaning structures mean that people will interpret and communicate differently about the purpose and value of new technology, and this in turn translates into different ways of acting and using new applications— which results in a change that wanders off in a wide variety of directions and ultimately fails. Organizations can try to evade these problems by translational activities that produce learning and reflection among people in order to overcome interpretive differences. Such activities are focused on social interactions that contextualize the technology and (hopefully) create knowledge out of information (see Chapter  2; Brown and Duguid, 2001; Kallinikos, 2001). In this way, this dimension and its activities and resources are semantically oriented since they involve an interpretive approach that aims to minimize misunderstandings and different assumptions (Carlile, 2004; Foerderer et al., 2019; Rosenkranz et al., 2014). In practice, this entails explaining and translating the change in such a way that stakeholders get a clear picture of what the translation means for them on a day-to-day basis. This is often done through formal activities such as workshops, seminars, conferences, teaching and learning activities, seminars, Q&A sessions, or through more informal and daily activities such as conversations in the corridors and at the coffee machines. Such activities are really, from a scientific point of view, different sensemaking activities (Weick, 1995) that aims to create some sort of order in the flow of experienced events with the purpose of making the world more structured, meaningful, and above all workable. The translating

The Employee Side of the Digital Change 113 activities, being formal or informal, aim to create this kind of sensemaking among employees. As such, sensemaking activities are at the very heart of common meaning, and if such undertakings are managed, led, combined, and aligned, then this can increase the common meaning. A manager and leader has the possibility to some extent use sensemaking (and sensegiving) activities to their advantage during a digital change, and our earlier work presented some ideas on how this can be accomplished (Iveroth and Hallencreutz, 2015). As the concept of sensemaking implies, an important aspect of activities in common meaning is the component of interactivity and dialogue. For example, as one change agent that we interviewed expressed: “It’s no use going to the local organization like ‘men in black’ from Stockholm [i.e., headquarters] with an adamant and hard attitude. We just don’t kick in the door and say, ‘let’s do this’ ”. Another agent that we interviewed told us similarly: That is one thing that is very important when you go out [to a local company]: that you listen to people. Because if you don’t allow them to talk and air their frustration, then it will just build up. So you need to listen, then you can understand them, then you can make things happen.3 In this level of change complexity, the role of the leader has the dual role of being a translator (Nonaka and Takeuchi, 1995; Polanyi, 1958; Røvik, 2016; Whittle et al., 2010) and an expert (Goodall and Pogrebna, 2015) of local and global practices connected to the new digital technology. The leader should not only understand the complexity of the digital change but should also be able to decode it in such a way that people can comprehend the direct consequences for their daily work—being able to address, for instance, questions like: “what are the local implications and consequences of this digital change?”, “What does this new digital technology, and the change that it brings, mean to me, my daily practice and my local organization?” and “How will I perform my work in the future?”. One change manager that we interviewed in one of our research projects summarized this role when saying: One of the most important things is that you can really translate the change message to all the different stakeholders of the change—all the way from the top of the organization to the lowest level. For every stakeholder the message of change is different. You should not have a message that says that now we want to cut costs, improve figures, making things more effective and so forth. The person way out in the organization do not want to hear that. He is more interested in

114  The Employee Side of the Digital Change hearing that it gives him the opportunity to move on, develop and work on tasks that are more skilled and rewarding. He wants to hear what this all means for his daily work. It is all about trying to translate the message so buy-in is creates. So being able to translate the message of change is really central and important in what I do all the time. As this quote demonstrates, one of the key aspects of establishing a common meaning is social activities and translation performed by certain individuals and targeted to different types of stakeholders. Therefore, the resources that are of prime concern in this dimension are soft resources and often connected to the individual. They include things like experiencebased knowledge, training, inter-personal skills, teaching skills, and two-way communication. This can be compared to the resources of common ground that are more tangible and oriented towards structure and hard resources. For instance, a respondent that we interviewed that was responsible for a group change agents explained the importance of this softer side of the resources of digital change to us: It’s about the people, it’s not about turning a parameter in a system. This is what I search for when I look for new members to join my group. It is of no interest to me if you have managed a multi-million [dollar] project or if you have developed a new technical solution. I am interested in your capacity to manage and influence people. In summary, the common meaning dimension refers to the meaning that people connect with the new internal and external demands, needs, and expectations that will come with the digital change. When complex change is executed people will most likely understand and embrace it in different ways. Their interpretations of what the change truly means for their daily practice begins to diverge. In turn, people begin to make sense, act, and go about their daily practices in different ways, which ultimately leads to a change initiative not reaching intended objectives. An organization can try to reduce this risk of different interpretations and meanings by allocating more resources towards translational activities such as candid conversations and structured dialogue in different fora. By doing so, the difference in meaning can be reduced. An organization should therefore invest time in education, training, and workshops but also by making sure that the change agents that work out in the field are experts on the new digital technology and have the skills to translate it in such a way that people can understand it. Dimension Three: Common Interest A strong common ground creates a situation where people share the same “language” and work logic so that it increases the possibility

The Employee Side of the Digital Change 115 that they will take action in the same direction. And a strong common meaning enables people to have a similar interpretation of the new technology that enables them to actually use the technology in a similar manner. Both these commonalities are important. However, they do not automatically translate into motivation and stimulus for actually changing their behavior needed to unleash the full effect of the new technology. Therefore, leaders should also establish a common interest in the change—and this is especially important when the digital technology means changing deeply ingrained local practices. Leaders can do so by engaging in relational activities that are of two types: political and supportive. These are called relational because the heart of the activities in this dimension lies in the connection between the people that are affected by the change. This dimension is also the most complicated to manage and control, and failure to win the hearts and minds of the employees is a common reason for why many change initiatives go wrong, and this is also why we spend more time here than in the other dimensions. This dimension as well as common meaning are geared towards the soft-factors of change, and this is where the studies pertained to the Organizational imperative (if you remember this concept from Chapter 2) have been mostly concerned (and in doing so, neglecting the other dimensions). The Political Type of Relational Activities The political type of relational activities signifies that the leader that functions as a change agent works as a negotiator (Johnson and Cooper, 2009; Watson and Hoffman, 1996). In this role, the agent aims to gain influence and power by building formal or informal relationships in order to create change legitimacy and create a buy-in for the change—helping the digital change happen. By getting people gradually “on board” that are well respected and that have formal or informal authority it will be easier to get change acceptance from other employees. This political element is an important part of a digitalization initiative because when a new technology is implemented it will influence stakeholders in different ways (Constantinides and Barrett, 2006; Jasperson et  al., 2002; Pfeffer, 1981). Employees might lose their jobs, roles, or prestige, and they will therefore resist change. Others will gain something from the change and thus embrace the new. Some individuals are early adopters, others are laggards. Moreover, external stakeholders can also be affected in different ways. In other words, there is always something “at stake” for stakeholders. Therefore, there is always, openly or behind closed doors, political activities that the change agent needs to address and partake in. To do otherwise will most certainly create change resistance that ultimately leads to failure. And this is also why it can be very beneficial to make different forms of stakeholder analysis in order to

116  The Employee Side of the Digital Change understand the power and interest of the different people affected by the change and what to do about it. What is important to note is that the change agent’s power to exercise political activities is not given from the start and must be earned through hard and continuous work. You will not have real power and change legitimacy just because you are from the headquarters or because you have a fancy title. Instead, political skills are often accumulated through all the small and informal things you do, like having a cup of coffee, small-talking, and listening with both heart and mind. In this way, the power of your political skills is not something you have from the start. Instead, it is something you always have to acquire. Here is an illustrative example of such political skills coming from a change agent working on a global digitalization project. When he arrived at one of the local organizations he soon discovered—through his networking and social skills—that the individual employee with the most informal influence on people was actually the secretary. This person was a well-known and respected employee, had numerous contacts at all levels of the organization, and was highly familiar with local and informal procedures. In short, she had the real power to change people’s minds and make things happen. By getting the secretary “on board” the change agent managed to convince the other employees at the site that they had indeed a common interest in the upcoming change. Because of the secretary’s informal influence, she was able to create a legitimacy for the new technology that ultimately boosted the buy-in of the whole change process. By doing so, he had created a local change agent, or soul-of-fire, striving for the same cause as he did. Therefore, the ability to decode local social systems and win over both formal and informal leaders is crucial. Besides locating and creating souls-of-fire (that are change agents in themselves), you need to identify the people that are less enthusiastic about the change and try to convince them that it is in their (and the local organization’s) best interest to buy in to the digital change. In doing so, the agent has to struggle with responding to questions like “Why should we adjust the way we work and our practices so that it supports this new digital change?”, “How does our local organization fit into the big picture?”, and “Why should we adjust the way we work and our practices so that it supports this digital change?” and ”Why should we bother?”. The Supportive Type of Relational Activities However, just dealing with rational persuasion through political activities for creating a common interest is often not enough. What is missing is the supportive part of relational activities executed by the change agent that has the role of being a coach (Athanasopoulou and Dopson, 2018;

The Employee Side of the Digital Change 117 Stein et al., 2015; Taylor et al., 2019). A clear example of this is a change agent that shows management support, visual leadership (i.e., being there), one-on-one communication, and by trying to manage recipients’ feelings, emotions, and motivation. Such activities of the heart (rather than the mind) are crucial because when an organization becomes digitalized it fundamentally questions “the way we have always done things around here”. The supportive type of relational activities is often a neglected area in the literature and theories about technological change and digitalization (Avgerou and McGrath, 2005, 2007; Ciborra, 2006; McGrath, 2006). For example, if you pick up almost any book within this subject you will most likely find few, if any, chapters or sections devoted to emotional and relational aspects. The same goes for most lectures and speeches on the same topic. If you instead look at what people actually are doing and what they are experiencing during digitalization projects (and not the rational and often abstract theories connected to the subject) a different picture quickly emerges. For example, if you talk to an honest change agent about their main issues the agent will probably tell you that one aspect of their job is to manage employees that are crying and are angry because they are re-assigned or will lose their role or job. The agent will most likely also tell you that in such a stressed environment the agent needs to motivate people and get them to accept the change, especially the employees working in the front end that most likely also will meet new customer demands, needs, and behaviors. One change agent and an interviewee in one of our research projects, for example, explained to us one of his most important principles in his line of work: Personally I think that emotions are important. This is my message here: we are working with people and never, ever forget that. Try to understand the situation they are in, if you do that, then it is a little bit easier to help them. This message was even reflected in the operational guidelines for change agents of his organization: “Increasing willingness to change by moving away from analysis, towards feelings!”. We then asked the follow-up question to the agent of why he and his organization were focusing on emotions and feelings in their work. He then explained to us that in the very beginning his organization had spent most of their time trying to create buy-in by oral presentation with PowerPoints, calculations, and complex Excel spreadsheets. He then told us that this, in most cases, did not create enough change legitimacy and buy-in, and therefore their change projects often failed. At best the employees affected by the change nodded their heads and said, “yes, yes, we will do this”, but afterwards

118  The Employee Side of the Digital Change they fell back into old behaviors. He summarized by saying that they had learned the hard way that change includes both analytical/cognitive and emotional elements and should be managed accordingly. Another aspect of the supportive type of relational activities that is a common theme in change is the importance of top management support, and we endorse this. During times of uncertainty, the change agents need to feel that they are not standing alone. They need to be assured that management are determined to see this through and are willing to spend considerable time, energy, and resources for the project to succeed. One change agent explained this to us in a very concise way: The most important thing is top management support. I  have that with me. I am the one facing the employees and as long as I believe, and trust, and have the support of management behind me, then I can stand and look people in the eye, and say this is what I want to do, I believe it, this is important, and defend the strategy. So you just have to have that foundation otherwise everything will fall apart. Common interest change is the most complicated to manage and control out of the four different dimensions, and this is because this dimension aims partly to change people’s mindset (Davidson, 2006; Gal and Berente, 2008; Gardner, 2006). In many ways, common interest is about not only making people change their opinion but also changing their ingrained behaviors. This is increasingly so if the change is situated to the right in the Strategic Continuum of Digital Change, since in that position technology has the potential to alter the very things we do in an organization, the practice of everyday work. However, the introduction of new technology will not be transformational or disruptive if the people within the organization are not ready to actually change their way of doing things. In other words, digital technologies are only disruptive and transformational to the extent that we as change leaders allow them to be so. Another way to express this is: technological change evolves revolutionarily through sudden and dramatic moves, but organizational change evolves evolutionarily through small steps. The challenge for leaders is to try to make people keep up with the technological change. Such a paramount challenge is at the very core of digital change and was summarized by one of our respondents from one of our research project in the following manner: When I had to tell my parents what I was doing it was a little bit difficult. . . . I tried to explain by saying: ‘Imagine that people have been eating with a spoon in their right hand their whole life. Suddenly you come and tell them that they have to change, that “now you have to use your left [hand]”. That is not easy.

The Employee Side of the Digital Change 119 In summary, the dimension of common interest is about trying to align the different interests that exist among the different stakeholders of the digital change. This is done through two types of relational activities: political and supportive. The political type means that the change agent works as a negotiator and tries to gain influence and power by building informal relationships in order to create change legitimacy and generate buy in. The supportive part of relational activities involves the change agent working as a coach, demonstrating management support, and trying to manage recipients’ feelings, emotions, and motivation. Dimension Four: Common Behaviour The purpose of the fourth dimension is to make sure that people are using the new technology as intended and that new behavior and routines are firmly established. This is important because in many cases employees fall back into old routines and procedures, which can lead to redundant or overlapping systems, processes, and behaviors. For instance, you may use the new CRM system, but you also keep your old Excel solution to be on the safe side. Or you neglect the new interactive web page with a chat function and stick to sending emails instead. Common behavior is present during the whole change (often more informal in the early phases) but more dominant in later parts of the process and hopefully present after the change is formally finished (as changing behavior takes time). Here the leader performs stabilizing activities that aim to make sure that people do indeed change their behaviors and that new routines are aligned with the intended functionality and outcome of the new digital technology. The role of the change agent in this dimension is to be an observer that monitors the recipients’ behavior across time and makes sure that the change “stick”. In practice, stabilizing activities consists of remote or direct monitoring and measurements of different types of financial and non-financial Key Performance Indicators (KPI). But it can also be more simple and straight forward things such as just calling up people to see how things are going or visiting the local office and chatting with people to see how they are assimilating and getting along with the new digital processes. Whether being formal or informal the stabilizing activities aim to keep up the momentum and make the digital change stick in such a way that it becomes part of the culture and “the way we do things around here”. What is crucial to this dimension is that stabilizing activities are done across time, such as monitoring, measuring, and talking to recipients every month or for a longer period after the transformation process has ended (Kunisch et al., 2017). However, a common mistake is to neglect this time dimension. Ultimately, the digital change is successful when long-term and iterative behaviors of employees are ascertained. The transformation can also be incomplete, and management realizes through the

120  The Employee Side of the Digital Change stabilizing activities that the employees have retreated to the old way of doing things. On such occasions, the change agents need to start playing the role of an intervener. As the word implies, the agent will have to get involved again. Perhaps the recipients did not after all really get a common meaning or perhaps did not get a common interest of the change. Perhaps the sensemaking processes backfired. What is important here (and what many eager project managers forget) is to include the intervening role in the strategy of the digital change from an early stage. For example, the activities connected to the role of being an intervener should be included in the role description of change agents, making it a natural part of the job as well as creating a legitimacy for such activities. And time and resources should be allocated to this in the plan and budget. This is even more crucial in organizations populated by engineers and technicians or if the change initiatives are driven from a classical “IT department”. As noted earlier, one common way of performing stabilizing activities is by using KPIs. But in many cases the measuring of KPIs is not done across time and often they do not really measure change of behavior. A clarifying example of this comes from a manager and an interviewee working with the implementation of a digital bank transaction system connected to a research project: the goal [of the KPI of the implemented bank transaction system] is not to have the company sign off that it has participated in the new technological solution and that they use it. The goal is instead that we see X percentage of the bank transaction through the new bank. There is a big difference between implementing a solution and getting the people to change their behavior so that they start using the new solution. This is really important because behavioral change takes time. There are also more creative ways to perform stabilizing activities. For example, one change agent that we talked to explained that his best “personal KPI” was how many times he got an invitation to private social celebrations and activities and by people that lost something out of the change. If he was not invited to any such occasions, he considered this an early warning signal that the change might fail because he had not created enough common meaning and interest. Indeed, there are many ways in which organization, or an individual for that matter, can work with stabilizing activities. Some less formal than others. In any case, they need to be structured, systematic, and included as a central part of the digital change strategy. In summary, the aim of common behavior dimension is to make sure that the change recipients have established a habitual new behavior

The Employee Side of the Digital Change 121 aligned with the objectives of the digital change. In other words, the dimensions aim to make sure that people have actually changed their behaviors in a way that strengthens the digitalization and that they are actually doing so routinely and across time. This can be secured with different forms of stabilizing activities such as observations, monitoring, and the use of KPIs coupled with one-way and two-way communication skills (depending on the situation). The role of the agent is to be an observer, and occasionally an intervener if things go wrong. Change is successful when long-term and iterative behaviors of employees can be ascertained. We finish this chapter with a warning: mastering all four dimensions in The Commonality Framework for Digital Change is less likely to come about overnight, and it includes many trials and errors across time (Iveroth and Hallencreutz, 2015; Lindvall and Iveroth, 2011). An illustrative example of this comes from a corporate manager that had been engaged in one of the most successful transformations that we have studied. We asked him what the secret to success was and he gave this answer: When you recognize that you are sitting on a dead horse you better step off immediately. When you discover that the things you are doing is in a deadlock—when you are in a blind alley—then don’t be afraid to step off and change direction. . . . We have turned many times and still do this when we discover that maybe a certain idea was not good—then we try something else—you should not be afraid of this.

So What? In Chapter  2, we showed how digitalization has evolved as different S-curves with a high amount of technological discontinuity in the overlaps between the curves. One of the conclusions was that the ones that manage to adopt the new technology were often the ones that made the necessary organizational changes. One question that arises from such a claim is what leaders, employees, and other stakeholders actually do in practice to achieve these organizational changes. The Commonality Framework for Digital Change is one way to explain how to go about doing so. More specifically, the framework explains that organizational changes triggered by digitalization is an interplay between hard (structure) and soft factors (actors) across time. When people generally talk about the hard factors of change they often mean technological, economical, and structural factors and issues. In practice, these are things like functional digital technology, structures, change plan, change messages, vision, change goals, one-way communication, common language, common culture, KPIs, milestones, systems

122  The Employee Side of the Digital Change for monitoring, rewards and feedback, and structures for institutionalizing new behavior. These hard factors are also the issues that dominate common ground and common behavior, shown in Table 6.2. On the other side of the coin, we have the soft factors, and these are generally things like people, social, and organizational issues. In reality, these are often resources such as experience-based knowledge, interpersonal skills, HR, education, teaching skills, learning, two-way communication, sensemaking, sensegiving, emotional intelligence (EQ​ ), coaching, dialogue, networking, mediation, and conflict resolution. And these are what dominate the dimensions of common meaning and common interest (see Table 6.2). The main point is that both the hard and the soft factors are combined during the process of digital change (as in most organizational changes). The hard factors such as functional digital technology and formal and informal structure are only the enablers—being the foundation—and they represent only one-half of the digital change. However, since digital change is also a human activity, the soft factors represent the other half and are the elements that ultimately make the change successful. Overall, the most common reason for failure is a pre-occupation with the hard factors of change in common ground and common behavior. In these situations, managers treat technology as an isolated and mechanical tool that is and should be set aside and managed by the engineers or the “geeky IT nerds”. The underlying principle in this is that once these people unleash the new technology, change spreads throughout the organization, and employees simply and automatically adapt to the new Table 6.2  Hard and Soft Factors of Digital Change Change Dimension

Focus

Common Ground

Hard factors: e.g., functional IT and technology, structures, change plan, change messages, vision, change goals, one-way communication, common language, common culture Soft factors: e.g., education, experience-based knowledge, interpersonal skills, HR, teaching skills, learning, two-way communication Soft factors: e.g., emotional intelligence (EQ), coaching, dialogues, networking, mediation, conflict resolution Hard factors: KPIs; milestones; systems for monitoring, rewards, and feedback; structures for institutionalizing new behavior

Common Meaning

Common Interest Common Behavior

The Employee Side of the Digital Change 123 circumstances. In short, you have a strong technology rationality mindset where managers often think that digital technology will take care of itself once it is implemented. What they tend to forget, however, is that digital technology is intimately interlinked with the organization and the way people go about their daily work. As a result, successful digital changes imply managing both the technology itself and its social and organizational implications as discussed in many places in this book. In short, they have mastered the hard factors of change but in the process of doing so they neglect the soft factors of change, often amounting to failure. Such organizations have a blind faith towards technology and strongly believe that digital changes can be accomplished only by working with the activities of common ground and common behavior. For example, they might have misjudged the magnitude of the change, believing that it is a minor digital tuning or adaption change when it is more likely to be outside the existing strategy, structure, and culture and thus transformational and disruptive to its nature. Tech driven leaders spend considerable amount of resources developing the technology, then they focus on structural issues such as developing processes, vision, goals, and a project plan, and then they simply communicated using one-way communication. Often these leaders just presume that things will work out because things are explained in detail in the transaction of the change message (i.e., common ground). Afterwards they perform stabilizing activities by checking out if things have worked, at best (i.e., common behavior). In other words, such change initiatives fail because people overemphasize the hard factors of change, and this is aligned with the Technology imperative that we talked about in Chapter 2. Of course, it can also be the other way around—projects and organizations that tend to focus too much on the soft factors of change and allocate fewer resources to the hard factors of change. Here there is too much talk and endless discussion, diplomacy, and patchy and ad-hoc activities, and too little structure, concrete plans, control and coordination, or even fully functional technology. This is aligned with the Organizational imperative from Chapter 2. A more theoretical way of explaining the rationale of the framework, and to revisit the last part of Chapter 2, is that it underlines the digital change (as most changes) which requires an interplay between actor (i.e., soft factors) and structure (i.e., hard factors) during on-going practice. The dimensions of common ground and common behavior are dominated by materiality and structure (Technological imperative), and in the dimensions of common meaning and common interest the actors and their social activities have primacy over structure and materiality (Organizational imperative). A too strong dominance for the former or the latter will ultimately fail (for both practitioners and researchers). This is so because interplay between actors and structures are paramount for

124  The Employee Side of the Digital Change driving change forward: on the one hand, an actor with agency but without structure amounts to no more than a sightless journey, whereas on the other hand, structure without the actor is little more than an abandoned ship drifting on its own accord. The point is that the framework shows the entanglement of both structural-material and actor-social properties that together only come into being during the practice of on-going change. In this way, the framework theoretically contributes (Cecez-Kecmanovic et al., 2014) both with a method and a lower-level theory that can work as a sensitizing device (Klein and Myers, 1999) and help us understand digital change where technology is seen in its context, and where both technology and people are brought forth to center stage (see, e.g.: Iveroth, 2011, 2012; Iveroth and Bengtsson, 2014). So, and in summary, the framework argues that digital change comes about as an interplay between the four dimensions that leaders have to try to manage and control. This interplay becomes more intense and important the more we move to the right in the Strategic Continuum of Digital Change—or as we move through the “Z” in the middle of Figure 5.1. Digital fine tuning might not need to use all four dimensions to their full force, while Digital disruption will require full attention to the activities, roles, and resources pertaining to all dimensions. The importance of both hard and soft factors of change is by no means new (see, e.g.: Balogun, 2006; Beer, 2008; Jørgensen et al., 2009; Leppitt, 2006; Markus, 2004a), but when earlier research has had a similar rationale they have to a large extent left out a practice perspective (Burgelman et al., 2018; Jarzabkowski et al., 2019). In other words, what is it that people actually do when they lead digital change projects? This is one of the contributions of the framework. The commonality framework uncovers the roles and day-to-day activities that together can create a balance between the soft and hard factors when leading the employee side of digital change. Now, an obvious follow-up question would be: what is the most appropriate interplay and balance between hard and soft factors in order to increase the odds of a successful digital change? The answer is that it often depends on the resources connected to the digital change and the organization in which it is implemented. On the one hand, older and bureaucratic organizations with low market pressure often tend to have a strong focus on hard factors pertained to common ground and common behavior. For example, public authorities, municipalities, old universities, or military organizations are often organized as vertical silos with little communication across departments, and they are highly regulated, structured, and bureaucratic. They usually have policies, procedures, KPIs, and in-grained processes, and routines for almost anything. This is of course natural in the evolution of organizations since such hard factors are developed over time and have after a while become part of

The Employee Side of the Digital Change 125 the taken-for-granted assumptions (Burns and Scapens, 2000; Scapens, 2006). These organizations have a weakness when it comes to the soft factors connected to common meaning and common interest. On the other hand, new, smaller, and agile entrepreneurial organizations are often strong in the soft aspects connected to common meaning and common interest. For example, they have a strong feeling of togetherness, share a common view of things, and lots of social interactions between most people of the organization. Together and with a strong community, they often feel that their organization can make a big difference. However, they often lack hard factors such as clear written policies, KPIs, process, and organizational structures that facilitate work. When these type of organizations start to grow (going from being a small organization to a larger organization), they often fall apart because they lack structural aspects that are crucial for a large organization to function properly. These examples of old and bureaucratic organizations versus new and entrepreneurial organizations are very rough examples (and might not fit all organizations). Nevertheless, they illustrate the key point that the question of balance between the hard and soft factors of change is always connected to the unique circumstances of every organization. By using The Digitalization Map, The Strategic Continuum for Digital Change, and The Commonality Framework as starting points, these organizations can identify and discuss their respective strengths and weaknesses before they embark on their digital change journey.

The Framework and Potatoes Now that we have presented The Commonality Framework for Digital Change conceptually and explained the overall rationale, we will revisit our friends Carlsson and Andersson from Chapter 4. Viewing their potato ordeal through the lens of the framework can visualize the key points for how to lead and control digital change in a simplified and playful way. Overall, every dimension of the framework has their respective change activity, role, and resource that could be recognized in the potato story, as Andersson used different activities, played different roles, and used different resources in order to change (see Table 6.3). Let us go through every dimension sequentially and address some of the key points. To start with, Alströmer and the people at Royal Swedish Academy of Science seemed to have misjudged the complexity of making farmers change from old crops to nutritious potato production. As the events of the ordinary people of Andersson and Carlsson reveal, change is a long process from beginning to end that requires different activities, different roles, the use of different types of resources, and different types of questions. Change will not come overnight, and it

126  The Employee Side of the Digital Change Table 6.3  The Framework Applied to the Potato Story Change Dimension

Change Activity

Change agent and leadership role

Examples from the potato story

Common Ground — Scene One

Transactional activities such as the transfer of a change message between change agent and change recipient

Messenger

Common Meaning — Scene Two

Translational activities aimed at overcoming interpretive differences between actors through learning and reflection

Expert and Translator

Common Interest — Scene Three

Relational Negotiator activities, both and Coach political and supportive nature. The political activities align interests by negotiations and informal relationships, and the supportive activities manage feelings and emotions, and motivates change recipients

Common Behavior — Scene Four

Stabilizing activities— consisting of monitoring, communicating, and intervening actions—which secure long-term and recurrent behavior aligned to the new IT

• Swedish authorities send out vision, change message, Alströmer’s book, and seed tubers to Andersson • Failed analytical transaction because lack of common ground when Andersson eats the leaves and the fruits and gets sick • Carlsson translating and discussing potato production with words, gestures and demonstration to Andersson • Carlsson being an expert because he is an herbalist and gardener, and a successful translator because he has to explain complicated matters to uninformed customers • Carlsson putting forth arguments to Andersson for why potato production is better than wheat and barley • Carlsson telling Andersson that he will change people’s minds and the prejudice in the parish through the use of his friend the priest during church service • Carlsson coaching Andersson by reassuring that the rumors was false, that Carlsson would stop by during the changeover and support him, giving the emotional message that even the king and queen of France wore the potato flower in clothes and hair • Carlsson that during his morning walks talked to Andersson, counting potato plants and number harvested, checking out the garbage hill

Observer and Intervener

The Employee Side of the Digital Change 127 will not be as simple as sending out a change message, Alströmer’s writings, and some seed tubers. The dimension of common ground is dominated by transactional activities that are unidirectional such as communicating a change through a one-way speech, email, phone, or post. This approach may work fine if the change involves very minimal adjustments to local practices. However, changing behavior such as the ingrained practice of farming that the Andersson family has done for generations is not trivial, even if the Andersson family had been starving for long and surely felt an urge to find something new and different. In the story, the transactional activities are illustrated by the efforts made by governmental authorities in Stockholm, as they send Andersson a package containing a letter, Alströmer’s book, a manual for how to grow potatoes, and some seed potatoes. As noted, this amounted to failure, as there was no common ground established. Mr. Andersson did not share the same “ground” or “syntax” as the Swedish authorities and consequently he could not understand the message of change. He was less successful in comprehending the abstract description of new farming practices and the awkward language. In addition, he could not relate to the vision of the change. He preferred a miracle from God. Therefore, he went back to the way he had always done things. The disastrous outcome, using the words from the framework, was the result of a failed transactional activity due to a lack of a common ground. The Swedish authorities would probably have been more successful if they had realized that this was a major transformation or disruption for the farmers and addressed them directly. They could have, for example, organized a network of change agents and change sponsors that could have communicated (two-way) the change in the town hall, the churches, and the market of every village and town in Sweden. Instead, they injected mistrust and an even greater resistance to the new and strange root. In the dimension of common meaning (scene two), we find greater social interactions that transform information into meaningful knowledge— contextualization occurs. For example, Carlsson attempts to explain potato production to Andersson not only orally but also through activities, gestures, and examples that reinforced the message. On other words, different combination of sensemaking and sensegiving activities. Indeed, such activities are the most powerful when the sensemaking cues comes from combined and aligned sensations: making sense out of “what we hear, what we see, what we feel and what we use” (Iveroth  & Hallencreutz, p. 168). Accordingly, Carlsson and Andersson go to the field and try things out, they go to Carlsson’s cellar to check out how the potatoes are stored, and they go into the kitchen to enjoy mashed potato. These are all translational activities consisting of sensemaking and social interaction that surmounts the incompatible meaning structures between Carlsson and Andersson.

128  The Employee Side of the Digital Change These translational activities turn out to be successful partly because of two things. First, Carlsson is an expert since he is an herbalist and gardener by trade and therefore knows farming and potato cultivation inside and out. Second, he is also a good translator because he sells exotic crops and plants to often-uniformed customers in his shop. Because of these roles, together with experienced-based knowledge, inter-personal skills, and pedagogical skills, Carlsson could tailor the change communication in such a way that it became comprehensible for Andersson. Moving on, in the dimension of common interest, Carlsson first plays the role of being a negotiator and performs relational activities of political nature. He does so because Andersson does not fully understand the value and personal benefits of potato production. In his negotiating activities, Carlsson puts forth a number of arguments for why Carlsson should start growing potatoes: greater number of crops per square meter, great nutritional value, salvation from pilferage, easy cooking, and mixing crops. Then Carlsson plays the role of a coach by performing relational activities of supporting nature because Andersson feels afraid and shows change resistance. Much in the same way as digital technology (or any change of greater magnitude for that matter) is sometimes associated with strong feelings and prejudice. Andersson feels that the stakes are high because his family could starve, that dark forces are at play, and that he could be expelled from the county. Carlsson tackles Andersson’s emotions head on by reassuring that since they were close neighbors, and since he himself is an expert on potato production, he could stop by from time to time and help him with potential problems. By doing so, Carlsson coached and motivated Andersson as he went over to a new crop. Carlsson also reinforces this message by adding that if worse comes to worst, Carlsson could even come over for dinner. Yes, Carlsson has his own agenda, but he is still seen as a trusted informal leader in the parish. Then Carlsson goes back to play the role of being a negotiator and performs relational activities of political nature in order to address wider concerns—namely, using his friend the priest to act as a change sponsor in order to get rid of all the prejudices and false rumors, and to create a buy-in and common interest for potato production in the whole parish (with the use of both formal and informal activities). Carlsson realized that if he did not address wider problems that existed in the parish then Andersson’s attempt to grow potatoes would quite soon result in failure. That is, even if Carlsson could convince Andersson to start growing potatoes he would most likely fall back to his earlier behavior because Andersson would lose respect and get alienated by his fellow farmers. In this way, Carlsson performed political activities and acted as a negotiator by not only addressing Carlsson’s individual concerns but also by dealing with the wider problems connected to the whole community.

The Employee Side of the Digital Change 129 As a final point within this dimension, Carlsson goes even further by addressing more of the heart of Andersson rather than the mind, subliminally mentioning that in the “magically and exotic” nation of France the royal family values the beauty of the potato flower. By doing so, Carlsson reinforces the emotional content of the message of change in order to increase Andersson’s motivation to change to another crop—“kickstarting” the change. In the last scene, Andersson takes the role of being an observer as he monitors Carlsson’s behavior across time. During spring and summer, he observes Andersson by using different forms of stabilizing activities that include a form of performance indicators. For example, he converses with Andersson (which most likely included checking if he had lost weight), counting the number of potato plants and the number harvested. Carlsson even goes as far as observing if there were potato peels in the garbage hill. He did so because he was interested to see to what extent Carlsson walked the walk and did indeed eat his potatoes. Besides this, one of the points here is that the stabilizing activities were done systematically across time and included both qualitative and quantitative based “data”. As we reveal in the epilogue, Andersson’s transformation was in the end successful. But if it would have failed, and Andersson would have fallen back to his old way of doing things, then Carlsson would been forced to start playing the role of intervener and started the whole change process up again. For example, during his talks with Andersson, Carlsson might have discovered that Andersson was very thin, that there were few plants harvested, and that there was almost no potato tops and potato peels in the garbage hill. In such a scenario, Carlsson would have intervened. He would have started to see if they had a common ground by, for example, checking that the seed tubers were all right. He would have once again explained how the potato could be planted, harvested, and eaten in the best way. This time around Carlsson might have made the translational activates even more interactional and reflective than before by, for instance, inviting Andersson to visit his own potato field and together harvest and prepare a potato dinner at his home (and by doing so making the sensemaking and sensegiving activities even more powerful). And Carlsson might have tried to create a greater common interest in the parish by having talks and discussion in the town hall. In this way, Carlsson would have had to work with the activities in the dimensions all over again. Altogether, the balance between hard and soft factors propelled the change forward. For example, if the hard factors of change in common ground and common behavior were not present, Andersson’s attempts to start growing potatoes would have most likely resulted in failure. In common ground the change message and vision from the authorities created

130  The Employee Side of the Digital Change some change legitimacy; the writings of Jonas Alströmer, as well as the manual, created change awareness; and without the seed tubers Andersson would not have started trying out potato farming in the first place. Likewise, if it was not for Carlsson’s stabilizing activities of common behavior, Andersson would have most likely gone back to his old way of doing things. The same goes for the soft factors in our potato story. For instance, without Carlsson’s translational activities of common meaning, Andersson would not have understood the true meaning and the very details of potato cultivation. Similarly, without the relational activities of political (e.g., making use of the priest in the parish) and emotional nature (e.g., Carlsson’s attempts to convince Andersson that potato was not the work of the devil), Andersson’s potato farming would have most likely fallen short. In summary, the framework shows that leading digital change is a multifaceted and complex practice across time that necessitates performing different activities, playing different roles, and using different forms of resources and skills. Many practitioners out there think that if we simply build a functional digital technology, devote immense effort and time to the material artifact, and place it “out-there” in the organization, then people will understand its brilliance and start using the digital technology, and changes will more or less automatically come about. And whoosh!— the organization’s performance improves almost instantly. This is similar to what we saw in the potato story when the Swedish authorities thought that they could make the farmers change into potato production just by distributing information with some potato tubers. Surely, they must understand this, as we do, and start using this exotic and wonderful new crop, “it’s all there”. However, as we have seen, people are vital to digital change and not just the functional digital technology and one-way communication. Yet what is even more important is what people have in common. This chapter suggests that different forms of commonality during different phases of a digital change are imperative for the success of leading such projects. People in all organizations always have some attributes and things in common that bind them together. The different varieties of such commonalities can be used as a resource in the practice of successfully leading people through digital change.

Notes 1. The framework has earlier been published in California Management Review (Iveroth, 2010), Journal of Change Management (Iveroth, 2011), and Journal of Environmental Management (Iveroth and Bengtsson, 2014). Please see these articles for further theoretical background, research methods, as well as different empirical applications. 2. Some prefer of using the word shared instead of common, such as shared knowledge. However, there is a distinct difference between common and

The Employee Side of the Digital Change 131 shared. A  group of individuals that share something have things in mutual to a greater extent than if they would have had things in common. Common simply means that a group of people have some attributes that binds them together. In this way, the word common is a more ”looser” terms that it signifies a weaker connection between people, compared to shared. Lee (2001, p.  24) provides an example of the difference between common and shared knowledge that clarifies the distinction: Common (or background) knowledge is that information which members of a particular community assume to be held common by virtue of the fact they have very similar background or up-bringing. For example, I accept the information that London is in the south of Britain while Edinburgh is to the north to be common knowledge between my brother (a Singaporean who has never been to Britain) and me, even though we have never talked about the relative locations of the two cities before. The reason is because we have very similar childhood and school experiences. But once we have talked about taking a possible holiday together to the two cities and about whether we should rent a car or take the train up and down Britain, then that information about the locations of the two cities becomes part of our shared knowledge. 3. This chapter has its focus on the employee side of change, but we would like to remind the reader that similar sensemaking activities are equally important to undertake with external stakeholders. Sensemaking within customer cocreation processes is crucial to deploy to stay on pace with the ever-changing business environment of today.

References Agarwal & Lucas Jr (2005). The information systems identity crisis: Focusing on high-visibility and high-impact research, MIS Quarterly, 29(3), pp. 381–398. Armenakis  & Harris (2002). Crafting a change message to create transformational readiness, Journal of Organizational Change Management, 15(2), pp. 169–183. Athanasopoulou & Dopson (2018). A systematic review of executive coaching outcomes: Is it the journey or the destination that matters the most? The Leadership Quarterly, 29(1), pp. 70–88. Avgerou  & Mcgrath (2005). Rationalities and emotions in IS innovation, in: Howcroft & Trauth (Eds) Handbook of critical information systems research: Theory and application, pp. 299–324 (Cheltenham: Edward Elgar). Avgerou  & Mcgrath (2007). Power, rationality, and the art of living through socio-technical change, MIS Quarterly, 31(2), pp. 295–315. Balogun (2006). Managing change: Steering a Course between intended strategies and unanticipated outcomes, Long Range Planning, 39(1), pp. 29–49. Bartunek  & Moch (1994). Third-order organizational change and the Western mystical tradition, Journal of Organizational Change Management, 7(1), pp. 24–41. Beer (2008). Transforming organizations. Embracing the Paradox of E and O, in: T.G. Cummings (Ed) Handbook of organization development, pp.  405–428 (London: SAGE). Bies (2013). The delivery of bad news in organizations: A framework for analysis, Journal of Management, 39(1), pp. 136–162.

132  The Employee Side of the Digital Change Brown  & Duguid (2001). Knowledge and organization: A  social-practice perspective, Organization Science, 12(2), pp. 198–213. Burgelman, Floyd, Laamanen, Mantere, Vaara & Whittington (2018). Strategy processes and practices: Dialogues and intersections, Strategic Management Journal, 39(3), pp. 531–558. Burns & Scapens (2000). Conceptualizing management accounting change: An institutional framework, Management Accounting Research, 11(1), pp. 3–25. Campbell, Carmichael  & Naidoo (2015). Responding to hostility: Evidencebased guidance for communication during planned organizational change, Business and Professional Communication Quarterly, 78(2), pp. 197–214. Carlile (2004). Transferring, translating, and transforming: An integrative framework for managing knowledge across boundaries, Organization Science, 15(5), pp. 555–568. Cecez-Kecmanovic, Galliers, Henfridsson, Newell  & Vidgen (2014). The sociomateriality of information systems: Current status, future directions, MIS Quarterly, 38(3), pp. 809–830. Ciborra (2006). The mind or the heart? It depends on the (definition of) situation, Journal of Information Technology, 21(3), pp. 129–139. Constantinides & Barrett (2006). Large-scale ICT innovation, power, and organizational change: The case of a regional health information network, Journal of Applied Behavioral Science, 42(1), pp. 76–90. Davidson (2006). A  technological frames perspective on information technology and organizational change, Journal of Applied Behavioral Science, 42(1), pp. 23–39. Foerderer, Kude, Schuetz & Heinzl (2019). Knowledge boundaries in enterprise software platform development: Antecedents and consequences for platform governance, Information Systems Journal, 29(1), pp. 119–144. Gal & Berente (2008). A social representations perspective on information systems implementation: Rethinking the concept of “frames”, Information Technology & People, 21(2), pp. 133–154. Gardner (2006). Changing minds: The art and science of changing our own and other peoples minds (Boston, MA: Harvard Business School Press). Goodall & Pogrebna (2015). Expert leaders in a fast-moving environment, The Leadership Quarterly, 26(2), pp. 123–142. IBM (2008). Making change work. Continuing the enterprise of the future conversation (IBM: IBM Global Services). Iveroth (2010). Inside ericsson: A framework for the practice of leading global IT-enabled change, California Management Review, 53(1), pp. 136–153. Iveroth (2011). The sociomaterial practice of IT-enabled change, Journal of Change Management, 11(3), pp. 375–395. Iveroth (2012). Leading IT-enabled change across cultures, European Management Journal, 4(3), pp. 340–351. Iveroth  & Bengtsson (2014). Changing behavior towards sustainable practices using information technology, Journal of Environmental Management, 139(June), pp. 59–68. Iveroth & Hallencreutz (2015). Effective organizational change: Leading through sensemaking (London: Routledge). Iveroth, Magnusson  & Lindvall (2018). Digitalisering och styrning (Lund: Studentlitteratur).

The Employee Side of the Digital Change 133 Jarzabkowski, Lê & Balogun (2019). The social practice of coevolving strategy and structure to realize mandated radical change, Academy of Management Journal, 62(3), pp. 850–882. Jasperson, Carte, Saunders, Butler, Croes & Zheng (2002). Review: Power and information technology research: A metatriangulation review, MIS Quarterly, 26(4), pp. 397–459. Johnson & Cooper (2009). Power and concession in computer-mediated negotiations: An examination of first offers, MIS Quarterly, 33(1), pp. 147–170. Jørgensen, Owen & Neus (2009). Stop improvising change management! Strategy & Leadership, 37(2), pp. 38–44. Kallinikos (2001). The age of flexibility: Managing organizations and technology (Lund: Academia adacta). Klein & Myers (1999). A set of principles for conducting and evaluating interpretive field studies in information systems, MIS Quarterly, 23(1), pp. 67–93. Kunisch, Bartunek, Mueller  & Huy (2017). Time in strategic change research, Academy of Management Annals, 11(2), pp. 1005–1064. Lee (2001). Mutual knowledge, background knowledge and shared beliefs: Their roles in establishing common ground, Journal of Pragmatics, 33(1), pp. 21-44. Leppitt (2006). Challenging the code of change: Part 1. Praxis does not make perfect, Journal of Change Management, 6(2), pp. 121–142. Lindvall (2018). Information: kunskap som grund för verksamhetens styrning, in: Iveroth, Lindvall & Magnusson (Eds) Digitalisering och styrning, pp. 39–63 (Lund: Studentlitteratur). Lindvall  & Iveroth (2011). Creating a global network of shared service centres for accounting, Journal of Accounting  & Organizational Change, 7(3), pp. 278–305. Markus (2004a). Technochange management: Using IT to drive organizational change, Journal of Information Technology, 19(1), pp. 4–20. Markus (2004b). Technochange management: Using IT to drive organizational change, Journal of Information Technology, 19(1), pp. 4–20. Markus & Benjamin (1997). The magic bullet theory in IT-enabled transformation, Sloan Management Review, 38(2), pp. 55–68. Mcgrath (2006). Affection not affliction: The role of emotions in information systems and organizational change, Information  & Organization, 16(4), pp. 277–303. Nonaka & Takeuchi (1995). The knowledge-creating company: How Japanese companies create the dynamics of innovation (New York: Oxford University Press). Pfeffer (1981). Power in organizations (Marshfield, MA: Pitman). Polanyi (1958). Personal knowledge: Towards a post-critical philosophy (London: Routledge & K. Paul). Rosenkranz, Vranešić  & Holten (2014). Boundary interactions and motors of change in requirements elicitation: A dynamic perspective on knowledge sharing, Journal of the Association for Information Systems, 15(6), pp. 306–345. Røvik (2016). Knowledge transfer as translation: Review and elements of an instrumental theory, International Journal of Management Reviews, 18(3), pp. 290–310. Scapens (2006). Understanding management accounting practices: A  personal journey, The British Accounting Review, 38(1), pp. 1–30.

134  The Employee Side of the Digital Change Shannon & Weaver (1949). The mathematical theory of communication (Urbana, IL: University of Illinois Press). Södergren (2018). Förändringsförmåga, in: Iveroth, Lindvall & Magnusson (Eds) Digitalisering och styrning, pp. 383–409 (Lund: Studentlitteratur). Stein, Newell, Wagner & Galliers (2015). Coping with information technology: Mixed emotions, vacillation, and nonconforming use patterns, MIS Quarterly, 39(2), pp. 367–392. Stjernberg & Philips (1993). Organizational innovations in a long-term perspective: Legitimacy and souls-of-fire as critical factors of change and viability, Human Relations, 46(10), pp. 1193–1219. Taylor, Passarelli  & Van Oosten (2019). Leadership coach effectiveness as fostering self-determined, sustained change, The Leadership Quarterly, 30(6), p. 101313. Watson & Hoffman (1996). Managers as negotiators: A test of power versus gender as predictors of feelings, behavior, and outcomes, The Leadership Quarterly, 7(1), pp. 63–85. Weick (1995). Sensemaking in organizations (Thousand Oaks, CA: Sage). Whittle, Suhomlinova  & Mueller (2010). Funnel of interests: The discursive translation of organizational change, Journal of Applied Behavioral Science, 46(1), pp. 16–37.

7 Summary and Final End Notes

We have arrived at the last chapter of this endeavor, and it is time to wrap up and summarize. The starting point of this book was the statement that the challenge with digital change is twofold: there is an external challenge of dealing with the continuous relationship with customers and other external stakeholders, and there is an internal challenge of changing organizational strategies, structures and people. Successful digital change must embrace both. The external side of digital change is mainly about capturing and handling what we in the book have called the digitalization paradox. Digital services have come closer but personal relations have gone astray in the process. The gap between companies and customers has never been perceived as wide as today. At the same time, dealing with the paradox and the on-going relationship with customers yields great internal digital change challenges, as the technology used by customers must be integrated into the processes, peoples’ behavior, and preferably in the overall organizational strategy. This requires the development of strategies, structures, and skills that tackle both the soft and hard factors of digital change. We continued our journey with a bigger frame in Chapter  2 that afforded an historical overview of digitalization and an illustration of how the research field has developed since the middle of the last century. We started Chapter 2 by stating that technological change as such is nothing new, and we have actually been dealing with management and control problems connected to different forms of technology for thousands of years. We also argued that we are indeed currently experiencing the fourth industrial revolution, which is a double-edged sword, as it holds great promises as well as perils. Then we learned that the different waves of dominant digital technology move through six different phases that amount to different forms of organizational learning and management control. Put in a greater perspective, these phases resemble waves (or S-curves), and there have been four such waves since the 1960s, each with their own respective but yet connected issues. Across these years digital technology has evolved from playing an automating role, into an informating role, and finally into playing a transformative role.

136  Summary and Final End Notes We subsequently paid particular attention to the overlaps of the waves and S-curves by explaining that the companies that comes out as winners during technological discontinuity are the very ones that avoids having a blind faith towards technology and structure and at the same time they open up and lead organizational change. We also showed that during technological discontinuity, there is both creative accumulation and creative destruction going on at the same time, and we concluded that in the bigger picture and across time there are different types of digital change that require different strategies and approaches. The second part of Chapter  2 afforded an overview of three different streams of research that has had their own respective approach of viewing and dealing with issues of technology and its organizational consequences. The Technology imperative view came first by having a deterministic view of technology, and then the Organizational imperative with its voluntarist approach. We showed that overall the Technological imperative and the Organizational imperative can be seen as a reaction against each other, either attributing the causality of change to technology and structure or to people. Then we offered the currently dominant stream of Entanglement-in-practice that provides a more adequate theoretical lens for understanding technology-induced change since it rests upon a more balanced view of actor and structure, and since our practice is increasingly becoming more sociomaterial, and since technology is increasingly becoming ubiquitous, in the Cyber-physical wave. This overview of the three different streams theoretically underlined the combination (and interplay) of the most important and complex soft factors of change (actor) as well as the basic hard factors of change (structure and technology)—this is was also what we brought up in Chapter 1, showed in different chapters, and that finally came into full being in Chapter 6. In Chapter 3, we deepened the discussion about how digitalization profoundly has changed customer behavior. Through longitudinal customer perception studies, we showed that technology is no longer a driver for customer satisfaction and loyalty. Instead, a digitalization paradox has emerged, in the sense that digital services have become available around the clock, but the access to real human customer relations has become scarcer. Digital services have come closer, but customers feel distanced and abandoned. We summarized key differences between leaders and laggards when leading digital change and noted that those who are successful in mastering the digitalization paradox share some key attributes. They have a clarity about how and where to invest in digitalization and have articulated a proactive vision. They lead through sensemaking and sensegiving and keep employees informed and involved through the whole process. They know their customers and observe how customers behave before, during, and after interactions, and they design the digital customer experience based on this information. They can zoom in on image and service, avoid self-deception, and fight organizational habits claiming that

Summary and Final End Notes 137 “we know our market and our customers”. Moreover, successful mastering of the digitalization paradox means to focus on parallel stakeholders. Customers and employees of today are enlightened, conscious, and purposeful. Aspects such as social responsibility, sustainability, ethics, and conduct are critical. Therefore, successful digital change leaders use all available channels to improve customer reach and engagement and get closer to both customers and employees as well as other interested parties in an intertwined and interconnected environment. Finally, we concluded that successful management of the external side of digital change requires good use of customer data and a scientific approach to decision making. In the Cyber-physical wave, it is more important than ever to understand customers’ demands, needs, and expectations. In Chapter 4, we provided a more playful frame that was fundamentally different compared to the earlier chapters. Here we travelled back to 18th-century Sweden and followed Jacob Andersson’s transformational journey towards potato cultivation, which was facilitated by Einar Carlsson. This colorful story communicated the multifaceted and complex activities and processes of technology-enabled change, first, by showing the common reluctance to change, and later, by illustrating how it was defeated. This ultimately amounted to new behaviors as well as new business models and mindsets. The underlying rationale as well as different key points in the story were later used to decode abstract and theoretical reasoning throughout the remaining parts of the book. In Chapter 5, we went inside the organization and discussed four different types of strategic change that requires their respective ways of strategizing, leading, and controlling: Digital Adaption, Digital Tuning, Digital Transformation, and Digital Disruption. Here we offered The Digitalization Map that can serve as a starting point for discussions in the board room about what type of change an organization is facing and the consequences it provides. Through The Strategic Continuum of Digital Change, we further showed these consequences in connection to every type of change, as well as underlining that the consequences might be different for different people in different parts of the organization. We increased the complexity by highlighting that there are very few organizations that are actually in need of transformational or disruptive digital change, and that in most cases change is continuous in nature. We continued by explaining that in reality many organizations in the current volatile business environment are often forced to handle digital change that is situated at different places in The Digitalization Map, and that this requires bimodality or ambidexterity. Finally, we finished off by illustrating that The Digitalization Map is historically sensitive since a certain technology (and the change that it yields) can “travel” across time and be positioned at different places in the map. Chapter  6, went even deeper into the organization and explored what it is that you actually do when you lead employees and the whole

138  Summary and Final End Notes organization through digital change. This was done by providing The Commonality Framework for Digital Change that suggests that such change has four different dimensions of complexity: common ground (hard), common meaning (soft), common interest (soft), and common behavior (hard). We also described that these dimensions have their respective activities, leadership roles, and resources that are at play during digital change. We also connected the framework to the earlier chapter by saying that the interplay between the soft and the hard factors becomes more crucial when moving from the left to the right side of The Strategic Continuum of Digital Change (or moving through the Z in the middle of Figure 5.1). One of the key points was that both hard and the soft factors are combined during the process digital change, where the hard factors are the foundation that only at best represents one-half of the digital change, and the soft factors represent the other half and are the elements that ultimately make the change successful. This is, of course, also a way to go full-circle by re-addressing the issue presented in the introduction that the soft factors are the ones that presents the greatest challenges in the fourth industrial revolution and the Cyber-physical wave. So, what should be our endnote? Why not finish where we started—in Jacob’s kitchen. After the walk around the lake and the drop in at Bergholm, we put down three guiding notes on a napkin. These notes (slightly polished) can now serve as our concluding comments: • The term digitalization refers to the individual, social, organizational, and societal implications that come out of the diffusion and adoption of new information technology. Digitalization is often described as a societal change that is disruptive in nature, but in reality such change is very rare. In fact, quite few organizations, business processes or business models are in a real need for (or running the risk of) disruptive digital change. Most need for digitalization comes from ordinary operational and strategic technology and not from disruptive technology. In real life, societal digitalization is in general continuous and emergent to its nature and has been so for decades. Not all old truths need to be overthrown. Not everything should be digitalized. AI and robots will most likely not take over the world and kill us all while we sleep. • Customer behavior, demands, needs, and expectations have changed over time due to digitalization. New digital services and customer interfaces trigger new expectations and push internal organizational changes. And the internal side of digital change is, apart from new interconnected technology, as always mainly about people and culture. Successful change leaders know how to use technology to get close to customers, empower their employees, and fully understand both the customer and employee side of digital change. They have a clarity about how and where to invest and focus on the people side of change.

Summary and Final End Notes 139 • Digital change is not far from any organizational change as one of the most important cornerstones is behavioral change. Successful digital change is less about technology per se and more about people and new ways of thinking, feeling, and doing. Success lies in the people side of change. In a practice point of view, this translates into the complex leadership of performing different activities, playing different roles, applying different skills, and empowering different kinds of resources. In a more broader and strategic point of view, this decodes into a leadership challenge of assuring that the development of technology, organizations, and customers are synchronized. And all this will require a certain amount of bimodality, or ambidexterity. Indeed, digital change is multifaceted, and all pieces of the hollow Russian Babushka must be understood, managed, and controlled. A keystone conclusion is that the core of leading digital change is (after all) nothing new. The main parts of change theory is known, and many principles, practices, and tools are already out there. The only thing that stresses us all is the ever present need to change our behavior in tandem with technology. But do we have to bother? Well, let us close with yet another metaphor from the 18th century: you can stick to your wheat and barley or you can start cultivating potatoes. The choice is yours.

Index

Note: Page numbers in italic indicate a figure and page numbers in bold indicate a table on the corresponding page. absent presence 29 – 30 accumulation, creative 28 – 29, 28, 136 adaptation see digital adaptation agency 30 – 34, 124 Airbnb 23 – 25 Amazon 18, 20, 93 Apple 18 – 19, 49 automate 19, 24 Bell Labs 13 brand image 45, 51, 53, 57, 59, 111 business ecology 23 – 24, 84, 94 business logic ix, 4, 23, 94 car industry 47 – 50 closeness 58, 63, 111 coaching 108, 122, 122, 126 co-creation of value Commonality Framework for Digital Change, The 7, 35, 105 – 121, 108, 125, 138; common behavior 119 – 121; common ground 109 – 112; common interest 114 – 119; common meaning 112 – 114 common behavior 107, 108, 119 – 121; hard and soft factors 122 – 124, 122; and the potato story 126, 129 – 130 common ground 107 – 112, 108; and common meaning 114; hard and soft factors 122 – 124, 122; and the potato story 126, 127, 129 common interest 107, 108, 114 – 119; and common behavior 120; hard

and soft factors 122, 123, 125; and the potato story 126, 128 – 129 common meaning 84, 107, 108, 111 – 115; and common behavior 120; hard and soft factors 122 – 123, 122, 125; and the potato story 127, 126, 130 consumer consciousness 51 Contagion 14 – 16, 14, 22, 29 Control 14 – 16, 14, 29 corporate transformation 84 CPS (Cyber-Physical System) 21 – 22, 49 creative accumulation 28 – 29, 28, 136 creative destruction 28, 28 critical thinking 6, 63 customer expectations 49, 54, 67 customer focus 44, 53 customer journey 4 customer satisfaction 4 – 5, 43 – 44, 61 – 62, 64n1 – 2, 67, 136; and the digitalization paradox 46 – 47, 56 – 59, 56; evolution of 44 – 46, 45; measuring customer perceptions 52 – 55, 54 customization 2 – 3, 46 – 47, 49, 51, 60, 63 Cyber-physical wave 16 – 17, 17, 21 – 26, 35, 137; and the employee side 105 – 106; and strategy 81, 94 Data Administration 14 – 16, 14 Desktop wave 16 – 20, 17, 26, 93 destruction, creative 28, 28 dialogue 113 – 114, 122, 122 dichotomization 52

Index  141 Digital Adaption 88 – 91, 89, 96, 111, 137 digital change viii – ix, 3 – 7, 35, 135 – 139; challenges 5; customer side of 46, 50 – 53, 57 – 64; employee side of 105 – 108, 110 – 116, 118 – 125, 130; hard and soft factors of 122; sorting change by magnitude 83 – 85; sorting change by tempo 85 – 88; strategic aspects of 81 – 83, 88 – 92, 96 – 98, 97, 102n1; see also Commonality Framework for Digital Change, The Digital Disruption 93 – 94, 96, 100 – 101, 124, 137 digitalization viii, 3 – 6, 30, 35, 42, 135, 138; conceptualizing 9 – 12; the customer side 45, 53; drivers behind 55 – 59, 56; earlier forms of IT 12 – 14; the employee side 105, 115 – 117, 121; four waves of 16 – 24, 17; historical overview of 12 – 29, 14, 17, 28; six stages of organizational learning 14 – 16, 14; and strategy 81 – 82, 87; see also Digitalization Map, The; digitalization paradox Digitalization Map, The ix, 7, 137; the employee side 111, 125; and strategy 83, 85, 88 – 96, 89, 98 – 101, 102n1 digitalization paradox ix, 2, 5, 43 – 44, 106, 136 – 137; deconstructing 46 – 52; management from a customer perspective 59 – 64; understanding drivers behind 55 – 59, 56 Digital Transformation 88, 89, 92 – 94, 96, 100, 137 Digital Tuning 88 – 92, 89, 95 – 97, 97, 101, 111, 123 disruption see digital disruption dissatisfaction 44, 46, 55, 58 DP wave 16 – 18, 17, 20, 24, 26, 93 Eastman Kodak 29 easy access 60 ecosystem 23; see also business ecology education 12, 90, 114, 122 emotional intelligence (EQ) 6, 122, 122

employees 5 – 7, 18 – 19, 27 – 28, 32, 61 – 62, 105 – 106, 136 – 138; and strategy 83 – 84, 91 – 92, 96 – 97, 97; see also Commonality Framework for Digital Change, The Entanglement-in-practice 9, 24, 29 – 30, 33 – 35, 136 EPSI model (Extended Performance Satisfaction Index Model) 54, 54, 56 – 57, 64 – 65n3, 67 – 68 EPSI Rating initiative (European Performance Satisfaction Index) 64n1 Ericsson 49, 94 – 95 expectation spillover 2, 64 experience-based knowledge 108, 114, 122, 122 external customer side 4 – 5 external perspective 2 Facebook 18 faith, falling 51 – 52 fake news 3, 12 fine-tuning 83, 96, 101 first-time right 60 5G networks 21 fourth industrial revolution (4IR) 10 – 12, 22, 98, 105, 135, 138 Fujifilm 29 globalization 13, 53, 58 Google 10, 18, 29, 34 – 35 IBM 5 – 6, 13, 18 – 19, 29, 93, 100 – 101, 106 ICT (Information Communication Systems) 21 IKEA 91 – 92 Image 54, 56 – 59, 62, 67 image, brand 45, 51, 53, 57, 59, 111 image and service 62, 136 imbrication 36n12 incremental adjustments 83 – 84 informate 19, 24 – 25 Initiation 14 – 16, 14 Integration 14 – 15, 14 internal perspective 2 internet 19 – 21, 44 – 47, 49 – 51, 58, 60 – 61 interpersonal skills 108, 122, 122 IT 6 – 7, 9 – 11, 16 – 22, 26 – 27, 32; earlier forms of 12 – 14; the employee side 120, 122; and strategy 82, 87

142 Index KPIs (Key Performance Indicators) 119 – 121, 122, 124, 125 Levi-Strauss 20 loyalty 52 – 55, 58 – 59, 68 magnitude 83 – 85, 88, 89, 92, 95, 100, 123 make-and-sell 20, 22 – 23, 50, 106 management 5 – 6, 13, 15 – 17, 44; the employee side 111 – 112, 117 – 119; and strategy 90 – 92, 99 – 100; technology geared organizing studies within 29 – 35 materiality 33 – 35, 36n11 – 12, 123 Microsoft 18, 29, 49, 93 Maturity 14, 14, 16 mechanization 10 microcomputer 18 – 19 modular transformation 84 Morse code 12 – 13 networking 18, 21, 52, 108, 122, 122 Network wave 16, 17, 19 – 22, 25 Nokia 94 – 95 Organizational imperative 9, 29, 32 – 33, 115, 123, 136 organizational learning 9, 14, 25, 135; four waves of 16 – 24, 17; six stages of 14 – 16, 14 organizing studies see technology geared organizing studies parallel stakeholders 62, 137 PC (Personal Computer) 18, 29, 100 perceived loyalty 55 perceived product quality 60, 67 perceived service quality 60, 67 perceived value 44, 54, 56, 58, 67 potato story 69; and the employee side 106 – 109, 125 – 130, 126; epilogue 77 – 78; prologue 69 – 70; scene one 70 – 72; scene two 72 – 73; scene three 73 – 76; scene four 76 – 77; and strategy 82 – 83, 91 – 95, 100 – 101; what actually happened 78 – 79 proactivity 60 – 61, 90 – 93 productivity studies 27 product quality 55 – 58, 56, 60, 67

relational activities 108, 126, 128, 130; political type of 115 – 116; supportive type of 116 – 119 sense-and-respond 20, 22 – 23, 35, 106 sensegiving 61, 113, 122, 127, 129, 136 sensemaking 33, 61, 136; and the employee side 109, 112 – 113, 120 – 122, 127 – 129, 131n3 service 3 – 5, 23, 44 – 47, 49 – 50, 52 – 53, 55 – 62; image and service 62, 136 service quality 8, 55, 57 – 60, 67 servitization 4, 49 – 50, 53, 58 simplicity 60 SKF 48 social constructivism 33 social media 45, 51 – 53, 60, 62 social sciences 24, 34 social skills 6, 116 sociomateriality 24, 34 Spotify 23 – 25, 29, 93 stage theory 14 – 16, 21, 25, 36n6 stakeholders 90, 111 – 116; external 114, 131n3, 135; parallel 62, 137 structure 17 – 18, 20, 30 – 35, 36n11 – 12; and the employee side 122 – 124, 133; and strategy 83 – 86, 92 – 94, 99 – 100 surveys 5, 55, 62 sustainability 10 – 11, 46, 63 teaching skills 108, 114, 122 technical rationality 31 – 32 technology geared organizing studies 29 – 35 Technology imperative 9, 29 – 32, 34, 136 telegraph 12 – 13 tempo 85 – 88, 89, 91, 95, 100 transformate 24 – 25 transformation see digital transformation trust 45 – 47, 57, 63 two-way communication 82, 108, 114, 122 Uber 23 – 25 value-for-money see perceived value Volvo 47 – 50 World Economic Forum 6, 11 Y2K 19, 45