Product Innovation Management: Intelligence, Discovery, Development (Management for Professionals) 3030750108, 9783030750107

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Management for Professionals

Stefano Biazzo Roberto Filippini

Product Innovation Management Intelligence, Discovery, Development

Management for Professionals

The Springer series Management for Professionals comprises high-level business and management books for executives. The authors are experienced business professionals and renowned professors who combine scientific background, best practice, and entrepreneurial vision to provide powerful insights into how to achieve business excellence.

More information about this series at http://www.springer.com/series/10101

Stefano Biazzo • Roberto Filippini

Product Innovation Management Intelligence, Discovery, Development

Stefano Biazzo Department of Management and Engineering University of Padua Padova, Italy

Roberto Filippini Department of Management and Engineering University of Padua Padova, Italy

ISSN 2192-8096 ISSN 2192-810X (electronic) Management for Professionals ISBN 978-3-030-75010-7 ISBN 978-3-030-75011-4 (eBook) https://doi.org/10.1007/978-3-030-75011-4 Translated from Italian: Management dell’innovazione by Stefano Biazzo, and Roberto Filippini, # De Agostini Scuola S.p.A. 2018. Published by De Agostini Scuola S.p.A.. All Rights Reserved. # Springer Nature Switzerland AG 2021 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG. The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Contents

1

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Reference . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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The Challenge of Product Innovation . . . . . . . . . . . . . . . . . . . . . . 2.1 Why Innovate? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Who Innovates? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 What Kind of Innovation? . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Towards Successful New Products . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . . . . .

5 5 6 10 15 19

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Managing Product Innovation: A Framework . . . . . . . . . . . . . . . . . 3.1 The Innovation Pyramid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Intelligence: Absorbing Information . . . . . . . . . . . . . . . . . . . . . 3.3 Discovery: Exploring Opportunities for Innovation . . . . . . . . . . 3.4 Development: Bringing New Products to the Market . . . . . . . . . 3.5 Managing Product Innovation: A Challenge Between Continuity and Discontinuity . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

21 22 23 28 34

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Intelligence: Uncovering Innovation Opportunities Through Customer Involvement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Customers’ Voices: Need-Information and Solution-Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Involve Customers to Capture Their Needs . . . . . . . . . . . . . . . . 4.3 Involve Customers to Capture Solution-Information . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

41 45 52 57

Searching for Innovation Opportunities: Idea Generation and Technology Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 Innovation Workshop . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Innovation Contest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 Exploring the Technology Space . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

61 62 69 73 78

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Contents

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Product Development: Managing Uncertainty and Knowledge Integration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 6.1 The Strategic Problem of Uncertainty Reduction: The Stage-Gate Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 6.2 Flexible Product Development and the Evolution of Stage-Gate Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88 6.3 Spiral Development Processes: The Emergence of Agile Approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 6.4 The Organizational Problem of Cross-Functional Integration in the Formulation of Key Design Decisions . . . . . . . . . . . . . . . 95 6.5 Lean Thinking in Product Development . . . . . . . . . . . . . . . . . . 99 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104

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Creating the Project Value Proposition . . . . . . . . . . . . . . . . . . . . . . 7.1 Product Concept Definition . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2 Concept Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3 Concept Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.4 System-Level Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.5 Project Economic Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Organizing Development Projects: Structural Choices and Planning Approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.1 Organizing Product Development: The Structural Choices . . . . . 8.2 Managing Product Development Projects: Rational and Relational Approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3 The Agile Revolution: From Scrum to Agile-Stage-Gate . . . . . . 8.4 The Relational Paradigm in Hardware Product Development: The Lean Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.5 Development Speed and Overlapping . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Managing the Development Portfolio . . . . . . . . . . . . . . . . . . . . . . . 9.1 Project Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.2 Portfolio Visualization and Project Selection . . . . . . . . . . . . . . . 9.3 Project Portfolio Planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Product Innovation and Business Models . . . . . . . . . . . . . . . . . . . 10.1 Innovation and Digital Transformation . . . . . . . . . . . . . . . . . . 10.2 Business Model: The Company’s “Way of Being” in the Competitive Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.3 Business Model Canvas: A Visualization Tool . . . . . . . . . . . . 10.4 Business Model Innovation . . . . . . . . . . . . . . . . . . . . . . . . . .

107 107 116 117 124 127 129 131 131 137 140 144 152 155 159 160 161 167 174

. 177 . 177 . 179 . 181 . 186

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Product and Business Model Innovation: The Case of a Connected Product . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193

1

Introduction

We like to open our book with this passage by Paulo Coelho, taken from The Alchemist.1 “The crystal merchant awoke with the day and felt the same anxiety that he felt every morning. He had been in the same place for 30 years: a shop on the top of a hilly street where customers passed. Now it was too late to change anything—the only thing he had ever learned to do was to buy and sell crystal glassware”. But just before lunchtime, a boy stopped in front of the shop. He was dressed normally, but the practiced eyes of the crystal merchant could see that the boy had no money to spend. “I can clean up those glasses in the window, if you want”, said the boy. “The way they look now, nobody is going to want to buy them”. Taking the jacket out, he began to clean the glasses. In half an hour, he had cleaned all the glasses in the window, and, as he was doing so, two customers had entered the shop and bought some crystal. The merchant turned to the boy and said, “I’d like you to work in my shop. Two customers came in today while you were working, and that’s a good omen”. The boy had been working for the crystal merchant for almost a month. “I’d like to build a display case for the crystal” the boy said to the merchant. “We could place it outside, and attract those people who pass at the bottom of the hill”. “I’ve never had one before” the merchant answered. “People will pass by and bump into it, and pieces will be broken”. “Well, when I took my sheep through the fields some of them might have died if we had come upon a snake. But that’s the way life is with sheep and with shepherds”. That day, the merchant gave the boy permission to build the display. Not everyone can see his dreams come true in the same way. Two more months passed, and the shelf brought many customers into the crystal shop. One afternoon the boy had seen a man at the top of the hill, complaining that it was impossible to find a decent place to get something to drink after such a climb.

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Coelho (1995).

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The boy, accustomed to recognizing omens, spoke to the merchant. “Let’s sell tea to the people who climb the hill”. “Lots of places sell tea around here”, the merchant said. “But we could sell tea in crystal glasses. The people will enjoy the tea and want to buy the glasses. I have been told that beauty is the great seducer of men”. The merchant told the boy that he could begin to sell tea in the crystal glasses. Sometimes, there’s no way to hold back the river. The men climbed the hill, and they were tired when they reached the top. But there they saw a crystal shop that offered refreshing mint tea. Before long, the news spread, and a great many people began to climb the hill in a trade that was so old. Other shops were opened that served tea in crystal, but they weren’t at the top of the hill, and they had little business. Eventually, the merchant had to hire two more employees. He began to import enormous quantities of tea, along with his crystal, and his shop was sought out by men and women with a thirst for things new”. (Paolo Coelho) Innovation is timeless. In Coelho’s story, the boy is capable of seeing beyond, he grasped the needs of others, he intercepted the signs, even weak ones, that hinted at the possibility of new paths, he deployed intuition and creativity and gave the old owner of the crystal shop the courage to take risks. In the exponential speed of technological and market changes of our times, managing innovation has become an utterly complex challenge. It is hard to capture the weak signals of change in society and markets. It is exhausting to search for new opportunities systematically and to abandon the known for the unknown, and it is not easy to accept that the creation of something new is always the result of trials and errors. Innovators are comfortable with experimentation-driven failures, and they firmly believe that innovation processes cannot be ‘designed’ in the same way as repetitive business processes, where errors (results that do not conform to expectations) must be minimised. In a repetitive process, the aim is to eliminate variability. The output is known, and the system of activities that realises it can be engineered and optimized for maximum efficiency. On the other hand, in innovation processes, the paths leading to the creation of something new are inevitably marked by “waste” (discarded ideas, prototypes that do not meet expectations, roads that turn out to be dead ends). Innovation requires a paradigmatic shift in organisational design: from focusing on eliminating variability to the pervasive adoption of the logic of experimentation— the Darwinian model of variation and selection. At the root of many companies’ inadequate innovative performance lies the difficulty of producing variation and selection. Effectively adopting the logic of experimentation is a great challenge, as it requires management to be ambidextrous: reducing variability in repetitive processes, while exploiting variation in innovation activities.

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Introduction

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The future, like everything else, is not what it used to be. So wrote Paul Valéry in 1931, reflecting on the future and using a typewriter. In 1931, all typewriters featured the same product architecture: the dominant design of the Underwood No. 5 of 1899, which represented the technical standard of the typewriter for over 50 years (see Chap. 2). The future “is not what it used to be”. It has always been so. But today we have an additional (big) problem: we live in a world characterised by accelerated and non-linear change: a dominant design can last perhaps a few years and not tens of years as in Valéry’s time. In order to cope with such turbulent and unpredictable competitive contexts, it is necessary to have the organisational capability to implement rapid and sustainable learning cycles. It is not the isolated successful product or the single technological breakthrough that can make the difference, but the capability to: • be faster than others in catching the weak signals of change and imagining and experimenting with new value propositions; • bring new products to market quickly, aware that they too are an ‘experiment’ to be validated; • learn from mistakes and adapt their products to customer feedback with a constant stream of incremental improvements. This book will provide the conceptual frameworks, methodologies, and tools that make up the core ingredients of innovation management. The second chapter is dedicated to an in-depth examination of product innovation’s phenomenon in its multiple manifestations to understand better the nature and complexity of the managerial and organisational challenges that enterprises have to face. In the third chapter, the model of the innovation pyramid is presented, which highlights the extent to which the innovative capability of a company is based on a system of interdependent activities: the three levels of the pyramid (intelligence, discovery, development) metaphorically represent the three “factories” that generate the three output streams needed to innovate systematically—inspirations, feasible product ideas, and a portfolio of profitable products. The fourth chapter is dedicated to customer involvement in innovation processes; among intelligence activities, there is no doubt that the development of empathic relationships with users and buyers represents a central challenge in searching for successful products. In the fifth chapter, we focus on the organisational challenges of discovery processes (creative ideation and technology development). The following three chapters deal with the third level of the innovation pyramid: the design of an effective product development process (Chap. 6); the definition of a development Project Value Proposition (Chap. 7); the structural and methodological choices in organising and managing development projects (Chap. 8). Chapter 9 addresses the issue of portfolio management—the transfer process from “front-end” innovation activities (levels 1 and 2 of the innovation pyramid) to product development efforts and investments (level 3).

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The aim of Chap. 10 is to examine the relationship between product innovation and business model innovation, as the ability to unlock the transformative potential of new products may depend, in many cases, on the change of other components of the firm’s “way of being” in the competitive arena. Particular attention will be given to digital technologies, given their potential disruptive effect on several industries.

Reference Coelho, P. (1995). The Alchemist. HarperCollins Publishers.

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The Challenge of Product Innovation

Abstract

Although it is possible to “innovate” in all business activities, it is product innovation that plays a central role in creating value for the customer. Products materialize the value proposition of a company with a combination of tangible and intangible elements and are at the core of any business model (see Chap. 10). Product innovation requires human, financial, organizational and technical resources; it is a complex and risky activity. History teaches us that innovation initiatives fail frequently and that even successful innovators have difficulty sustaining their performance (Pisano, Harvard Business Review, 93(6), 44-54, 2015). Unsuccessful products undermine the company’s economic and financial viability and harm the company’s reputation. Product innovation is not an option; it is a necessity. In this chapter, we explore the phenomenon of product innovation in its multiple manifestations, to better understand the nature and complexity of the managerial and organizational challenges that companies have to face.

2.1

Why Innovate?

In the prevailing and generally accepted view, firms are motivated to innovate to maintain or improve their competitive position and market share against their competitors; this view is in line with the well-known slogan “innovate to compete.” But this is not the perspective that characterizes the most successful companies, where what gives meaning to innovative efforts is the satisfaction of customer needs. The focus of managerial attention is not on competitors, but on the beneficiaries of the value proposition: “innovating for customers” is the guiding principle. James Dyson, a successful designer, entrepreneur and founder of the eponymous company that designs and manufactures vacuum cleaners, fans and hand dryers (who has not been pleasantly satisfied with the Air Blade that we find in so many # Springer Nature Switzerland AG 2021 S. Biazzo, R. Filippini, Product Innovation Management, Management for Professionals, https://doi.org/10.1007/978-3-030-75011-4_2

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airports?), in describing his approach to innovation in a company video, points out: “We don’t focus our attention on sales targets and market shares; we are much more interested in making products that people love, using our engineering skills to solve problems1”. The strategic orientation that shapes and drives innovative activities is an essential factor influencing the long-term performance of the company: the excessive focus on competitors and financial results is an obstacle to the formulation of successful innovation strategies. Serial innovators have embodied in their DNA a very clear vision of which direction should guide the organizational action: the value for the client (Case Study 2.1).2 Case Study 2.1 In a successful Business-to-Business (B2B) medium-sized firm, the entrepreneur asked his employees to reflect on why the company had innovated continuously. Many said that innovation had been a critical factor in maintaining competitiveness against other companies in the sector. The engineering manager replied that technological progress requires keeping up with increasingly high-performance products so as not to be overtaken by the competition. Ultimately, managers agreed that the underlying motivation could be summed up in the formula “innovate to compete”. The entrepreneur, shaking his head, said that this was not the real reason behind all the efforts and risks undertaken: “try to think carefully; our company has remained competitive thanks to innovations always oriented to solve the problems of customers, to find new solutions to their unmet or emerging needs. Maintaining competitiveness has been the result of our constant attention to our customers, to offer them ever greater value”.

2.2

Who Innovates?

There are time frames, sometimes very long ones, in which the rate of innovation in a particular sector is modest, and there are only incremental improvements. This usually happens when a well-defined product architecture (technical, functional and aesthetic) is established in the market, which is dominant over alternatives and becomes the de facto standard of a sector (dominant design3). In this situation, price

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www.dyson.com. It is important to note that “value for the customer” has been recognized by Womack and Jones (1996) as the cornerstone of the Lean revolution in production systems and, more generally, in the corporate organization (Lean Thinking). 3 Utterback (1994). 2

2.2 Who Innovates?

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Fig. 2.1 Underwood n. 5: an example of dominant design (source: Duc N. Ly, licensed under CC BY-SA 2.0)

competition is exacerbated, as the products of the various competitors differ marginally from each other as variations of a dominant design. A good example is the typewriter sector, characterized for several decades by a dominant architecture: the model 5 of the Underwood Typewriter Company of 1899,4 which prevailed over alternative product architectures and which represented the standard of the typewriter for over 50 years (Fig. 2.1). Model 5 harmoniously combined a series of product attributes that perfectly captured the basic needs of the users of the time: QWERTY keyboard, the most widespread already at the end of the nineteenth century (even though it was not an optimal configuration for writing speed); visible typing (you could immediately see what was being written, unlike almost all the competitors); quieter, single keyboard with SHIFT key for upper case letters (unlike the enormous full-keyboards with a separate key for each character, which slowed down typists a lot); tabulation key (TAB); ribbon with ink extremely easy to replace. In this situation, who is capable of breaking the established equilibrium and disrupting the dominance of a consolidated architecture? In 1933 IBM moved into the typewriter business by acquiring Electromatic Typewriters, the first company to market an electric typewriter. The Electromatic model, while replacing the mechanical strength of the fingers with that of an electric 4 The first commercially successful typewriter was introduced by Remington in 1873 (the model is known as the Sholes & Glidden Type-Writer); it had a QWERTY keyboard with capital letters only and an up-strike architecture: you couldn’t see what you were writing (the hammers hit the paper from bottom to top). Remington was the dominant producer of the late 1800s; Underwood (who supplied Remington with coal paper and ribbons) entered the market in 1895 with a novelty: the visible typing ( front-strike architecture) . . . which Remington ignored until 1908.

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motor, is architecturally perfectly aligned with the dominant design that emerged more than 30 years earlier with the Underwood model 5 (it is a classic mechanical typewriter with the addition of an electric motor to move the metal bars that contain the characters). Right from the start, IBM focused on a largely unmet need, but ignored by the leading companies that have made history in the industry: typewriters are noisy, slow and fatigue the fingers of employees. The leaders of the time seem not to be interested in the benefits that the electric motor brought to users: Underwood introduced the first electric model only in 1946 (22 years after the introduction of the first electric machine in the market); Remington in 1949; Royal in 1950 and Smith Corona in 1955 (these four manufacturers held, in the 50s, almost 90% of the market). After years of incremental improvements to the Electromatic, aimed at improving the working environment, reducing fatigue and increasing efficiency, in 1961 IBM launched the Selectric—an electric and silent typewriter, with an extremely lighttouch keyboard—with a product architecture that radically departs from the dominant design: all characters are inserted into a single rotating head (“golf ball”), and all traditional metal bars connecting with the keys are eliminated (Fig. 2.2). Selectric marks the beginning of a new era in the industry and the rapid rise of IBM as the uncontested leader. The favourable trend of the demand for motorcycles in the 50s and early 60s in Italy saw an increase in the number of companies. There were more than one hundred motorcycle manufacturers;5 motorcycles were little differentiated from each other, almost all single-cylinder and small engine (125, 150 cc), drum brakes, limited power (with a few exceptions that emerged in the mid 1960s with the not very high-performance twin-cylinder models developed by Moto Guzzi, Laverda and Gilera): there was a clear dominant design in the Italian market. In 1968 Honda launched the 750 Four: four cylinders, four exhaust pipes, extended chrome plating, captivating sound, disc brakes, exhilarating performance and high cornering stability; a very different mix from the dominant design of the bikes of the time (Fig. 2.3). Was Honda successful because of technical innovations? Not only that, the 750 Four had answered a latent need, which was spreading rapidly: from the bike as a means of transport (home—work) to the vehicle for the pleasure of driving and speed (enjoy riding). In a few years, 90% of the Italian motorcycle companies closed their doors. There are many other examples in which new entrants to the sector introduce products with a high level of diversity and originality and which undermine competitive equilibrium.6 Think, for example, of Apple with the entry into the world of portable digital players (iPods) and mobile phones (iPhones). Leading companies are

See, for example, the special issues of the magazine Motociclismo dedicated to the exhibition of food and motorcycles in Milan (No. 49, December 1956; No. 48-49, December 1959; No. 49-50, December 1960). 6 Christensen and Raynor (2003); Kim and Mauborgne (2005a). 5

2.2 Who Innovates?

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Fig. 2.2 The beginning of a new era (1961): IBM Selectric (source: Jamoca1, licensed under CC BY-NC-SA 2.0)

Fig. 2.3 Honda CB 750 Four (1969) (source: Shinobu Matsukawa, licensed under CC BY-NC-ND 4.0)

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often misled by the focus on competitive efficiency and locked into a “sustaining innovation” strategy (a concept that we will explore in more detail in the next paragraph). They are focused on what Kim and Mauborgne call the Red Ocean:7 overcoming competitors by progressively improving products within the status quo of the sector; and the (often dramatic) disruption comes from outside: from companies, sometimes much smaller than the leaders, which are able to radically renew the value offered to customers and to open up new market spaces. However, the key players in the innovation game are not only the producers: the subdivision that gives them an active role in the innovation processes and the users a passive role is, without doubt, a partial and reductive vision. In certain situations, it is the users themselves who personally create and experiment with new solutions aimed at better satisfying their needs, as has been well highlighted by the seminal studies of Von Hippel8 that have brought to light the phenomenon of user innovation. The active role of users has been studied and demonstrated in various fields, such as scientific instruments;9 medical and surgical instruments;10 CAD software;11 sports equipment (kayaking, kite surfing, snowboarding, mountain biking12) (see Chap. 4).

2.3

What Kind of Innovation?

Product innovation can have different intensities, in terms of the depth of the improvements introduced and the level of novelty and originality. In determining the different types of innovation, it is essential to distinguish between the two different perspectives with which we observe and judge the degree of discontinuity of the new product: the perspective of the sector and that of the individual company. From the perspective of the sector, the traditional classification is the distinction between incremental and radical innovations (or breakthroughs); the differentiating element is the degree of novelty in technology. The output of radical innovation is a product that presents a significant technological change compared to products on the market, and that offers substantial improvements in performance and functionality.13 This classification, however, does not distinguish the dual nature of a product, which has been clearly highlighted by Verganti:14 a product is indeed a functional

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Kim and Mauborgne (2005b). Von Hippel (1998, 2005). 9 Von Hippel (1998); Riggs and von Hippel (1994). 10 Lettl et al. (2006). 11 Urban and Von Hippel (1988). 12 Franke et al. (2006), Luethje et al. (2005), Hienerth et al. (2014) and Shah and Tripsas (2007). 13 Veryzer (1998), Pisano (2015). New technologies do not always immediately offer a performance leap; they may not initially demonstrate their superiority, as they are at the early stage of maturity and are at the beginning of the S-curve of their improvement path; see Christensen (1992a, 1992b). 14 Verganti (2009). 8

2.3 What Kind of Innovation?

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tool linked to the practical execution of an activity or task; but it is also, in many areas, an object capable of arousing emotions and symbolic values (the “meaning” of a product15) through a language made of signs: the material, the geometric shape, the type of surface, the colours, the brand. Based on these two dimensions, Verganti identifies three categories of innovation: • market-pull: these are the innovative efforts that result in incremental performance improvements and product attributes adaptations to dominant sociocultural trends (such as, for example, changes in the aesthetic style of a product to match the most trendy canons of beauty in the market); • technology-push: this category coincides with the concept of “radical innovation” described above; this is the case of significant improvements in the technical performance of the product or the introduction of new functions; • design-driven: it is the radical innovation of meanings, the proposal of a new vision on why a product should be bought and used (for example, a lamp to create atmospheres and arouse emotions and not to illuminate16). The previous classifications are both focused on the product; if we shift our attention to the customers, it is possible to refine our understanding of the different manifestations of innovation and distinguish between sustaining innovation and disruptive innovations, Christensen17 emphasizes that innovation is sustaining when the innovative effort is oriented towards maintaining a specific trajectory of improvement, which is followed by all competitors: better and better products are offered to existing customers seeking increasing margins. Improvements can be incremental or even radical, but they are always of the same nature: “to do better what has always been done”. In his research, Christensen points out that in this quest for progressive improvement the phenomenon of overshooting18 frequently emerges: there are large groups of customers for whom the products on the market are too sophisticated and high performing in relation to their real needs; think, for example, of our experience as consumers, when we interact with products of which we use a minimum percentage of possible features and benefits. Overshooting is a window of opportunity for companies that have the capability to identify it; however, it is often the new entrants in the industry who take advantage of the mismatch between existing products and “overshot customers” and can change the rules of the competitive game. Three types of disruption can be identified: low-end disruption, new market disruption and high-end disruption.

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See Dell’Era and Verganti (2007). See the case of Artemis’ Metamorphosis lamp discussed in Verganti (2003). 17 Christensen (1997). 18 See Christensen (1997) and Christensen and Raynor (2003). 16

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The Challenge of Product Innovation

In low-end disruption, the company that seizes the opportunity of overshooting offers a new product for the lower end of the market, much simpler and cheaper, but well-tailored to the needs of that segment. The entry of this new product is often undisputed as leading companies have no incentive to invest in low-end market segments, as they are concentrated on the most profitable market segments. Later on, in the course of progressive innovation, the low-end product is improved continuously and, over time, it can reach a sufficiently good performance level, able to meet the needs of the highest standards. The “good enough” product may be able to disrupt the traditional, more expensive and over-performing products. A significant example is the case of the ECG (electrocardiogram) equipment developed by General Electric (GE) for the rural Indian market; in this market the traditional low-end equipment (structurally similar to the high-end equipment: large size, with an integrated monitor, keyboard and printer in A4 format) were, in fact, in a situation of full overshooting compared to the needs of small clinics and doctors forced to reach their patients in remote locations. GE grasped the need for portability and sheer ease of use by launching a “good enough” portable device (MAC400) at a price level equal to 30% of the cheapest product on the market: a very small and light equipment, with only 2 keys, without ECG storage functions, that simply makes an electrocardiogram and prints it in a roll of paper with the format of a fiscal receipt of a cafeteria (it should be noted that the technology of the mini printers present in the buses in the district of Bangalore has been used), is “good enough” for that market segment. The outcome of this innovation is remarkable: in the following months and years the MAC400 invaded the western market, and the evolutions (in “progressive” style) of this portable device (MAC600 and MAC800) attacked the highest levels of the market all over the world. In the new market disruption, the new product is offered to non-users (see Chap. 4): those who are not able to purchase the products offered on the market because they are too complicated, too high performing and too expensive for their needs. Perhaps the most famous example is the case of Honda’s entry into the US motorcycle market in the early 1960s with the SuperCub, a 4-stroke single-cylinder engine with 50cc capacity. The SuperCub is a middle ground between a scooter and a motorcycle, extremely reliable, easy to maintain and inexpensive. The success in the “non-bikers” segment was overwhelming, and the Honda brand quickly became a symbol of quality and reliability. The outcome of this Japanese invasion is well known: Honda, left unchallenged in the new market (apart from a failed attempt by Harley Davidson), has progressively attacked the highest price segments becoming a world leader in the sector; in 2017 it celebrated the achievement of the goal of 100 million SuperCub sold. In the previous cases, disruptive products are typically less expensive, simpler, with sufficiently good performance and functions: they represent a “bottom-up” attack on existing competitors.

2.3 What Kind of Innovation?

13

In high-end disruption, the product that changes the rules of the game attacks the top of the market:19 Apple’s iPod+iTunes and iPhone+AppStore are two cases of extraordinary success and dramatic upheaval of competitive equilibria. The iPod was launched at a price higher than the majority of competing products (about 50 in 2001, almost all of which have now disappeared); the same applies to the iPhone in 2007. The iPhone+AppStore system has revolutionized the very concept of the cellular phone, which has become an infinitely customizable platform with applications developed by third parties; the iPod+iTunes system has defined a new way to buy, store and listen to music. Kim and Mauborgne have effectively summarized the three forms of disruption that we have examined with the term value innovation:20 the creation of a different product, which changes the rules of the game and profoundly transforms the value curve, differentiating it from that of competitors. As we will see in Chaps. 5 and 8, the value curve is a way to graphically represent how a company configures its offer, through three variables: (a) price positioning; (b) the fundamental attributes of the product that represent the key competitive factors; (c) the offering level that customers receive for each attribute. The classifications examined so far differentiate the types of innovation with the sector as a focal point. Adopting now the perspective of the single firm, it is useful to consider a more analytical taxonomy that refers to product development projects, i.e. the set of activities aimed at transforming innovation opportunities into products that can be produced and sold profitably (the third level of the activity system on which the innovative capacity of the enterprise is based; see Chap. 3). Development projects may be differentiated according to the degree of output novelty. (1) New product for the company and the market (new-to-the-world). It is the most challenging and complex project to undertake. New products can combine new technologies with existing ones and must penetrate a market that has no experience of use. The company is, therefore, facing both market difficulties (Which exactly will be the customers who will buy the new product? We will meet the needs of customers?), and problems related to the fine-tuning of technologies that are used for the first time in a commercial product. The risk of failure can be extremely high, and the first mover can also fail because of “too much anticipation” in the introduction of a new technology, which is not yet sufficiently reliable and performing for the majority of customers. There are examples in a wide variety of fields: we can remember the failure of Qube, the interactive cable television of the 70s, a significant

19 20

See Utterback and Acee (2005); Dyer and Bryce (2015). See Kim and Mauborgne (1999, 2005a).

14

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The Challenge of Product Innovation

anticipation of what would later become the social media phenomenon; Sinclair launched in 1985 an electric city car: the performance of the batteries were too poor to compete with petrol cars, fuel was still cheap, and customers had no sensitivity on energy saving and respect for the environment. Today, digital technologies in the cloud era open up enormous opportunities to offer radically new, intelligent and connected products and undertake, therefore, new-to-the-world product development projects. The possibility of transferring information between products and customers, between users and manufacturers, amplifies the value offered and also allows to innovate the business model: think of the possible transformations of the value provided through an intelligent and connected car or with an intelligent and connected machine tool that allows the monitoring, control and predictive management of maintenance (see Chap. 10). (2) New product for the company but not for the market (diversification with a new product line). The level of complexity and technical uncertainty is high for the company, as a new competitive space is approached. As an example, Samsung, a company in the electronics sector, has entered the (mature) domestic appliance market; Montblanc, alongside its traditional pens, has joined the luxury watch sector. There are different reasons to undertake such projects: diversification of the business or exploitation of a brand with a strong reputation; and there are two main difficulties to be faced: the limited knowledge of the competition and customer needs; the need to adopt new technologies for which the company has insufficient experience. (3) Products that renew existing product lines, which often present significant levels of originality for the market. These are strategically important projects and can offer substantial technological challenges; think, for example, of the introduction by UNOX (see Chap. 9) of a new family of “intelligent” professional ovens, equipped with a graphical touch interface, network connection and software for optimizing cooking processes. (4) Repositioning:21 the introduction of a new product (or new applications of current products), based on existing skills, technologies and resources, in a different market segment or for a new type of customers. Think, for example, of a sneaker company that has diversified into the work shoe market, using its existing know-how and most of its production equipment. Or the case of a company specialized in burners for gas boilers for residential use, which, due to the slowdown in building construction, decided to explore the possible novel applications of burners: the sector of industrial ovens for food was identified as a new and potentially attractive market. The initial stages of the repositioning project were devoted to defining the extent of the technical adaptations necessary to adjust the product to the industrial ovens, and to building an appropriate level of market knowledge. Afterwards, with limited product redesign costs and using the existing manufacturing resources, a new business was started through the “repositioning” of current products. Garmin is

It should be noted that the concept of “repositioning” used by us differs from the traditional “repositioning” category of Booz, Allen, and Hamilton (1982).

21

2.4 Towards Successful New Products

15

another example of a company that has often introduced new products in different markets (naval, aeronautical, automotive and sports), exploiting its skills and technologies. Although this innovation strategy may reveal impressive growth prospects, it is not widely practised; as we have previously pointed out about the phenomenon of disruption, companies are often blocked, from a conceptual and organizational point of view, within the boundaries of known market spaces. (5) Revisions of existing products. At a lower level of complexity, we find development projects that are aimed at “replacing” a product that has become obsolete for technical or functional or aesthetic reasons. With these projects, companies try to maintain their position in the market, which can be compromised by those products that have now reached the end of their life cycle. (6) Marginal improvements to existing products. These are the simplest projects from a management point of view, aimed at eliminating possible dissatisfaction factors (e.g. elimination of defects found by users in the field) or reducing costs (Value Engineering). The innovative efforts of a company can, therefore, show different levels of discontinuity vis-à-vis the status quo. It is clear that the distribution of investments in innovation is usually unbalanced towards incremental innovations; discontinuous innovations are, in fact, intrinsically very risky and complex and, although essential and critical for the future of the company, they cannot represent the majority of investments.22 In Chap. 3, we will delve into the organizational and managerial implications of discontinuous innovation.

2.4

Towards Successful New Products

As we have previously pointed out, many new products are not successful: they do not reach the estimated revenues and profit margins or have a short life cycle in the market (Case Study 2.2). Managing innovation processes is one of the most demanding and complex managerial challenges (see Chap. 3). The methods used to manage innovation are crucial in achieving product success; the link between good innovation management practices and product success is now widely recognized.23 In this perspective, the following chapters are focused on the organizational methodologies and management tools necessary to enhance the capability to create new products that generate value for customers and the company.

22 23

Nagji and Tuff (2012). Cooper (2017).

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The Challenge of Product Innovation

Case Study 2.2 If the majority of products are not successful, we must ask ourselves what to do when we are experiencing failures. William McKnight, 3M’s renowned president, addressed his associates in 1949 as follows: “. . .it is necessary to delegate responsibilities and encourage people to exercise their initiative. This attitude requires a considerable amount of tolerance. . . mistakes will be made, but if management is destructively critical when mistakes are made, it kills initiative. . .” McKnight’s vision has permeated 3M’s organizational culture of innovation, teamwork, and learning from mistakes and failures in a lasting way.24 But what are the primary characteristics of a successful product? Firstly, a successful product is characterized by the presence of a harmonic combination of multiple attributes, which capture the set of needs that are perceived as most relevant by the target customers (Case Study 2.3): functional attributes (a technical feature: i.e. weight); emotional attributes (an attractive form, a valuable material that evokes exclusivity, the brand); and support services (pre-sales and after-sales). Secondly, the success of a product depends on the perceived value; the value offered must be recognized by the customer during the purchasing decision process. Case Study 2.3 The iPhone has undoubtedly been a successful product. The factors that led to the incredible results of sales and margins are many. The iPhone+AppStore system has revolutionized the very concept of the phone, which has been transformed into an infinitely customizable platform with applications developed by third parties; the ease of use has been profoundly improved (compared to the old generation “feature phones”); of course, considerable attention has been given to the emotional aspects related to aesthetic refinement and the use of materials. The symbolic value of the Apple brand and first-class service quality also played an important role (think of the user experience of buying from an Apple Store, and the comprehensive technical assistance service that few competitors in consumer electronics can match). The value for the customer is therefore influenced by two factors: product attributes and how these attributes are communicated. Figure 2.4 shows that the perception of value depends on two factors: what the customer perceives directly from the product itself (the attributes of the product “are talking” to the customer) and how the product is represented, narrated and explained in the communication

24

See McKnight Principles on the 3M institutional website (solutions.3M.com).

2.4 Towards Successful New Products

17

- Emotional attributes

Product Communication Strategy

- Support services

- Words and Images

Product

What to communicate?

- Functional attributes

PERCEIVED VALUE

by the customer

Fig. 2.4 The perception of value

processes. Consequently, the communication strategy (what do we want to communicate?) is crucial to the success of a product. The central role of communication is, of course, evident in the emotional and symbolic perception of a product. Think, for example, of how Rolex presents the historical origins of the Milgauss model and creates the image of a watch linked to the world of avant-garde scientific research: “To alter the reliability and precision of a standard mechanical watch, a magnetic field of 50 to 100 gauss is sufficient. Many scientists, however, come into contact with magnetic fields of much higher intensity during their research. The solution Rolex presented to the scientists of the European Organisation for Nuclear Research (CERN) in 1956 was the Milgauss, a unique watch capable of withstanding magnetic fields of 1000 gauss, hence the origin of its name. In those contexts where the functional dimension is dominant, the role of communication is often perceived as less critical; this is a limited view that can adversely affect the success of a product (Case Study 2.4). Words and images are a factor that is always relevant in the perception of value, particularly in the case of new products that have not yet been experienced in the market (Case Study 2.5). Case Study 2.4 A leading company in the field of paints for the building industry, in response to the problems posed by new environmental regulations, decided to develop a new type of paint adapted to the new regulatory standards, without deteriorating the excellent product performance achieved previously. The new product was placed in a higher price range than traditional products, (continued)

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Case Study 2.4 (continued) which did not comply with the latest environmental regulations. The price increase provoked an adverse reaction from the customers, and many of them postponed the purchase; the new regulation was not, at the moment, binding. The company decided to better understand the problems and points of view of painting companies, through direct interviews and a focus group. They understood what was considered relevant: the weather resistance of the paint, its durability and, in particular, the drying time of the paint. The shorter the time the operator waited to “give the second coat”, the less time they had to wait, and this meant an increase in the productivity of their work (and therefore a lower cost of the interventions). This requirement could make a higher price of paint acceptable. The manufacturer then redefined the communication and presentation of the product to customers, moving away from the previous focus on “compliance with new regulations”. The new communication, which was the result of an intelligent understanding of the needs and problems of the customers, stated: “The new paint, which complies with the new rules, allows the two coats of paint to be applied in a single shift, to increase the productivity of painters significantly. The perception of value changed radically: the market reacted enthusiastically, and the company was able to be recognized for its premium price.25

Case Study 2.5 When Angelini entered the busy over-the-counter headache market, it carefully chose the product name—Moment—to evoke the product’s rapid effectiveness. Toyota entered the busy small car market (segment B) in 2000 with the highly successful Yaris model. It focused its communication on the four theorems of the little genius: “The smaller the car, the larger the interior space; given a small engine capacity, increasing power, the lower the fuel consumption; the smaller the car, the higher its safety”. These four pillars of communication derived from an analysis of the four needs usually not satisfied for those who buy a small car, generally considered as low performance, unsafe in case of an accident, with little technology on board. Toyota has communicated these factors of differentiation and value for the customer because linked to needs usually not satisfied. Communication is also crucial in the field of industrial goods. A machine tool company has designed a new, high-speed, five-axis milling machine with (continued) 25

Adapted from Anderson et al. (2006).

References

19

Case Study 2.5 (continued) features that are superior to those of the competition. It focused not only on the technical aspects but also on the area of communication and product representation, defining a name of immediate appeal (that of a well-known sports car of the past) and colouring the milling machine red, like Ferrari. The product was immediately associated with speed and innovation and captured immediate and keen interest from buyers. Until now, we have focused on the value of innovation from the perspective of the company and its customers. Innovative activities also have a much more far-reaching impact on the economy and society; the subject is of considerable concern, but it is not in the aims of this book to address the link between innovation and economic and socio-cultural progress. It is clear that innovation changes the world in which we live with very complex systemic effects: the possibility of moving around the world with ease and speed unimaginable for a man of the early ‘900, has generated enormous problems of pollution and global warming. The value for society of artificial intelligence applied in the most disparate fields (agriculture, aid to people with paraplegia, assistance in driving and reducing accidents, real-time medical diagnoses, etc.) will be enormous. Still, the extensive use and diffusion of personal data will open up pressing questions of privacy management. The innovative company has, therefore, a great responsibility: to be able to generate value for the customer, without forgetting the broader impact on society: it is a great challenge, which requires courageous strategic choices and managers capable of a long-term vision. As Coda26 pointed out, successful business formulas and models, robust and sustainable over time are characterized by an integrated and circular idea of “success”: they imply a balanced interest and attention to economic results, social results (the quality of the relationship with employees and the social impact of industrial activities) and competitive results: “Profit qualifies because it derives from a superior ability to serve the needs of the customer and feeds a superior ability to meet the expectations of all social partners, which, in turn, produces trust, dedication, cohesion and motivation, all essential elements to a superior competitive performance”.

References Anderson, J. C., Narus, J. A., & Van Rossum, W. (2006). Customer value propositions in business markets. Harvard Business Review, 91–99. Booz, Allen & Hamilton. (1982). New products management for the 1980s. Booz, Allen & Hamilton.

26

See Coda (1988).

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Christensen, C. M. (1992a). Exploring the limits of the technology S-curve. Part I: Component technologies. Production and Operations Management, 1(4), 334–357. Christensen, C. M. (1992b). Exploring the limits of the technology S-curve. Part II: Architectural technologies. Production and Operations Management, 1(4), 358–366. Christensen, C. M. (1997). The innovator’s dilemma: When new technologies cause great firms to fail. Harvard Business Review Press. Christensen, C. M., & Raynor, M. E. (2003). The innovators solution: Creating and sustaining successful growth. Harvard Business Review Press. Coda, V. (1988). L’orientamento strategico dell’impresa. UTET. Cooper, R.G. (2017). Winning at new products. Accelerating the process from idea to launch (5th ed.), Cambridge, Massachusetts: Basic books. Dell'Era, C., & Verganti, R. (2007). Strategies of innovation and imitation of product languages. Journal of Product Innovation Management, 24(6), 580–599. Dyer, J., & Bryce, D. (2015). Tesla’s high end disruption gamble. Forbes 20/8/2015. Franke, N., Von Hippel, E., & Schreier, M. (2006). Finding commercially attractive user innovations: A test of lead-user theory. Journal of Product Innovation Management, 23(4), 301–315. Hienerth, C., Von Hippel, E., & Jensen, M. B. (2014). User community vs. producer innovation development efficiency: A first empirical study. Research Policy, 43(1), 190–201. Kim, C. W., & Mauborgne, R. (2005a). Blue ocean strategy. Harvard Business Review Press. Kim, C. W., & Mauborgne, R. (2005b). Value innovation: A leap into the blue ocean. Journal of Business Strategy, 26(4), 22–28. Kim, W. C., & Mauborgne, R. (1999). Creating new market space. Harvard Business Review, 77 (1), 83–93. Lettl, C., Herstatt, C., & Gemuenden, H. G. (2006). Users’ contributions to radical innovation: Evidence from four cases in the field of medical equipment technology. R&D Management, 36 (3), 251–272. Luethje, C., Herstatt, C., & von Hippel, E. (2005). User-innovators and “local knowledge”: The case of mountain biking. Research Policy, 34, 951–965. Nagji, B., & Tuff, G. (2012). Managing your innovation portfolio. Harvard Business Review, 67–74. Pisano, G. P. (2015). You need an innovation strategy. Harvard Business Review, 93(6), 44–54. Shah, S. K., & Tripsas, M. (2007). The accidental entrepreneur: The emergent and collective process of user entrepreneurship. Strategic Entrepreneurship Journal, 1(1–2), 123–140. Urban, G. L., & Von Hippel, E. (1988). Lead user analyses for the development of new industrial products. Management Science, 34(5), 569–582. Utterback, J. M. (1994). Mastering the dynamics of innovation. Boston: Harvard Business Review Press. Utterback, J. M., & Acee, H. J. (2005). Disruptive technologies: An expanded view. International Journal of Innovation Management, 9(01), 1–17. Verganti, R. (2003). Design as brokering of languages: Innovation strategies in Italian firms. Design Management Review, 14(3), 34–42. Verganti, R. (2009). Design driven innovation. Harvard Business Review Press. Veryzer, R. W. (1998). Discontinuous innovation and the new product development process. Journal of Product Innovation Management, 15(4), 304–321. Von Hippel, E. (1994). “Sticky information” and the locus of problem solving: Implications for innovation. Management Science, 40(4), 429–439. Von Hippel, E. (1998). The Sources of Innovation. Oxford: Oxford University Press. Von Hippel, E. (2005). Democratizing innovation. MIT Press. Womack, J. P., & Jones, D. T. (1996). Lean thinking: Banish waste and create wealth in your organisation. Simon & Shuster.

3

Managing Product Innovation: A Framework

Abstract

Despite the pivotal role that product innovation plays in competitive success, few companies have developed a distinctive organizational capability in identifying, creating and exploiting innovation opportunities systematically. Why are some companies constantly more innovative than others? What capabilities need to be fostered to make innovation management effective? Innovation is not the result of sudden “illuminations”. It is natural to be in tune with this statement; in fact, we are well aware of the complexity and interdisciplinary nature of innovative activities. At the same time, however, this belief is often denied in contemporary organizational practice. Innovation processes are frequently managed without the allocation of appropriate resources and energy to exploration and exploitation activities, trusting in the sudden appearance of a brilliant idea that quickly leads to the birth of a new successful product or service. The myth of creative genius is resilient: “We believe that great ideas pop fully formed out of brilliant minds, in feats of imagination well beyond the abilities of mere mortals (Brown, Harvard Business Review, 86(6), 85–92. 2008). The exceptionality of the imaginative and visionary talents of some key people can, of course, be a valuable resource. Still, the ability to be systematically innovative is rooted in the collective intelligence within the organization, in the external network of competencies, and in the ability to connect and coordinate these fragments of knowledge. Product innovation is a complex and multidimensional phenomenon that requires the integration of skills of a different nature: skills to capture unmet manifest needs and new embryonic needs, to identify values and trends that are emerging in society and to exploit new technological opportunities and discover new business models. This chapter presents the innovation pyramid framework: it highlights the system of interdependent activities on which firms’ innovation capability is based. The three levels of the pyramid (intelligence, discovery and development)

# Springer Nature Switzerland AG 2021 S. Biazzo, R. Filippini, Product Innovation Management, Management for Professionals, https://doi.org/10.1007/978-3-030-75011-4_3

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3 Managing Product Innovation: A Framework

VE L

OP M

EN

T

Product Portfolio In the Market

DE

New Product Development

IN TE LL IG EN CE

DI

SC OV

ER Y

Supermarket of Feasible Product Ideas

Creative Ideation

Technology Development

Supermarket of Inspirations VOC Research

Foresight Research

Benchmarking Analysis

Technology Scouting

Fig. 3.1 Intelligence, discovery, development: the three innovation “factories”

metaphorically represent the three “factories” that generate, at the same time, the three output streams needed to innovate systematically: inspirations, feasible product ideas, and a portfolio of profitable products.

3.1

The Innovation Pyramid

Our innovation management framework adopts the pyramid metaphor (Fig. 3.1) to illustrate the three types of interdependent activities on which the company’s innovative capability is based: intelligence, discovery and development. • The first level of the innovation pyramid concerns all those activities aimed at absorbing knowledge from the outside: customer and society focused intelligence activities (voice of the customer research and foresight research); supplierfocused intelligence activities (competitive & cross-industry benchmarking and technology scouting). In the graphical representation of the pyramid, we wanted to visualize the intelligence efforts’ output as a supermarket of inspirations, a “shelf” which is available for the activities of the second level. • The second level refers to discovery activities (see Chap. 5), which can be divided into two broad categories: (1) activities aimed at generating new product ideas (creative ideation), e.g. the organization of Innovation Workshops involving the adoption of specific creative techniques; (2) technology development activities aimed at resolving technical knowledge gaps and introducing significant changes

3.2 Intelligence: Absorbing Information

23

in the performance and technical attributes of products. The combination of these two types of activities leads to the creation of a supermarket of feasible product ideas—preliminary concepts of potential future products that can range from clear statements about anticipated product features and benefits to early prototypes. New and feasible product ideas are the fundamental inputs to the third level of the pyramid, as they outline the objectives and the direction of product development projects. • The third level concerns all activities aimed at transforming innovation opportunities into products that can be produced and sold profitably; it is the level of product development projects (see Chaps. 6, 7, 8 and 9), aimed at updating and renewing the portfolio of products offered to the market. With the pyramid metaphor, we want to visualize the level of interdependence between development, discovery and intelligence activities. New product development effectiveness is influenced, on the one hand, by the creative ability to imagine new product ideas, unique “value propositions” for the market; and, on the other hand, by the ability to experiment and create new technologies that can significantly improve the performance and product attributes that customers perceive as essential. In the innovation management literature, there has been much debate about the origins of innovative products. The pyramid model highlights the dual-source of product development projects: product ideas to respond in a new way to the needs of customers (manifest or latent) and new technologies that enable new features and performance. Figure 3.1 illustrates, moreover, that the discovery capability (of creative ideation and technology development) is nourished and sustained by the systematic absorption of information from the outside world (the shelf of “inspirations” generated by intelligence activities). The three levels of the pyramid metaphorically represent the three “factories” that generate, simultaneously on different levels, the three output streams necessary to innovate: inspirations at the first level, novel product ideas at the second and, finally, new products at the third. In an increasingly dynamic and volatile environment,1 the sustainability of competitive advantage is deeply grounded on a constant flow of innovations; and this requires persistence and method in managing intelligence, discovery and development.

3.2

Intelligence: Absorbing Information

Intelligence activities, as shown in Fig. 3.1, can be organized into the following four categories: voice of the customer (VOC) research, foresight research, competitive & cross-industry benchmarking analysis and technology scouting.

1

It is common today to define the competitive and social situation today by the acronym VUCA, short for volatility, uncertainty, complexity and ambiguity.

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3 Managing Product Innovation: A Framework

The ability to fully capture the “voice of the customer” is essential to drive innovative efforts. VOC research activities are designed to understand and absorb two types of information: need-information and solution-information (see Chap. 4). The first type of information refers to the needs domain: needs analysis differs from conventional market research in that it is not focused on the evaluation of existing solutions or new product concepts already developed, but on the search for information on the problems that the customer must face and solve. Needs analysis is not a trivial collection of what the “customer wants”: it is a research on the “why” (the research space of the “problems” to be solved) and not on the “what” (the solution space). The identification of unmet manifest needs and latent needs is a vital source of inspiration to generate new product ideas that have some chance of success. What characterizes systematically innovative companies is their ability to identify unexpressed needs and to identify the drawbacks and obstacles that customers are used to taking for granted and that competitors often ignore.2 Case Study 3.1 An interesting example of how the analysis of customer needs represents a crucial source of inspiration for the generation of new product ideas is the case of the product chotuKool (“little cold”)—winner of an Edison Awards Gold Prize.3 Godrey & Boynce—India’s leading appliance manufacturer—in an effort to win over “non-consumers” (who account for more than 80% of the population) analysed how rural people bought, prepared and stored food and beverages; interviewing, observing and interacting with people, they found that the fundamental problem to be solved was to keep milk, vegetables and leftovers fresh for a day or two, both at home and away from home. These categories of “consumers” did not need a standard, low-cost refrigerator at all, as the research team had initially suggested. From a detailed analysis of the needs underlying the problem of storing food for a short time, the idea of chotuKool emerged: a portable refrigerator (30 litres per 7.2 kg) that does not use the traditional compressor, but a thermoelectric chip that keeps it cool with an external battery or a 12-volt direct current; positioned at a price equal to half that of a standard entry-level refrigerator, chotuKool represented the birth of a new product category. In case study 3.1, we focused on needs that can be defined as functional, which concern the practical execution of an activity or a job. As we pointed out in Chap. 2, functional needs are only a component of the spectrum of customer needs. In many markets, emotional needs are of primary importance, whether they are related to the aesthetic dimension or the symbolic meaning of the product. 2 3

See Hamel (2012). The case is summarised in Markides (2012); see also Wooldridge (2010).

3.2 Intelligence: Absorbing Information

25

Going back to the case of the portable refrigerator in India, it is interesting to note that chotuKool was designed with the colour red, in stark contrast to the colour typically associated with cold—blue or white. This choice is linked to the fact that red is, in India, the colour symbolically associated with luck; and one of the unexpressed needs, but identified by the research team, was the desire to express a “lucky” status in owning the first household appliance. Some types of customers can also be a valuable source of solution-information;4 as we will see in Chap. 4, the so-called Lead Users can play a leading role in product innovation by suggesting, or developing autonomously, even if in prototype form, original and relevant technical answers to problems still poorly solved (user innovation). The second category of intelligence activities is foresight research5—all those initiatives that aim to image the future by analysing today’s strong and weak signals of change. Foresight research includes consumer trend analysis, megatrend analysis and scenario building. Consumer trend intelligence focuses on the evolution of consumer-user behaviour, values, beliefs and expectations across various sectors and markets, which are shaped by macro changes that take place over the years or even decades. It is important to point out that here we will use the word “trend” not only to highlight transformations that are clear and potentially known to all, but above all to refer to emerging trends, linked to weak signals6—the first, but incomplete, indications of a change. Spotting trends is a complex task as it is necessary to observe changes in consumer behaviour from a multisectoral perspective; this requires significant investment in research, sociological skills and the ability to creatively synthesize field observations. It is therefore critical for companies, especially small ones, to develop connections and strong relationships with those consulting firms specializing in trend research. In this perspective, it is interesting to note that there are now many consumer trend analysis companies operating online and with low-cost positioning strategies, which are extremely interesting for small and medium enterprises (for example, Trendwatching.com). Consumer trends represent a formidable source of inspiration for discovery activities as they can foster potentially disruptive creative processes based on the connection of ideas born in (apparently) distant worlds; trend analysis allows to have a vision of the evolution of customer expectations that goes beyond a specific industry or region and, therefore, can provide stimulating and original insights. An example of a consumer trend identified by Trendwatching.com is the constant 4

Von Hippel (1994, 1998); Ogawa and Piller (2006). As Schweitzer et al. (2019) highlight, foresight research “can support organizations in anticipating what might drive the industry and consumers in the next decades”. See also Rohrbeck et al. (2015). 6 Mendonça et al. (2004) provide the following definition of weak signals: “the early signs of possible but not confirmed changes that may later become more significant indicators of critical forces for development, threats, business and technical innovation. They represent the first signs of paradigm shifts, or future trends, drivers or discontinuities”. 5

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growth of “pre-tail”: consumers want to be more and more involved in the pre-launch of products and services, not only with the pre-purchase options of a new product but also with the possibility of having a relationship with the company and with the people who will realize the product (for example, through crowdfunding platforms, created to raise funds from huge groups that want to support an innovative idea). Another interesting example is the “upgrade” trend: the expectation of a rapid and constant updating and improvement of products, native to the digital world, is spreading significantly in the world of tangible products (think, for example, of the case of Tesla, which is now able to “update” online several performance). While consumer trend analysis is focused on consumer behaviours and attitudes, megatrend research broadens the observation horizon, aiming to grasp society’s evolutionary dynamics from a political, economic, environmental, social, technological point of view—the so-called PEEST or STEEP analysis. Megatrends represent significant changes in the global competitive environment with potentially major impacts on society and business. Malnight and Keys at Global Trends, for example, have identified ten global trends, some of which we believe are of particular interest: • Social everything: the increasingly dominant and pervasive role of social technologies in everyday life; a role that will also have a significant impact on the organizational structures and processes of companies; • Redefining value: the notion of value is being redefined; consumers are looking for more and more product customization and participation in value creation (“cocreation”). • Distributed everything: the tools to create and capture value will be increasingly distributed; think, for example, of the evolution of 3D printing or the change in educational systems with the increasing diffusion of distance learning platforms; • From profit to purpose: many companies are “reinventing” their role to be able to face the economic and social challenges of the future; companies must seek legitimacy and credibility in the eyes of consumers, employees and stakeholders and redefine their mission in the perspective of “responsible capitalism7”. Megatrend and consumer trend analysis form the basis for scenario building, i.e. a method for describing complex and consistent visions of plausible possible futures8 to identify threats, recognize opportunities and inspire discovery activities. Competitor’s product comparative analysis belongs to the third category of intelligence activities—benchmarking. Great ideas can also originate from “innovative imitation” efforts—to use Levitt’s evocative expression, a renowned Harvard marketing professor.9

7

Mackey and Sisodia (2013). See Martelli (2014) and Webb (2016, 2017). 9 See Levitt (1986). 8

3.2 Intelligence: Absorbing Information

27

It is important to point out that the notion of competitors is used here in a broad sense. The importance of alternative sectors as a source of inspiration in innovation processes has been well highlighted by Kim and Mauborgne in the book Blue Ocean Strategy; they state that one of the obstacles in identifying new opportunities for innovation is to accept the conventional boundaries of one’s sector. Alternative products are those that offer the same functions, but in different forms: for example, electronic agendas versus paper agendas; financial software versus the frugal alternative of pen and paper or the accountant. In some cases, there may be alternative products or services that have both different functions and forms, but share the same purpose: for example, restaurants and cinemas, alternatives that can be implicitly compared in the selection of the product to be recruited to “spend a nice evening out”. The analysis of critical success factors in alternative sectors and the monitoring of their evolution can offer essential stimuli in the creative processes of generating new product ideas or new business models: which are the alternative sectors to ours? Why do customers prefer and switch to the alternative industry? We can move beyond the idea of alternative products with cross-industry benchmarking, where the focus is the search for analogies between distant sectors in the “problems to be solved” (for example, automotive “fleet management” versus building tools “fleet management”) to creatively imitate and adapt already existing solutions to the needs of the company’s current market or products.10 The fourth category of intelligence activities is technology scouting: the systematic absorption of knowledge on scientific research and technology developments in specific fields of interest considered relevant and critical for the company’s future.11 Scouting activities can be based on three sources of information: the “visible” web, the “invisible” web12 and personal networks. The visible web represents everything that can be captured by search engines such as Google or Bing; the term “invisible” refers to information not freely accessible contained in professional databases. In the field of technology scouting, the “invisible” web is a remarkably relevant source of information, and the use of professional databases (such as, for example, Derwent Innovation by Clarivate Analytics in the field of intellectual property) is, in fact, indispensable. The advantages of using such databases are manifold: the regularly updated and controlled data sources (patent data, scientific literature, economic journals) and the availability of advanced data mining and semantic analysis tools greatly facilitate the transformation of information into usable knowledge. An effective technology scouting system should be able to identify technologies that have the potential to revolutionize or disrupt an industry sufficiently in advance to allow the company to take advantage of the opportunity or react quickly to threats. However, there are not many companies that have the internal resources to manage

10

See Enkel and Gassmann (2010). Rohrbeck (2010). 12 Sherman and Price (2001). 11

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such activities in total autonomy; in this perspective, it is imperative to activate and develop relationships with the so-called technology brokers (Case Study 3.2). Case Study 3.2 CRIT is a company specialized in technology scouting and collaborative innovation. It was founded in 2000 on the initiative of 14 leading companies from Emilia-Romagna, including Ferrari, Datalogic and Tetra Pak; today there are 27 members. CRIT divides the technological scouting activity into six different types.13 State of the Art—It is a targeted service of research and analysis of technical and scientific documentation concerning a particular technology of interest to the company. Technological Problem-Solving—Search for ready-to-use solutions to be used in products and manufacturing processes or identification of a possible range of technological alternatives to be tested to solve a tricky technical problem. Supplie/Competence Search—Search for technological partners and detailed analysis of their products and related expertise. Patent Analysis - Analysis of patents aimed at understanding the technological positioning of one or more competitors, key players and technology trends. Technology Foresight—Analysis of technical and scientific documentation to assess the evolution of innovative or emerging technologies. Quick Search—Analysis of technical and scientific information aimed at producing, in a short time, an essential report containing a collection of selected documents from specialized databases and some summary data.

3.3

Discovery: Exploring Opportunities for Innovation

The discovery space is characterized by two fundamental directions of exploration— creative ideation and technology development—whose combination can lead to novel and feasible product ideas. In the matrix of Fig. 3.2, we have highlighted four different approaches to creative ideation, distinguished by two dimensions: (1) interaction and (2) competition between the participants (the “problem-solvers”) involved in creative ideation sessions and processes. At the bottom left, we find the default mode of the ideation approach that characterize many companies, called “idea fishing” to highlight its passive and reactive nature. In this approach, product ideas are merely collected. Creative

13

See www.crit-research.it.

3.3 Discovery: Exploring Opportunities for Innovation

High

Innovation Contest

29

Hackathon

Level of COMPETITION between problem-solvers

Low

Innovation Workshop

Idea Fishing

Low

Level of INTERACTION between problem-solvers

High

Fig. 3.2 Creative ideation: four approaches

ideation is a responsibility delegated to individuals in the context of their role (and, therefore, a responsibility more or less felt in relation to the organizational function to which they belong), and the company’s problem is to build the appropriate communication channels to “capture” such ideas. The level of interaction is, typically, low: the creative ideation takes place in the fabric of daily activities and there are no specific events and processes (such as the Innovation Workshops that we will describe shortly) focused on the proactive generation of new product ideas. The exclusive focus of creative ideation on individual skills and initiative has strong limits today. In order to face competitive environments with increasingly accelerated rates of innovation, it is necessary to strengthen the company’s creative capability. Hamel (2009) argues that the creative potential of any company is extremely high, but is often blocked by the absence of “internal markets of ideas”, where innovators and investors (top managers) can meet efficiently and unfettered by hierarchical constraints determined by the organizational structure. The growing need to give cadence to the generation of new product ideas is revealed in the emergence of complementary approaches to idea fishing. Figure 3.2 shows two orthogonal paths to strengthen the creative capability of a company: the first path (innovation workshop) is focused on collaborative processes and strong interactions between a limited number of people; the second path (innovation contest) is, instead, focused on the organization of idea generation competitions;

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hackathons combine the characteristics of the two previous approaches. Collectively, these creative approaches can be described as “idea hunting”, to metaphorically contrast “hunting” with “fishing”. Advocating the necessity to enhance creative ideation does not mean denying the role of serendipity and randomness in the development of successful products; on the contrary, the organization of idea hunting events is just a way to embrace serendipity and randomness actively. As Pasteur said, “chance favours only the prepared mind”; more precisely, chance favours only the company that invests in creating a fertile ecosystem that promotes experimentation and exploration of unknown territories. An innovation workshop is an initiative in which a selected group of people, through a well-defined process and the use of specific methodologies, is engaged in the collaborative generation of new product ideas. Although there are many formats and creative techniques that can be used in the design of such initiatives (see Chap. 5), there is a fundamental and common element: the creation of a frictionless learning environment that allows participants to express their imaginative potential to the full; an environment characterized by a climate of creative freedom, to favour the formulation of any idea, however, unusual or extravagant it may be. It is interesting to note that the characteristics of such an interaction context are consistent with many recent studies on the relationship between organizational culture and innovation. Rao and Weintraub,14 for example, point out that innovative environments are characterized by some peculiar values: the tolerance of ambiguity, the orientation towards experimentation, the assumption that “errors” (experiments that do not lead to the hoped-for results) are necessary for creative paths and therefore must be accepted as an inevitable consequence of exploration. Through Innovation Workshops we try to proactively generate new ideas using the creative efforts of a selected group of people, both inside and outside the company; obviously, this approach is appropriate when the knowledge domains from which the most intriguing and valuable ideas are supposed to emerge are easily identifiable. With Innovation Contests there is a radical change of approach: it is assumed that the origin of the best ideas cannot be known a priori; therefore, it is not possible to choose the participants ex-ante. An innovation contest (or “tournament15”) is a process of predefined duration that starts with the definition of a creative challenge that is launched to a “crowd” of problem-solvers. The size and heterogeneity of the crowd is an essential success factor: the more numerous and varied the problemsolver pool, the more likely it is that unexpected proposals with innovative prospects of solving the proposed problem will be obtained. The participants who decide to accept the challenge compete with each other, and the contest ends with the selection

14

Rao and Weintraub (2013). Innovation contests were discussed with reference to the generation of new product ideas; the logic of the tournament can also be used for technological and scientific challenges that require prototyping activities. As we will see in Chap. 4, crowdsourcing is also an innovative way of outsourcing technological development activities.

15

3.3 Discovery: Exploring Opportunities for Innovation

31

of the winning proposals. Participation in the competition can be reserved to internal staff or open to everyone; this second option has taken on considerable importance in recent years and has given rise to the phenomenon of crowdsourcing (see Chap. 5). Hackathon is a combination of the two previous categories. The word hackathon is a shortening of “hacking marathon”: a time-boxed event where small groups compete with each other. Hackathons were born in the context of software development in the late 1990s and, in this context, an intense prototyping activity typically characterizes them: ideas must be concretized in working programs and algorithms. Over the years, the format has widely spread beyond the boundaries of programming (Case Study 3.3). Case Study 3.3 H-FARM was born in 2005 as a start-up accelerator; today it is a company with a dual mission: to help young people in the creation of new business models and to support the digital transformation of companies (h-farm.com). H-ACK is the hackathon format designed by H-FARM for businesses. It is organized as a 24-hour marathon where the sponsor company launches a creative challenge to a set of pre-selected teams of “h-ackers”. For example, Luxottica’s most recent H-ACK focused on designing the “shop of the future”, to innovate sales processes, rethink the role of the physical object and redesign innovative shopping experiences. Each team is built with the logic of reproducing a small start-up, with a mix of multidisciplinary skills. After 24 h, each team presents its project (with the archetypal 3-minute elevator pitch), and then the winner is selected. H-ACK has been used in recent years by more than 60 companies, among them: Luxottica, Merck, Technogym, Autogrill, BT Italia, Heineken, Kiko, Leroy Merlin. The second direction of exploration is technology development, as new product ideas may require the resolution of knowledge gaps through research and experimentation to ensure feasibility; the capability to quickly and effectively integrate new technologies (new materials or new components and subsystems) into new-generation products can, in certain circumstances, be a powerful competitive weapon. It is widely recognized16 that this integration capability is highly dependent on the level of organizational decoupling between technology development and product development that the company has been able to achieve. There are three primary reasons for this decoupling:

16 On the issue of decoupling between technology development and product development see Chiesa (2001), Chiesa and Frattini (2007), Chiesa et al. (2009).

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• technology development requires suitable organizational approaches and management styles as the problems to be addressed are of a more uncertain and fuzzy nature and require a high rate of experimentation and trial & error iterations; • the need to compress new product development lead time demands the reduction of the complexity and uncertainty of such projects by minimizing the technological exploration within them; • the growing demand for product reliability and quality is more easily achievable with well-tested and consolidated technologies; a still immature technology makes product engineering and design for manufacturing extraordinary difficult and challenging. Decoupling can be structural (creation of ad hoc organizational units focused on level 2 of the pyramid) or operational (creation of ad hoc processes and clear separation in the project portfolio between product development projects and technology exploration; see Chaps. 5 and 6). In smaller companies the structural separation of technological exploration is an exception. A compelling case in this regard is that of Eurotech, a leading company in the field of miniaturized and high-performance computers and the Internet of Things. Eurotech’s organizational structure includes a research centre focused on technological exploration (ETH-Lab) and an organizational unit dedicated to intelligence activities (Foresight Unit). Another relevant case is that of Unox, a company that designs and manufactures professional ovens and cooking systems (see the case study in Chap. 9). The strong orientation towards innovation and systematic product improvement has led the company to significantly invest in its innovative capability with two distinct organizational units: the Research function (with skills in physics, chemistry, firmware and mechanical engineering), which deals with technology development and research on cooking processes; and the Design & Industrial Engineering function (with skills in mechanical and electrical engineering, industrial design and process engineering), focused on product development projects. The problem that often arises for small businesses is the difficulty—and in some cases, the impossibility linked to the limited scale of operations—of investing resources in activities focused on technological exploration. In these contexts there are two alternatives: • incorporate experimentation into ordinary design activities, accepting the risks this entails in terms of management complexity, increased technical uncertainty and the likelihood of lengthening product development times; • establish strong technology partnerships with external actors as research institutions or universities, embracing the logic of Open Innovation. The opening up of technology development activities to the outside world— essential for small businesses—is, however, a general trend that is independent of the size of the company. The phenomenon of Open Innovation is linked to the fallacy of the Closed Innovation paradigm in the current competitive context: in a world where knowledge is abundant and distributed, it is increasingly evident that it is no

3.3 Discovery: Exploring Opportunities for Innovation

33

longer possible—not even for the largest multinationals—to innovate relying exclusively on their internal research forces. An innovation model uniquely based on internal research reflects the paradigm of vertical integration, control and isolationism, which reduces opportunities for innovation in our hyper-connected and rapidly changing world. Noteworthy is the well-known case of Procter & Gamble which, for some time now, has enhanced the central research and development function (www.pgscience. com) with the creation of an external knowledge network called Connect & Develop: an IT platform has been set up to share technological updates with the leading suppliers; a network of “technology entrepreneurs”, located all over the world, has been created to identify new products, ideas or technologies; “innovation markets”—such as NineSigma and Yet2.com (see Chap. 5 on the practice of technology crowdsourcing)—are regularly used to get in touch with anyone with exciting ideas/technologies, wherever they are.17 In technology development activities, systematic collaboration with universities and research centres plays an important role as a means of access to a considerable stock of talent and skills. However working with universities poses significant challenges: firstly, the nature of academic activities has to deal with the intellectual property protection requirements of companies; secondly, while academic research tends to be oriented towards medium and long-term major challenges, industrial research is more focused on medium or short-term technical problem-solving projects. There are different ways of interacting between companies and universities to turn different orientations and perspectives into an advantage:18 (a) the “ideas laboratory”, where companies work with universities on small-scale “exploration” projects, leaving open the option of publishing the results and at the same time securing a non-exclusive licence to use the results; (b) the “big challenges” with medium and long-term projects aimed at creating new knowledge; (c) the “commercial collaborations” of applied research where the results are not disseminated, and there are precise confidentiality agreements in which the universities are involved to solve problems that require highly specialized resources and different problemsolving perspectives that can, therefore, significantly expand the stock of expertise of the company. Another important source of technical knowledge comes from suppliers, even those belonging to production chains far from the business in which the company operates: very often there are great opportunities if you can encourage the transfer of innovative solutions between even significantly different sectors. An interesting example in this regard is the case of Pompea,19 which introduced a radical technological innovation in 2000—seamless underwear—with the substantial contribution of sock machine suppliers, adapting the technology and materials used in another

17

Huston and Sakkab (2006). Perkmann and Salter (2012). 19 See Verganti et al. (2004). 18

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sector to the underwear sector. Cooperation with suppliers is, therefore, a valuable practice to strengthen your exploration capacity; suppliers represent a sort of “technological spy” that allows organizations to access new skills and new information. The kind of technology collaborations we have discussed so far is based on partners selected ex-ante according to their skills. Today, through the mechanisms of crowdsourcing it is possible to collaborate also with a very high number of subjects that are not selected ex-ante, but ex-post according to the quality of the solutions offered to meet the challenge launched by the company; the underlying logic of crowdsourcing will be further discussed in Chap. 5.

3.4

Development: Bringing New Products to the Market

The objective of the third level of the innovation pyramid is to renew the product portfolio in the market; it is the organizational space of new product development— the set of activities that transform feasible product ideas into profitable products.20 Three fundamental problems need to be addressed in new product development: 1. a process management problem (see Chaps. 6 and 7): what are the standards that all product development projects must meet? Although each development project is unique, it is necessary to define a product development process that incorporates the best knowledge available in the company—in terms of tools, methods and progression of activities—on how to transform ideas into profitable products; 2. a project management problem (see Chap. 8): which organizational structure is adopted and which planning and control methodologies are used to manage the execution of product development projects? These choices determine how people work together and collaborate in carrying out a specific project effort; 3. a portfolio management problem (Chap. 9): How and by what criteria is the portfolio of product development projects managed? Development portfolio choices determine the allocation of resources and the mix of opportunities that the company intends to pursue.

Process Management In order to effectively manage new product development activities, it is necessary to define a product development process. A product development process standardizes how a company brings a new product to the market, and (if carefully and adequately

20

Ward and Sobek (2014) emphasize that product development produces operational value streams: “Operational value streams run from suppliers through factories, into product features, and out to customers. They don’t exist until development processes create them. Drawings, analysis, and tests have value if they create quality operational value streams”.

3.4 Development: Bringing New Products to the Market

35

designed) represents an essential stock of managerial knowledge—the codification of the “best practices” that the company has developed over time. The definition of a product development process is important for three fundamental reasons. First, for a quality issue: if the process has been carefully designed, adopting “good practice” standards in the execution of the activities is a way to ensure the quality of the final result. Second, a process standard is an essential resource for project planning and control. Finally, the definition of a set of standards is necessary for continuous improvement, as is well highlighted in the literature and practice of Lean Management. The standardization of the product development process defines the “rules of the game” to which individual development projects must comply. These rules relate to two fundamental issues (see Chap. 6): • the strategic problem of risk and uncertainty reduction; • the organizational problem of cross-functional integration in the formulation of key design decisions.

Project Management The project management problem concerns the definition of the project organizational structure and the adoption of planning and control methodologies. As we will see in Chap. 8, the role of the project manager is a critical variable in the success of product development projects: regardless of the specific configurations of responsibilities and authority that this role can assume, the project manager is the focus of most of the considerable tensions generated by the search for the inevitable trade-offs between often conflicting needs of functional specialists. Regarding the way development projects are planned and controlled, we can identify two contrasting paradigms: the rational paradigm, based on the classic corpus of Project Management knowledge and characterized by the underlying assumption that it is possible to centrally plan the entire project in detail before its execution (“heavy” upfront planning); and the relational paradigm, focused on a decentralized and iterative approach to planning and control (“light” upfront planning). The application of classic Project Management methodologies in the context of new product development has significant limitations; relational approaches, such as Agile methodologies in the field of software development and Visual Planning in the field of physical products, represent a response to these limitations.

Portfolio Management Managing the development portfolio is a dynamic decision-making process through which a list of product innovation projects is regularly reviewed and updated.

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3 Managing Product Innovation: A Framework

Through this process, new projects are evaluated, selected and finally prioritized, and available resources can be allocated or reallocated between active projects.21 Development portfolio management is a crucial activity that aims to address two key issues (see Chap. 9): • the lack of discrimination and prioritization between projects, which leads to the problem of resource overload; • the lack of balance between short- and long-term orientation: without a strategic vision and an explicit project portfolio management, short-term tactical choices typically prevail, and projects with a more immediate and less uncertain financial impact are inevitably favoured.

3.5

Managing Product Innovation: A Challenge Between Continuity and Discontinuity

Unquestionably, we are living in “exponential times”, in a world characterized by an accelerated and non-linear change;22 it is hard to find today a sector characterized by long periods of stability, where “doing better what has always been done” can be considered sufficient to face competition and to sustain growth and success. Exponential change bewilders those companies that are unable to capture weak signals and trends in markets and technologies;23 it requires non-linear responses: discontinuous innovation, however, risky and complex, must be present (albeit in a minority proportion) in the company’s project portfolio. To capture the weak signals and to be able to generate discontinuous innovation, companies must necessarily enhance its intelligence and discovery capabilities—the first and second levels of the innovation pyramid: • intelligence capability to amplify peripheral vision24 (being able to see beyond the familiar territories of your industry, your technologies and your customers); • discovery capability to identify the best opportunities for developing new products and new business models well in advance (see Chap. 10). Discontinuous innovations are inherently risky and complex and, therefore, can only represent a small percentage of the company’s investment portfolio.25 This form of innovation must be intertwined with a constant flow of incremental innovations and systematic improvements to the Value Proposition (see Chap. 7);

21

See Cooper et al. (1999, 2001). See the introductory chapter of the book by De Toni et al. (2015). 23 De Toni et al. (2015); on the concept of trend and weak signal see Saritas and Smith (2011). 24 Schoemaker et al. (2013); Haeckel (2004). 25 Nagji and Tuff (2012) state that, on average, performing companies allocate about 70% of their investments to incremental innovation activities. 22

3.5 Managing Product Innovation: A Challenge Between Continuity and Discontinuity

37

a flow characterized by “continuity”, but which is equally essential for the sustainability of earnings and competitive results. Managing innovation is a matter of balancing continuity and discontinuity, between the pursuit of profitability in the short term and the ability to anticipate non-linear changes and sustain success in the long term: • discontinuous innovation requires peripheral vision in intelligence activities; continuous innovation requires a focus on current customers and a careful monitoring of direct competitors; • discontinuous innovation is rooted in creative conception and technological experimentation; continuous innovation is rooted in the speed of development processes for new versions and new variants of existing products; • discontinuous innovation requires product development processes that are suitable to cope with high levels of uncertainty and risk (the concept of flexibility; see Chap. 6); incremental innovation requires processes focused on speed.26 It is not easy to combine organizational routines that aim at divergent objectives (the so-called ambidexterity27): on the one hand, the exploration of opportunities to renew one’s offer; on the other hand, the systematic and progressive improvement of existing products (exploitation). The challenge of ambidexterity is particularly demanding for small companies which, in general, are not large enough to create complex organizational structures with different units specialized in the different activities that make up the three levels of the innovation pyramid. Managing innovation is an extraordinarily difficult challenge. Innovation performance depends on the ability to manage and organize a complex network of different interdependent activities. Managers often ask us what “rules” must be followed to innovate products successfully;28 the next chapters will aim to offer an overview of the organizational approaches and management tools that make up the core “ingredients” of innovation management. But these ingredients do not and cannot determine pre-packaged recipes or formulas; methodologies and tools must be

26

See MacCormack et al. (2012). See O’Reilly and Tushman (2008). 28 Mangelsdorf and Posner have selected the most relevant articles published in recent decades in the MIT Sloan Management Review to highlight several key insights. We recall some of them: 27

• innovation is the search for “new value” and not merely “technological progress”; • discontinuous innovation can be generated not only by radical changes in technology but also by changes in business models; • product development processes in situations of high uncertainty must be managed as a series of “learning loops”; • innovation requires openness, variety and experimentation; • customers, and in particular users, can be crucial allies in the innovation challenge. These issues will be discussed in more detail in the following chapters.

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adapted, tested and modified according to the specific organizational situation, product typologies and the peculiarities of the competitive context.

References Chiesa, V. (2001). R&D strategy and organization. Managing technical change in dynamic contexts. Imperial College Press. Chiesa, V., & Frattini, F. (2007). Exploring the differences in performance measurement between research and development: Evidence from a multiple case study. R&D Management, 37(4), 283–301. Chiesa, V., Frattini, F., Lazzarotti, V., & Manzini, R. (2009). Performance measurement of research and development activities. European Journal of Innovation Management, 12(1), 25–61. Cooper, R. G., Edgett, S. J., & Kleinschmidt, E. J. (1999). New product portfolio management: Practices and performance. Journal of Product Innovation Management, 16(4), 333–351. Cooper, R. G., Edgett, S. J., & Kleinschmidt, E. J. (2001). Portfolio management for new products. Basic Books. De Toni, A., Siagri, R., & Battistella, C. (2015). Anticipare il futuro: Corporate Foresight. Egea. Enkel, E., & Gassmann, O. (2010). Creative imitation: Exploring the case of cross-industry innovation. R&D Management, 40(3), 256–270. Haeckel, S. H. (2004). Peripheral vision: Sensing and acting on weak signals: Making meaning out of apparent noise: The need for a new managerial framework. Long Range Planning, 37(2), 181–189. Hamel, G. (2009). Moonshots for management. Harvard Business Review, 87(2), 91–98. Hamel, G. (2012). What matters now: How to win in a world of relentless change, ferocious competition, and unstoppable innovation. Jossey-Bass. Huston, L., & Sakkab, N. (2006). Connect and develop. Harvard Business Review, 84(3), 58–66. Levitt, T. (1986). The marketing imagination. Simon & Schuster. MacCormack, A., Crandall, W., Henderson, P., & Toft, P. (2012). Do you need a new productdevelopment strategy? Research-Technology Management, 55(1), 34–43. Mackey, J., & Sisodia, R. (2013). Conscious capitalism. Harvard Business Review Press. Markides, C. C. (2012). How disruptive will innovations from emerging markets be? MIT Sloan Management Review, 54(1), 23. Martelli, A. (2014). Models of scenario building and planning: Facing uncertainty and complexity. Palgrave Macmillan. Mendonça, S., Cunha, M. P., Kaivo-oja, J., & Ruff, F. (2004). Wild cards, weak signals and organisational improvisation. Futures, 36(2), 201–218. Nagji, B., & Tuff, G. (2012). Managing your innovation portfolio. Harvard Business Review, 67–74. O’Reilly, C. A., III, & Tushman, M. L. (2008). Ambidexterity as a dynamic capability: Resolving the innovator’s dilemma. Research in Organizational Behavior, 28, 185–206. Ogawa, S., & Piller, F. T. (2006). Reducing the risks of new product development. MIT Sloan Management Review, 47(2), 65–70. Perkmann, M., & Salter, A. (2012). How to create productive partnerships with universities. MIT Sloan Management Review, 53(4), 79–105. Rao, J., & Weintraub, J. (2013). How innovative is your company’s culture? MIT Sloan Management Review, 54(3), 29–37. Rohrbeck, R. (2010). Harnessing a network of experts for competitive advantage: Technology scouting in the ICT industry. R&D Management, 40(2), 169–180. Rohrbeck, R., Battistella, C., & Huizingh, E. (2015). Corporate foresight: An emerging field with a rich tradition. Technological Forecasting and Social Change, 101, 1–9.

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Saritas, O., & Smith, J. E. (2011). The big picture–trends, drivers, wild cards, discontinuities and weak signals. Futures, 43(3), 292–312. Schoemaker, P. J., Day, G. S., & Snyder, S. A. (2013). Integrating organizational networks, weak signals, strategic radars and scenario planning. Technological Forecasting and Social Change, 80(4), 815–824. Schweitzer, N., Hofmann, R., & Meinheit, A. (2019). Strategic customer foresight: From research to strategic decision-making using the example of highly automated vehicles. Technological Forecasting and Social Change, 144, 49–65. Sherman, C., & Price, G. (2001). The invisible web: Uncovering information sources search engines can’t see. Information Today. Verganti, R., Calderini, M., Garrone, P., & Palmieri, S. (2004). L'impresa dell'innovazione - La gestione strategica della tecnologia nelle PMI. Edizioni Il Sole 24. Von Hippel, E. (1994). “Sticky information” and the locus of problem solving: Implications for innovation. Management Science, 40(4), 429–439. Von Hippel, E. (1998). The sources of innovation. Oxford University Press. Ward, A. C., & Sobek, D. K., II. (2014). Lean product and process development. Lean Enterprise Institute. Webb, A. (2016). The signals are talking: why Today’s fringe is tomorrow’s mainstream. PublicAffairs. Webb, A. (2017). The flare and focus of successful futurists. MIT Sloan Management Review, 58 (4), 55–58. Wooldridge, A. (2010). The world turned upside down. The Economist, 15 Aprile.

4

Intelligence: Uncovering Innovation Opportunities Through Customer Involvement

Abstract

Successful products are loved by customers and in synch with their needs and wishes. Harmony between product and customer can be pursued by developing appropriate knowledge about their conscious and latent expectations. The ability to skilfully capture the “voice of the customer” (VOC) is fundamental to direct innovative efforts and to identify valuable and attractive solutions. VOC research is a primary source of opportunities for innovation. Nowadays it is widely acknowledged that a company cannot innovate on its own. The term open innovation is frequently used to characterize a system in which innovation comes from extensive collaboration with external actors: customers should play a key role in firms’ networking efforts, given their decisive impact on the processes of adoption and diffusion of new products. Companies must, therefore, build a deep relationship with customers to be able to innovate in the right direction its value proposition. It should be noted, however, that some customers may represent an element of inertia towards radical innovations. As we shall see in this chapter, it is critical to recognize the variety of voices and types of customers and the diversity of their contributions to innovative processes.

4.1

Customers’ Voices: Need-Information and Solution-Information

VOC research can capture two major categories of information:1 (1) Need-information: products are “instruments” to solve “problems”, carry out activities and achieve objectives. Needs reveal the motivations for which 1

Von Hippel (1994).

# Springer Nature Switzerland AG 2021 S. Biazzo, R. Filippini, Product Innovation Management, Management for Professionals, https://doi.org/10.1007/978-3-030-75011-4_4

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products and services are “recruited”: needs analysis is not a collection of what the customer wants in terms of desired solutions; it is thorough research on the deep motivations for hiring products and services.2 However, it is not uncommon to come across in managerial practices that distort the concept of need and trivialize VOC research activities. Needs analysis explores the complex domain of why customers choose specific solutions to solve their “problems” (the how); therefore, it is necessary to “move away” from the products and focus on the activities that customers have to perform or the experiences they desire to live. Needs are hidden in the context of actions and experiences; as Sawhney and colleagues aptly point out, “customers seek particular outcomes, and they engage in activities to achieve them3”. Utilitarian needs refer to the practical outcomes or benefits that customers desire when performing an activity: for example, the reduction of the perceived noise and rustling while riding a motorcycle on the motorway; or the minimization of the amount of vibration that is felt in the hand when operating a chainsaw.4 Hedonic needs refer to the feelings and emotions that customers love to sense;5 for example, the playfulness of making tea with the iconic Alessi kettle with a bird-shaped whistle: “when the water starts boiling, the bird sings. . .leading to an inevitable smile6”. (2) Solution-information: new product ideas, proposals to modify existing products and services or even new solutions already implemented by expert customers in response to unmet needs. In VOC research, the customer is any subject who interacts with the product and experiences specific needs; in this perspective, we can identify three types of customers: 1. the end-users of the product: individual consumers in Business-to-Consumer (B2C) and firms in Business-to-Business (B2B) sectors; 2. the actors involved in the purchasing and distribution process: buyers, dealers and purchasing decisions influencers (architects, for example, in the furniture sector); 3. the other actors involved in the product life cycle (installers, maintainers, etc.). The customer is not, therefore, a single subject and the influence of the various types of actors varies according to the industrial context and product category. VOC See Christensen et al. (2007): “When customers find that they need to get a job done, they ‘hire’ products or services to do the job. This means that marketers need to understand the jobs that arise in customers’ lives for which their products might be hired”. 3 Sawhney et al. (2003). 4 Needs analysis with a focus on the “jobs-to-be-done” was developed by Christensen & Ulwick; see Ulwick (2005, 2016); Ulwick and Bettencourt (2008); Christensen and Raynor (2003); Christensen et al. (2007); Christensen, Dillon, et al. (2016). 5 As regards the distinction between hedonic and utilitarian benefits, see Chitturi et al. (2008). 6 See www.alessi.com: Kettle 9093 designed by Michael Graves. 2

4.1 Customers’ Voices: Need-Information and Solution-Information

43

is, in reality, a polyphonic chorus of voices that provides a complex set of information on needs or possible solutions that refer to several activities performed by one or multiple actors—the customer-activity cycle:7 purchasing, installing, learning to use, using, maintaining, repairing, upgrading and so on. However, there is no doubt that the end-user and user activities should, in general, deserve privileged attention; if the product does not satisfy the user, it is useless to accurately capture the needs of the other actors involved in the customer-activity cycle. End-users can be classified into the following categories: (1) Ordinary users: are all those who use consumer products (food, clothing), durable consumer products (cars, furniture) or industrial products without having specific professional or technical skills. (2) Demanding users: are those who for professional reasons (for example, surgeons, software designers) or hobby (kayakers, mountain bikers) use the product frequently and are very demanding in performance. They are competent in the “problems” that the product has to solve and sophisticated in product usage. In the industrial field (B2B) they are, for example, companies that purchase components or subsystems that are particularly critical for their final product. Demanding users also include users who operate under extreme conditions (extreme users), with a product usage at the performance frontier or under particularly severe environmental conditions (e.g. automatic gate users and installers in Nordic countries). Demanding users may include users who, in addition to being professionally competent in the use of the product, also have technical skills (for example, on architectural solutions or materials); these skills may be more or less sophisticated and hard to develop depending on the technological complexity of the product. (3) Innovative users: they have extensive user experience and technical expertise on the product. They are extremely demanding and, since they are dissatisfied with the status quo, they create and test new solutions to meet their needs better. (4) Lead users8 constitute a peculiar category of innovative users (see Sect. 3.3): users who not only innovate personally, but who are also at the forefront of a significant market trend and, therefore, express in advance needs that in the future will become widespread in the market (emerging needs); the probability that their innovations are commercially attractive is, therefore, high. A lead user could be a consumer or a firm that, for example, purchase a piece of industrial machinery and then modify it internally to optimize its operational performance. (5) Finally, we must not overlook “non-users”. Christensen, in his research on the phenomenon of disruptive innovation9 highlighted how high can be the danger 7

Several authors have focused their attention on the activities that customers engage in to achieve a specific set of outcomes, elaborating similar concepts: the customer-activity chain (Sawhney et al., 2003); the customer-activity cycle (Vandermerwe, 1993); or the buyer experience cycle (Kim & Mauborgne, 2000). Kim and Mauborgne have articulated the buyer experience cycle in six stages: purchase, delivery, use, supplements, maintenance and disposal. 8 Von Hippel (1986); Urban and Von Hippel (1988); Thomke and Von Hippel (2002).

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NonUsers

NeedInformation

SolutionInformation

Understanding "unheard" needs of the sector

X

Ordinary Users

Demanding Users

Demanding Users with technical expertise

Knowledge refinement of widespread needs

X

Innovative Users

Lead Users

Identification of emerging needs

Rough solutions

Detailed solutions & early prototypes

Fig. 4.1 The role of different categories of users in VOC Research

of confronting and focusing only on the most demanding users of the market. Significant opportunities for innovation can be driven by understanding the needs of those who are not able to buy the products offered in the market because they are too complicated, too performing and too expensive: they express the “unheard needs” of the sector. Kim and Mauborgne have brilliantly highlighted the importance of grasping the needs of non-users: new market spaces (the “blue oceans” in the authors’ metaphor10) can be seized by trying to convert “noncustomers” into a new demand. One of the examples of “non-users” proposed by Kim and Mauborgne is particularly instructive: it is the case of sports enthusiasts who could have chosen golf but never started playing because of a perception of excessive difficulty and slowness in achieving a minimum level of mastery of technical gestures. A leading club manufacturer started from the understanding of the needs of non-players to create an ad hoc equipment and managed to create a new market space and new opportunities for growth. Another historical example (end of the 1980s) is the birth of disposable cameras from Fuji and Kodak (radically simple to use and cheap), dedicated to two segments of non-users: young people (who could not afford an expensive equipment) and those who, having no photographic skills, did not own and did not use a traditional camera. In Fig. 4.1, we have highlighted the role of the different categories of users (both in B2B and B2C contexts) in relation to the focus of VOC research (needinformation or solution-information).

9

Christensen (1997). Kim and Mauborgne (2005).

10

4.2 Involve Customers to Capture Their Needs

45

This chapter focuses on customer involvement initiatives that are conceptually placed in the first level of the innovation pyramid (intelligence); customer interaction is, of course, also relevant in the context of activities located in the upper levels of the pyramid model (discovery and development). In Chap. 5, for example, we will address the topic of innovation workshops—events in which a selected group of people, through a well-defined process and the use of specific methodologies, is engaged in the collaborative generation of new ideas in response to a “challenge”; customers and users can play a leading role in such creative groups. A strong relationship with customers is also significant in the early stages of product development projects, especially in product concept evaluation and testing activities (see Chaps. 6 and 7). In the remainder of this section, we will refer to products both in the B2C and B2B context. However, it should be noted that the relationship with customers in the specific case of engineer to order (ETO) companies with products of high technical complexity is peculiar: in such situations, the product is developed after an explicit request from the customer. It is designed ad hoc in response to specific technical needs. Understanding needs is, in this situation, a natural part of the technicalcommercial activities aimed at analysing the feasibility of an offer request—the initial phase of the order management process. Let’s think, for example, of the case of a company engaged in the field of industrial automation, which receives an offer request for the robotization of the assembly activity of the plates of an automotive battery. In order to respond to the request, it is necessary to interact with the customer to fully understand the “problem to be solved” by analysing the battery assembly process; once the needs are understood, the preliminary design activities necessary to formulate a solution proposal and a price quote will be carried out.

4.2

Involve Customers to Capture Their Needs

The objective of involvement is to interact with customers and their context of action and life to grasp their needs and understand their importance and relative value. It is not uncommon to come across situations where these activities are carried out hastily and superficially; in marketing and sales departments and technical offices, it is taken for granted that you already know the needs of your customers in-depth. Many needs can be undoubtedly well known, stable and studied for a long time. Still, over time latent needs can emerge, in response to socio-cultural phenomena or environmental changes generated by technological progress: these needs must be intercepted and understood as soon as possible. The excessive time compression of VOC research significantly reduces the opportunity to generate robust and valuable need-information. This can lead to the realization of unsatisfactory product ideas and concepts, which can lead to unplanned and costly product revisions. Needs analysis requires methodological approaches that address the following objectives:

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• Which customers? • Where to focus attention on the customer-activity cycle?

ANALYSIS • Interviews • Observation • Focus Groups

FOCUS

PRIORITIZATION

• Need Statements

• Importance Rating • Satisfaction Rating

SYNTHESIS

Qualitative VOC Research

Quantitative VOC Research

Fig. 4.2 Capturing need-information: the four phases of a typical VOC project

• identify not only explicit needs but also latent needs (which only a few customers perceive, but which may spread in the market in a short or medium term) and hidden needs—“issues and problems that customers face but have not yet realized”;11 • provide consistent support for the definition of new product visions and concepts and the evaluation of product performance and functionality from the customer’s perspective, ensuring the focalization of products on customer needs; this is important to avoid the risk that some technical features do not respond to a real need (a situation that can happen when the product is designed according to the company’s beliefs about what the customer would expect); • develop an organization-wide awareness and deep knowledge of customer’s needs. Typical activities of a need-focused VOC research project are illustrated in Fig. 4.2: • focus: define which customers to interview and observe and where to concentrate on the customer-activity cycle; • analysis: collect information directly from customers about their experiences when interacting with products and services, to see their world and understand their feelings; • synthesis: reduce this amount of information into a set of well-defined needs and generate insights on the deep reasons underlying the needs—why customers demonstrate certain behaviours, feelings and thoughts;

11

See Goffin et al. (2010).

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• prioritization: uncover customer segments with unique sets of crucial unmet needs—i.e. groups of customers who converge in prioritizing needs in terms of importance and current satisfaction level; this is the quantitative phase of a VOC research project. The objective of the first phase (focus) is to define which customer categories to involve and where to focus attention on the customer-activity cycle. Valuable sources of information could come from a variety of sources: users, non-users, competitors’ customers, “lost customers” or other actors that influence purchasing processes, such as resellers or maintenance workers. Companies often listen only to established customers, with whom they have frequent interactions; but in this way, they can lose a wealth of information residing in other subjects. The second phase (analysis) can be carried out in various ways, mixing different techniques: (1) Interviews: face-to-face conversations conducted in the customer’s environment (contextual interviews) or delivered online with video communication tools in case it is necessary to efficiently reach geographically dispersed respondents; (2) Focus group (i.e. focused group discussion): it is a group interview technique in which participants are free to interact with each other. Through a set of predefined open-ended questions, the moderator stimulates a 1–2 h discussion with a group of 8–10 customers; the meeting is usually recorded so that conversations and behavioural dynamics of the session can be analysed in detail. (3) Systematic observation of real situations of use: by observing the clients with video recordings or photographs, it is possible to analyse the actual product– customer interactions and the potential problems that customers are not able to articulate (e.g. observing the use of surgical equipment during a surgery can facilitate the understanding of the issues and the needs to be satisfied). Customer interviews and focus groups require a sound preliminary preparation to select the customer categories to involve and choose which customer activities to focus on, according to the general objectives outlined in the first phase of the VOC research process. For example, in the case of an end-user, attention could be focused on the initial learning activities of the use of the product; or on the (unwanted) maintenance activities that must be carried out; or on the whole process of use of the product.12 It is also good practice to prepare a set of key open-ended questions in advance to guide the interview process. Table 4.1 shows an example of an interview plan for a VOC research regarding a piece of mechanical equipment used in a workshop.

12

Kim and Mauborgne (2000).

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Table 4.1 An example of an interview plan focused on three “voices”: users, dealers and maintainers Market segment Occasional User Factory Worker Craftsmen

Expert user 3 3

User 5 8 6

Dealer 4

Maintenance centre 2

It is common that in the dialogue technical suggestions on possible product improvements or comments on product defects may emerge. To uncover customer needs it is important to investigate why specific solutions are desired, or particular attributes of current products are judged unsatisfactory. Information about needs is nested in the reasons given for the appreciation or criticism of technical solutions; contextual interviews are particularly useful as it is easier to thoroughly understand customer actions, thoughts and feelings when the interviewer is immersed in the social setting that is being studied. Systematic observation in VOC research is a form of applied ethnography: the goal is to watch and interact with customers in their natural environments and understand situations through their eyes, producing a “thick description” of customers behaviours and feelings.13 With systematic observation, it is possible to explore how customers really interact with products and services and to uncover problems and desires that customers don’t even realize they have. In essence, it is an “immersion” in the context of customers actions and experiences to capture insights on their frustrations, satisfactions and hidden needs. Interaction with customers can be carried out independently by company personnel or facilitated by external consultants; however, VOC research projects should not be outsourced, as the understanding of customer needs is a core competence that has to be nurtured and developed. A frequent objection to the use of interviews and observation concerns their cost; it is erroneously believed that it is necessary to expand the number of respondents according to the “statistically significant” sample theory. Instead, the concept of theoretical saturation is crucial: the “continuation of sampling and data collection until no new conceptual insights are generated14”. Experience shows that there is a saturation effect on the acquisition of information after a limited number of respondents: for example, in the case of end-users in a consumer goods market segment, a few dozen interviews (or 8 to 10 focus groups) may often be enough.15 All information captured through customers interactions should then be distilled in a set of need statements—the synthesis phase (see Case Study 4.1)—that should provide insights into customers’ utilitarian and hedonic desired outcomes.

13

See Goffin et al. (2012) and Goffin et al. (2010). See Bloor and Wood (2006). 15 Griffin and Hauser (1993): “Our data suggest interviews with 20–30 customers should identify 90% or more of the customer needs in a relatively homogeneous customer segment”. 14

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Case Study 4.1 BFT Automation (manufacturer of access automation systems for residential, collective and urban use) wanted to understand better the needs of installers of automation systems for swing gates, focusing on the installation process. Interviews and observations (distributed between specialized installers with a high degree of technical expertise, and occasional installers) were recorded and carefully analysed. Subsequently, 20 need statements were drawn up relating to the four fundamental phases of the installation process: preparation, mechanical installation, cabling, system start-up. The need statements have been built with a standard syntax able to highlight the needs related to the “perfect execution” of the installation process; the language used follows the style of Agile User Stories (see Chap. 8). Below are some examples. • I want to be able to carry out the preliminary risk analysis of the plant in a simple way and in the shortest possible time. • I want to rapidly identify the reason for the malfunction of a specific system component. • I want to adjust the maximum opening and closing position as quickly and as simply as possible. • I want to use the minimum number of tools for the installation of a swing actuator to minimize time. • I want to reduce the time I use to customize the operation of the system according to the customer’s requirements (e.g. automatic closing time, photocell management, etc.). • I want to minimize the time it takes to explain the operation of the system to the customer. Needs do not all have the same importance, and there may be customer segments who differ in how they prioritize needs. Identifying crucial needs of a specific customer segment is essential to focus the generation of desirable new ideas and overload technical solutions with attributes (and therefore costs) linked to unimportant needs for which the customer will not be willing to accept a premium price. A commonly used method for prioritization is a close-ended questionnaire16 which can be massively distributed through online survey platforms. It is necessary to prepare a multiple-choice survey form with a list of needs statements that have been identified during the qualitative phase of the VOC research; for each need statement, an evaluation of the importance on a five-point Likert scale is requested (1: not important and not necessary; 5: absolutely important).

16

See Katz (2004) and Ulwick (2016).

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Table 4.2 An example of a close-ended survey for need importance rating and prioritization Need statement I want to precisely adapt the heat flow according to the delicacy of the food. I want to precisely adjust the humidity level in the oven according to the cooking technique I have chosen. I want to be able to store the parameters of a cooking session quickly and easily. I want to be able to cook dishes with different cooking styles at the same time.

Importance level 1 Not 2 Slightly important Important

3 Moderately Important 3 Moderately Important

4 Important

5 Very important

4 Important

5 Very important

1 Not important

2 Slightly Important

1 Not important

2 Slightly Important

3 Moderately Important

4 Important

5 Very important

1 Not important

2 Slightly Important

3 Moderately Important

4 Important

5 Very important

An excerpt of a survey form used to identify the importance of the needs in the field of professional ovens is shown in Table 4.2. After interviewing several customers, the VOC research team analysed the recordings and meetings memos and summarized the information in a list of need statements; they then identified a sample of users to which they distributed the form shown in Table 4.2. The needs with an average score greater than or equal to 4 were considered top priorities and, therefore, the primary focus of the innovative efforts. A further useful elaboration for the prioritization of needs is the evaluation of the current level of satisfaction with the products on the market with a five-point Likert scale (1: very dissatisfied; 5: very satisfied). Needs importance and satisfaction can then be crossed (Fig. 4.3): the area of the matrix characterized by high importance and low satisfaction is, of course, a space of opportunity to look for product changes that customers are willing to pay for (differentiation with premium price). The area of low importance and high satisfaction could, instead, hide situations of overshooting (the product is redundant compared to real needs) and offer opportunities for lower-price differentiation and disruptive innovations:17 the reduction of irrelevant performance can be appreciated by overshot customers, who prefer a simplified product at a lower price. An example of a VOC research process is presented in Case Study 4.2.

17

Christensen (1997).

4.2 Involve Customers to Capture Their Needs

51

Lower-price differentiation opportunities High

Actual need satisfaction

Premium-price differentiation opportunities

Low

Low

Need Importance

High

Fig. 4.3 Need priority matrix

Case Study 4.2 S-BAG is a leading manufacturer of garbage bags. The disappearance of traditional plastic bags in supermarkets and the simultaneous spread of new forms of waste collection have led to a growing demand for refuse sacks. Producers tried to differentiate and expand their offer but had to understand what their customers’ needs were in the new context. In a first meeting, some attributes of the product were identified, which corresponded to a set of needs and benefits considered important and which conditioned, in addition to price, consumer choices: – the type of closure of the bag (lanyard, handle, t-shirt, double knot or other) – product packaging (envelope, band, shrink-wrap, other) – resistance, colour, antibacterial enrichment or perfume. Below is a brief description of the various phases adopted by the company to proceed with the needs analysis: (continued)

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Case Study 4.2 (continued) (a) appointment of the VOC research project manager and project team members; (b) need analysis through an initial round of interviews with a group of employees in the role of users and consumers; (c) inter-functional meetings to synthesize the data provided by the interviews and define the set of needs; (d) drafting of a questionnaire for the interviews (using scales with a score from 1 to 5 and leaving a couple of questions open to grasp other unforeseen inputs) and carrying out a mini-test with a small group of customers for its development; (e) definition of the sample. A group of supermarkets located in some areas of the country, with different waste management characteristics, was identified and a minimum number of interviews was defined for each supermarket; (f) choice of interviewers (five young employees of the company) and training on how to conduct the interview; (g) carrying out the interviews in several supermarkets; (h) processing the data and drawing up a report on the results obtained; (i) inter-functional meetings to examine data and analyse the implications for product choices. Some product ideas freely expressed by some consumers that reflected unmet needs were also discussed. Afterwards, idea generation sessions were launched, leading to the definition of a new successful product plan. The involvement of customers and an analytical understanding of the key needs in different customer segments has created an important knowledge base to redesign the company’s offer thoroughly.

4.3

Involve Customers to Capture Solution-Information

Customer involvement can also pursue the absorption of information on possible new solutions that address emerging or unmet needs. A significant amount of research has shown that many innovations in different sectors (surgical instruments, scientific instruments, industrial machinery, sports equipment, software applications, household products, etc.) are devised by users (user innovation18). Recent empirical research conducted in several countries has brought to light the scale of the phenomenon in the B2C context: Von Hippel and colleagues19 estimate 18 19

Von Hippel (2005). Von Hippel et al. (2011); Franke et al. (2016).

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53

that millions of consumers (e.g. 6% of the population over the age of 18 in the UK, 5% in the US, and 3.7% in Japan) have made changes to consumer products to adapt them to their needs. In sports communities of enthusiasts, the percentages of innovative users are even higher.20 In B2B sectors, the possibility to absorb relevant solutions-information and to activate meaningful co-design collaborations is very high because B2B customers often have significant technical expertise on the products used and have a keen interest in innovation, as new solutions can significantly improve companies’ internal performance and efficiency. The traditional subdivision that assigns an active role to producers and a passive role to users represents a biased and limiting vision. Customers and, in particular, users can play a leading part by providing accurate indications to manufacturers on possible directions for product improvement, or by self-designing such solutions. Not all users have the ability to generate innovative ideas. The probability of obtaining attractive product ideas increases with the experience and intensity of product use and technical expertise: • as the user experience increases, better skills are developed, and the ability to perceive and analyse usage problems is refined; • as technical expertise on the product increases, the likelihood that meaningful and novel ideas are formulated with a high level of technical detail. An example of expert user involvement for idea generation is the following case about adjustable legs for kitchen cabinets. These components are installed when positioning the furniture in an apartment; the fitter must bow himself, or more often lie down on the floor, to adjust the various legs to level the furniture. The levelling process is known to be time-consuming and particularly tiring. A leading firm in the design and production of high-quality components for kitchens and furniture believed that the best way to define a new levelling system was to turn to experienced and technically proficient users: experienced fitters which “know the ropes” and may have devised prototype tools to ease and simplify the installation process. Some very experienced fitters were interviewed and observed during several installation sessions organized in company’s headquarters, where they could try various types of installation supporting tools, demonstrate their “tricks of the trade” and suggest new solutions. A new product concept emerged in these meetings: a leg that could be adjusted using a ring nut that is easily hooked by a particular telescopically adjustable arm. This solution solved two key problems felt by fitters: fatigue and complexity of adjustments; it was also appreciated by retailers and furniture manufacturers, for the reduction of assembly time and the greater precision in the levelling process.

20

Franke and Shah (2003).

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• Identify important trends in the target market • Find a proxy measure of high expected benefit

SPECIFY

IDENTIFY • Identify lead users through mass screening technique or pyramiding search process

• Select and invite a small sample of lead users to participate in innovation workshops

EVALUATE • Test attractiveness of lead user’s product ideas with mainstream users in the target market

GENERATE

Fig. 4.4 Involving customers to capture solution-information: Von Hippel’s Lead User Method

Involving demanding and technically competent users is, therefore, an excellent strategy to capture attractive new ideas; even better, though, is to connect to lead users. As we pointed out in the introductory paragraph, lead users represent a key target group in solution-focused VOC research because they have two distinctive characteristics: • they “live in the future” relative to others in the target market. As Von Hippel states: “they face needs that will be general in the marketplace, but face them or years before the bulk of that marketplace encounters them21”—lead users are ahead of an important need-related trend and there is a high probability that their innovations are commercially attractive; • they expect strong benefits from innovation, and they have the technical skills to design and test new solutions to solve their leading-edge personal needs. An enlightening and well-known example of lead users identification can be found in the 3M’s Medical-Surgical Division case described by Von Hippel, Thomke and Sonnak.22 3M was searching breakthrough solutions in the area of surgical drapes (products that prevent infection from spreading during surgery), where the emerging trend was the growing need for much cheaper, easy to use and more effective infection control methods. Lead users were identified among doctors from developing countries, military medics, veterinarian surgeons: professionals able to control infection rates effectively despite facing challenging or hostile conditions and severe cost constraints. Von Hippel and colleagues developed a four-phase method23 to identify and involve lead users in generating new product ideas (see Fig. 4.4):

21

Von Hippel (1986). Von Hippel et al. (1999). 23 See Urban and Von Hippel (1988), Von Hippel et al. (1999); Von Hippel, Churchill, et al. (2009); Lüthje and Herstatt (2004). 22

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(1) Specify lead user characteristics: as lead users are in advance of the market with respect to specific need-related trends, the first step is to identify important trends in the product/market of interest on which to base the search of users with a leading position. Lead users are also characterized by a high expected benefit of solving their leading-edge personal needs; so, the second step is to find a proxy measure of this variable, such as the evidence of innovation-related activity by users.24 (2) Identify lead users: once trend(s) and proxy measures of high expected benefit have been specified, we can identify lead users through classical mass screening techniques (which involves the collection of information from every member of a population or sample) or through “pyramiding”—a sequential search process based upon the idea that “people having a strong interest in a given attribute or quality, for example a particular type of expertise, will tend to know of people who know more about and/or have more of that attribute than they themselves do25”. (3) Generate product ideas with lead users: invite a selected sample of the lead users identified in phase 2 to participate in a creative ideation workshop with company personnel. (4) Test lead user ideas with “ordinary” users: the final phase involves testing whether mainstream users in the target market find valuable and attractive the product ideas developed by lead users. The examples described so far in this chapter refer to customer involvement projects focused on the absorption of a specific type of information: needinformation (BFT and S-BAG) or solution-information (adjustable legs for kitchen cabinets and 3M). In many circumstances, it can be useful to plan for more complex involvement initiatives, aimed at deepening the knowledge on needs and at the same time capture ideas to improve products; in Case Study 4.3 we present an example in a B2B context. Moreover, due to the massive growth of social networking platforms, new customer involvement initiatives that couple needs analysis and solution search have recently emerged, such as netnography, crowdsourcing idea contests and virtual customer communities for co-creation.26 In B2C contexts, netnography—the adaptation of ethnographic techniques to study online communities27—uses information publicly accessible on the web to analyse needs and possible solutions that consumers have discussed in online conversations. Online communities are independent consumer groups centred on a common passion or hobby that use the Internet to exchange ideas and experiences; a

24

Herstatt and Von Hippel (1992). Von Hippel, Franke, et al. (2009). 26 For a thorough discussion of the concept of “co-creation” see Prahalad and Ramaswamy (2004a, 2004b). 27 See Kozinets (2002). 25

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remarkable example is NikeTalk—“The Ultimate Sneaker Enthusiast Community”, an Internet forum started by Nelson Cabral in 1999. Through netnography it is possible to identify highly creative consumers that demonstrate sufficient skills and motivation to develop novel solutions.28 Idea generation contests through crowdsourcing web platforms could be used to find lead users with an ex-post approach based on actual innovative behaviour (the submitted ideas).29 As we will see in Chap. 5, with crowdsourcing it is possible to connect with remarkably innovative users, as the logic of outsourcing creative activities through an open call on the Internet exploits the power of skill diversity and the strength of intrinsic motivation of self-selected problem-solvers. Beyond the sporadic and time-bounded connections provided by crowdsourcing, firms are nowadays able to establish a permanent interaction with their customers through the creation of virtual customer communities. Through proprietary web platforms, companies can engage their customers in an ongoing two-way dialog in product-related discussions and capture valuable information on underserved needs and possible new solutions.30 Customer communities are particularly effective when members are enthusiastic brand fans:31 passionate users who often demonstrate extensive technical knowledge that they are eager to share with others, as in the well-known cases of Ducati Motor and Lego Group communities.32 Case Study 4.3 CUKI is a medium-size subcontractor that designs and manufactures stovetops for manufacturers of high-end kitchens furniture. Its customers are very demanding on the design and functionality of stovetops, which must be consistent with the aesthetic level of their kitchens. The pressure from kitchen manufacturers on the frequency and number of new hob proposals has always been very intense, to the point of undermining the creative capacity of CUKI’s marketing and design departments. To meet these demands, the marketing manager proposed to listen to the voice of the end-user to gather emerging needs and new product ideas. He was, in fact, confident that through the involvement of a group of very demanding users, precious insights and ideas could be grasped. CUKI’s owner and CEO was not, at first, positive: “we are too far from the user, kitchen manufacturers and retailers are in the middle, and then we don't know how to involve the users, who are certainly not designers”. The resistance was due to the incorrect perception of the potential of the information (continued) 28

Füller et al. (2007). See Brem and Bilgram (2015) and Piller and Walcher (2006). 30 See Füller et al. (2008), Nambisan (2002). 31 See Füller et al. (2008) and Füller (2006). 32 See Sawhney et al. (2005) and Marchi et al. (2011); Antorini et al. (2012). 29

References

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Case Study 4.3 (continued) coming from users, in particular from demanding users with strong user experience: demanding users not only know their needs very well but can also provide new ideas, even if not accompanied by technical and construction details. The marketing director, after a lengthy discussion, was able to convince the CEO based on a series of arguments: “We are looking for ideas, not detailed technical solutions, which require technological and engineering skills that users do not have; but those who use the product every day and perhaps have had different types of stovetop over time have a clear idea of what is wrong, or what would be needed. Moreover, the cost of interviewing a group of users is not high; we can also involve the company’s employees or their friends and relatives”. So CUKI proceeded to identify and involve 25 intensive and demanding users. Many unsatisfied needs emerged from the interviews, such as, for example, the difficulty of cleaning the stovetop, the marks left by the sponge, the distance between the fires not suitable for placing large and small pots, the non-ergonomic shape and arrangement of the power buttons and so on. These dissatisfaction factors could quickly be taken into account to improve existing products. But it was the innovative ideas expressed by some users that surprised CUKI’s managers: “my kitchen is small, and the most convenient thing would be to put the hob in the corner . . .”. “I love steam cooking, and I’d like to have a space set aside for that . . .”. “My family likes grilled fish; how nice it would be to have a small grill right in the stovetop. . .”. Customer interviews were analysed and summarized in a PowerPoint report; afterwards, in a cross-functional workshop, the most original ideas were identified and prioritized. Renderings were developed to give shape, albeit embryonic, to new products. These renderings were submitted for evaluation by a further group of users; then the most attractive ideas were elaborated considering both marketing and technical issues together. Finally, two new product concepts were selected for development.

References Antorini, Y. M., Muñiz, A. M., Jr., & Askildsen, T. (2012). Collaborating with customer communities: Lessons from the LEGO Group. MIT Sloan Management Review, 53(3), 73. Bloor, M., & Wood, F. (2006). Keywords in qualitative methods: A vocabulary of research concepts. Sage. Brem, A., & Bilgram, V. (2015). The search for innovative partners in co-creation: Identifying lead users in social media through netnography and crowdsourcing. Journal of Engineering and Technology Management, 37, 40–51. Chitturi, R., Raghunathan, R., & Mahajan, V. (2008). Delight by design: The role of hedonic versus utilitarian benefits. Journal of Marketing, 72(3), 48–63.

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Christensen, C., Dillon, K., & Hall, T. (2016). Competing against luck: The story of innovation and customer choice. Harper Business. Christensen, C. M. (1997). The innovator’s dilemma: When new technologies cause great firms to fail. Harvard Business Review Press. Christensen, C. M., Anthony, S. D., Berstell, G., & Nitterhouse, D. (2007). Finding the right job for your product. MIT Sloan Management Review, 48(3), 38–47. Christensen, C. M., & Raynor, M. E. (2003). The innovators solution: Creating and sustaining successful growth. Harvard Business Review Press. Franke, N., Schirg, F., & Reinsberger, K. (2016). The frequency of end-user innovation: A re-estimation of extant findings. Research Policy, 45(8), 1684–1689. Franke, N., & Shah, S. (2003). How communities support innovative activities: An exploration of assistance and sharing among end-users. Research Policy, 32(1), 157–178. Füller, J. (2006). Why consumers engage in virtual new product developments initiated by producers. ACR North American Advances. Füller, J., Jawecki, G., & Mühlbacher, H. (2007). Innovation creation by online basketball communities. Journal of Business Research, 60(1), 60–71. Füller, J., Matzler, K., & Hoppe, M. (2008). Brand community members as a source of innovation. Journal of Product Innovation Management, 25(6), 608–619. Goffin, K., Lemke, F., & Koners, U. (2010). Identifying hidden needs: Creating breakthrough products. Palgrave. Goffin, K., Varnes, C. J., van der Hoven, C., & Koners, U. (2012). Beyond the voice of the customer: Ethnographic market research. Research-Technology Management, 55(4), 45–53. Griffin, A., & Hauser, J. (1993). The voice of the customer. Marketing Science, 12(1), 1–27. Herstatt, C., & Von Hippel, E. (1992). From experience: Developing new product concepts via the lead user method: A case study in a “low-tech” field. Journal of Product Innovation Management, 9(3), 213–221. Katz, G. (2004). The voice of the customer. In K. Kahn (Ed.), The PDMA Handbook (2nd ed.). Wiley. Kim, C. W., & Mauborgne, R. (2005). Blue ocean strategy. Harvard Business Review Press. Kim, W. C., & Mauborgne, R. (2000). Knowing a winning business idea when you see one. Harvard Business Review, 78(5), 129–138. Kozinets, R. V. (2002). The field behind the screen: Using netnography for marketing research in online communities. Journal of Marketing Research, 39(1), 61–72. Lüthje, C., & Herstatt, C. (2004). The Lead user method: An outline of empirical findings and issues for future research. R&D Management, 34(5), 553–568. Marchi, G., Giachetti, C., & De Gennaro, P. (2011). Extending lead-user theory to online brand communities: The case of the community Ducati. Technovation, 31(8), 350–361. Nambisan, S. (2002). Designing virtual customer environments for new product development: Toward a theory. Academy of Management Review, 27(3), 392–413. Piller, F. T., & Walcher, D. (2006). Toolkits for idea competitions: A novel method to integrate users in new product development. R&D Management, 36(3), 307–318. Prahalad, C. K., & Ramaswamy, V. (2004a). Co-creation experiences: The next practice in value creation. Journal of Interactive Marketing, 18(3), 5–14. Prahalad, C. K., & Ramaswamy, V. (2004b). The future of competition: Co-creating unique value with customers. Harvard Business School Press. Sawhney, M., Balasubramanian, S., & Krishnan, V. V. (2003). Creating growth with services. MIT Sloan Management Review, 45(2), 34–44. Sawhney, M., Verona, G., & Prandelli, E. (2005). Collaborating to create: The internet as a platform for customer engagement in product innovation. Journal of Interactive Marketing, 19(4), 4–17. Thomke, S., & Von Hippel, E. (2002). Customers as innovators: A new way to create value. Harvard Business Review, 80(4), 74–85. Ulwick, A. W. (2005). What customers want: Using outcome-driven innovation to create breakthrough products and services. McGraw-Hill.

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Ulwick, A. W. (2016). Jobs to be done: Theory to practices. Idea Bite Press. Ulwick, A. W., & Bettencourt, L. A. (2008). Giving customers a fair hearing. MIT Sloan Management Review, 49(3), 62–68. Urban, G. L., & Von Hippel, E. (1988). Lead user analyses for the development of new industrial products. Management Science, 34(5), 569–582. Vandermerwe, S. (1993). Jumping into the customer’s activity cycle. Columbia Journal of World Business, 28(2), 46–65. Von Hippel, E. (1986). Lead users: A source of novel product concepts. Management Science, 32 (7), 791–805. Von Hippel, E. (1994). “Sticky information” and the locus of problem solving: Implications for innovation. Management Science, 40(4), 429–439. Von Hippel, E. (2005). Democratizing innovation. MIT Press. Von Hippel, E., Churchill, J., & Sonnack, M. (2009). Lead user project handbook: A practical guide for lead user project teams. Von Hippel, E., Franke, N., & Prügl, R. (2009). Pyramiding: Efficient search for rare subjects. Research Policy, 38(9), 1397–1406. Von Hippel, E., Ogawa, S., & De Jong, J. P. (2011). The age of the consumer-innovator. MIT Sloan Management Review, 53(1), 27–35. Von Hippel, E., Thomke, S., & Sonnack, M. (1999). Creating breakthroughs at 3M. Harvard Business Review, 77, 47–57.

5

Searching for Innovation Opportunities: Idea Generation and Technology Development

Abstract

What distinguishes consistently innovative companies is their organizational capability in systematically exploring new opportunities, the second level of the innovation pyramid (discovery). This exploration capability emerges in (1) activities aimed at generating new product ideas (creative ideation) and in (2) technology development, whose objective is the resolution of knowledge gaps through research and experimentation to ensure the feasibility of new product ideas and introduce significant or radical changes in the performance and technical attributes of products. The combination of these two types of activities leads to the creation of a shelf of novel and feasible product ideas—preliminary concepts of potential future products that can range from clear statements about anticipated product features and benefits to early prototypes. As we have seen in Chap. 3, we can identify four different approaches to creative ideation: the default mode, called idea fishing to highlight its passive and reactive nature, where product ideas are merely collected; and three proactive approaches (idea hunting). In the next paragraphs, we will examine in depth the logic of the two opposite ways of moving away from the passive approach of the idea fishing: innovation workshops (based on collaboration between a limited number of selected people) and innovation contests (centred around competition between a unknown crowd of problem-solvers). In the last section, we will direct our attention to technology development.

# Springer Nature Switzerland AG 2021 S. Biazzo, R. Filippini, Product Innovation Management, Management for Professionals, https://doi.org/10.1007/978-3-030-75011-4_5

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5 Searching for Innovation Opportunities: Idea Generation and Technology. . .

Innovation Workshop

The capability to generate new product ideas systematically does not emerge spontaneously; it needs ad hoc organizational solutions capable of creating a fertile environment in which people can develop and express their imaginative and creative skills. An innovation workshop is an initiative in which a selected group of people, through the use of specific methodologies, is engaged in a collaborative and wellstructured process of creative conception. A remarkable example is the following format developed by the well-known consulting firm IDEO,1 which use a “design thinking”2 process: (1) Empathize: At this early stage the team needs to empathize with clients in order to fully understand their needs and to clearly frame the problems to be addressed. (2) Define: it is the time to focus and define the key problems to be addressed in the next design phase. An interesting and simple tool suggested by IDEO to frame the key needs is the acronym HMW (How Might We?): the object of the challenge is clarified through a series of questions focused on the needs considered most relevant, expressed with the formula HMW: how might we [answer the need XY]? (3) Ideation: it is the divergent phase of the creative process. It is the moment where we have to aim for the broadest possible expansion of the spectrum of possibilities; determining the best option is an issue to be addressed in the following stages. Interesting are the eight fundamental rules of a “perfect brainstorming” developed by IDEO: 1. Defer judgment. Don’t block someone else’s idea if you don’t like it. . .put it on the whiteboard and maybe you’ll be able to build on it later. 2. Go for volume. Getting to 100 ideas is better than 10, no matter what you initially think about the “quality”. Try setting a goal for the number of ideas you’ll get to in a certain amount of time to provide some stoke. 3. One conversation at a time. When different conversations are going on within a team, no one can focus. 4. Be visual. Sketch your ideas out for your teammate. It will communicate them more clearly than words alone, plus you might inspire some crazy new ideas. 5. Headline your idea. Make it quick and sharp, then move on to the next one. 6. Build on the ideas of others. This leverages the perspectives of diverse teams and can be especially useful when you feel like you’re stuck.

IDEO (www.ideo.com) is a leading consultancy firm in the field of product and service innovation; see Kelley (2001), Brown (2008), Kelley and Kelley (2013). 2 “Design thinking is a human-centred approach to innovation that draws from the designer’s toolkit to integrate the needs of people, the possibilities of technology, and the requirements for business success” (https://designthinking.ideo.com). 1

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Design Thinking Process High

Value Innovation Process

Strategic Roadmapping

Inside-out Process EFFORT

Low

One-off idea generation session with creativity techniques

Single-stage

Sequence of idea generation sessions with creativity techniques

PROCESS

Multi-stage

Fig. 5.1 Innovation Workshop: four approaches

7. Stay on topic. Your idea for an edible cell phone is awesome, but not during a brainstorm on making opera more exciting for children. 8. Encourage wild ideas. The crazier the better. . .you never know where your team might be able to take it. (4) Prototyping:3 it is the beginning of the convergent phase. IDEO suggests making the best ideas visible and tangible with “artefacts” (any entity with which it is possible to interact physically), to be realized quickly and with minimum effort.4 (5) Testing: the search for feedback from users and customers on some form of “raw artefact” is essential to understand the potential of new product ideas. In Fig. 5.1 we classify the different ways of organizing an Innovation Workshop according to two dimensions: (1) the effort (time and financial resources) required from the participants; (2) the complexity of the creative conception process: a single session workshop (single-stage) or a sequence of sessions and activities distributed over time (multi-stage).

In IDEO the “prototype” is an artefact with which you can interact; a set of post-it, a role-playing activity that simulates a service, an object, a virtual simulation, a drawing, a storyboard, etc. Prototyping in IDEO must follow the “3R” rule: Rough, Rapid, & Right. 4 Kelley (2001), Brown (2005), Thomke (2001). 3

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The IDEO approach is an example of a multi-stage Innovation Workshop that requires a significant time commitment. Another interesting example is the process of generating “high strategic impact” product ideas, aimed at profoundly changing the company’s strategic profile. Kim and Mauborgne, in their renowned book Blue Ocean Strategy, propose a methodology to radically innovate the value offered to customers (Value Innovation) and to look for “blue oceans”, i.e. market spaces characterized by low or non-existent competition intensity because the value proposition is radically different from that of other companies.5 The Value Innovation process proposed by Kim and Mauborgne is organized in five main steps6 and is centred on the concept of “value curve” (see Chap. 7), which is the key tool to be used in analysis of the current state—the group session defined as “visual awakening”—and in reimagining the future state. In the initial as-is analysis, the “Blue Ocean Team” has to build the value curve of its own company and its main competitors by identifying (1) the set of product/service attributes on which the competition is focused; and (2) by assessing the level customers receive for each attribute (in a simple qualitative scale representing the relative performance of the various competitive players). Subsequently, a diagram is constructed with the set of key product/service attributes in the horizontal axis, and the offering level in the vertical axis. The value curve visually reveals the strategic profile of a company’s value proposition. The analysis of strategic profiles is the basis of the following steps focused on the possible directions of change of the value curve. Kim and Mauborgne propose four key questions to imagine possible transformations: which attributes–taken for granted and considered necessary in the sector–can be eliminated? Which attributes can be substantially reduced (as they are oversized compared to the needs)? Which attributes can be enhanced? Which unique attributes—unknown to direct competitors—can be introduced? A further innovation workshop approach focused on the search for radically innovative product ideas that can outline new directions in product development (redefining the fundamental attributes of the offer and its meaning for the customer) has recently been proposed by Verganti (Inside-out process7). Verganti reverses the direction of the traditional Design Thinking creative flow: in the IDEO process the starting point is the understanding of customers’ needs; in the Inside-out process

5

On the concepts of Value Innovation and Blue Ocean Strategy, see Kim and Mauborgne (2005, 2017). 6 The five-step process is described in Blue Ocean Shift (Kim & Mauborgne, 2017): (1) set the scope of the initiative by focusing on a specific “product/service offering” or business; (2) analyse the current state with the Value Curve (“strategy canvas”); (3) discover the pain points of existing customers and the ignored needs of noncustomers; (4) gain new insights on how value could be unblocked through the six-paths framework, redefine the value curve through the four-actions approach (Reduce, Raise, Create, Eliminate), and identify multiple “future-state” options; (5) select the to-be Value Curve to pursue. 7 The inside-out process is briefly described in Verganti (2016); see Verganti (2017) for more details.

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the starting point is the personal visions on the new motivations that, in the future, could push people to buy, use and love a product. The process is structured in four main steps:8 (1) a small group of people within the company is entrusted with the task of reflecting individually on new product ideas that move away from the current value proposition of the company, in search of new meanings that redefine the “whys” of company’s products. (2) Each person seeks a peer (interested in the idea) to whom the vision developed can be subjected to criticism, to elaborate and refine it together; the role of constructive criticism9 among peers is considered by Verganti to be particularly valuable and finds significant historical evidence in many great innovations in the artistic and scientific field. (3) Constructive criticism is strengthened by using a wider network of people (called “radical circle10”) to compare the visions developed in the previous phases and identify new ones. (4) A selected set of visions are, finally, submitted to external actors (the “interpreters”: experts in the same industry, in adjacent domains or in “outside of the network” domains) who can provide insightful reflections and challenging assessments, and to customer-users for testing value propositions. Let us now focus our attention on the upper left quadrant of the matrix in Fig. 5.1: this is the case of high-effort and single-stage processes. An interesting example is represented by Strategic Roadmapping workshops, which aim to capture in a single large poster (Strategic Roadmap)—in a visual, synthetic and integrated way—the expected evolutionary dynamics in markets, products and technologies.11 These workshops create an organizational context that facilitates discussion of emerging scenarios and knowledge sharing that is synthesized and visualized with a roadmap. The basic format of a strategic roadmap should include (Fig. 5.2): • three horizontal layers: market (the evolution of customer needs and competitive factors), products and services offered to the market, and technologies; • the visualization of the time horizon in the X-axis; e.g. short, medium and long term (to be customized accordingly to the dynamics of an industry: short ¼ 2 years, medium ¼ 4 years, etc.).

8

Verganti (2016). Verganti underlines the importance of the work of the sociologist Michael Farrell Collaborative Circles: Friendship Dynamics and Creative Work (2001), who studied the collaborative dynamics of the impressionists and other innovative groups in art and science. 10 For a compelling analysis on the birth of Microsoft Xbox and the role of the radical circles, see Verganti and Shani (2016). 11 Phaal et al. (2007). 9

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5 Searching for Innovation Opportunities: Idea Generation and Technology. . . Short term

Medium term

Market

ProductService Systems

Technology

Long term

WHY?

WHAT?

HOW?

Fig. 5.2 The standard architecture of a strategic roadmap (adapted from Phaal & Palmer, 2010; Phaal & Muller, 2009)

This standard architecture can be customized according to specific situations, both in terms of number and content of horizontal layers and time frame. For example, particular sub-categories can be identified in the “technology” layer that focuses on critical components and skills. If the company provides a subsystem to another company, the “product” layer could be divided into two zones that illustrate both the evolution of the subsystem and the final product. The same applies to the market perspective, which could be broken down into two sub-categories: direct customers and end-users. What is important is to maintain a suitable format to provide an integrated and concise vision and to support interaction and dialogue between the various business perspectives and functions. The aim is to develop a consensus on the vision of the future, and the identification of challenges and opportunities. The strategic roadmap provides a structured framework for discussing, collecting and analysing information on three critical issues across multiple time horizons: • Market layer: Why innovate? • Product-service layer: What to offer? • Technology layer: How? A Roadmapping workshop has to be carefully prepared and planned: on the one hand, the roadmap architecture has to be defined according to the specific company situation; on the other hand, participants have to do a preparation work before the group session. Participants are invited to prepare their “visions” and summarize them in post-it cards. This preparation activity is a way to stimulate and focus the intelligence activities that people informally conduct in their daily activities and relationships; afterwards, the visions of the participants are shared during the

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workshop. The workshop should include a divergent phase (sharing the visions and generating further visions that emerge during the interaction) and a convergent phase to bring out the emerging key issues (aggregating, for example, the visions in clusters) and to determine the importance of the individual visions through a group vote. Roadmapping is a process of knowledge sharing, in which inconsistencies can arise, and alternative visions of the future have to be valued. The search for consensus in such sessions should not be forced; in imagining the future, it is perfectly acceptable that there might be conflicting visions that lead to alternative scenarios. We now conclude our examination of Fig. 5.1 by shifting our attention to the lower part of the matrix, where reference is made to initiatives characterized by a low level of effort and investment. Many creativity techniques can be used in focused sessions of Idea Generation12 (a one-off single session; or multiple short sessions, distributed over time, using different techniques). These techniques aim to break the established patterns of reasoning and the predefined structures with which the problem to be addressed is interpreted. An interesting example is the morphological analysis technique (also called Idea Box), which structures the creative process in the following steps: 1. Identify the relevant parameters that describe the “problem to solve” and on which to work to solve the creative challenge. For example, if the focus was the search for a new lamp, the parameters could be the following: power supply, light intensity, material, type of bulb, lamp positioning, etc.; 2. Find possible variations for each parameter; for example, for the power supply: battery, mains, crank, etc. It is important to try to identify “anomalous” variations (the crank, in our example) to increase the creative potential of the technique; 3. Try, in random mode, to combine the variations of the parameters; each combination acts as a stimulus to the generation of new product ideas. With four parameters and five variations for each parameter, 3125 combinations are possible; if only 5% of these were of any use, we would have about 150 potential new ideas available (Case Study 5.1). New ideas are often the result of a bricolage:13 a unique combination of existing information and knowledge. Morphological analysis technique leverages on this peculiar quality of creative processes, stimulating the imagination of participants with unusual and provocative combinations.

12 13

See Michalko (2010). For an interesting analysis on the origin of “good ideas”, see Johnson (2010).

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Case Study 5.1 (by Mauro De Bona) The company that manages the Predazzo lift in Northern Italy (LATEMAR 2200) is working to find an idea to increase the number of users of the lift from the bottom of the valley to the mountain. The aim is to attract families who frequent Val di Fiemme and the surrounding areas, especially in summer: they have small children, are not mountain experts and do not walk. The hikes on the Latemar, on the other hand, are all quite demanding or long enough for this type of customers: it is necessary to create loop trails, of medium-short length and with no difference in altitude, which can also be covered with a stroller. The challenge is not easy, both because we do not want to carry out interventions that have an impact on the environment, and because the LATEMAR 2200 Marketing and Special Projects Manager aims at something totally new, original and different from the solutions adopted in mountain or tourist centres. During a half-day workshop led by two creative experts, it was decided to adopt the morphological analysis technique. Once the problem had been defined (how to bring more families to altitude during the summer?), the main elements (or parameters) that have a relation with the problem were listed. It is a good practice to identify a dozen or so factors; in the following, we analyse only 4 of them: • • • •

users of the lift; purpose of the excursion; type of excursion; accompanying persons.

For each element, the possible variations were then identified: the suggestion given by the experts is to insert at least one intentionally absurd, illogical, strange one, to favour the breaking of the schemes and a “lateral” vision of the problem. In the following table, these “divergent” variations are reported in italics. ELEMENTS Lift users Purpose of the excursion Type of the excursion Accompanying persons

VARIARIATIONS Men, Women, Kids, Animals . . . . Walk, Enogastronomy, Study, Rescue mission . . . Daily, Short, Naturalistic, Interactive . . . Tour Guide, Hostess, Lifeguard, Artist . . .

Therefore, having created the “space of possibilities” to explore, we proceeded to search for combinations of declinations. One of the first (continued)

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Case Study 5.1 (continued) combinations that has been proposed and that deliberately includes also some divergent variations, is the following: ELEMENTS Lift users Purpose of the excursion Type of the excursion Accompanying persons

CHOSEN VARIATION Kids Rescue mission Interactive Artist

This combination has triggered a series of thought-provoking reflections: • Who or what needs saving? • How can the excursion be made interactive? • How does an artist accompany children? These questions have stimulated the memory of local traditions and legends: it is said that dragons inhabited the Latemar mountain in ancient times. Maybe some of them are still in the woods today and need to be rescued. . . The idea of a new service started to take shape. The result of the workshop was the embryo of what later became the thematic trail The Forest of Dragons of MontagnAnimata: • the trail is expressly dedicated to families with children; • children must save a dragon egg through challenges to be overcome along the way; • along the trail there are seven interactive stations, operated by sensors and electromechanical devices, which allow children to interact with trees and rocks to solve puzzles and to save the dragon; • many of these stations are designed and made by artists from the valley, who also accompany children on his adventure.

5.2

Innovation Contest

An innovation contest is a challenge launched to a group of “problem solvers”, who decide to work on the proposed problem. The challenge is characterized by a welldefined time window, during which the problem-solvers submit their work, and closes with the selection and rewarding of the winning ideas. The idea of outsourcing an innovative activity through an open call to a wide audience is not a novelty of the twenty-first century. A renowned historical precedent is the case of the “Longitude Prize” of 1714. The British government offered a huge gold award (the equivalent of about £10 million today) to reward those who

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could devise a quick and efficient method of calculating longitude at sea with extreme precision. The longitude problem had plagued sailors for centuries and that a few years earlier (in 1707) had caused the death of more than 2000 sailors, and the destruction of an entire fleet of warships off the Scilly Islands due to an error in longitude estimation. Fascinating is the outcome of this competition: a watchmaker (John Harrison) solved the problem by proposing a time-based method (the measurement of the difference between London time and local time in the middle of the sea) in sharp contrast to the dominant approaches grounded on star observations14 and supported by astronomers and scientists of the time such as Newton and Halley. Internet and social networking technologies have given a dramatic boost to the growth of innovation competitions through crowdsourcing software platforms, where challenges are launched to a “global crowd” of unprecedented size. An example that highlights the transformative potential of an approach to innovation and product development centred on the use of the “crowd” is the Topcoder case. Through its challenge-based crowdsourcing platform (which has a worldwide community of more than one million software developers and data scientists) it is possible to manage the entire software development cycle—from idea generation to deployment to customers. Through a web platform it is possible to define and launch a problem to the crowd connected to the platform, examine the proposals, select the winners, award the prize and get the intellectual property of the winning idea (or formulate other ways of compensation, for example, a collaboration agreement on future activities). Many crowdsourcing platforms enrich the competitions with collaboration mechanisms between participants (the possibility of viewing personal profiles, systems for exchanging messages and mutual comments on ideas, viewing user activities, etc.). The inclusion of a “community” dimension in a competitive environment is in line with some research15 that shows a positive correlation between the increase in the intensity of cooperation between participants and the novelty of ideas. The possibility to cooperate in an innovation contest allows accomplishing what naturally happens in innovation workshops: the amplification of the creative capability resulting from the cross-fertilization of ideas (Case study 5.2). Case Study 5.2 DESALL (desall.com) is a crowdsourcing platform that integrates competitive and cooperative elements in design competitions and involves an international community of industrial designers from all over the world (to date, more than 90,000 people from over 150 countries). DESALL offers companies a tool to strengthen their organizational skills to generate new product ideas, create new (continued)

14

The story of John Harrison and the development of the four timekeepers in response to the Longitude Prize is fascinating; see Sobel (1996). The watches are on display at the Royal Observatory Greenwich in London. 15 See Bullinger et al. (2010) and Hutter et al. (2011).

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Case Study 5.2 (continued) architectural and aesthetic solutions or optimize existing products. The versatility of the platform and the modularity with which the contests can be structured have made it possible to collaborate with various small-to-medium sized companies, which can open—with limited investments—their exploratory processes and access a vast and varied network of creative and design skills, unimaginable until a few years ago. There are two fundamental reasons behind the diffusion of the crowdsourcing phenomenon: the power of diversity and the strength of intrinsic motivation. The real advantage of having a large number of people or organizations trying to deal with the problem is the variety of approaches, skills, competencies and experiences that the individual problem-solvers bring with them.16 Winning ideas might be far removed from the company’s core competencies: crowdsourcing tries to transform a distant search into a local search—looking for members of the crowd with very different knowledge and expertise, but for whom solving the problem is a local search and so easier to address.17 The search for diversity makes it possible to leverage the innovative potential of the so-called intersectional ideas; Johansson18 proposes a distinction between directional and intersectional ideas. The former are those that have a clear direction: directional innovation improves a product or service in a fairly predictable way. Intersectional innovations, on the other hand, make sudden leaps in unexplored directions; they are the result of a combination of concepts belonging to different disciplines, cultures and areas of specialization. The emphasis given to diversity contrasts with the natural predisposition to consider “experts” as the best possible choice in selecting the resources to be used to solve problems. Recent research has shown that the use of expertise is unavoidably accompanied by the acquisition of constraints on how to solve problems. The “marginality”, i.e. the fact of being on the “margins” from a technical point of view (being distant in terms of expertise from the field of reference of the problem) and from a social point of view (being remote from the establishment in one’s professional community) can be an advantage and not a disadvantage. Fringe individuals or organizations have alternative knowledge and adopt novel approaches that can prove successful in solving the problem.19 The importance of intrinsic motivation must also be considered. Indeed, the role of financial motivation is essential in attracting problem-solvers. Still, in this context other types of incentives also have a significant impact: the reputation effect in social

16

Boudreau and Lakhani (2013). Afuah and Tucci (2012). 18 Johansson (2004). 19 Jeppesen and Lakhani (2010). 17

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networks, the pleasure of engaging in an intellectual challenge of one's own choice, the passion linked to a particular area of expertise.20 The motivational dimension has a far from negligible importance: this temporary organizational form (the problemsolver network that is activated for a specific problem) seems to be able to create a climate of passion, an environment of high involvement that induces everyone to give their best. Precisely that environment that is so difficult to achieve in traditional organizations and a significant challenge that companies need to face in the future. Contemporary management literature is rediscovering the key role of intrinsic motivation in rethinking management systems.21 The growing and widespread awareness of the value of building organizational spaces that allow people to seek new challenges, test their skills and grow through learning, is linked to the massive emergence of unstructured network collaborations unimaginable until 20 years ago. A phenomenon that cannot go unnoticed and that cannot be ignored. The global diffusion of crowdsourcing has stimulated many companies to reflect on the potential of innovation tournaments reserved for internal staff (internal crowdsourcing22), as organizational conditions fostering the inner creative potential often lack. Knowledge is, in fact, typically geographically fragmented and organizationally isolated. Internal crowdsourcing is a tool aimed at capturing the knowledge distributed in the organization, to transform it into a new internal source of innovative ideas. The organization of internal contests requires an accurate definition of the tournament management process and reward mechanisms (Case Study 5.3). Case Study 5.3 VIDEOTEC, a company operating in the field of professional products for video surveillance, felt imperative to strengthen its innovative capability by introducing a new company process (the “Factory of Ideas”), aimed at creating idea “tournaments” systematically. The launch of the tournaments and the selection of winning ideas is the responsibility of VIDEOTEC’s top management team. In designing the tournament’s operating mechanisms, particular attention was paid to defining a standard for the presentation of ideas that, on the one hand, would be extremely simple but, on the other hand, would present all the elements useful for a transparent evaluation; the format developed gave rise to an idea proposal composed of 7 sections (product vision, features and functionality, target segments, etc.). The critical point in enhancing idea generation processes is the cadence in launching challenges. With this in mind, internal contests related to the world of video surveillance are presented every six months to stimulate the interest and curiosity of employees towards strategic topics (the Videotec Challenges). (continued) 20

Boudreau and Lakhani (2009). See Birkinshaw (2012) and Pink (2011). 22 Malhotra et al. (2017). 21

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Case Study 5.3 (continued) Particular attention has been paid to the precise definition of the idea evaluation process and the question of rewards, critical elements to ensure objectivity and to encourage participation. The evaluation of ideas is organized in two rounds. In the first round, rapid analysis of attractiveness is carried out based on a series of predefined key factors; if the outcome is positive, in-depth technical analysis or the development of a preliminary concept with the logic of time-boxing is required (the concept must be developed in a well-defined time window). At the end of the second round, if the proposal is accepted, the product idea will be inserted in the project portfolio, and the priorities of the portfolio will be re-examined.

5.3

Exploring the Technology Space

Exploration of the technology space is the set of activities aimed at advancing the frontier of technical and scientific knowledge through technology development projects,23 whose aim is the resolution of knowledge gaps through research and experimentation to ensure the feasibility of new product ideas. Technology development activities aim at introducing significant changes in the performance and technical attributes of products. The objective is to transform a technology that has been identified as promising into a technology that is mature and reliable enough to be incorporated into a specific product, achieving a set of “technological feasibility points”—the minimum set of performance requirements that the new technological subsystem must ensure to reduce uncertainty and risk in product development.24 As we have already noted in Chap. 3, technology development needs to be decoupled from product development for three fundamental reasons.25 1. The high levels of uncertainty that characterize technology development projects require managerial practices that differ from those suited for product development.

23

We will not consider basic research activities, typically carried out in public institutions and Corporate Research facilities of very large multinational companies. This activity is characterized by very long-time horizons and aims to advance scientific knowledge. 24 See Eldred and McGrath (1997a, 1997b). 25 On the issue of decoupling between technological development and product development, see Chiesa (2001), Nobelius (2004), Chiesa and Frattini (2007), Chiesa et al. (2009), De Toni et al. (2015).

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2. The need to accelerate product development processes makes it necessary to contain risk and uncertainty and, therefore, to minimize technological exploration within product development. 3. The demand for ever-higher levels of reliability and quality of products is more easily achievable with well tested and consolidated technologies; technological innovations in a subsystem generate a significant increase in uncertainty on system behaviour and escalate the complexity of product design and system integration. Two major problems need to be addressed to manage technological development effectively: • the definition of a process to manage the internal activities of technology exploration, based on the recognition of the high levels of uncertainty and unpredictability that characterize research and experimentation; • the organization of technological collaborations, to expand internal development capabilities and absorb skills and knowledge from outside.

Managing Technology Development Technology development is an activity characterized by high levels of uncertainty; the company ventures into territories where it has gained limited or (in extreme cases) no experience, and the results of the exploration are, of course, hardly predictable. The specific flow of activities that transforms a promising technology into a tested and sufficiently reliable technology cannot be thoroughly predefined. On the contrary, in the context of product development activities, it is possible to standardize how new products are conceived, designed, industrialized and launched on the market (see Chaps. 6 and 7). Technology development is an iterative process, centred on a succession of cycles of experimentation and learning, and it must be managed accordingly; a consolidated model is the Technology-Stage-Gate26 (TSG) (Fig. 5.3). In the TSG process, the starting point of a technology development initiative is a summary document (project charter) that defines its objectives and aligns the expectations among the different corporate stakeholders: the purpose of the project charter is to set the project goals, the resources to be committed and the timing of the first Technology Review (TR0). The activities that end with the TR0 event represent the initial planning phase (Phase 0). In this phase, the technological feasibility points are defined, i.e. the objectives in terms of performance and reliability of the new technology. For example, in the case of the development of new printer ink, one of the critical performances to be specified could be the minimum drying time and the desired level of stability and repeatability in obtaining the experimental results.

26

See Ajamian and Koen (2004) and Cooper (2006).

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Project Charter

TR0

TR1, 2, ... N

Phase 0 Planning

Experimentation Cycles 1, 2, ... N

Iteration

to Level 3 – New Product Development

Fig. 5.3 Managing technology development: The Technology-Stage-Gate (TSG) process

a) The initial plan of the Future-3D technology development project, formulated in TR0 TR1

TR0 Phase 0 Planning

CYCLE 1

TR2 CYCLE 2

today

TR3 CYCLE 3

Planning

b) The actual progress of the Future-3D project TR1

TR0 Phase 0 Planning

CYCLE 1

TR2 CYCLE 2

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TR3 CYCLE 3

CYCLE 4

CYCLE 5

Fig. 5.4 Technology-Stage-Gate process: planned cycles (a) vs. actual cycles (b)

At the same time as defining the technological feasibility points, an outline plan of the number of experimentation cycles and a detailed plan of the first cycle downstream of TR0 must be drawn up. Each TRi (Technology Review—TRi) represents a review event aimed at evaluating the results and planning the next exploration and experimentation cycle. As an example, let us consider a technology development project concerning the redefinition of the architecture and geometry of a product subassembly in the perspective of additive manufacturing (“Future-3D”). In Fig. 5.4, we represented two snapshots of the “Future-3D” project: • the upper part (a) illustrates the vision of the TSG process in TR0; at that moment, three cycles of experimentation are foreseen to complete the project. For example,

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in cycle 1 it is expected to study the four architecture alternatives identified in the planning phase; in cycle 2 only the two most promising ones will be refined and tested; in cycle 3 the solution that proved to be the most performing in cycle 2 will be further developed; • the lower part (b) shows the actual progress of Future-3D project in TR4, which differs both in time length and numbers of experimentation cycles from the original plan: the iteration plan (a) had to be redefined to respond to unforeseen results and new information acquired along the exploration journey. Project uncertainty and complexity influence the number of iterations and the ability to accurately define their technical content. The sequence of iterations should be oriented to maximize learning and the reduction of critical uncertainties; this planning logic is known as critical assumption planning.27 The basic idea is to prioritize the activities that can significantly close key project unknowns in the shortest possible time. The aphorism “fail fast, fail cheap28” well summarizes this management practice. Each Technology Review event is focused on the results of the cycle that has just ended to redefine the project plan; given the intrinsic unpredictability that characterizes exploration, detailed activity planning can realistically be carried out only with a time horizon limited to the next iteration. During the course of the project, it may also be necessary to redefine the number of iterations, as seen in the example in Fig. 5.4. On the contrary, in product development, the number of phases and deliverables could be standardized ex-ante (see Chap. 6).

Technological Collaborations The continuous growth in product complexity among many sectors makes technological collaborations with external partners necessary. As we have already highlighted in the second chapter, in a world where knowledge is hyper-specialized and distributed, it is no longer possible to innovate relying exclusively on one’s own internal forces of exploration. There are multiple organizational forms to access external sources of knowledge and to manage technological collaborations; these forms of relationship between the company and external actors can be grouped into four main categories:29 acquisitions, joint ventures, alliances and outsourcing. In acquisitions, one partner (P1) acquires full ownership of the tangible and intangible resources of the other partner (P2) to exploit P2’s technological expertise. In a joint venture, P1 and P2 create a third company (JV) by allocating financial, physical and know-how resources to it; the JV contract specifies the distribution of

27

Sykes and Dunham (1995). Hall (2007). 29 For an in-depth analysis of the four forms of collaboration, see Chiesa (2001); Chiesa and Manzini (1998). 28

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exploitation rights and ownership of the results of the activities between the partners. The alliance is a form of non-equity collaboration (i.e. without an exchange of shares) in which two or more partners share tangible and intangible resources to carry out together specific activities with well-defined objectives. Typically, the alliance is set by a formal contract that defines the contributions of the individual partners and the exploitation rights of the results. In the fourth form of collaboration—outsourcing—P1 acquires the results of the technology development activities carried out by P2, which has used its intellectual and physical resources to conduct the exploration effort. In traditional forms of outsourcing, P2 is selected ex-ante through an evaluation of its knowledge and expertise. In recent years a new form of outsourcing has emerged: adopting the logic of open innovation contests, partners can be selected ex-post through a crowdsourcing platform. Innocentive.com (IC) is, in this regard, an example. Born in 2001 as a spin-off of the pharmaceutical company Eli Lilly, IC manages a web-based platform mainly focused on solving scientific and technological problems. A team of challenge experts (PhDs in a wide range of scientific disciplines, from biology to mechatronics) supports corporate clients in the formulation of the “challenge” to be launched, articulating a clear and complete description of the problem and the requirements the solution must meet.30 IC technological challenges are divided into two types: (i) theoretical, where a detailed description of the solution is expected, without experimental tests or prototypes; and (ii) reduction to practice (RTP), in which solutions are required experimentally validated with the creation of physical prototypes. IC platform also supports the setting up of problem-solver teams, to face the most complex challenges from an interdisciplinary point of view, through virtual collaboration spaces (Team Project Room). At the same time, IC coordinates the definition of legal agreements between the group members regarding intellectual property rights and awards sharing. Another example of a technological crowdsourcing platform is NineSigma. Its Technology Search/RFP (Request for Proposal) is aimed at finding technological partners and attracting solution proposals from new and unexpected sources; the research does not include a prize but ends with a partnership agreement. Ninesigma also offers an Innovation Contest service—an open tournament organized in two main phases. In the first phase, the problem to be solved is initially defined, and solution requirements are specified. The challenge is presented to the problem-solver community, who are asked to submit a preliminary solution concept. Then a group of finalists is selected for phase 2 (prototype development); Ninesigma partially remunerates the activities of the second phase for all finalist teams, to increase the quality of phase 2 proposals and to spread the message that the sponsoring company values the prototyping efforts and not only the final winning result. 30

See Spradlin (2012).

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References Afuah, A., & Tucci, C. L. (2012). Crowdsourcing as a solution to distant search. Academy of Management Review, 37(3), 355–375. Ajamian, G., & Koen, P. (2004). Technology stage-gate: A structured process for managing highrisk new technology projects. In P. Belliveau, A. Griffin, & S. Somermeyer (Eds.), The PDMA Toolbook 1 for new product development. John Wiley & Sons. Birkinshaw, J. (2012). Reinventing management: Smarter choices for getting work done. John Wiley & Sons. Boudreau, K., & Lakhani, K. (2009). How to manage outside innovation. Sloan Management Review, 50(4), 69–76. Boudreau, K. J., & Lakhani, K. R. (2013). Using the crowd as an innovation partner. Harvard Business Review, 91(4), 60–69. Brown, T. (2005). Strategy by design. Fast Company, 95, 52–54. Brown, T. (2008). Design thinking. Harvard Business Review, 86(6), 85–92. Bullinger, A. C., Neyer, A. K., Rass, M., & Moeslein, K. M. (2010). Community-based innovation contests: Where competition meets cooperation. Creativity and Innovation Management, 19(3), 290–303. Chiesa, V. (2001). R&D strategy and organization. Managing technical change in dynamic contexts. Imperial College Press. Chiesa, V., & Frattini, F. (2007). Exploring the differences in performance measurement between research and development: Evidence from a multiple case study. R&D Management, 37(4), 283–301. Chiesa, V., Frattini, F., Lazzarotti, V., & Manzini, R. (2009). Performance measurement of research and development activities. European Journal of Innovation Management, 12(1), 25–61. Chiesa, V., & Manzini, R. (1998). Organizing for technological collaborations: A managerial perspective. R&D Management, 28(3), 199–212. Cooper, R. G. (2006). Managing technology development projects. Research-Technology Management, 49(6), 23–31. De Toni, A., Siagri, R., & Battistella, C. (2015). Anticipare il futuro: Corporate Foresight. Egea. Eldred, E. W., & McGrath, M. E. (1997a). Commercializing new technology - I. ResearchTechnology Management, 40(1), 41–47. Eldred, E. W., & McGrath, M. E. (1997b). Commercializing new technology—II. ResearchTechnology Management, 40(2), 29–33. Hall, D. (2007). Fail fast, fail cheap. Business Week, 32, 19–24. Hutter, K., Hautz, J., Füller, J., Mueller, J., & Matzler, K. (2011). Communitition: The tension between competition and collaboration in community-based design contests. Creativity and Innovation Management, 20(1), 3–21. Jeppesen, L. B., & Lakhani, K. R. (2010). Marginality and problem-solving effectiveness in broadcast search. Organization Science, 21(5), 1016–1033. Johansson, F. (2004). The Medici effect: Breakthrough insights at the intersection of ideas, concepts, and cultures. Harvard Business Review Press. Johnson, S. (2010). Where good ideas come from: The natural history of innovation. Penguin. Kelley, D., & Kelley, T. (2013). Creative confidence: Unleashing the creative potential within us all. Crown Business. Kelley, T. (2001). The art of innovation: Lessons in creativity from IDEO, America’s leading design firm. Crown Business. Kim, C. W., & Mauborgne, R. (2005). Value innovation: A leap into the blue ocean. Journal of Business Strategy, 26(4), 22–28. Kim, C. W., & Mauborgne, R. (2017). Blue ocean shift. Pan Macmillan. Malhotra, A., Majchrzak, A., Kesebi, L., & Looram, S. (2017). Developing innovative solutions through internal crowdsourcing. MIT Sloan Management Review, 58(4), 73. Michalko, M. (2010). Thinkertoys: A handbook of creative-thinking techniques. Ten Speed Press.

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Nobelius, D. (2004). Linking product development to applied research: Transfer experiences from an automotive company. Technovation, 24(4), 321–334. Phaal, R., Farrukh, C. J. P., & Probert, D. R. (2007). Strategic roadmapping: A workshop-based approach for identifying and exploring innovation issues and opportunities. Engineering Management Journal, 19(1), 16–24. Phaal, R., & Muller, G. (2009). An architectural framework for roadmapping: Towards visual strategy. Technological Forecasting and Social Change, 76(1), 39–49. Phaal, R., & Palmer, P. J. (2010). Technology management—Structuring the strategic dialogue. Engineering Management Journal, 22(1), 64–74. Pink, D. H. (2011). Drive: The surprising truth about what motivates us. Penguin. Sobel, D. (1996). Longitude. Harper Business. Spradlin, D. (2012). Are you solving the right problem? Harvard Business Review, 90(9), 84–93. Sykes, H. B., & Dunham, D. (1995). Critical assumption planning: A practical tool for managing business development risk. Journal of Business Venturing, 10(6), 413–424. Thomke, S. (2001). Enlightened experimentation: The new imperative for innovation. Harvard Business Review, 79(2), 66–75. Verganti, R. (2016). The innovative power of criticism. Harvard Business Review, January– February, 89–95. Verganti, R. (2017). Overcrowded. Designing meaningful products in a world awash with ideas. MIT Press. Verganti, R., & Shani, A. B. R. (2016). Vision transformation through radical circles. Organizational Dynamics, 2(45), 104–113.

6

Product Development: Managing Uncertainty and Knowledge Integration

Abstract

Product development activities are aimed at transforming new feasible product ideas into profitable products. This transformation requires the progressive reduction of uncertainty about market needs and technological choices. Market uncertainty arises from the complexity in translating customer needs (which change over time) into functional and emotional product attributes; technical uncertainty is linked to the degree of novelty in product and manufacturing process design decisions. In designing a product development process, it is essential to distinguish two kinds of problems: the strategic problem of risk and uncertainty reduction; and the organizational problem of cross-functional integration in the formulation of design decisions. In this chapter we first address the strategic problem of uncertainty reduction with the Stage-Gate model, exploring the concept of anticipation: the idea that the product development must be front-loaded with activities that allow to anticipate the resolution of knowledge gaps and aggressively reduce uncertainty in the early phases of the process. Then we present the recent evolution of the Stage-Gate model towards a process that is consistent with turbulent market conditions, in which the focus on anticipation is combined with reaction—the ability to keep the product concept open, preserving options in the advanced stages of development ( flexible Stage-Gate). Finally, we focus on the role of integration events in tackling the organizational problem of cross-functional integration and the emergence of spiral and lean approaches to product development.

# Springer Nature Switzerland AG 2021 S. Biazzo, R. Filippini, Product Innovation Management, Management for Professionals, https://doi.org/10.1007/978-3-030-75011-4_6

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Product Development: Managing Uncertainty and Knowledge Integration

The Strategic Problem of Uncertainty Reduction: The Stage-Gate Model

The effectiveness and speed of uncertainty reduction depend on the quality of the product development process, which defines the standard of good practices (tools, methodologies and key decisions flow) that guide projects execution. Uncertainty reduction is a critical problem since the cost of unforeseen engineering changes (due, for example, to the late discovery of the ineffectiveness of a product attribute in satisfying customer needs) grows exponentially with the progression of development activities. A well-known model for dealing with risks in product development is the StageGate process which can be defined as a “map for moving new product projects from idea to launch1”. This map clarifies: • the “stages”—sets of activities and key deliverables (the tangible and transferable outputs of complex activities); • the strategic discontinuities of the process (“gates”) in which senior leadership has to review the key deliverables of the preceding stage and make a critical decision: go ahead, revise some activities or kill the project. The generic Stage-Gate model illustrated in Fig. 6.1 is composed of five stages and four gates and closes with a post-launch review. The definition of each stage highlights its main product-related objectives (for example, Stage 1 is called “concept development”); actually, each stage contains a complex set of multidisciplinary activities. The model described is deliberately generic, and its structure is not representative of any best-practice standard. Each company must design its Stage-Gate model according to its competitive and organizational conditions, in order to effectively solve the risk and uncertainty problem and optimize project lead times. Moreover, as we will see further on, this model is scalable, i.e. adaptable to the complexity of the innovative effort. A product development project starts when a product idea (generated by exploration activities) is (a) sufficiently attractive to justify the investment of time and resources needed to carry out the initial stages of development, and (b) acceptable from a technological and market risk perspective. Portfolio Management practices outline how to evaluate, select and launch development projects (Chap. 9). Below there is a brief description of the generic Stage-Gate model. Stage 1: Concept development. The product idea outlined during exploration activities is transformed into a well-rounded product concept: the description of the benefits, functions and target market of the future product. It is an extremely critical phase where the development direction is defined, setting out the utilitarian and

1

The Stage-Gate model was developed and disseminated by Cooper (1988, 2017a).

6.1 The Strategic Problem of Uncertainty Reduction: The Stage-Gate Model

Feasible Product Idea

Portfolio Management

Product Development Project

83

Intelligence & Exploration

Product Development Process

Gate 1

Gate 2

Gate 3

Gate 4

Stage 1

Stage 2

Stage 3

Stage 4

Stage 5

Concept Development

System-level Design

Detail Design

Testing & Validation

Launch

Project Value Proposition Post-Launch Review

Fig. 6.1 A generic Stage-Gate model

hedonic product attributes that have to satisfy a selected bundle of customer needs (see Chap. 7). The complexity of this stage obviously depends on the level of detail of the product idea provided at the beginning of the process; in the case of well-organized exploration activities (level 2 of the pyramid), preliminary product concepts are sometimes generated and tested with experimental prototypes before the product development process begins.2 In these situations, the objective of the first stage is to analyse and refine these preliminary concepts from a multi-functional perspective and converge to a comprehensive product concept definition to be evaluated at Gate 1. As Ulrich et al. (2020) emphasize, product success is heavily influenced by the quality of the underlying concept: “a good concept is sometimes poorly implemented in subsequent development phases, but a poor concept can rarely be manipulated to achieve commercial success”. Product concepts can be more or less open, i.e. envisage alternative solutions that must be subsequently evaluated and selected; in the following Sect. 6.2, dedicated to flexible forms of Stage-Gate systems, we will discuss this topic. Chapter 7 illustrates the key activities of product concept definition, selection and testing.

2

See Koen et al. (2001), Ulrich et al. (2020), Terwiesch and Ulrich (2009).

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Gate 1. In this first gate, the strategic alignment, feasibility, manufacturability and market attractiveness of the product concept are evaluated. Stage 2: System-level design. The concept is further specified by refining the overall technical product architecture. Architectural choices concern (1) the definition of a scheme by which the functions of the product are arranged into physical building blocks (components and subassemblies), (2) the level of modularity and the planning of product options and variants, (3) the use of carryover (sharing of components between product generations) and (4) the allocation of design responsibility to suppliers (co-design). Virtual or physical prototypes are built and tested to detect unforeseen problems in product architecture and validate the design with customers. At the same time, supply-chain choices, quality tests, manufacturability constraints and trade compliance issues are explored. Sales and marketing plans are also drafted along with phase-in and old product phase-out strategies. Finally, the development team create a plan for the following stages and perform an economic analysis of the project (business case). As shown in Fig. 6.1, the first two stages create the Project Value Proposition (PVP), which is a strategic set of documents (deliverables) to be evaluated by the management board (see Chap. 7). Gate 2. It is the gate that opens the doors to product and supply-chain detail design; after this gate, financial commitments are considerable. A senior leadership team evaluate the attractiveness of the project from a strategic and financial perspective and approve (or not) the Project Value Proposition. Stage 3: Detail Design. In this stage, the project team undertake the detail technical design of the product. Geometry, materials and tolerances of components are specified; manufacturing processes and tooling are defined, along with the configuration of the supply chain. During this stage, one or more physical prototypes are made, which are tested internally and, in certain contexts, validated with customers in their use environment. Gate 3. The top management and the project team of decision-makers review the deliverables of the detail design stage and re-evaluates the financial and strategic attractiveness of the project. Stage 4: Testing and Validation. Product design decisions and manufacturing processes are definitively tested and validated with pilot production runs (pre-series) using the intended supply-chain system. Field tests of the product under actual use conditions are also be conducted to identify any remaining flaws (product use testing). Furthermore, a “soft launch” to a small and selected set of customers can be carried out to capture early market feedback. Finally, a full market launch and production ramp-up plans have to be finalized; the market launch plan typically concerns key decisions regarding sales-force training, product price positioning, communication strategies and distribution channel configuration. Gate 4. This gate opens the door to full-scale production and commercialization. The evaluation is focused on the results of Stage 4 tests, the readiness of operations and market launch plans, and the permanence of financial and strategic attractiveness of the project.

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Stage 5: Launch. This final stage involves the implementation of market launch and production ramp-up plans, which requires a highly coordinated action between marketing, production, logistics, distribution and sales departments. Post-Launch Review. It marks the formal conclusion of the development project, where the product and the project’s performance are assessed a few months after the launch date. Post-launch reviews are a powerful mechanism for organizational learning and knowledge transfer between projects. The objective of this retrospective analysis is to capture any lessons learned from the project to continuously improve the development process, capitalizing not only on successes but also on failures. A well-designed Stage-Gate process is characterized by these five key features. (1) The Stage-Gate model fosters a strong focus on customer needs. Product concept desirability must be a central question in Stages 1 and 2, which has to be explored through concept testing with customers. In the case of flexible StageGate (see Sect. 6.2), iterations with customers may also continue in the late stages through prototyping cycles (or “spirals”): build, test, get customer feedback, revise.3 (2) The stages are cross-functional; each stage requires skills and efforts of multiple functional areas and organizational units. In particular, the contribution of marketing, design and manufacturing functions is central throughout all the process (team working is strategic especially in the first stages and at the end of the process). (3) Each stage requires an increase in human and financial resource allocation compared with earlier commitments. (4) Each stage requires the creation of a set of well-defined and prescribed deliverables, necessary to ensure the quality of the overall development results. Deliverables represent the key inputs to be assessed in gate reviews. (5) The Stage-Gate system is scalable: different configurations of stage and gates are needed according to the complexity and the innovativeness of the project. For example, the generic model in Fig. 6.1 is potentially appropriate for complex and innovative projects; compact versions (e.g. merging stages 1 and 2 into a single-stage) should be devised for simpler projects, aimed at incremental product improvements or cost reductions. Figure 6.1 depicts two loops to highlight the possibility that the project team, during Stage 3 (or 4), has to revisit a decision made in the previous gate, thereby generating rework. For example, an architectural choice defined in Stage 2 has to be reconsidered during Stage 3 and, as a consequence, some activities already completed in the previous stage have to be carried out again. Typically, this can happen due to the emergence of unforeseen technical trade-offs between product specifications and/or unexpected conflicts between cost and desired product attributes. The term “rework” is used to emphasize that such process loops are, in 3

Cooper (2017b).

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general, undesirable (as they increase the development lead time and consume resources) and unpredicted. The first two stages are crucial to avoid such undesirable loops. In this perspective, the basic idea in the traditional Stage-Gate system is to (1) anticipate knowledge generation as much as possible by “front-loading” the development process with activities aimed at reducing design uncertainties as much as possible, and (2) conceive a sharp, early and fact-based product definition4 at Gate 2. There are several methods to anticipate knowledge generation and reduce design uncertainties during the first two stages of the development process: • the early involvement of all functions in the organization to tackle project challenges with a multidisciplinary perspective; • the management of knowledge transfer between projects to learn from experience systematically; • the adoption of integrative methods aimed at supporting problem-solving and decision-making processes of multidisciplinary teams (i.e. the concept-screening matrix in Chap. 7); • the testing of early prototypes to explore the feasibility (the alignment with the firm’s technical and organizational capabilities) and integrity (the alignment with customer needs) of product concepts. With front-loaded prototyping,5 concept development and system-level design take the form of trial and error iterations. The objective is to acquire a sufficient level of knowledge and confidence to justify the project's transition to a phase that requires high financial commitments (Stage 3). An interesting example of front-loaded prototyping is the Electrolux Stage-Gate model: in the Product Concept Definition and Validation phase6 (Stage 2 in a 7-Stage process), a prototype version of the new product concept is tested by a sample of consumers. The concept test is deemed successful when at least 70% of the sample express positive evaluations for the Electrolux product concept compared to existing solutions. It is also important to clarify the relationship between Stage-Gate and concurrent engineering. Concurrent engineering7 is the practice of performing interdependent activities in parallel (generally product and process development). Let us consider, for example, the case of Fig. 6.2 where Stage 3 consists of 4 activities that must be completed before Gate 3. Now let us focus on activity A and activity B: A is the design of a plastic component, and B is the design of the mould needed to manufacture it in large volumes. Activity B is dependent on activity A because it relies on information

4

Cooper (1988) and Cooper and Kleinschmidt (1986). See Smith (2007). 6 The basic structure of the Electrolux process is illustrated in Committed to Quality, Electrolux QBook (2016). 7 Terwiesch et al. (2002). 5

6.1 The Strategic Problem of Uncertainty Reduction: The Stage-Gate Model

STAGE 3

STAGE 4

Overlapping

GATE 3

Activity E

Activity A

Activity F

Activity B

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Overlapping

Overlapping Activity G Activity C

Activity H

Activity D

Fig. 6.2 Overlapping: a task execution strategy

supplied by A. With concurrent engineering we try to overlap the execution of A and B in order to reduce the cumulative lead time of the two activities. Whoever performs B must start working with preliminary information8 and be able to minimize the risks of rework due to the lack of precision in the initial information (for more details, see Chap. 8). The practice of concurrent engineering is, therefore, a project management problem (scheduling and coordinating parallel activities) and not a process management problem (the determination of key events and deliverables); the overlapping “intensity” of a Stage-Gate system depends on the task execution strategy9 adopted within the stages (Fig. 6.2). As we will see in Chap. 8, the effectiveness of simultaneous execution strategies relies on the ability of the project team to interact frequently, to exchange preliminary information and manage adjustments that result from the concurrent execution of interdependent activities. Therefore, the juxtaposition between Stage-Gate and concurrent engineering has no rationale: stages are by definition in sequence as they cannot be executed simultaneously. A stage is defined by the set of deliverables that have to be completed before the next strategic approval event (gate). If there is a need to move an activity from one stage to another, the content of the stages has to be changed. In Fig. 6.2, for example, the activity E previously placed in Stage 4 (e.g. the creation of a 3D prototype) could be anticipated in Stage 3, so the decisions in Gate 3 must take into account of the information given by a 3D prototype. This modification in the content of Stages 3 and 4 represents a redesign of the Stage-Gate system, which has no impact on task execution strategy within the stages (e.g. the anticipated activity E could be executed after activity D or in parallel). A further clarification concerns the detrimental phenomenon of bureaucratic deviance of Stage-Gate systems, i.e. the excessive demand for deliverables and reporting for control purposes. The bureaucratic deviation of Stage-Gate (often seen in large organizations) has induced some supporters of Lean Product Development (see Sect. 6.5) to consider the Stage-Gate system not consistent with one of the

8 9

Clark and Fujimoto (1991), Wheelwright and Clark (1992). Terwiesch et al. (2002).

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fundamental Lean principles—the flow, i.e. the minimization of process lead times through the elimination of non-value adding activities. Stage-Gate systems are often seen as a superstructure that would hinder the flow through discontinuity decision points; this perspective is highly questionable, as the real problem is the bureaucratic deviance which distorts the system and undermines its benefits,10 not the system per se. An appropriately designed Stage-Gate system creates a process standard that addresses two fundamental challenges—risk management and quality of execution—and can reduce development lead time since it contributes to limit rework during the process. As we will see in the next setion, the real problem is to define a process standard that is consistent with the level of uncertainty and complexity of the projects to be managed.

6.2

Flexible Product Development and the Evolution of Stage-Gate Systems

A large body of research has pointed out the need for a contingent approach in the design of new product development processes.11 Development processes suitable for situations where technological and market uncertainty are moderate might prove to be ineffective in turbulent environments. The focus on anticipation directed at sharp and early product concept definition loses its effectiveness in contexts characterized by high uncertainty and turbulence. Multiple factors can generate such hardly predictable environments. • customer expectations are evolving rapidly, and the “problems to be solved” are not well understood; • architectural solutions present a wide range of possibilities, as a dominant product design12 has not yet established; • the product concept involves the inclusion of new technologies on which the development team has limited knowledge; • competition is intense, and there is a high risk of new entrants who may disrupt the “rules of the game” of the industry. In such contexts, freezing all product concept decisions in the early phases of development is a risky strategy entailing substantial rework in the following stages of the process. Anticipation must be accompanied by reaction capabilities: to be able to partially define the product in the early stages and efficiently introduce

10

The limits and application problems of the Stage-Gate model are discussed in Cooper (2008). A synthesis on how to adapt the development process to the level of environmental uncertainty can be found in MacCormack et al. (2012). 12 A dominant design is how a product is “supposed to look and operate” in the minds of users and producers; it is the de facto standard in terms of fundamental technical choices (see Utterback, 1994). 11

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concept changes late in the process, during detailed product and process design activities. Development processes focused on reaction are defined as flexible.13 A flexible development process has three main characteristics: • the ability to delay the “freezing” of the product concept, specifying what is fixed and what is flexible;14 • a focus on fast experimentation cycles through prototyping to explore alternative solutions, close knowledge gaps and introduce design changes in the advanced stages of development; • the involvement of customers in prototyping cycles to systematically receive information on the matching of design solutions to customer needs. Customer involvement in experimentation cycles can be implemented in different ways: for example, through prototype use testing with selected customers at the company’s headquarters; or with the creation of user communities or panels to maintain a continuous interaction during development, or the promotion of partnerships and cooperative relationships with lead users. Recent evolutions of Stage-Gate systems15 address this problem: the principle of “sharp and early product definition” is replaced by the principle of planned flexibility:16 only some areas or part of the product (the fixed parts) are frozen at the end of the Project Value Proposition phase (Gate 2 in Fig. 6.1), while decisions on flexible parts are delayed, leaving room for exploration of different options in the Detail Design Stage. In a flexible Stage-Gate, the product concept is kept open in a controlled mode, delaying specific system-level design decisions to acquire more information through experimentation and prototyping; this approach has been called set-based design17 (or set-based concurrent engineering) in Lean Product Development literature (see Sect. 6.5). Flexibility implies investment: creating and maintaining options during the late phases of product development is a costly endeavour (except for software, where the cost of change is much lower than for hardware). Front-loading efforts are, therefore, crucial also in the perspective of flexibility in order to understand which elements of the product concept can be fixed in early stages and which should be explored experimentally during detail design. Flexible product elements are those that require

13 For a systematic review and a critical analysis of product development flexibility, see Biazzo (2009). 14 Ballé et al. (2016) and Morgan and Liker (2018). 15 The evolution of the Stage-Gate system towards adaptability and flexibility is discussed in Cooper (2008, 2014). 16 Verganti (1999). 17 See Ballé et al. (2016), Ward and Sobek (2014), Morgan and Liker (2006), Kennedy et al. (2014), Smith (2007).

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more accurate prototype testing (for example, an alpha-prototype test) to better understand the design space and converge to a final solution. A well-known example of flexibility is the Toyota product development process, widely studied as one of the best-practice cases in the literature of Lean Product Development.18 Toyota deliberately keeps many options open until the first vehicle prototype stage (called 1S). In stage 1S, the prototype department builds the first new vehicles (30 to 50 on average) from soft tools. Toyota uses this stage not only for comprehensive vehicle testing and manufacturability assessment but also for making final decisions on product subsystem alternatives. For example, during 1S Toyota typically tests two or three options of the power steering module and several variants of the exhausts systems and other functional parts (such as the air conditioning units or suspension springs).19 It is clear that the speed of experimentation cycles plays an essential role in the search for flexibility; three key factors influence rapid experimentation:20 • an organization that allows fast information exchange; the most suitable organizational forms for this purpose are the heavyweight team or autonomous team structures (see Chap. 8); • the use of advanced technologies to support experimentation, such as virtual and rapid prototyping; • the adoption of modular architectures and decoupled interfaces between modules of the product that allow isolating product areas that require greater flexibility, so that the design changes in one area do not propagate into other parts of the system. In Fig. 6.3, we highlighted the difference between traditional and flexible StageGates by focusing on the approach to managing convergence to the final product concept: (a) in a traditional Stage-Gate, the concept is frozen and thoroughly defined at Gate 2. The detail design stage is viewed as an implementation effort and, in predictable environments, the frozen concept is easily and rapidly transformed into a manufacturable product; projects are characterized by minimal changes in the product concept;21 (b) the traditional Stage-Gate collapses in turbulent environments; erroneously believed “definitive” concept decisions must be revisited, thereby generating rework, extra-costs and delays in lead time; (c) in a flexible Stage-Gate process, the product concept is kept (partially) open, delaying specific system-level design choices and preserving options to acquire

18

See Ward et al. (1995), Sobek et al. (1998, 1999), Morgan and Liker (2006), Ballé et al. (2016). See Sobek (1997), Smith (2007). 20 See Verganti (1999) and Thomke (1998, 2001). 21 Iansiti (1995). 19

6.3 Spiral Development Processes: The Emergence of Agile Approaches

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Gate 2

Project Value Proposition

Detail Design

(Stage 1+2)

(Stage 3)

Closed Concept

(a) Traditional Stage-Gate in predictable environments

(b) Traditional Stage-Gate in turbulent environments

Build-Test-Revise Iterations to narrow down a set of options

Closed Concept

Rework Build-Test-Revise Iterations to narrow down a set of options

Rework

Open Concept (c) Flexible Stage-Gate

Build-Test-Revise Iterations to narrow down a set of options

Fig. 6.3 Traditional and Flexible Stage-Gate systems

more information through experimentation and prototyping in the following stages.

6.3

Spiral Development Processes: The Emergence of Agile Approaches

As we have seen in the previous section, anticipation (of decisions) and reaction (to market and technology changes) are two fundamental characteristics of product development processes. We can identify four development process models depending to the level of reaction and anticipation that is pursued (Fig. 6.4): traditional Stage-Gate, flexible Stage-Gate, functional relay-race and spiral development. (a) Traditional Stage-Gate, appropriate for a stable environment, is focused on anticipation: as a matter of fact, the main goal is to converge as early as possible to a sharp and comprehensive product definition before entering the detail design stage. (b) Flexible Stage-Gate simultaneously searches for a high level of anticipation and reaction: anticipation capability is needed to understand which areas of the concept have to be kept open; reaction capability is required to manage multiple

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Spiral Development

Flexible Stage-Gate

Functional relay-race Process

Traditional Stage-Gate

REACTION Level

LOW

HIGH

LOW

ANTICIPATION Level Fig. 6.4 Anticipation and reaction: four process model

options and be fast in detail design iterations to converge to the final concept configuration. (c) Functional relay-race process is characterized by a lack of attention to both dimensions: each functional department, as in a relay-race in athletics, independently contributes to product development. Typically, Marketing hands-off product requirements to Product Design which, after the completion of its activities, “passes” the project on to Manufacturing. The well-known effects of this underperforming process are long lead times and significant extra-costs linked to errors and rework.22 (d) Spiral development. Low anticipation and high reaction identify the so-called spiral process.23 The key feature of spiral processes is the minimization of investment through anticipation, while flexibility is maximized through an incremental and iterative product development approach; the emphasis is on experimentation, development speed and interaction with customers.

See Takeuchi and Nonaka (1986). Cooper (2008) uses the term “functional, phased-review” process. See also Buijs (2003). Another expression typically used to refer to this traditional development systems is the “over-the-wall” approach (Scott 1998). 23 See Blank and Dorf (2012) and Boehm (1988). 22

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93

Product Increment

Rapid Iterations (from concept development to testing)

ITERATIONS

Launch

Product Release

Product Increment Review

Fig. 6.5 Spiral process in software development: an iterative-incremental approach

The idea of spiral development is a key feature of Agile Software Development methodologies. Spiral processes in software development proceed through a series of rapid iterations embracing all phases from concept development to testing and validation, which are called Sprints in the Scrum framework—one of the best-known Agile approaches. Each iteration ends with a review of its output—the “product increment” (a fully tested and usable new software functionality). The product increment review (Sprint Review in Scrum) is the base for planning and launching the next cycle, which creates a new increment and/or modifies the preceding one (see Chap. 8). Iterations proceed until enough features are completed to release a product into live operation to customers (Fig. 6.5). The applicability of the iterative-incremental process model to the development of physical products has, however, severe limitations: • physical products are not as divisible as software: it is incredibly challenging to build hardware incrementally through a sequence of “product increments”; • physical products are less malleable than software: the cost and lead time of hardware design changes are much higher than software code rewriting. For hardly divisible and malleable products, the most suitable process model for pursuing flexibility (in turbulent environments) is one that succeeds in integrating reaction with anticipation, such as the flexible Stage-Gate systems. To significantly increase the flexibility of their development processes, many companies have recently experimented the integration between Scrum (one of the best-known Agile software development methodologies) and Stage-Gate, leading to Agile-Stage-Gate hybrids,24 which combine the gating system with the adoption of

24

See Sommer et al. (2015), Cooper (2016) and Cooper and Sommer (2016).

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MVP

Rapid Global Iterations (all development activities, from concept development to launch)

ITERATIONS

Customer Feedback

Fig. 6.6 Spiral development process in the Lean Start-up approach

a decentralized and iterative-incremental approach to manage the development stages (see Chap. 8). Despite the limitations mentioned above in hardware product development, the spiral development process is considered the reference model in the Lean Start-up approach,25 where each spiral has the objective to bring to the market a version of the product quickly (the “minimum viable product”—MVP) through a rapid and global iteration which encompasses all development activities, from concept development to launch. With customer feedback, it is possible to revise the initial assumptions, restart the cycle, bring the re-designed product to the market and receive further customer input to iterate again (Fig. 6.6). The MVP contains the minimum set of critical features to be usable and attractive for the so-called “earlyvangelists” (early adopters + evangelists): early adopters that are willing to take risks by acquiring the new product and bet on the new business. These customers are also “evangelists” as they will be the ones who can spread and testify the value of the product to the rest of the market. Once the attractiveness of the MVP with the earlyvangelists has been verified, the successive iterations are aimed at enriching the MVP to win over mainstream customers and thus find a scalable and profitable business model. It is important to underline once again that the concept of MVP and rapid iterations are well suited to the context of software products, while in the case of physical products the iterative-incremental approach to product development and launch is a high-risk and a high-cost endeavour.

25

See Blank and Dorf (2012), Blank (2013), Ries (2011).

6.4 The Organizational Problem of Cross-Functional Integration in the. . .

6.4

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The Organizational Problem of Cross-Functional Integration in the Formulation of Key Design Decisions

We can consider two different approaches to address the problem of cross-functional integration in a development process: • a task-based approach: the pattern of execution of all activities is fully specified ex-ante. The integration problem is solved by an in-depth standardization of the workflow; • an event-driven approach: a series of integration events26 are defined in advance. An integration event is a milestone in which a cross-functional team shares knowledge, elicits feedback and makes key decisions regarding technical choices. A task-based approach is obviously suitable for repetitive processes (for example, in the case of very simple incremental improvement projects or small product customizations), where it is useful to specify ex-ante the operational details that define the transformation of inputs into outputs. Product development processes are, on the contrary, difficult to standardize in detailed procedures that aim to predefine the execution pattern of the complex network of tasks needed to transform a product idea into a manufacturable product. In an event-driven approach, the focus is on decision making27 and the organizational problem of cross-functional integration is solved with a minimum amount of standardization: the specification of the sequence of key design decisions through the definition of integration events. The case of Konsberg (a Swedish manufacturer of automotive components) well illustrates the nature of these events. Konsberg, as part of a Lean transformation project of the product development process, has introduced in its Stage-Gate system a progression of 5 integration events inside the first two stages:28 • in Stage 1 (Define) there are 2 integration events: Project Targets Integrated, where the team meets to finalize and formalize the project targets; and Select what to Develop & Quote, where the team makes an agreement on which design ideas will be proposed to the customer; • in Stage 2 (Development—this stage starts after quote approval and the Definition Gate) there are 3 integration events: Success Assured, in which the team has to demonstrate for one or more alternative solutions the fulfilment of customer requirements; Final Design Selected, where the team reviews early prototypes

26

See Ward and Sobek (2014), Oosterwal (2010), Mascitelli (2011), Radeka (2017), Morgan and Liker (2018). 27 For a comprehensive review on product development decisions, see Krishnan and Ulrich (2001). 28 The example is taken from Ward and Sobek (2014) and integrated with internal documents of Kongsberg Automotive, which describe in detail their development process—called KBD (Knowledge Based Development).

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and virtual models to converge to the final solution; and, finally, the Design Fixed event is focused on reviewing, adjusting and freezing the final design with the customer before the Tooling Gate (where senior management approves production investments). The inclusion of such events within development stages is aimed at synchronizing the activities in a pull mode: key design decisions to be made in an integration event pull the work of the development team. An integration event is most effective when (1) its purpose is precisely defined (which key decisions have to be made?), and (2) key decisions are based on some form of prototype. While gates are strategic decision points focused on the evaluation of the past by top managers (deliverables are examined to open or not the doors to the next stage), integration events are future-oriented: key decision points to steer the evolution of the new product in a specific direction. Key design decisions at the core of integration events are those choices that have a crucial impact on customer value and product profitability and require a high level of cross-functional collaboration, such as: the technical specification of customerrelevant product attributes and performance, material choices, product architecture definition, the selection of a specific supplier’s solution for a subassembly or makeor-buy decisions. The definition of integration events can follow two distinct approaches. A first approach is to define ex-ante a sequence of events to establish a standard progression of key design decisions, as in Case Study 6.1 and in the Konsberg case previously discussed. Case Study 6.1 PLASTIK is a medium-sized company that manufactures plastic products to furnish indoor settings such as garages and laundry rooms, as well as outdoor areas like gardens, terraces and verandas. Its product development process includes six Milestone Review (MR1. . .MR6) that have been divided into strategic approval events (gate) and integration events (see Fig. 6.7): • MR1 (Integration Event): selection of a set of alternative product concepts for further study and refinement; • MR2 (Gate): concept freeze; • MR3 (Integration Event): assessment of die design alternatives and selection of the best option. • MR4 (Gate): project economics approval; • MR5 (Integration Event): first try-out assessment to identify die adjustments; • MR6 (Gate): first pilot production run assessment and approval of production ramp-up and sales launch.

6.4 The Organizational Problem of Cross-Functional Integration in the. . .

Stage 3

Stage 2

Stage 1 MR2 (Gate) Concept freeze

97

MR4 (Gate) Project Economics approval

MR6 (Gate)

Ramp-up approval

MR1 (Integration Event) Selection of alternative concepts MR3 (Integration Event)

Assessment of die design alternatives MR5 (Integration Event)

First tryout assessment for die adjustments

Fig. 6.7 Integration events and gates in PLASTIK development process

A second approach is to define a standard cadence of integration events: each Stage is structured as a sequence of time-boxed iterations, and the content of each event is specified as the project progresses; this logic draws inspiration from the spiral development model and agile approaches. For example, in Case Study 6.2, a standard cadence of four weeks is established for the Product and Process Design Stage. Case Study 6.2 VTEC designs and manufactures HVAC (Heating, Ventilation and Air Conditioning) solutions for industrial markets. The product development process is structured with a single Gate, called Unique Selling Proposition & Concept (USP&C); this strategic event separates the two main Stages into which the process is divided: Feasibility Stage and Product & Process Design Stage. The Feasibility Stage is managed with a time-box approach: a time limit consistent with project complexity is allocated (e.g. 3 months), and the date of the USP&C event is planned. The responsibility for this Stage is entrusted to a so-called Concept Team composed by the Project Leader and representatives from the marketing & sales, manufacturing and after-sales service departments. In the USP&C Gate, a top management committee approves the “Project Value Proposition” (see Chap. 8) with a partially open concept (continued)

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Feasibility Stage

Integration Event 2 Design Loop 2

Integration Event 3 Design Loop 3

Product & Process Design Stage USP & C Gate

Fig. 6.8 The VTEC development process

Case Study 6.2 (continued) that includes a range of options in terms of subsystem performance characteristics. In VTEC, a three-months cadence of integration events is established; Integration events represent a pull signal for the project team—the “last responsible moment29” to make specific key design decisions. The number of Design Loops is planned in the USP&C Gate accordingly to the complexity and novelty of the project, along with the definition of the specific objectives of the first integration event (Fig. 6.8). In defining a product development process, three dimensions have to be considered (Fig. 6.9): 1. the establishment of number and position of strategic discontinuities (gates); the “no-gate” option shown in Fig. 6.9 may be adopted in small organizations when top management is involved continuously in product development projects and/or full strategic decision-making autonomy is entrusted to the project manager; 2. the standardization of good practices through the creation of a set of stages with prescribed deliverables; 3. the definition of integration events (with or without a standard cadence) to tackle the organizational problem of cross-functional integration in formulating key design decisions.

29

A set-based design approach is characterized by a progressive narrowing of a set of options over time. The “last responsible moment” idea refers to the ability to preserving options and delay as much as possible a critical decision without dramatically impacting the project deadlines or the development costs (see Ward et al., 1995; Sobek et al., 1999; Kennedy et al., 2014).

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(2) Standardization of Good Practices: Stages & Key Deliverables #2 Gate

(1) Strategic Discontinuities (Gates)

Gate 1

Gate 2

(2) Standardization of Good Practices: Stages & Key Deliverables #1 Gate

Gate

(2) Standardization of Good Practices: Stages & Key Deliverables #0 Gate

(3) Integration Events

Fig. 6.9 Defining a product development process: three dimensions

6.5

Lean Thinking in Product Development

John Krafcik, in his paper at the end of eighties setting out the results of MIT’s ground-breaking research into the competitive situation of the automotive industry in the world,30 used the term “Lean” for the first time to describe a new approach to operations management that overcomes traditional mass-production techniques. Two years later, the results were disseminated by Womack, Jones and Roos with the well-known book The Machine that Changed the World. Since then, a large body of research has focused on the diffusion and potential applications of Lean approaches outside manufacturing. In 1996, Womack and Jones advocated the competitive need to transform any process in a Lean way, developing the conceptual model of the five principles of Lean Thinking.31 The five principles represent a compelling and fascinating synthesis of what the future status of a “Lean Organization” could be. A Lean Organization (1) profoundly understands what value means for the customer (Value); (2) knows in detail how value is created and delivered (Value Stream); (3) searches for a continuous flow of value in carrying out activities by eliminating any form of waste (Flow); (4) aims to

30 31

Krafcik (1988). Womack and Jones (1996).

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respond promptly to the market, being “pulled” by customers (Pull); (5) continuously pursues improvement in search of a (never attainable) perfection (Perfection). Lean Manufacturing has now clearly established itself as the dominant paradigm in operations management. However, the translation of Lean concepts into product development processes (Lean Product Development—LPD) is by no means straightforward. Product development significantly differs from manufacturing processes in terms of intensity of cross-functional communication flows and task repetitiveness and uncertainty. The “translation” of Lean Thinking in product development can be synthesized into 12 key principles,32 which address process, project (Chap. 8) and portfolio (Chap. 9) management issues.

Principle 1. Focus on Customer-Defined Value LPD literature emphasizes that delivering customer-defined value is the most important task in product development.33 The product concept has to be defined in the early stages of the process to outline the product objectives from the customer perspective. As flexibility and set-based design are key features of LPD processes (principle 6), it is considered essential to create open product concepts specifying fixed and flexible elements, in order to preserve options in the advanced stages of development and converge to final solutions with more accurate information (see Sect. 6.2).

Principle 2. Early Identification of Manufacturability Problems Waste linked to the lack of consideration of manufacturing implications of design solutions is strongly highlighted in LPD literature, addressing an issue widely debated in the Design for Manufacturing (DFM) research stream.34 Manufacturing departments have to be involved at the beginning of the development process to anticipate knowledge generation on manufacturability issues ( front-loading problem-solving35).

32 The 12 key LPD principles summarize the results of two previous works (Biazzo et al., 2016; Panizzolo et al., 2014). 33 Morgan and Liker (2018). 34 See, for example, the classic work of Adler (1995). 35 Thomke and Fujimoto (2000).

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Principle 3. Focus on Integration Events LPD literature strongly underlines the crucial role of integration events in managing key design decision and cross-functional integration (see Sect. 6.4).

Principle 4. Intensive Supplier Involvement (Co-Design) The increase in the breadth and depth of specialist knowledge needed in developing increasingly complex products calls for the mobilization of specialized sources of technical knowledge outside the company—especially suppliers. LPD suggests that organizations have to build a strong partnership with a restricted base of suppliers of critical parts or subsystems to leverage their specialized knowledge better and optimize system-level design, searching for a high level of integration between components and the product.36

Principle 5. Focus on Modular Architectures and Variety Reduction The design of modular products and the search for waste from “useless variety” due to components with different characteristics but which could be standardized without affecting product performance, is a strategic necessity in a context where customization of products and services is becoming an increasingly widespread trend: product variants explode and customers demand specific solutions for their specific needs. Modularity allows to offer customized products while maintaining efficiency and speed of delivery;37 it allows to pursue both customer variety and component standardization. Moreover, modular product architectures can isolate product areas that require greater flexibility and change, facilitating set-based design (see Sect. 6.2 and principle 6).

Principle 6. Focus on Set-Based Design A set-based design approach is characterized by a progressive narrowing of a set of options over time: multiple solutions are explored in parallel to converge to the final one. The central idea is to preserve options in the detail design stage and keep the product concept open38 (see Sect. 6.2). The set-based approach is generally juxtaposed with the traditional point-based design style—“jump to the solution,

36

See Clark (1989) and Ward and Sobek (2014). See Danese and Filippini (2012). 38 See Ward et al., 1995; Sobek et al., 1999; Kennedy et al., 2014). 37

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then fix”: select as early as possible what is considered the best solution, and then iteratively modify it to solve problems that will appear later in the project.39 In order to effectively explore multiple solutions, it is necessary to develop an experimentation capability and be fast in prototyping cycles (see Sect. 6.2).

Principle 7. Create a “Supermarket” of Reusable Knowledge Organizations that have developed effective means to capture and share knowledge eradicate a fundamental waste: re-invention of solutions already implemented and repetition of design errors. Knowledge, to be reusable, has to be formalized, generalized (it must include information on how it was created and in what context, to understand the limits of applicability) and easily accessible. The metaphor of the “supermarket40” suggests what an effective knowledge management system has to look like: knowledge “items” should be easily searchable, visible and retrievable. A well-known example is the accumulation of engineering knowledge in a database of trade-off curves (stored in standard A3 format)— a fundamental element of the Toyota product development system:41 trade-off curves define the limits of technical possibilities in a system by graphically illustrating the key relationships between parameters (for example, the noise emitted and the back pressure on a muffler42).

Principle 8. Search for Heavyweight Project Managers LPD strongly advocates the role of a heavyweight project manager.43 His/her responsibilities go far beyond simple coordination: he/she is the decision maker, the champion and the guardian of the product concept,44 with a strong influence over the people working on the project. There is a highly suggestive expression used in LPD literature to refer to this Project Manager archetype: Entrepreneurial System Designer (ESD). This denomination highlights that the primary responsibility of a heavyweight project manager is to lead the system-level design choices and deliver value to the customer with a profitable supply chain.

39

Morgan and Liker (2018). Radeka (2012). 41 See Ward and Sobek (2014); Morgan and Liker (2006); Ward et al. (2018). 42 Kennedy et al. (2014). 43 Clark and Wheelwright (1992). 44 Clark and Fujimoto (1990). 40

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Principle 9. Establish Teams of Responsible Experts LPD team members must be responsible for the project success, not only for the outputs of their activities. It is also expected that they continuously develop their expertise, learning from experience and staying up to date with technical and scientific literature.

Principle 10. Decentralized, Iterative and Visual Project Planning & Control In LPD systems, the act of planning is a coordination activity that must be carried out by the people carrying out the work. Plans must be simple to update, easy to read and immediately accessible and visible; the relational paradigm of Project Management is embraced, characterized (1) by a decentralized, cadenced and iterative approach to planning and control and (2) by the visualization of work and transparency of information. In this perspective, it is necessary to create an adequate physical context for interactions and team integration. The Obeya Room (“big room”) is the place where the team meets and where all information about the project is permanently displayed in an easily visible way (Visual Project Board).

Principle 11. Takt Time in Portfolio Planning Setting a takt time in portfolio planning means defining a cadence in project launches:45 it is the “heartbeat” of the product development “factory” (see Chap. 9). The purpose of the takt time approach is to create a development system capable of generating a constant flow of new products at a given pace.

Principle 12. One-Piece Flow in Project Execution The one-piece flow concept addresses the problem of resource overload and team fragmentation due to the assignment of multiple projects to team members. Project prioritization and cadence should minimize multitasking in order to maximize flow and increase focalization in project execution.

The concept of portfolio cadence was introduced by Wheelwright and Clark (1992)—the “development train schedule”—and was taken up, many years later, by Oosterwal (2010) and Ward and Sobek (2014). 45

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References Adler, P. S. (1995). Interdepartmental interdependence and coordination: The case of the design/ manufacturing interface. Organization Science, 6(2), 147–167. Ballé, M., Morgan, J., & Sobek, D. K. (2016). Why learning is central to sustained innovation. MIT Sloan Management Review, 57(3), 63–71. Biazzo, S. (2009). Flexibility, structuration, and simultaneity in new product development. Journal of Product Innovation Management, 26(3), 336–353. Biazzo, S., Panizzolo, R., & de Crescenzo, A. M. (2016). Lean management and product innovation: A critical review. In A. Chiarini, P. Found, & N. Rich (Eds.), Understanding the lean enterprise - strategies, methodologies, and principles for a more responsive organization. Springer. Blank, S. (2013). Why the lean start-up changes everything. Harvard Business Review, 91(5), 63–72. Blank, S., & Dorf, B. (2012). The startup owner’s manual: The step-by-step guide for building a great company. K&S Ranch. Boehm, B. W. (1988). A spiral model of software development and enhancement. Computer, 21(5), 61–72. Buijs, J. (2003). Modelling product innovation processes, from linear logic to circular chaos. Creativity and Innovation Management, 12(2), 76–93. Clark, K. B. (1989). Project scope and project performance: The effect of parts strategy and supplier involvement on product development. Management Science, 35(10), 1247–1263. Clark, K. B., & Fujimoto, T. (1990). The power of product integrity. Harvard Business Review, 68 (6), 107–118. Clark, K. B., & Fujimoto, T. (1991). Product development performance: Strategy, organization and Management in the World Auto Industry. Harvard Business Review Press. Clark, K. B., & Wheelwright, S. C. (1992). Organizing and leading “heavyweight” development teams. California Management Review, 34(3), 9–28. Cooper, R. G. (1988). The new product process: A decision guide for management. Journal of Marketing Management, 3(3), 238–255. Cooper, R. G. (2008). Perspective: The stage-gate idea-to-launch process—Update, what’s new, and nexgen systems. Journal of Product Innovation Management, 25(3), 213–232. Cooper, R. G. (2014). What’s next?: After stage-gate. Research-Technology Management, 57(1), 20–31. Cooper, R. G. (2016). Agile–stage-gate hybrids: The next stage for product development blending agile and stage-gate methods can provide flexibility, speed, and improved communication in new-product development. Research-Technology Management, 59(1), 21–29. Cooper, R. G. (2017a). Idea-to-launch gating systems: Better, faster, and more agile. ResearchTechnology Management, 60(1), 48–52. Cooper, R. G. (2017b). Winning at new products. Accelerating the process from idea to launch (5th ed.). Basic Books. Cooper, R. G., & Kleinschmidt, E. J. (1986). An investigation into the new product process: Steps, deficiencies, and impact. Journal of Product Innovation Management, 3(2), 71–85. Cooper, R. G., & Sommer, A. F. (2016). Agile-stage-gate: New idea-to-launch method for manufactured new products is faster, more responsive. Industrial Marketing Management, 59, 167–180. Danese, P., & Filippini, R. (2012). Direct and mediated effects of product modularity on development time and product performance. IEEE Transactions on Engineering Management, 60(2), 260–271. Iansiti, M. (1995). Shooting the rapids: Managing product development in turbulent environments. California Management Review, 38(1), 37–58. Kennedy, B. M., Sobek, D. K., & Kennedy, M. N. (2014). Reducing rework by applying set-based practices early in the systems engineering process. Systems Engineering, 17(3), 278–296.

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Koen, P., Ajamian, G., Burkart, R., Clamen, A., Davidson, J., D’Amore, R., Elkins, C., Herald, K., Incorvia, M., Johnson, A., Karol, R., Seibert, R., Slavejkov, A., & Wagner, K. (2001). Providing clarity and a common language to the “fuzzy front end”. Research-Technology Management, 44 (2), 46–55. Krafcik, J. (1988). Triumph of the lean production system. MIT Sloan Management Review, 30(1), 41. Krishnan, V., & Ulrich, K. T. (2001). Product development decisions: A review of the literature. Management Science, 47(1), 1–21. Sobek, D. K., Liker, J. K., & Ward, A. (1998). Another look at how Toyota integrates product development. Harvard Business Review, 76(4), 36–49. MacCormack, A., Crandall, W., Henderson, P., & Toft, P. (2012). Do you need a new productdevelopment strategy? Research-Technology Management, 55(1), 34–43. Mascitelli, R. (2011). Mastering LPD: A practical, event-driven process for maximizing speed, profits and quality. Technology Perspectives. Morgan, J. M., & Liker, J. K. (2006). The Toyota product development system. Productivity Press. Morgan, J. M., & Liker, J. K. (2018). Designing the future: How ford, Toyota, and other worldclass organizations use lean product development to drive innovation and transform their business. McGraw Hill Professional. Oosterwal, D. (2010). The lean machine: How Harley-Davidson drove top-line growth and profitability with revolutionary lean product development. AMACOM. Panizzolo, R., Bernardel, F., & Biazzo, S. (2014). Lean transformation in small and medium enterprises: Practices, enabling factors. In V. Modrák & P. Semančo (Eds.), Handbook of research on design and management of lean production systems. IGI Global. Radeka, K. (2012). The mastery of innovation: A field guide to lean product development. CRC Press. Radeka, K. (2017). The shortest distance between you and your new product: How innovators use rapid learning cycles to get their best ideas to market faster. Chesapeake Research Press. Ries, E. (2011). Lean startup. Crown Business. Scott, G. (1998). The new age of new product development: Are we there yet? R&D Management, 28(4), 225–236. Smith, P. (2007). Flexible product development: Building agility for changing markets. John Wiley & Sons. Sobek, D.K. (1997), Principles that shape product development systems: A Toyota-Chrysler comparison, PhD Thesis, University of Michigan. Sobek, D. K., Ward, A., & Liker, J. K. (1999). Toyota’s principles of set-based concurrent engineering. Sloan Management Review, 40(2), 67–83. Sommer, A. F., Hedegaard, C., Dukovska-Popovska, I., & Steger-Jensen, K. (2015). Improved product development performance through Agile/Stage-Gate hybrids: The next-generation Stage-Gate process? Research-Technology Management, 58(1), 34–45. Takeuchi, H., & Nonaka, I. (1986). The new new product development game. Harvard Business Review, 64(1), 137–146. Terwiesch, C., Loch, C. H., & Meyer, A. D. (2002). Exchanging preliminary information in concurrent engineering: Alternative coordination strategies. Organization Science, 13(4), 402–419. Terwiesch, C., & Ulrich, K. T. (2009). Innovation tournaments: Creating and selecting exceptional opportunities. Harvard Business Review Press. Thomke, S. (2001). Enlightened experimentation: The new imperative for innovation. Harvard Business Review, 79(2), 66–75. Thomke, S., & Fujimoto, T. (2000). The effect of “front-loading” problem-solving on product development performance. Journal of Product Innovation Management, 17(2), 128–142. Thomke, S. H. (1998). Managing experimentation in the design of new products. Management Science, 44(6), 743–762.

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Ulrich, K. T., Eppinger, S. D., & Yang, M. C. (2020). Product design and development (7th ed.). McGraw-Hill. Utterback, J. M. (1994). Mastering the dynamics of innovation. Harvard Business Review Press. Verganti, R. (1999). Planned flexibility: Linking anticipation and reaction in product development projects. Journal of Product Innovation Management, 16(4), 363–376. Ward, A., Liker, J. K., Cristiano, J. J., & Sobek, D. K. (1995). The second Toyota paradox: Delaying decisions can make better cars faster. Sloan Management Review, 36(3), 43–61. Ward, A. C., Oosterwal, D. P., & Sobek, D. K., II. (2018). Visible knowledge for flawless design: The secret behind lean product development. Taylor & Francis. Ward, A. C., & Sobek, D. K., II. (2014). Lean product and process development. Lean Enterprise Institute. Wheelwright, S. C., & Clark, K. B. (1992), Creating project plans to focus product development. Harvard Business Review, March–April, 3–14. Womack, J. P., & Jones, D. T. (1996). Lean thinking: Banish waste and create wealth in your organisation. Simon & Shuster.

7

Creating the Project Value Proposition

Abstract

The definition of a project value proposition (PVP) is a crucial and strategic phase in the development process. As we have highlighted in the previous chapter, the PVP phase consists of a broad set of multi-functional activities: the development of a product concept definition and the establishment of the product architecture; the assessment of manufacturability, quality testing and trade compliance issues; the exploration of supply-chain choices and the first definition of sales and marketing plans, along with the economic analysis of the project. PVP includes activities and deliverables of Stage 1 and Stage 2 and pinpoints the value to be offered to customers and users. This chapter will focus on the following three key activities essential to define PVP: • product concept: definition, selection and test; • product architecture: definition and carryover strategy (i.e. system-level design); • project economic analysis (base case). In the description of these activities, we will assume that the product development process starts with a broadly defined product idea, leaving the project team considerable scope for exploration in the concept development phase.

7.1

Product Concept Definition

The product concept is the result of a teamwork where several skills must be deployed to transform an idea into a clear and comprehensive definition of the new product. The contribution of a cross-functional team that can integrate three fundamental “voices” is necessary: the voice and the needs of the customer # Springer Nature Switzerland AG 2021 S. Biazzo, R. Filippini, Product Innovation Management, Management for Professionals, https://doi.org/10.1007/978-3-030-75011-4_7

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(marketing manager), the voice of engineering and the voice of the manufacturing system. Other skills, depending on product complexity and industry characteristics, may be necessary; for example, procurement expertise is critical when the strategic and economic value of purchasing components is significant. Product concept definition is a process that requires interdisciplinary integration and an iterative approach; product concepts can (and sometimes must) be modified or refined after testing or during the system-level design stage if unexpected technical and/or economic trade-offs are uncovered. Moreover, as we have seen in the previous chapter, turbulent environments require the definition of an open product concept, specifying fixed and flexible elements to preserve options in the advanced stages of development and converge to final solutions with more accurate information. The concept has to clarify: • • • • •

who are the target customers; what customer needs must be addressed; what value is offered to target customers; what makes it different from the competitors; why the company must invest in its development.

The concept must become a clear reference point for all the following development activities. It is a guide for the project team to guarantee both (a) internal integrity (consistency between the concept and the final product) and (b) external integrity (alignment to customer needs and differentiation from competing products). Therefore, it has to be formalized in a short document (the result of the work of the development team) that seek to specify: 1. 2. 3. 4.

Who are the target customers; What the product does: the utilitarian dimension of the product; What the product is or appears to be: the hedonic dimension of the product; What the product means to customers: what is the distinct value offered to customers and users? Why should they prefer our product? What are the key attributes of the product that generate satisfaction from the customer's perspective? In a nutshell, the so-called unique selling proposition should be specified. 5. What makes the product different from competitors: building a competitive positioning map (see Case Study 7.1) allows to visualize the uniqueness of the concept, considering both product attributes and price position. The positioning map is a valuable and often neglected tool that contributes to clarify the differentiation strategy and define the product concept better. 6. What value the product offers to the company: the concept has to be evaluated in the perspective of the company’s competitive strategy and product portfolio, and a first and rough economic analysis has to be performed to assess its expected profitability (base case).

The concept contains three fundamental information areas: (a) need information: the target customer needs and the new product’s unique value proposition;

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Table 7.1 The benefits map of the new lift

Smaller volumes required due to absence of a machine room Ease of installation Ride comfort Energy saving Lower maintenance costs Modern design

Construction companies +++ +++ + + +

Architects +++

Users +

+

++

+++ ++ ++ ++

(b) solution information: the functional and hedonic product attributes; and (c) business information: the economic and strategic justification of the project that constitute the so-called business case. A robust product concept has to respond to the needs of different customer categories (see Chap. 4)—the “product stakeholders”. For example, during the development of the concept of the world's first lift without a machine room, it was necessary to assess product benefits from different perspectives (Table 7.1). For construction companies and architects, the greater construction freedom and lower cost due to the absence of the machine room was the most valuable attribute. For the end-user (tenant or apartment owner), the major benefits were related to lower energy consumption and low maintenance costs, as well as greater ride comfort. A clear definition of the product concept is at the origin of many successful products. In 1936, Citroen designed a vehicle specifically dedicated to meet the needs of country people and farmers: the 2CV. Boulanger, Citroen’s CEO at the time, stated the essence of the new vehicle concept as follows: • it must carry four passengers and one sack of potatoes at 60 km/h with a consumption of 3 litres/100 km; • the suspension must allow to cross a ploughed field, with a basket of eggs on board, without even breaking one; • it must be designed simply so that a farmer, with his hat on, can get in and drive it easily, offering unquestionable comfort. It was a concept that expressed a product with a strong personality, innovative and complex to develop. The Toyota Yaris is a similar case, where a clear and strong concept contributed to Toyota successful entry in the large and hypercompetitive segment of small cars in 1999, populated by many manufacturers (Fiat, Ford, Citroen, Peugeot, Renault, Opel, Volkswagen). It was a great challenge to offer a winning vehicle in such an overcrowded market; the starting point for defining the Yaris concept was the unsatisfied or unfulfilled customer needs. Four critical needs formed the essence of the concept and were later used to communicate the value of the new product in the marketing campaign. A utility car suffers from: (a) lack of space onboard, (b) modest performance, (c) limited technology, (d) poor safety features. The concept defined by Toyota to

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attack the small car segment revolved around the metaphor of the “little genius” able to overcome these limits. The product communication was centred on “Yaris’ theorems”, such as: “the smaller the car, the bigger space inside”; or “with a 1000 cc engine, increasing power, the consumption decreases”. All these value propositions were the essence of the concept outlined at the beginning of the product development process. These two examples, so far apart in time, have in common two crucial elements that highlight the importance of a strong concept as a driving force for the success of the product. First, the concept must be challenging for designers. The technical work to implement and deliver the concept can be very demanding, as was the case for the two examples cited; product and process engineering must leverage not only all the resources and expertise within the company but also external knowledge (e.g. suppliers). Secondly, the concept must be focused on the target market’s significant and underserved needs, so it can be the basis for communicating the value of the product (see Chaps. 2 and 4). It is unnecessary to develop unusual or eccentric communication strategies if the new product is based on a concept with a strong personality and consistent with the needs of the target segment. Product communication can be built on the key elements of the concept. The search for differentiation from competitors is a fundamental activity in concept definition and is played out along three categories of product attributes: • product functionality: the opportunities for action that are afforded by a product;1 • product performance: how well a product implements its intended functions;2 • product language: the signs (material, colours, geometric shape, type of surface, brand, etc.) that can arouse emotions and evoke symbolic values3 (see Chap. 2). A simple example of a differentiation matrix is shown in Table 7.2: a company has developed a new tripod for professional photographers with two differentiating attributes (a reduced height when closed plus a lighter weight) and an aggressive price positioning against competitors. In the definition of the product concept, differentiation factors against competitors must be carefully assessed. It is quite clear that proposing a new product that is entirely similar to existing products, in terms of price and characteristics, cannot lead to success. How to clearly analyse the differences in price and features of the different products in the market? How to represent synthetically at Gate 2 the price-features combinations proposed by competitors, to better map the competitive space and define an attractive market position for the new product, thereby clarifying the unique value that is offered to customers? A positioning map is an effective tool to deal with these problems.

See Ziamou and Ratneshwar (2003): “product functionalities enable people to engage in purposeful activities, mental and physical, such as eating, traveling, reading, relaxing, communicating and so forth”. 2 Ulrich et al. (2020). 3 See Dell'Era and Verganti (2007). 1

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Table 7.2 A differentiation matrix of a tripod for professional photographers Height when closed [cm] Maximum height [cm] Minimum height [cm] Weight [kg] Price [€]

New Product 30 160 15 1.3 170

Competitor A 47 180 15 1.9 200

Competitor B 62 162 15 2.5 255

A straightforward positioning map is a matrix with two key dimensions: product attributes (X-axis) and price (Y-axis: producer’s selling price or final market price). In the X-axis we can synthesize the value offered to the customer with an overall “performance index” consisting of a weighted average of the values assigned to several product attributes that are linked to highly important needs. Relevant competitors must be identified, i.e. those who position themselves in the strategic group in which the company intends to compete with the new product. For each competitor, data and evaluations on product attributes should be collected using, for example, a group of experts (internal and external). A synthetic performance data is then obtained for each competitor; with price information, it is possible to map each product in the positioning map. We must therefore look for an empty space that is attractive to competitors: as we will see in Case Study 7.1, a pairwise comparison will be made between the hypothetical position of the new product and each competitor; this is a heuristic method that helps to identify an advantageous market position for the new product. Case Study 7.1 Company AB designs and manufactures equipped office walls (Fig. 7.1). This type of product offers, compared to traditional masonry walls, the advantage of being able to effortless modify at any time the office layout and to quickly equip the walls with furniture, shelves, etc. AB has identified four direct competitors (C1-4) and the following relevant attributes from the customer perspective: • • • • • • • •

variety of product options (number and type of available modules) aesthetic perception ease of assembly flexibility of configurations range of finishing adaptability to various architectural contexts ease of relocation wall add-ons (a wall can be equipped with different types of accessories, to complete it according to the needs of use) • soundproofing. (continued)

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Fig. 7.1 Equipped office walls

Case Study 7.1 (continued) The evaluations (using a Likert 1-5 scale) expressed by a group of experts (AB managers, installers and architects) for each competitor and each attribute were collected. The sum of the average evaluations of each attribute represents a proxy of the customer value assigned to each competitor (“performance index”); Table 7.3 illustrates the evaluation matrix (each column reports the evaluation of one expert) for competitor C3. With all the assessments obtained, it is possible to build a positioning map and investigate in which area would be possible to place the new product. Once the position of the new product has been defined, it is possible to examine its competitive strength through a pairwise comparison. Looking at Fig. 7.2, it is immediately evident that the position of the new product is advantageous compared to competitors C1 and C4 (higher performance and equal or lower price) and C2 (slightly lower performance but with lower price). C3 is instead a very aggressive competitor that has been able to contain the price for a high-performance product.

Completeness of the product Aesthetic perception Ease of assembly Flexibility of configurations Range of finishing Adaptability Ease of relocation Wall add-ons Soundproofing TOTAL

Exp1 3 3 3 4 4 4 4 3 4

Exp2 5 4 4 5 4 4 5 3 4

Exp3 4 3 3 4 4 4 4 5 3

Exp4 5 2 4 5 4 5 45 4 3

Exp5 5 4 5 4 5 3 4 5 4

Exp6 5 4 4 5 5 4 2 4 3

Exp7 4 3 4 5 4 4 4 3 3

Exp8 4 3 3 3 3 3 4 4 4

Average 4.4 3.3 3.8 4.4 4.3 3.9 4.0 3.9 3.5 35.5

7.1 Product Concept Definition

Table 7.3 Evaluation matrix of competitor C3

113

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140

AB Current Product C2

Price C4 C3 C1

New Product

50 22

30

38

Performance Index Fig. 7.2 Positioning map: an example

Another positioning analysis that simultaneously displays all the relevant attributes among competitors is the value curve,4 which highlights: • the set of product attributes on which the competition is currently focusing, usually including price; • the offering level that customers receive or experience for each attribute (in a simple qualitative scale). As we have already highlighted in Chap. 5, the value curve can stimulate a number of interesting questions: which attributes can be eliminated as no longer relevant for customers? Which attributes can be substantially reduced? (i.e. are customers currently over-served?) Which attributes can be enhanced? Which new attributes—unknown to direct competitors—can be created and new kinds of value can be offered? Figure 7.3 shows the value curve of the Nintendo Wii and its main competitors in 2006. The Wii had a disruptive impact on the market as it radically changed the kind of value offered and opened up the market attracting new users (older people and those who had no interest in traditional games).

4

The value curve is also known as “strategy canvas” (Kim & Mauborgne, 2005, 2017).

7.1 Product Concept Definition

115

HIGH Nintendo Wii (first release)

LOW

Xbox 360 & Playstation 3

PRICE

High-resolution Graphics

Games Variety

Aesthetics

Ease of Use

Physical Movement

Fig. 7.3 The Nintendo Wii Value Curve at the time of its launch (adapted from Kim & Mauborgne, 2013)

This case is useful to underline the importance of “noncustomers” and “nonusers” in concept definition. The former refers to potential customers of a company, but who buy and use competitors’ products; it is therefore fundamental to fully understand the reasons for the preference for competing products. Non-users, however, are those individuals (or companies) who, in a particular sector or market, do not buy/use that type of product at all (see Chap. 4). They are dissatisfied with current products, or they are not able to use existing products or do not have sufficient resources to buy them. A well-known example is the so-called disposable cameras. In 1987 Fuji was the first to launch a disposable camera dedicated to two segments of “non-users”: young people (who could not afford an expensive camera) and those who, having no photographic skills, did not own or use the camera (but who had the desire to take pictures). Fuji’s Quicksnap had no adjustments to either the time, lens aperture or focus (adjustments that at the time were present on all traditional cameras for skilful users). Kodak quickly realized that the market had expanded to non-users (millions of potential new customers) and, in a short time, was able to develop a new platform for disposable cameras, the FunSavers—a worldwide success for many years. New market spaces can be conquered by widening the horizon of exploration, systematically analysing non-users5 who do not buy the industry's products for

5

Kim and Mauborgne (2017) distinguish three categories of noncustomers (an expression they used to refer to non-buyers and non-users): first-tier (the soon-to-be noncustomers of the industry— people or organizations that use the current offerings minimally waiting for something better); second-tier (refusing noncustomers—who has consciously rejected the industry’s offering); thirdtier (who has never been thought as a potential customer of the industry).

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different reasons: (a) economic (hence the idea of low-end products); (b) functional (e.g. this was Fuji's initial intuition, but it was also Apple's with the first Macs that were easy to use even by non-experts); (c) geographical (e.g. lack of distribution channels) and (d) cultural (assumptions, values or preconceptions; for example, Nintendo Wii has created a product to involve adults and not only young people in the videogame).

7.2

Concept Selection

Concept definition may lead to alternative options that leverage different technical, aesthetic or functional attributes. Concept selection is a process aimed at narrowing down the set of alternatives in order to further investigate, refine and test a smaller number of competing concepts. Two distinct evaluation approaches can be adopted in the selection process: • Global or synthetic evaluation: each concept is evaluated as a whole. For example, adopting a multi-voting (or “dot-voting6”) process, each member of the development team assigns a score to each concept and the concepts with the most votes are selected. Alternatively, the AHP (analytic hierarchy process7) methodology can be used, which is based on a sequence of pairwise comparison: for each comparison a score is assigned to the winner, and the sum of the scores defines the ranking; • Analytical evaluation with decision matrices: each concept is evaluated against a predefined set of attributes, as illustrated in the following example. A company that produces outdoor accessories is committed to the development of a trail running backpack, designed for semi-professional runners and mountain running enthusiasts. Trail running backpacks differ from the classic hiking or mountaineering products in terms of key attributes: waterproof materials, excellent back grip, easy access to all compartments where water and food reserves are stored, etc. An initial “preliminary selection” matrix compares the alternative concepts, attribute by attribute, and uses a single reference concept (a backpack model of the leading competitor) as the benchmark (Table 7.4): a relative score of “better than” (+), “same as” (0), or “worse than” (–) is placed in each cell of the matrix. This first rough analysis allows the less promising concepts to be identified. Using a “weighted selection matrix” it is possible to refine the comparative examination of the concepts, assigning a percentage value to the various attributes according to their importance from the customer's perspective and assigning a score from 1 (much worse than reference) to 5 (much better than reference) to the

6 7

See VanGundy (1988). Saaty (1988).

7.3 Concept Test

117

Table 7.4 Preliminary selection matrix (backpack for trail running)

ATTRIBUTE Cold protection Lightweight Back grip Compartments accessibility Adjustability Waterproofing Quality of materials PLUS SAME AS MINUS NET SCORE (plus – minus) RANKING

Concept A Score + 0 0 + 0 + + 4 3 0 4

Concept B Score + – + 0 + + + 5 1 1 4

Concept C Score 0 + + 0 0 0 – 2 4 1 1

Concept D Score 0 0 – – + 0 – 1 3 3 –2

Concept E Score 0 + + + – 0 + 4 2 1 3

1

2

4

5

3

individual attributes. Attribute weights and scores are assigned by the team, but external expert or customers may be involved. As an example, in Table 7.5, concepts A, B, C and E were compared with this type of decision matrix. In switching from the preliminary matrix to the weighted matrix, it may be useful to enrich the set of evaluation attributes to achieve a more accurate assessment. Decision matrices should not be used mechanically; they are simply a tool to support complex decisions that must also take into account many other factors, such as technical constraints, manufacturability issues and costs.

7.3

Concept Test

Verifying the value and coherence of the selected concept(s) well in advance is not a very common practice. Conversely, this activity is extremely valuable, especially when the product is new, and the early acquisition of feedback from the market is critical. Testing is useful to converge more quickly towards the definition of robust product concept with a higher probability of market success. The purpose of testing is twofold: • verify the coherence of product attributes (consistency matrix); • measure the purchase intent to forecast sales volume.

ATTRIBUTE Cold protection Lightweight Back grip Compartments accessibility Adjustability Waterproofing Quality of materials TOTAL SCORE RANKING

WEIGHT 25% 20% 10% 10% 5% 15% 15%

Score 5 4 4 5 2 4 5

Concept A Weighted Score 1.25 0.80 0.40 0.50 0.10 0.60 0.75 4.40 1

Table 7.5 Weighted selection matrix (backpack for trail running)

Score 5 2 5 3 5 5 4

Concept B Weighted Score 1.25 0.40 0.50 0.30 0.25 0.75 0.60 4.05 2 Score 2 5 5 3 2 2 3

Concept C Weighted Score 0.50 1.0 0.50 0.30 0.10 0.30 0.45 3.15 4

Score 2 5 5 5 1 2 5

Concept E Weighted Score 0.50 1.0 0.50 0.50 0.05 0.30 0.75 3.60 3

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7.3 Concept Test

119

Verify the Coherence of Product Attributes To assess product coherence, we have to discover whether the attributes valued as important by customers are perceived as being present in the concept. This analysis helps to fine-tune the concept, avoiding overshooting (presence of irrelevant attributes that generate unnecessary costs) or undershooting (poor or missing important attributes). A “coherence matrix” may be used for this purpose, which visualizes the relation between importance and presence of a set of relevant product attributes selected by the development team: • the horizontal axis shows the importance of each attribute as perceived by customers (e.g. with a 5-point Likert scale); importance does not depend on the specific solution proposed and reveals the value of the attributes from a customer needs perspective; • the vertical axis shows the presence of each attribute in the concept as perceived by customers (always with a 5-point scale). Three main situations can be identified (Fig. 7.4): • coherence: both the importance and the presence for the n-th attribute have similar values: what the customer asks for is present (high/high); or, what it

5

Overshooting

Coherence

reduce or maintain?

Attribute PRESENCE

3 raise

Coherence

Dissatisfaction

1 1

Fig. 7.4 Coherence Matrix

3 Attribute IMPORTANCE

5

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considered irrelevant is not present (low/low), and therefore the product is not charged with unnecessary costs; • dissatisfaction: high importance and low presence; the n-th attribute is underdeveloped compared to the customer's expectations. In this case, it is appropriate to invest in this attribute to reduce very likely customer dissatisfaction; • overshooting: high presence is matched by low importance. In this case, it could be reasonable to reduce the presence of an attribute perceived as redundant, particularly if it has a significant impact on costs: customers are not willing to accept a premium price on what is not considered important. However, it should be pointed out that this position in the matrix could hide a more complex phenomenon. An attribute could be regarded as unimportant because the underlying need is latent or even hidden, but the importance of this attribute could emerge strongly over time. A “reduction” strategy would not, therefore, be a correct choice. VOC research (Chap. 4) represents an essential source of knowledge to fully understand the complex nature of customer needs and their evolution over time and to interpret the consistency matrix properly. Figure 7.5 shows a simplified example of a hypothetical consistency matrix for a new smartphone, considering four attributes: • average battery life (consistency with the low importance customers attach to this feature);

HIGH

Car connection through mirroring

Ease of replacement of components

Attribute PRESENCE

LOW

Average Battery life

Night photography

LOW

HIGH

Attribute IMPORTANCE

Fig. 7.5 A hypothetical consistency matrix for a new smartphone concept (4 attributes)

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• night photography: attribute not present in the concept, but strongly desired by customers (to be increased and improved); • easy replacement of components (e.g. screen replacement). This attribute is not particularly desired by the target customers; if this perception is considered stable in the medium-short term, it might be appropriate to rethink this feature. Otherwise, its presence might be reinforced by an appropriate communication strategy aimed at bringing the underlying latent needs to the surface; • car connection with mirroring (consistency with customer expectations). Another example of a coherence matrix is illustrated in Case Study 7.2. Case Study 7.2 Lock Inc has developed the idea of a smart bicycle padlock, equipped with fingerprint recognition, and an alarm system connected to the smartphone through a dedicated application. This high-value lock was designed for owners of electric bicycles, to be sold online. A prototype version of the product concept was submitted to a series of potential target customers, identifying the key attributes to be evaluated to build the consistency matrix (Fig. 7.6). Two characteristics (lightness and variety of size) must be improved in order to satisfy customer needs.

5 Burglary and weather resistance Smart alarm system Automatic recognition system

Attribute PRESENCE

3

Lightness

Customization

Variety of sizes

1 1

3 Attribute IMPORTANCE

Fig. 7.6 Coherence matrix for a new smart padlock

5

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The concept to be tested can be presented to selected customers in three different ways: 1. descriptive: the product and its main attributes are described in words; it can be applied for industrial products or equipment, where the buyer is a technician or a professional buyer, who are generally able to evaluate the concept even from a simple product sheet; 2. descriptive and visual: the description is accompanied by a 3D rendering when the aesthetic appearance is an essential element of evaluation; 3. descriptive, visual and physical: a physical prototype completes descriptions and renderings. Usually, tests are administered “vis a vis” collecting evaluations directly from respondents, or, if physical trials are not necessary, virtually via web applications. To obtain valuable information, it is not necessary to repeat the test on a large number of respondents; the fundamental objective is to acquire qualitative feedback from a group of representative customers. As with interviews and observation in VOC research, the concept of theoretical saturation is crucial (see Chap. 4), and it is not necessary to expand the number of respondents according to the “statistically significant” sample theory. Conjoint analysis techniques could be adopted to analyse in depth the collected data.8

Measure the Purchase Intent to Forecast Sales Volume Purchase intent and sales forecasts are key elements for ex-ante evaluation of the feasibility and profitability analysis of the new product and are an essential element in the top management evaluation of the value proposition. However, the newer the product, the more difficult the forecasts are to make, as there are no historical sales data for similar products. The concept test could be a useful tool to support the elaboration of sales forecasts. In this case, it is appropriate to evaluate the question of the relevance of the survey sample carefully, to identify the statistical confidence intervals in estimating potential demand. Purchase intent can be measured by asking the following question (after viewing or testing the product concept): if the product had a price according to your expectations, would you be willing to purchase it within one year? The answer is on a 1–5 scale: 1. I wouldn't buy the product at all 2. I probably wouldn't buy it 3. Maybe I would buy it

8

See Gustaffson et al. (2001).

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123

4. I would probably buy it 5. I would definitely buy it. Answers 4 and 5 are those that are taken into consideration (top boxes); values 1–3 reflect little or no purchase intention and are not significant. In the case of very innovative products, it is not advisable to include price indications in the question; the aim is to measure only the interest in buying, without confusing the respondent with specific price information. On the contrary, for products that are already on the market, the price is usually included in the question. Think of a new personal computer where the respondent has a clear idea of the price scale of the products on the market, and his/her answer requires a comparative evaluation between prices and attributes. Once the purchase intent has been obtained, if no reference has been made to the price, a second question is asked: at what price would you be willing to buy the product? Price information has to be analysed for 4 and 5 responses, which indicate the price-value ratio assigned to the product by those who are willing to purchase. In this way, information on the customer's sensitivity to price can be obtained. In particular, we can compare the distribution of the data on price of the group that answered 4 (I would probably buy it) with those that declared 5 (I would definitely buy it). To forecast sales (both in B2C and B2B cases) it has to be considered: • the number of subjects (persons or companies) in the relevant market segment (S); • the percentage of persons or companies informed (I) of the new product during the first year. This percentage reflects the company investments in communication and distribution of the new product; • purchase probability (P), given by the sum of the percentage of answers 4 and 5, corrected to take into account the difference which always exists between intention and actual purchase (e.g. 0.25 for 4 and 0.35 for 5); using the factors 0.25 and 0.35 it is prudentially considered that only a quarter of those who answered 4, and only a third of those who answered 5, will proceed with the purchase of the product;9 • the number of times the purchase is estimated to be made during the year (N = 1 with no repeat purchase). The formula for estimating sales (VE) for the first year is as follows: VE = S × I × P × N½pieces=year]: For example, the company that developed the idea of a smart bicycle padlock has carried out a concept test with potential Italian and Dutch customers to estimate sales. The data used were as follows:

9

See Ulrich et al. (2012).

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• potential customers (S) = 2,900,000 e-bike owners in Italy and Netherlands; • percentage of informed customers (I) in the first year = 25% (due to low investment in communication); • purchase intent: during the test they obtained 28% (4: I would probably buy it), and 38% (5: I would definitely buy it); using a correction factor 0.25 for 4 and 0.35 for 5, you get a purchase probability of 0.28 × 0.25 + 0.38 × 0.35 = 0.203 = 20.3%; • N = 1 (no repeat purchase during the year, the life cycle of this product lasts several years). Sales are estimated at around 140,000 pieces (2,900,000 × 0.25 × 0.203); statistical confidence intervals have to be identified in relation to the survey sample strategy.

7.4

System-Level Design

System-level design, sometimes called “pre-design”, is the phase where the concept is further specified by refining the overall technical product architecture and formulating the carryover strategy. Carryover represents the percentage of parts or modules of the new product that are already used in current production on other products. A company can try to include in the new product components of the existing products to minimize the redesign of those parts that do not impact the product's critical attributes; this can be more easily done for components that are not visible to the customer. Carryover reduces the time and cost of design and the investment required for manufacturing equipment. Carryover may lead to some significant advantages: • shorter development time; • lesser costs and investments (also as a result of greater economies of scale in component manufacturing and buying); • grater quality and reliability of the components. At the same time carryover may have some disadvantages: • the reduction in the level of novelty of the new product perceived by the customer; • new components (which could have been used instead of existing components) could have lower purchase prices (a frequent case in electronic components) or offer better performance. Carryover choices are part of the broader problem of defining product architecture—a complex set of decisions that have a significant impact on product performance. Through architectural choices, the decomposition of the product into

7.4 System-Level Design

125

subsystems or parts and the assignment of functions to the different subsystems is defined; in other words, the product is structured as a set of well-defined functional groups (for example, for a machine tool, the spindle group, which includes mechanical, electrical, electronic and hydraulic components). Product architectures can be traced back to two fundamental categories, which have opposite characteristics: integral and modular architectures.10 A formula 1 car has an integral architecture: each part performs more than one function (for example, the chassis supports the engine, contains fuel, minimizes air resistance) and the parts have been integrated to maximize performance and reduce weight. If a part needs to be changed, other parts connected to it must also be modified. If, however, we consider standard cars the architecture is mainly modular: the chassis has been designed to accommodate different types of suspension or engines, to obtain a wide variety of models while minimizing the number of components. The same chassis can also be shared by several brands (think of the MQB chassis platform used by Volkswagen, Audi, Seat and Skoda) to maximize economies of scale. Modularity is a prerequisite for the creation of so-called product platforms11 (where the vast majority of parts remain unchanged in the various models), which make it possible to offer many variants (the “derivative” products) by changing a limited number of modules. The conceptual and physical basis necessary for the realization of a modular architecture lies in the definition of decoupled interfaces (physical, electrical or other) between product modules so that a change in one area does not propagate into other parts of the system. Consider, for example, the popular Victorinox knives: dozens of different models are offered by combining a limited number of components which have decoupled interfaces between them. Product architecture determines the level of internal variety (number of parts or components used) and external variety (number of final products obtainable). Modularity enables a certain level of external variety to be obtained with less internal variety, and therefore with lower direct and indirect costs. Figure 7.7 compares two architectural solutions. With the same external variety (number of models) offered to the market, the modular solution B, on the right, allows containing the internal variety (number of components), which strongly contributes to the reduction of direct costs (greater economies of scale) and indirect costs (lower stocks and lower costs for information management). Modularity can also enable to expand external variety by combining components in many different

10 See Ulrich (1995). Salvador et al. (2002) distinguish two types of modularity: component swapping modularity, where product variants are obtained by swapping components while maintaining a basic product body; and combinatorial modularity, where a higher number of variants can be obtained by combining components from different component families. 11 Robertson and Ulrich (1998).

126

7 External Variety

Architecture A

Internal Variety

Creating the Project Value Proposition External Variety

Architecture B

Internal Variety

Fig. 7.7 Impact of modularity on internal variety

ways (combinatorial modularity) or by changing parts from a component family while maintaining a fixed product body (component swapping modularity12). The trend toward modularity involves many sectors. For example, in the field of smartphones, Fairphone provides an architecture with a certain level of modularity. On the company's website, Fairphone is presented as an “ethical and modular smartphone” in which there are several modules that can be purchased and replaced directly by the user (camera module, head and front camera module, battery, speakers and microphone modules). Modularity also facilitates the separation of the various components at the end of the product life cycle, contributing to the reduction of undifferentiated waste. In general, modularity has many advantages, particularly where the unit volumes of individual finished products are not high: • reduction of development lead times; • reduction of direct costs (for economies of scale on a smaller number of components) and management and warehouse costs; • possibility to adopt assembly to order (ATO) production logic, thanks to the limited number of different parts and the opportunity to use the same component on several products. Conversely, modularity has some limitations: • aesthetics, weight and size may deteriorate compared to a more integral product; aesthetics may be negatively affected by standardization of interfaces and reduction of internal variety; weight and size may not be optimized as much as in an integral architecture (which can take full advantage of both geometric nesting and function sharing); • more design effort is required to define standard interfaces so that parts can be easily used in different products;

12

See Salvador et al. (2002).

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• long-term product planning is needed to be able to design modules and interfaces suitable for “next-generation” products.

7.5

Project Economic Analysis

In formulating the value proposition, it is necessary to evaluate the investments needed to transform the concept into a profitable product and to estimate revenues and costs. This economic analysis typically extends over 3 or 4 years, and it is based on estimates and forecasts since technical solutions have not yet been developed in detail. Revenues are derived from sales forecasts, which can be defined based on several elements: • extrapolation of historical data, if available (as in the case of derivative product development projects); • data from purchase intent surveys (e.g. concept test); • estimates produced internally by marketing and/or using information obtained from distribution channels, agents or other sales partners. In order to build a simplified economic and financial model of the project, costs can be divided into the following key categories: product design and testing, equipment and tooling, marketing and sales and, finally, production. With revenue and cost information, the net present value (NPV) can be calculated: the algebraic sum of revenues and costs for each period considered, converted to their present value using an appropriate discount rate that has to reflect the cost of the capital invested in the project.13 Table 7.6 shows an example of NPV calculation over a three-year period (divided into nine four-month periods) for a B2B product with an expected price positioning of 1000 euros. A lead time of 1 year is estimated for the detailed design, testing and launch phases; revenues are distributed over the second and third year. The net present value of the project is approximately €800,000. The simple base-case model in Table 7.6 can be useful to perform sensitivity analysis to evaluate the effect of changes in different input factors on NPV. For example, we can consider the following scenarios or a combination of them: • change in sales volume forecast; • change in component procurement policies (lower purchase prices);

13

The NPV formula used in Table 7.6 is as follows: VAN =

Pn

CF t t=1 ð1þk Þt

, where CFt is the cash flow

for period t (e.g. t = 4 months in Table 7.6), n are the periods considered (n = 9 in Table 7.6), and k is the discount rate for period t. For more details see Thuesen and Fabrycky (1994); Brealey et al. (2011); Garrison et al. (2012).

Sales volume Unit price Revenues (000 €) Product Design & Testing costs Marketing & Sales costs Equipment & Tooling costs Production costs TOTAL COSTS (000 €) CASH FLOW (000 €) Annual Discount Rate 6% PRESENT VALUE (000 €) Period NET PRESENT VALUE (000 €) 200

200 –200 –192.23 2

150 –150

–147.06 1

P2

150

Year 1 P1

Table 7.6 Base-Case Model for estimating NPV

–339.24 3 4

203.79

275 325 225

250 300 200 184.77

50

5

P2 550 1000 550

50

Year 2 P1 500 1000 500

6

221.99

300 350 250

50

P3 600 1000 600

7

252.46

350 410 290

60

Year 3 P1 700 1000 700

8

281.65

390 450 330

60

P2 780 1000 780

9 792.47

326.33

450 510 390

60

P3 900 1000 900

7

360 –360

250 30 80

P3

128 Creating the Project Value Proposition

References

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• reduction of the sales price in the first year for an aggressive market entry strategy; • increase in development lead time to introduce a high level of modularity in the architecture, with changes in design and manufacturing costs. As we have seen, the development of the project value proposition (PVP) requires the integration of diverse and multidisciplinary skills and the creation of several deliverables, which must be adequately summarized in a format that allows management to assess the strategic value of the project with clarity and wealth of information. Each company must create its own format for the presentation of the PVP which, of course, must be adapted to the complexity and riskiness of the different types of project that characterize its portfolio development strategy (Chap. 9). In the generic stage-gate system illustrated in Chap. 6, the PVP approval takes place at the gate that opens the doors to product and manufacturing process detail design; after this gate, financial commitments are considerable. The PVP gate is a crucial event in managing product development for several reasons: 1. It is a fundamental opportunity to share cross-disciplinary knowledge, perspectives and visions, in which both the management board, the project team and other managers, are involved. 2. It is the core milestone within which as much information as possible must be gathered to assess the project's attractiveness, both from a strategic and an economic point of view. 3. It is the decisive moment to revise (or kill) the project before entering the final heavy spending stages.

References Brealey, R. A., Myers, S. C., Allen, F., & Sandri, S. (2011). Capital budgeting. McGraw-Hill. Dell'Era, C., & Verganti, R. (2007). Strategies of innovation and imitation of product languages. Journal of Product Innovation Management, 24(6), 580–599. Garrison, R., Noreen, E. W., & Brewer, P. C. (2012). Programmazione e controllo: managerial accounting per le decisioni aziendali. McGraw-Hill. Gustaffson, A., Herrmann, A., & Huber, F. (2001). Conjoint analysis as an instrument of market research practice. In A. Gustaffson, A. Herrmann, & F. Huber (Eds.), Conjoint measurement: Methods and applications (pp. 5–46). Springer. Kim, C. W., & Mauborgne, R. (2005). Blue ocean strategy. Harvard Business Review Press. Kim, C. W., & Mauborgne, R. (2013). Case study: “Nintendo Wii”. Blue Ocean Strategy Institute. Kim, C. W., & Mauborgne, R. (2017). Blue ocean shift. Pan Macmillan. Robertson, D., & Ulrich, K. (1998). Planning for product platforms. Sloan Management Review, 39 (4), 19. Saaty, T. L. (1988). What is the analytic hierarchy process? In Mathematical models for decision support (pp. 109–121). Springer. Salvador, F., Forza, C., & Rungtusanatham, M. (2002). How to mass customize: Product architectures, sourcing configurations. Business Horizons, 45(4), 61–69. Thuesen, G. J., & Fabrycky, W. J. (1994). Economia per ingegneri. Il Mulino-Prentice Hall.

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Ulrich, K. (1995). The role of product architecture in the manufacturing firm. Research Policy, 24 (3), 419–440. Ulrich, K. T., Eppinger, S. D., & Filippini, R. (2012). Progettazione e sviluppo prodotto. McGrawHill. Ulrich, K. T., Eppinger, S. D., & Yang, M. C. (2020). Product design and development (7th ed.). McGraw-Hill. VanGundy, A. B. (1988). Techniques of structured problem solving. Springer. Ziamou, P., & Ratneshwar, S. (2003). Innovations in product functionality: When and why are explicit comparisons effective? Journal of Marketing, 67(2), 49–61.

8

Organizing Development Projects: Structural Choices and Planning Approaches

Abstract

Product development projects represent a considerable organizational challenge. Coordination and collaboration problems are amplified by a variety of factors: the multitude of disciplines and skills required, the strong and growing pressure on time reduction and the level of uncertainty and risk that typically characterizes product innovation. This chapter focuses on the set of organizational choices that influence the way people interact during a specific product development project. These choices deal with (1) the definition of the organizational structure that formalizes roles and power relations and (2) the adoption of specific planning and control methodologies for project activities.

8.1

Organizing Product Development: The Structural Choices

A well-established way to understand structural alternatives to ensure coordination and collaboration in development projects has been developed by Clark and Wheelwright.1 They identified four key options: 1. Functional structure. This is the traditional organization structure with units specialized by discipline, with no formal identification of project team and project leader. The coordination of the different functions involved in the project is the responsibility of functional managers; the effectiveness of coordination is linked, on the one hand, to the mutual adaptation and negotiation skills of the functional managers and, on the other hand, to the possibility of dividing the project into clearly specified and as much as possible independent sub-projects or phases, to be assigned separately to the individual functions. 1

Wheelwright and Clark (1992a, b, c).

# Springer Nature Switzerland AG 2021 S. Biazzo, R. Filippini, Product Innovation Management, Management for Professionals, https://doi.org/10.1007/978-3-030-75011-4_8

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This organization works well in contexts characterized by low uncertainty and complexity (for example, in derivative and incremental improvement projects), where the objectives are clear-cut, and the breakdown by functional sub-projects can be carried out accurately in the initial planning phase. As is well-known, the fundamental strength of the functional structure is the supervision and development of specialist skills: functions are the place where knowledge and expertise are accumulated, also through the capitalization of experience in solving similar problems. 2. Lightweight team structure: In this case, the functional structure is modified with the identification of a cross-functional team focused on the project,2 whose composition must reflect the multidisciplinary required by product development activities. In the case of complex projects requiring the involvement of a large number of people, it is advisable to articulate the cross-functional team on two levels: (1) the core team (the project key roles) coordinated by the project leader and (2) the extended team, composed of groups of people coordinated by the members of the core team (for example, the extended team could be articulated in sub-teams focused on product subsystems). The extended team may also include support roles (e.g. an expert in industrial accounting) and external actors such as suppliers or customers (in B2B contexts). The relative commitment of the different corporate functions varies with the progress of the project: typically, marketing and sales functions play an essential role in the initial and final phases (for example, in stages 1 and 5 of the model illustrated in Chap. 5), while the technical functions are strongly involved in the middle phases of the development. In the lightweight team structure, members of the project team stay in their respective functional units, are part-time resources, report to the functional managers and are coordinated by a lightweight project manager (PM). It is an organizational form that is generally referred to as a weak matrix structure: the project manager typically has a low level of control over key project resources, critical decisions and deadlines. He/she is, in fact, in a subordinate position vis-à-vis function managers. It is a role of coordination focused on controlling project progress and managing information flows. The lightweight approach maintains the same strengths of the functional organization and, at the same time, seeks to reinforce communication and coordination by introducing the project manager. The problem is that it is not easy for a lightweight project manager to guarantee the effectiveness of cross-functional integration, given its weakness in terms of status and formal power. Light project managers often find themselves in a situation where they are “tolerated” by functional managers: the risk

In some companies the project team is identified as a “simultaneous engineering team”, to emphasize the importance of early involvement of different business functions and the need for constant interdisciplinary integration; see Barkan (1991). 2

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is that the weak matrix will turn into a functional organization burdened with a formal coordination role unable to perform its work effectively. However, it can be suitable for managing incremental innovation projects. 3. Heavyweight team structure: In this organization, members of the crossfunctional team report to a heavyweight project manager, whose responsibilities go beyond simple coordination. She/he is directly responsible for the development of the product and is the guardian of the product concept and objectives during the project (PM as a “concept champion”); she/he has the technical skills to dominate the architectural design of the product, has a strong influence on the resources involved in the project and occupies a position of primary importance in the organization. Each team member continues to represent their corporate function, but the functional manager has limited authority and power even over the individual performance appraisal. Key team members are often allocated fulltime to the project and are physically co-located with the heavyweight project manager for the duration of the project. The heavyweight approach is suitable for innovative projects and allows to effectively manage the intricate task interdependencies that characterize complex development processes, ensuring internal and external product integrity (Chap. 6). The heavyweight project manager requires senior profiles with significant experience and skills to ensure authoritativeness and speed in making decisions. 4. Autonomous team structure: The cross-functional team is assigned full-time to a specific project led by a project leader; people are generally co-located, and the project leader has complete control over the resources allocated to him/her, including individual performance evaluations. The focus on the project is undoubtedly a great advantage of this organizational form; an autonomous team is an organizational unit concentrated on a single task and, therefore, can minimize coordination problems and be extremely effective in terms of development speed and quality (see Case Study 8.1). This level of autonomy could, however, harm the ability to integrate different development projects: for example, it could be challenging to work on the standardization of components as the autonomous team would tend to seek excellent solutions within it, but which could have a dysfunctional impact on component proliferation. A clear definition of the development process and the creation of appropriate design standards could reduce inter-project integration issues and impose boundaries on the level of team autonomy and project leader discretion. It is a solution that may be suitable for challenging and strategic projects where even redundancy (often inevitable in these cases) in the use of human resources can be accepted, albeit temporarily. An interesting variation of the concept of autonomous team and heavyweight project manager is the one provided by the Scrum framework (see paragraph 7.3), an approach to project management born in the context of software development. In Scrum, the separation between responsibility

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for project results (product owner) and authority over the people who carry out the activities (developers) is established. The heavyweight project manager is transformed and scaled back into the product owner, while the development team is self-managing, meaning they internally decide who does what, when and how3” (within a higher-level product release plan defined by the product owner). A relevant issue for the effects on project performance is the geographical dispersion of the team. Geographically separated teams are often referred to as “virtual teams” because they have to use coordination mechanisms based on digital communication technologies. Virtual teams have undoubted disadvantages compared to traditional teams: physical proximity favours frequent communication and facilitates the building of a climate of familiarity and mutual trust, while virtualization most likely leads to a reduction in the intensity and frequency of interaction; as a result, coordination and problem-solving processes become more complicated and slower. However, virtual teams also have advantages: access to excellent skills in remote locations and integration of different skills and cultures into the team.4 In any case, virtualization is a tough managerial challenge due to the increased complexity of interpersonal dynamics and project planning.5 It should be noted that, in many situations, the adoption of a virtual team is not an option, but a necessity linked to the development of products that compete on a global scale and require extremely diverse specialist skills that are difficult to find in a single geographical area (“global teams”). Case Study 8.1 The fragmentation of people’s commitment to several projects is a significant problem from various points of view. From the perspective of team members, there is the problem of de-focusing attention and dedication that must be distributed over different initiatives; from the project manager’s perspective, there is a time management problem, made complex by the strong interdependencies between projects using the same resources. Very often, project delays are linked to activities assigned to part-time team members and driven by the overlapping of commitments and conflicting priorities. For a long time at Carel Industries (a leading company in control systems for air conditioning, refrigeration, heating and cooling systems), development project teams involved more than ten people, the majority of whom devoted time to several projects in parallel and, therefore, with a very fragmented and unfocused commitment. Carel adapted the one-piece flow concept of lean manufacturing (minimize work in process inventory waiting for task execution or decision) in the allocation of engineering design resources to projects. After (continued) 3

Schwaber and Sutherland (2020). Siebdrat et al. (2009). 5 McDonough et al. (2001). 4

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135

Case Study 8.1 (continued) the approval of the value proposition by the management committee, the project is assigned to a team leader and a “compact team6”, composed by a few people who will work full-time on the project. At the same time, the so-called consultant and support roles are formally identified (the “extended team”). This “compact team” approach required a major investment in training to broaden and enrich the skills of individual team members (multitasking), to allow them to be substantially self-sufficient in the completion of a project. The leader of a compact team (called LPL, lean project leader) is a “heavy” project manager because his responsibilities go beyond simple coordination: he is personally responsible for the development of the product concept and is the guardian of the project vision and mission.

The Structural Choices: Organizational Contingency or Ideal Configuration? Organizational studies usually highlight that structural choices should depend on the complexity and levels of uncertainty of the tasks to be faced (organizational contingency): the four structural alternatives have been presented in ascending order concerning the ability to tackle projects with increasing complexity, level of innovation and uncertainty. In the classical perspective of organizational contingency, the best structure is the one that fits better the specific situation. However, the generalized increase in internal product complexity and external complexity linked to the increasing sophistication of customer needs makes organizational forms with weak coordination skills (functional structure and light team) unsuitable to govern product development in an era characterized by the rapid evolution of markets and technologies. Lean product development (LPD, see Chap. 5) has focused attention on the heavyweight team structure, as it is considered the organizational form that allows for balancing the attention on projects and specialized expertise. Particularly evocative is the “lean definition” of the heavyweight project manager: entrepreneurial system designer (ESD) or chief engineer (the term used in Toyota). These expressions highlight two central attributes of the project leader: systemic vision and full responsibility for concept development and design choices. The heavyweight PM should not be a project administrator but the leading product architect and the “voice” of the customer inside the company. The integration of multidisciplinary skills is a crucial element of this role, in which marketing, technical and manufacturing expertise are synthesized.

6

See Kerga et al. (2013).

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8 Organizing Development Projects: Structural Choices and Planning Approaches

Developing the skills required for the effective interpretation of this role is a complex challenge; they are very often fragmented into engineering, production and marketing. The challenge of creating a heavyweight project manager is particularly difficult in small- and medium-sized enterprises. In this context, “hybrid” solutions are frequently adopted: project leadership is entrusted simultaneously to more than one person from different functions (typically marketing and engineering) that together can provide the interdisciplinary vision of a heavyweight PM. Likewise, managing power relationships is extremely problematic: matrix organizations are characterized by unavoidable tensions between functional managers and project leaders on decision-making processes and resource control.7 The LPD literature stresses that the heavyweight team structure should require a change in the role of the specialist functions, which should become a centre of expertise at the service of projects,8 with the fundamental objective of maintaining and developing the specialist knowledge needed to generate innovative and reliable technical solutions. So far, we have focused our attention on the role of the heavyweight project manager; but the project success obviously depends also on the characteristics of the team members who, using Ward’s vivid definition, should be “responsible experts9”. • experts as providers of the necessary skills; they must effectively represent their functional perspective in the project; • responsible for the project success as a whole, not only for the results of their own functional activities. There are several factors influencing the success of cross-functional teams in product development. In Fig. 8.1, we have reported an adaptation of the McDonough’s model.10 The model considers two key performance indicators (time-to-market and product quality) and divides the factors influencing performance into three main areas: • stage-setters: the factors that define the conditions surrounding the project and reflect the managerial actions taken in the early stages of the development process (the existence of clear project objectives, the empowerment of team members, an organizational climate that creates a sense of urgency around the project by influencing its perceived importance, the adequacy of technical and interpersonal skills of team members); • team behaviours: level of cooperation and integration between team members; dedication to the project and identification with project objectives; mutual respect;

7

See the classic work by Larson and Gobeli (1988). Ballé et al. (2016) 9 Ward and Sobek II (2014). 10 McDonough (2000). 8

8.2 Managing Product Development Projects: Rational and Relational Approaches

137

Enablers • •

Participative Team Leadership Senior Management Sponsorship

• Clear project objectives • Organisational climate able to create a sense of urgency around the project • Adequacy of team skills

Stage-setters

• • •

Mutual trust Cooperation Dedication to the project

Team Behaviours

• •

Time to Market Product quality

Project Performance

Fig. 8.1 Factors influencing the success of teams in product development (adapted from McDonough 2000)

• enablers: those individuals who facilitate team’s efforts and foster the success of the project: on the one hand, team leaders who adopt a participatory style of leadership, supporting, developing and encouraging team members; on the other hand, senior managers who provide sponsorship to the project and who can remove obstacles and organizational resistance that the team may encounter. Enablers mediate the influence of stage-setters on team behaviours; the latter factor also has a direct impact on team behaviours which, in turn, affect project performance. This model highlights the key role of project leaders and senior managers on team behaviours and, consequently, on project performance. They have, in fact, a significant influence on the levels of cooperation, dedication, identification and mutual respect of the team, not only through the definition of the initial stage-setting elements but, above all, through their daily activities that moderate the effects of the different stage-setting factors and directly influence team behaviours.

8.2

Managing Product Development Projects: Rational and Relational Approaches

In project planning and control, we can identify two contrasting paradigms which can be described as follows:

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• the rational paradigm is characterized by a centralized and linear approach to project management, and vertical communication flows between planners and executors11; • the relational paradigm is instead centred on a decentralized and iterative approach to planning and control, where the communication flows are horizontal and delineate a non-hierarchical network capable of connecting all the actors of the project. In the rational paradigm, there is the basic assumption that it is possible to plan the whole project centrally and in detail before its execution ( full upfront planning). The planner can develop a reliable programme that only needs to be executed: the relationship between planning and execution is linear. The effective management of a project is a question of rationality and the application of appropriate planning techniques such as the critical path method (CPM) or the performance evaluation and review technique (PERT, also called “three-point-estimation”), techniques developed in the late 1950s but still used and widespread today. Both techniques involve the construction of the work breakdown structure (WBS, the structured breakdown of project work) and the network of activities that make up the project (project network diagram, PND). In the PND the dependencies between project activities are established, for example, by highlighting that activity B cannot start until activity A has finished, or that two activities must start at the same time or end at the same time. Every single activity is then associated with its duration (with a single estimate in CPM and with a three-point estimation technique in PERT to calculate the probability distribution of the project lead time). It is intriguing to note that the PERT method is historically presented as an evolution of the CPM to cope with projects with higher levels of uncertainty; it is evident how much this sort of “evolution” is bounded by the rational paradigm and based on the hypothesis that uncertainty can be faced through a sophistication of the estimation algorithm of project duration.12 With the estimation of activity durations and based on the project network diagram (PND), it is possible to calculate the early start and early finish and the late start and late finish of all project activities; activities that cannot be delayed (i.e. those for which the early and late start/finish coincide) represent the so-called critical path. PND, early and late start/finish dates and activity durations are generally displayed through the classic Gantt bar chart—the graphical output of the CPM schedule (or PERT in the case of a three-value estimate).

11

For a classification of project planning and control systems, see Wysocki (2014). For a broad description of classical planning and control methodologies, see Baglieri et al. (1999). 12 The refinement of the rational project planning approach did not stop at the PERT methodology; in fact, other even more complex methods were developed such as GERT and Q-GERT; see, for example, Taylor III and Moore (1980).

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There is no doubt that the rational paradigm has represented the dominant approach in the discipline of project management, to the point that some authors have highlighted the massive diffusion of a style of thinking called “critical path thinking13“to emphasize the centrality of algorithmic scheduling and control techniques in project management practices. However, these approaches have significant limits of application in dynamic and uncertain contexts, particularly in the field of innovation management.14 In recent years, the rational paradigm and the critical path thinking have been subjected to a resounding critique by two distinct communities.15 In software development, Agile methodologies have deeply challenged the basic logic of traditional approaches to project management. In the field of hardware development, lean thinking has inspired the creation of new techniques and methods of managing product development projects (visual planning) that reject the complexity and algorithmic sophistication of classical techniques to focus on simplicity and human relations. This critical review of the fundamentals of traditional project management revolves around the following observation: the rational approach is mainly aimed at the search for predictability in the execution of a project, and this orientation is acceptable and desirable under conditions of very low uncertainty and very clear project objectives. Traditional project management techniques reach crisis point in turbulent environments, given its emphasis on upfront planning and its “contractual approach” to planning (in which the plan should represent a clear and accurate “contract” between the project team and senior management). Agile and visual planning methodologies have in common the shift of focus from the activity network to the people network; this fundamental change in the locus of managerial attention marks the transition from the rational paradigm to the relational paradigm. Three crucial aspects distinguish the relational approach: 1. Decentralized and iterative planning: Team members actively participate in project planning, which is seen as a “cycle of promises” where participants make commitments one to each other through collaboration and negotiation. Each team member is induced to take responsibility for the activity they have committed themselves to within the agreed deadline. Planning is carried out iteratively and progressively (rolling-wave planning): work is planned in detail only in the near term adopting a regular cadence (the project “takt time”). 2. Visualization of work and transparency of information: The workflow is made visible to the team, and information is disseminated and easily accessible, 13

De Meyer et al. (2001). Traditional techniques are suitable for managing large projects with low uncertainty and high cost-of-change; in such contexts, several project management software packages based on CPM or PERT algorithms are widely adopted (see Wysocki 2014). 15 Critical path thinking has also been challenged by proponents of the critical chain method, based on Goldratt’s Theory of Constraints. This methodology remains within the rational paradigm and proposes a buffer-based, as-late-as-possible scheduling technique (see Leach 1999, 2004). 14

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allowing everyone to have a clear and frequent understanding of the progress of project activities; 3. Intensive collaboration: Building a working environment characterized by a high level of psychological safety is considered a fundamental objective: a climate of mutual trust induces people to freely and honestly share information, knowledge and problems.16 In the next paragraph, we will see how these three characteristics have been operationally declined in the Scrum framework—the most widespread and wellknown Agile software development methodology. The Scrum methodology plays a particularly relevant role as a radical interpreter of the relational paradigm and, consequently, represents a powerful source of inspiration for the development of new project management methods and tools.

8.3

The Agile Revolution: From Scrum to Agile-Stage-Gate

In the 1990s, numerous attempts to innovate the way software development projects were carried out emerged. These attempts embraced the spiral process model and were characterized by the idea of minimizing the upfront planning effort to leave room for an iterative development model centred on the continuous release of working software and frequent customer involvement and collaboration. In February 2001, 17 supporters and creators of innovative software development methodologies (who called themselves “organizational anarchists”17) met to discuss the peculiarities and similarities of the different approaches that had emerged in previous years. The result of this meeting was the elaboration of the Manifesto for Agile Software Development.18 Among the different Agile methodologies, Scrum is the one most known and used today. The term Scrum was first used by Takeuchi and Nonaka19 to characterize the style of multi-functional teams whose members, as in the rugby “scrummage”, all push together simultaneously in the same direction working as a single entity. Scrum is a software development methodology focused on iteration and incremental product release (the so-called product increment) in short cycles called Sprint—the “heartbeat” of the project. The product development process model underlying this methodology is, therefore, the spiral one (see Chap. 5). The Scrum framework foresees three key roles. The product owner represents the voice of the customer and has the responsibility for project success. Developers are the people responsible for the creation of the product specified by the product owner. The team of developers is multi-functional, i.e. it includes all the skills needed to

16

See Sting et al. (2015). See Rigby et al. (2016). 18 See www.agilealliance.org. 19 Takeuchi and Nonaka (1986). 17

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complete the deliverables required for each Sprint, and self-organized as it is directly responsible for planning and allocating the work among the members of the group. It should ideally consist of less than ten people, dedicated full-time to the project; in the case of large projects, it is necessary to form several teams working in parallel. The Scrum Master is the person who supports the team and teaches the Scrum practices to all those involved in the project, removes obstacles for the team and makes sure that Scrum processes are followed. A Scrum project20 starts with the definition of the project objectives in the form of a product backlog. The product backlog is an “ordered list of everything that is known to be needed in the product”21; this list evolves during the life of the project in response to any changes requested by the customers-users or generated by product increment testing and review. The product backlog is the responsibility of the product owner—the person who represents the voice of the customer and who is responsible for the success of the project. The Sprint planning meeting launches every Sprint. During the meeting, the product owner discusses the objective that the Sprint should pursue (Sprint Goal) and the product backlog items that would realize the Sprint Goal. Afterwards, the members of the development team, taking into account their actual available working capacity during the Sprint, define the Sprint Backlog—a set of selected items from the product backlog plus the list of tasks for delivering them. This list is commonly displayed physically through a set of cards organized on a board hanging on a wall—the so-called Scrum Board. A standard Scrum Board22 (Fig. 8.2) consists, in the simplest form, of three columns representing the workflow of each task (to do, doing, done), identified with a card (e.g. a post-it) and a set of rows representing the backlog items selected for the Sprint. The To-Do column contains tasks not yet started; the Doing column contains tasks started and not yet completed, and the Done column contains completed tasks. During the Sprint planning meeting, all cards are placed in the To-Do column and then moved according to their progress. The update on the progress of the Sprint takes place in the Daily Scrum—a timeboxed short meeting (15 mins) generally held every day at a fixed time. All team members attend it, and its function is to inspect what has been done the day before and to foster task synchronization and adaptation to emerging problems or situations.

20

See Wysocki (2014) and Deemer et al. (2010). Schwaber and Sutherland (2020). 22 In addition to the Scrum Board, another critical tool for the daily monitoring of the Sprint progress is the Burndown Chart, which illustrates in an X-Y graph the trend of the remaining workload (y-axis) for each day of the Sprint (x-axis), based on the estimated effort of each planned task to complete the Sprint Backlog. A typical Burndown Chart highlights both the “standard” line of linear absorption of the amount of work and the actual line of the amount of work remaining to be done in the Sprint. If the actual line is placed above the standard line, it means that the team is proceeding at a slower pace than estimated and may not meet the project commitments made. 21

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Fig. 8.2 A standard Scrum Board

Sprint time-box

To-do

Task

Doing

Done

Product Backlog Item

It is not a reporting meeting of the project status to a manager; the goal is to share information and expose problems regularly. Each team member, in turn, reports on three questions: (1) what has been achieved since the last meeting; (2) what will be done before the next meeting; (3) what problems or obstacles have been encountered. During the Daily Scrum Meeting, there is no room for discussion, but only for the exchange of information; ad hoc follow-up meetings are organized if necessary. If problems arise, the Scrum Master is responsible for providing support in removing any “impediments” that prevent the development team from meeting the Sprint Goal. A Sprint typically lasts one to 6 weeks (with a preference for two or 4-week iterations), during which the Scrum Team works on creating product increments (often also referred to as “potentially shippable product functionality”). Each Sprint ends with a key integration event—the Sprint Review Meeting—during which a demonstration of the deliverables is provided to the product owner and appropriate stakeholders. The product owner decides—according to the established acceptance criteria—whether or not a backlog item has been satisfactorily completed. Subsequently, the product owner can adapt the product backlog to new requirements that have emerged during the Sprint Review. The cycle then restarts with a new Sprint Planning Meeting, and the whole process continues until the product backlog is empty and/or the customer is satisfied with the last product increment. The orientation towards iterative and incremental development represents the heart of the Scrum methodology; however, there are three other peculiar characteristics that must be highlighted:

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1. Time-boxing: time is considered the central constraint in managing project activities. A fixed duration limits each Scrum event: each Sprint is a timeboxed iteration; the Sprint Planning Meeting must last a maximum of 8 h for a 4-week Sprint; the Sprint Review Meeting and the Retrospective Review Meeting have a predetermined duration of 4 h for a 4-week Sprint; the Daily Stand-up Meeting is limited to 15 mins. There are three fundamental reasons for timeboxing: (1) to create order and rhythm in an environment characterized by uncertainty and complexity; (2) to facilitate finite capacity planning: in the Sprint Planning Meeting the team must decide which backlog items can complete in the Sprint, taking into account the available working hours during the Sprint; (3) to focus attention on deliverables and on respecting deadlines: the Sprint Backlog has to be a reliable commitment as the duration of the Sprint is never extended, regardless of whether or not the team has finished the planned work. 2. Inspection and adaptation: change is proactively introduced in response to frequent and constant “inspections” on the progress of ongoing activities and project output. Changes in product backlog evolve in a controlled manner throughout the project life cycle, according to the results of Sprint Review Meetings. 3. Transparency of information: Scrum projects are characterized by a very high level of visibility of work processes and outputs. Objectives are known, formalized and accessible to everyone through the product backlog and the Sprint Backlog; the progress of each Sprint is updated in real-time and is immediately visible to everyone in the Scrum Board or other work visualization tools (such as the Burndown Chart); the overall project progress is clearly visible at the end of each Sprint in the form of a “product increment”. These three features have had a profound influence on the evolution of project management in the context of physical products; as a matter of fact, in the last few years, the Scrum framework has also aroused much interest in the field of physical product development. As mentioned in Chap. 5, many companies are experimenting with Agile-StageGate hybrids,23 where Scrum methods are embedded within the stages (particularly engineering design stages) to manage short-term planning and problem-solving activities through a series of time-boxed sprints. At the same time, the Stage-Gate structure represents the backbone for long-term planning activities, providing a highlevel overview of the project’s major milestones and expected deliverables for each stage. A significant challenge in Agile-Stage-Gate implementations is the redefinition of the “done sprint”, as in hardware product development is not possible to build a “part of the product” (the increment) that actually works by the end of each sprint. This problem has been frequently addressed by relaxing the notion of “product

23

See Sommer et al. (2015), Ovesen and Sommer (2015), Cooper (2016) and Cooper and Sommer (2016)

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increment” and considering as a Sprint output anything tangible that can be inspected and reviewable, from a prioritized list of customer needs or a business case to any kind of prototype,24 such as concept sketches, rendering, simulations, 3D models, mock-ups or fully functional pre-production versions of the product. The need to revisit the objectives of the Sprints and the content of the product backlog is made clear in the rapid learning cycles (RLC) framework,25 an interesting adaptation of the Scrum framework for hardware product development. RLC emphasizes that the focus of a Sprint cannot be a product “increment”, but an “experiment” aimed to generate new product knowledge. Sprints become learning cycles to close the knowledge gaps needed to make critical design decisions during integration events (see paragraph 5.4). The RLC framework supports a multi-level, rolling-wave project planning approach to integrate the long-term view of Stage-Gate models to the short-term focus of Agile managerial practices: • in the first level, the target dates of Gate review events are scheduled; • in the second level, the integration events needed to reach the next Gate review are planned; • the third level is where Agile logic is applied: integration events are reached through learning cycles, an adaptation of the Scrum Sprint which no longer has the objective of implementing a “product feature” pulled from a product backlog. Leaning cycles have to build the necessary knowledge to make critical decisions in the forthcoming integration event. As we have seen, the adaptation of Scrum in Agile-Stage-Gate experimentations abandons the logic of incremental development but maintains the focus on timeboxed iterations, adopting a spiral process model inside each Stage.26 In the next paragraph, we will see that the lean project management approach in developing physical products still focuses on iteration and adaptive planning, but without prescribing any specific development process.

8.4

The Relational Paradigm in Hardware Product Development: The Lean Approach

In the context of hardware product development, lean product development literature and managerial practice have made significant contributions to the evolution of project management methodologies by supporting the relational paradigm to project planning and control. The Lean approach to managing product development projects

24 Ulrich et al. (2020) define a prototype an “approximation of the product along one or more dimensions of interest”. 25 See Radeka (2017, 2019). 26 See Cooper and Sommer (2018).

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is commonly identified with the term “visual planning”27 and consists of two fundamental practices: visual management of the project workflow and management cadence.

Visual Management The importance of visualization in product development has been highlighted in various studies focused on Toyota’s product development system. Morgan and Liker28 underline the centrality of the “Obeya”, the “big room” where the whole project is made visible in its progress and which serves as a point of attraction and coordination tool for the team. The fact of being able to see the project as a whole within an Obeya facilitates dialogue, activates a more natural and spontaneous way of communication, supports collaborative planning and knowledge sharing. The analogy with the principle of transparency of information in the Scrum methodology is evident. Project work is made visible to everyone through the creation of visual boards. Typically, the boards are made of paper and hung on the walls of the Obeya; they have to “radiate” information simply and effectively. Nowadays, the increasingly frequent diffusion of physically dispersed teams fosters the use of virtual visual boards based on “agile-oriented” project management software and large touch screens. Visual Boards have to radiate different types of information29: project objectives and performance, open problems that have to be solved, and planning information. The document defining the objectives of a project is often called project charter; this document summarizes the direction to be taken by the project team and typically contains the following information: • the description of the product idea, which highlights the main characteristics of the new product and the elements of differentiation and uniqueness compared to existing products (the value of the product idea from the competitor’s point of view); • the identification of target markets and customer benefits (the value of the product idea from the customers’ perspective); • the definition of the strategic and economic objectives of the project (the value of the project for the company);

27

See Hines et al. (2006), Mascitelli (2011), Lindlöf and Söderberg (2011), Bertilsson and Wentzel (2015), Gingnell et al. (2012), Lindlöf et al. (2013), Stenholm et al. (2016). A specific implementation of visual planning is the knowledge intensive/visible planning (KI/VP) methodology developed by the consulting firm JMAC; see Chap. 18 of the book by Koudate (2003), written by Takashi Tanaka; see also Hines et al. (2006), Tanaka (2005) and Horikiri et al. (2008). 28 Morgan and Liker (2006); see also Horikiri et al. (2008). 29 Mascitelli (2011) and Oosterwal (2010).

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Project Charter

COMPETITIVE VALUE OF THE IDEA

the main features of the new product the elements of differentiation and uniqueness

PROJECT VALUE FOR THE COMPANY

Strategic objectives Economic objectives Competitive objectives

CUSTOMER VALUE OF THE IDEA

Identification of target customers Definition of key needs to be met

PROJECT CONSTRAINTS

Adoption of a new technology Localization of production sites Suppliers Time constraints

Fig. 8.3 Project Charter: an example

• the constraints of the project (e.g. the adoption of a newly developed technology; the location of production sites and suppliers). This information is quite similar to that contained in the description of a product concept. The logic of information transparency calls for the project charter to be summarized in a single document (Fig. 8.3); and this document can be converted into a large board to make the fundamental objectives of the project clearly visible to all. Further information on critical project performances can also be included together with the project objectives; key performance indicators of project success can be divided into three main categories: • time: e.g. any deviations between the planned and actual dates of the major project milestones; • cost: e.g. any deviation of development costs from initial assumptions; • quality: e.g. the number of hours of rework generated by design changes (not foreseen and not desired); or the level of adherence of the product under development to customer needs. The resolution process of unforeseen problems that arise during the project can also be visualized with a straightforward board (often referred to as the “Issue

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Key Deliverable Roadmap

Planning Matrix (Long-term)

To do Doing D one Events

Long term

Deadline E2

Deadline E1

Months

To do D oing Done

Deadline E3 To do Doing Done

Months E1

E2

T1

T1 Sub-teams

T2

T2

T3 T3

Time horizon

Kanban Board

Planning Matrix (Short-term)

Time-box (short-term planning cadence)

E1

Events

Short term

Sub-team T1

To-do

Weeks

Doing

Done

John

John Dave

Sub-team Dave T1

Kate

Kate

Time-based

Visualization focus

Workflow-based

Fig. 8.4 Planning Board typologies

Board”) divided into three columns (open, ongoing or closed), which displays the flow of a problem-solving initiative. Lean approaches underline the value of having a clear structure of integration events,30 as hardware development processes cannot focus exclusively on reaction at the expense of anticipation (see Chap. 5). Moreover, unlike software, physical products cannot be created by the aggregation of working, albeit feature-limited, “product increments”; instead, they are the result of a learning process guided by major milestones (integration events and gates) and centred on the construction of increasingly better approximations of the final product—from sketches and virtual models to full-scale production trials. Accordingly, project planning must include two different time horizons: a long-term planning of the project major milestones (integration events and gates) and a short-term planning focused on the activities necessary to reach the nearest milestone. Lean approaches propose different visualization layouts (see Fig. 8.4) to capture long-term and short-term planning horizons. A widely used planning board format is the so-called planning matrix; the long-term matrix presents the entire time horizon of the project on the x-axis (generally with a monthly granularity), where all critical events of the project are scheduled in the top row. The other rows of the matrix highlight organizational responsibilities; for example, in the case of a large project

30

See, for example, Ward and Sobek II (2014).

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team, the rows may represent the various development sub-teams (see paragraph 7.1). As planning has to be carried out iteratively and progressively (rolling-wave planning), key deliverables needed to reach the nearest milestone are planned with cards (post-it notes in a physical board) placed at the expected completion dates. A planning matrix radically differs from a classic Gantt diagram since neither the start date nor the duration and interdependencies of activities are considered31: the focus is on visualizing who has to do what by when. The short-term matrix shows details of the long-term planning, typically with a weekly granularity. In the case of a large project team, each sub-team will manage the short-term planning on a dedicated matrix, which specifies the activities (visualized with cards placed at the expected completion date) needed to complete the key deliverables displayed in the long-term matrix. Planning matrixes are centred on a time-based visualization; on the right-hand side of Fig. 8.4, we have exemplified a form of visualization focused on workflow, which has attracted much interest in recent years due to the widespread use of Scrum. In the long-term, the planning board becomes a key deliverable roadmap, which displays in the x-axis the scheduled dates of gates and integration events and the workflow status (to-do—doing—done) of the deliverables required to reach the next major project milestone. In the short-term, each sub-team can plan all the activities necessary to complete the key deliverables under its responsibility through a Kanban Board32 with a time-box that corresponds to the short-term planning cadence (see the following section). In Fig. 8.4, we have highlighted the four types of physical planning board that emerge by combining the visualization focus (time-based vs workflow-based) with the time horizon (short-term vs long-term). These four typologies represent the basic ingredients of a visual planning system; each company must adapt and combine these ingredients to create a visual board “recipe” that is consistent with the specific application context, and the number and level of complexity of the project portfolio. In Fig. 8.4, all planning boards refer to a single project; but they can be easily adapted to visualize multiple projects simultaneously by assigning projects to the rows. Case study 8.2 presents a multi-project visual board used to manage the simultaneous weekly progress of multiple projects involving the same team.

31

Koudate (2003); Hines et al. (2006); Mascitelli (2011). It should be pointed out that the term “Kanban” also identifies a particular project management methodology developed by Anderson (2010); in the context of the “Kanban methodology”, the Kanban Board is a tool used to visualize workflow and the WIP (work in progress) limit of each process phase (see Kniberg and Skarin 2010). In this book, we have used the term Kanban Board to identify a generic workflow-oriented visual board. 32

8.4 The Relational Paradigm in Hardware Product Development: The Lean Approach Project 1

Project 2

149

Project 3

ISSUE

ISSUE

ISSUE

TO DO

TO DO

TO DO

DOING

DOING

DOING

FIX

FIX

FIX

(Key Events)

(Key Events)

(Key Events)

DESIGN

DESIGN

DESIGN

Fig. 8.5 Vertical Kanban Board for multi-project status meetings

Case Study 8.2 Caminetti Montegrappa designs and manufactures stoves, boilers and fireplaces within the INVIFLAM Group, a European leader in the production of domestic biomass heating equipment. About ten product development projects are generally active concurrently. Due to the company’s size, there are not teams dedicated to individual projects and, consequently, the development team is involved in all projects. In the Obeya, each project is displayed with a sort of “Vertical Kanban Board” (Fig. 8.5), structured as follows: • Row 1 (Issue): Each post-it represents an issue, so all unforeseen activities that need to be completed to ensure the success of the project are kept under control. The post-it is crossed out once the issue has been resolved. • Row 2 (To-Do): Each post-it represents a planned activity with an end date. The product development process has been standardized through the definition of a set of macro-activities leading to the creation of specific Key Deliverables; these activities must be included in the To-Do list. • Row 3 (Doing): Post-its of the activities are moved into doing when they are in progress; they are removed from the board when completed. (continued)

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Case Study 8.2 (continued) • Row 4 (Fix—the project milestones): This line displays the planned dates of key project events (Gate and Integration Events). • Row 5 (Design). It is an area to display other significant information (for example the block diagram of the product architecture, or the latest version of 3D rendering). The Kanban Board update cadence of all projects is weekly. It should be stressed that the adoption of visual planning is not necessarily in contrast with Gantt diagrams. Relational approaches radically move away from network diagrams and CPM scheduling algorithm as short-term planning and project execution tools. However, a simple Gantt representation of the major phases and their duration may help the project manager visualize the timing of key events and communicate with top management and project stakeholders or customers.

Management Cadence The second key feature of Lean approaches to project management is cadence. The basic idea is that the complexity and the intrinsic uncertain of non-repetitive activities typical of new product development can be better addressed in a rhythmic work environment based on regular planning and coordination cycles. Management cadence has two components: • planning cadence: the frequency of long-term and short-term planning meetings; • problem-solving cadence: the frequency of alignment meetings to coordinate product design decisions. In determining the planning cadence, the risk of losing opportunities for alignment and clarification among team members should be limited. The longer the interval between meetings, the more likely it is that errors or delays will accumulate; in a constantly changing environment such as product development, the team must frequently meet to synchronize commitments, coordinate activities and bring obstacles and problems to light. The aim is to break the “information batches” caused by a low synchronization frequency; the optimal frequency of the meetings depends on the speed of information changes and knowledge creation. Regarding the problem-solving cadence, lean product development literature highlights the critical role of implementing systematic design reviews.33 These

33

See Morgan and Liker (2018).

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periodic reviews are essential to address the technical and design issues that continuously arise during the project in a coordinated, proactive and timely manner. Scrum implements the two cadences with four well-defined events (Sprint Planning, Sprint Review, Sprint Retrospective and Daily Scrum): Sprint Planning is a two-part meeting that integrates problem-solving and planning activities (part one is focused on reviewing the product backlog and devising the Sprint Goal; part two is dedicated to planning); Sprint Review and Sprint Retrospective are problemsolving meetings, and Daily Scrum is a fast-paced status meeting to ensure that work is on course. In visual planning approaches there are no such prescriptive schemes. The relationship between problem-solving cycles and planning cadence depends on multiple factors. For example, in the case of small organizations with products with low architectural complexity, the two types of cadence can be integrated into a single weekly meeting. In the case of Caminetti Montegrappa (Case Study 8.2), the initial focus of the weekly meeting on “open issues” (visualized on the top box of the Vertical Kanban Board) serves as a quick design review of the project. In more complex organizational situations with a core team and several sub-teams (as assumed in Fig. 8.4), it is good practice to link the problem-solving cadence only with the long-term planning cycle. The long-term cadence should become the “takt time” of the core team, and it could be implemented by a two-part monthly meeting (similar to Sprint Planning in Scrum) dedicated to reviewing design decisions, analysing knowledge gaps and then planning the key deliverables to be completed before the next meeting. Conversely, the short-term cadence (e.g. bi-weekly) becomes the “takt time” of sub-teams, focused on task planning and tracking. In cases of very complex product architectures, it may be necessary to set up a network of cyclical design reviews, separated from planning cycles and focused on specific issues; think, for example, of the weekly package meetings34 in automotive development projects, dedicated explicitly to space allocation problems between several vehicle modules.

Virtual Visual Planning In the previous pages, we have highlighted the primary quality of a visual board: to be a “radiator” of information and a physical reference point for the face-to-face interaction of the project team; these two characteristics are essential to maintain a high level of synchronization and collaboration and to increase the speed of planning and problem-solving. In recent years, several new project management software tools have emerged that digitize Visual Boards and capture the essence of the relational perspective, being focused on collaboration and sharing of information and knowledge, rather

34

See Terwiesch et al. (2002).

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than on activity scheduling algorithms (the heart of the rational project management paradigm). The adoption of software tools must be carried out with great care: virtual visual boards must remain information radiators. With digitization, the physicality, simplicity, interactivity and clarity of visual planning must be maintained; from the point of view of hardware equipment, it is clear that the use of large touch screens is central. Conversely, virtual visual planning offers several complementary advantages: • post-its are transformed into dynamic cards with a rich set of information: changes in the activity status; “conversations” that have taken place regarding task execution; relevant documents; task effort; etc.; • there are multiple ways to visualize the project (time-based; workflow-based; resource workloads; personal calendars with deadlines; etc.); • it allows to manage a project which involves people that are not on the same site; • customized and dynamic performance dashboards can be created on the status of the project.

8.5

Development Speed and Overlapping

“We are too slow; we arrive too late, and we have to compress our product development time”. These statements resonate very often in the meeting rooms of many companies; but why is the speed of development a critical and central issue? Time has long been regarded as a strategic competitive factor.35 In particular, time-to-market of new products is a key differentiating factor from competitors and a lever for competitive advantage. At the same time, customer expectation of something new and better is progressively growing across all sectors; customers categorized (by scholars of innovation diffusion processes36) as “Innovator” and “Early Adopter” represent a growing percentage of the market and drive demand for new products. This phenomenon is also fuelled by the speed of technological change pervading many sectors; think, for example, of what is happening with smart and connected products and digital technologies. The cumulative effect is a progressive reduction in the life cycle of the products and a constant increase in the number of new product launches. In the automotive sector, for example, a model introduced in the early 1970s had an expected life of around 10 years, while a model launched in the 2000s had a half-life. In general, a product today reaches the end of its life cycle even if it still performs well; technological progress and competitors pressure have the effect of shortening products life cycle. This phenomenon occurs in many industrial sectors, both B2C

35 36

Balckburn (1993). Moore (1991).

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Scenario 1 Company A (the hare)

Company B (the turtle)

Scenario 2 Company A (the hare)

Company B (the turtle)

Lead Time

Fig. 8.6 The advantages of rapid development: two scenarios

and B2B, with a cascading impact on suppliers who, in turn, have to compress development times. To fully understand the nature of the benefits of a short development time, we use a simple example: consider two direct competitors who are developing a new product. The fast company represents the “hare”, while the slow competitor is the “turtle”; let’s assume two scenarios (Fig. 8.6). Scenario 1: The two companies start development at the same time, but the hare gets to launch the product before the turtle. What advantages will it have? If the product development process is robust and effective, it will be able to have sales revenues before the second one and strengthen its image and market share. Scenario 2: Let us now consider the two companies in a different situation. They are simultaneously launching the new product on the market (this frequently happens, for example, when new products are presented at a trade fair). The turtle had to start development well before the hare. In this case, the advantages of the company with fast development are even more evident. The turtle had to make forecasts, examine customers’ needs, analyse the market well in advance, therefore in conditions of greater uncertainty and also more significant risk. The hare is in more favourable conditions to understand market trends and scenarios because it is closer to the product launch; moreover, it will be able to benefit from technological

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8 Organizing Development Projects: Structural Choices and Planning Approaches

innovations, incorporating new technological opportunities in the product. It could also happen, to the detriment of the turtle, that the changes that occur in the markets or technologies force the company to make changes to the project, with the consequence of further increasing the development lead time. Reducing development time is a complex problem that requires action on multiple fronts: 1. the reduction of the engineering complexity of the project, using, for example, carryover strategies and modular architectures (see Chap. 6); 2. the fit between the level of complexity of the project and type of project manager (e.g. heavyweight od lightweight) and composition of the team member; 3. the adoption of a product development process with a high level of anticipation and reaction (see Chap. 5) to avoid unwanted and unforeseen process loops (e.g. engineering changes), which are necessary when problems emerge, or new information is unexpectedly acquired that renders previously deliberate design decisions obsolete; 4. the simultaneous execution of interdependent activities which, theoretically, should be carried out in sequence: the practice of overlapping (see Chap. 5). Let us consider, for example, the following activities carried out by two distinct groups of designers in the context of a vehicle development process, as described by Terwiesch and colleagues37: Activity A (engine design) and Activity B (the design of the air intake and filter module of the air conditioning system). Activity B needs the outputs of Activity A, as it is necessary, for example, to know the available spaces for the air intake module in the engine compartment (the geometry of this module is strongly dependent on the geometry of the engine, and the available space is minimal). Overlapping consists of starting Activity B in advance (without waiting for the end of the upstream activity) with preliminary information on the geometry and available spaces. The practice of overlapping involves risks linked to the lack of accuracy of the preliminary information (Fig. 8.7): when A releases the final details on the engine geometry (which differs from that previously communicated), modifications to the design of the air intake module (rework in activity B) are necessary to make it suitable for the new geometric configuration. It is interesting to highlight that in the specific case studied by Terwiesch and colleagues, the overlapping “engine-air intakes” involved 18 design modifications to the air intake module. The practice of overlapping inevitably generates extra uncertainty due to the use of preliminary information; and this additional uncertainty can lead to rework, which could affect the benefits of overlapping. Managing the simultaneous execution of interdependent activities requires strong coordination among team members and a high communication capacity to exchange information systematically. Relational

37

Terwiesch et al. (2002).

References

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OVERLAPPING

Activity A

Preliminary information on the output of A

Final Information

Activity B

RE-WORK to adapt to final information Time

Fig. 8.7 Concurrent engineering: overlapping and rework (adapted from Terwiesch et al. 2002)

approaches to project management can effectively support overlapping strategies, given their focus on frequent and rapid exchanges of information.

References Anderson, D. J. (2010). Kanban. Successful evolutionary change for your technology business. Sequim. Baglieri, E., Biffi, A., Coffetti, E., Ondoli, C., Pecchiari, N., & Pilati, M. (1999). Organizzare e gestire progetti. Competenze per il project management. ETAS. Balckburn, J. D. (1993). Competere sul tempo. La rapidità di risposta al mercato come fattore strategico per le imprese. Etas. Ballé, M., Morgan, J., & Sobek, D. K. (2016). Why learning is central to sustained innovation. MIT Sloan Management Review, 57(3), 63–71. Barkan, P. (1991). Strategic and tactical benefits of simultaneous engineering. Design Management Review, 2(2), 39–42. Bertilsson, J., & Wentzel, G. (2015). Visual planning: Coordination and collaboration of multi-site teams in product development organisations. Department of Product and Production Development, Chalmers University of Technology.

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Cooper, R. G. (2016). Agile–stage-gate hybrids: The next stage for product development blending agile and stage-gate methods can provide flexibility, speed, and improved communication in new-product development. Research-Technology Management, 59(1), 21–29. Cooper, R. G., & Sommer, A. F. (2016). Agile-stage-gate: New idea-to-launch method for manufactured new products is faster, more responsive. Industrial Marketing Management, 59, 167–180. Cooper, R. G., & Sommer, A. F. (2018). Agile–stage-gate for manufacturers: Changing the way new products are developed integrating agile project management methods into a stage-gate system offers both opportunities and challenges. Research-Technology Management, 61(2), 17–26. De Meyer, A., Loch, C., & Pich, M. T. (2001). Uncertainty and project management: Beyond the critical path mentality (pp. 1–23). Insead. Deemer, P., Benefield, G., Larman, C., & Vodde, B. (2010). The SCRUM primer, Version 1.2. Gingnell, L., Ericsson, E., & Sörqvist, L. (2012). Swedish lean product development implementation. In ASQ World Conference on Quality and Improvement. Hines, P., Francis, M., & Found, P. (2006). Towards lean product lifecycle management: A framework for new product development. Journal of Manufacturing Technology Management, 17(7), 866–887. Horikiri, T., Kieffer, D., & Tanaka, T. (2008). Oobeya–next generation of fast in product development. QV Systems. Kerga, E., Rosso, A., Bessega, W., Bianchi, A., Moretti, C., & Terzi, S. (2013). Compact teams: A model to achieve lean in product development. In International Conference on Engineering, Technology and Innovation (ICE) & IEEE International Technology Management Conference (pp. 1–10). Kniberg, H., & Skarin, M. (2010). Kanban and Scrum-making the most of both. Lulu.com. Koudate, A. (2003). Il management della progettazione. Isedi. Larson, E. W., & Gobeli, D. H. (1988). Organizing for product development projects. Journal of Product Innovation Management, 5(3), 180–190. Leach, L. P. (1999). Critical chain project management improves project performance. Project Management Journal, 30(2), 39–51. Leach, L. P. (2004). Critical chain project management. Artech House Publishers. Lindlöf, L., & Söderberg, B. (2011). Pros and cons of lean visual planning: Experiences from four product development organisations. International Journal of Technology Intelligence and Planning, 7(3), 269–279. Lindlöf, L., Söderberg, B., & Persson, M. (2013). Practices supporting knowledge transfer–an analysis of lean product development. International Journal of Computer Integrated Manufacturing, 26(12), 1128–1135. Mascitelli, R. (2011). Mastering LPD: A practical, event-driven process for maximizing speed, profits and quality. Technology Perspectives. McDonough, E. F. (2000). Investigation of factors contributing to the success of cross-functional teams. Journal of Product Innovation Management, 17(3), 221–235. McDonough, E. F., Kahnb, K. B., & Barczaka, G. (2001). An investigation of the use of global, virtual, and colocated new product development teams. Journal of Product Innovation Management, 18(2), 110–120. Moore, G. (1991). Crossing the chasm. Harper Collins. Morgan, J. M., & Liker, J. K. (2006). The Toyota product development system. Productivity Press. Morgan, J. M., & Liker, J. K. (2018). Designing the future: How ford, Toyota, and other worldclass organizations use lean product development to drive innovation and transform their business. McGraw Hill Professional. Oosterwal, D. (2010). The lean machine: How Harley-Davidson drove top-line growth and profitability with revolutionary lean product development. AMACOM. Ovesen, N., & Sommer, A. F. (2015). Scrum in the traditional development organization: Adapting to the legacy. In Modelling and Management of Engineering Processes (pp. 87–99). Springer.

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Radeka, K. (2017). The shortest distance between you and your new product: How innovators use rapid learning cycles to get their best ideas to market faster. Chesapeake Research Press. Radeka, K. (2019). High velocity innovation. Career Press. Rigby, D. K., Sutherland, J., & Takeuchi, H. (2016). The secret history of agile innovation. Harvard Business Review, April 20 (Digital Article). Schwaber, K., & Sutherland, J (2020). The Definitive Guide to Scrum: The Rules of the Game. www.scrum.org Siebdrat, F., Hoegl, M., & Ernst, H. (2009). How to manage virtual teams. MIT Sloan Management Review, 50(4), 63–68. Sommer, A. F., Hedegaard, C., Dukovska-Popovska, I., & Steger-Jensen, K. (2015). Improved product development performance through Agile/Stage-Gate hybrids: The next-generation Stage-Gate process? Research-Technology Management, 58(1), 34–45. Stenholm, D., Bergsjö, D., & Catic, A. (2016). Digitalization challenges for lean visual planning in distributed product development teams. In DS 84: Proceedings of the DESIGN 2016 14th International Design Conference (pp. 1595–1604). Sting, F. J., Loch, C. H., & Stempfhuber, D. (2015). Accelerating projects by encouraging help. MIT Sloan Management Review, 56(3), 1–9. Takeuchi, H., & Nonaka, I. (1986). The new new product development game. Harvard Business Review, 64(1), 137–146. Tanaka, T. (2005). Quickening the pace of new product development. QV System. (in https://www. scribd.com/) Taylor, B. W., III, & Moore, L. J. (1980). R&D project planning with Q-GERT network modeling and simulation. Management Science, 26(1), 44–59. Terwiesch, C., Loch, C. H., & Meyer, A. D. (2002). Exchanging preliminary information in concurrent engineering: Alternative coordination strategies. Organization Science, 13(4), 402–419. Ulrich, K. T., Eppinger, S. D., & Yang, M. C. (2020). Product design and development (7th ed.). McGraw-Hill. Ward, A. C., & Sobek, D. K., II. (2014). Lean product and process development. Lean Enterprise Institute. Wheelwright, S. C., & Clark, K. B. (1992a), Creating project plans to focus product development. Harvard Business Review, March–April, 3–14. Wheelwright, S. C., & Clark, K. B. (1992b). Competing through development capability in a manufacturing-based organization. Business Horizons, 35(4), 29–43. Wheelwright, S. C., & Clark, K. B. (1992c). Revolutionizing product development: Quantum leaps in speed, efficiency, and quality. Simon & Schuster. Wysocki, R. K. (2014). Effective project management: Traditional, agile, extreme. John Wiley & Sons.

9

Managing the Development Portfolio

Abstract

Company’s competitiveness is closely linked to its ability to adapt its product offering to market and technological changes. A product portfolio’s complexity depends on various factors: type of industry, available resources and competitive strategy. Many companies have a portfolio focused on a core product line—the product around which the original business model was built; however, success and growth often depend on the progressive expansion of the offer and increase in product variety, aiming to capture more and more market segments. Decisions on the development portfolio is a matter of central importance. It determines the evolution of the value proposition with which the company positions itself in the market and faces competitors.

In this chapter, the two fundamental steps of portfolio management will be discussed (Fig. 9.1): 1. Analysis and Selection: the transformation of new product ideas into a portfolio of approved projects through project classification and portfolio visualization. 2. Planning: the transformation of approved projects into scheduled projects, visualized through a project portfolio plan and product and technology roadmaps. As shown in Fig. 9.1, portfolio management realizes a transfer process from “front-end1” innovation activities (levels 1 and 2 of the innovation pyramid) to product development efforts and investments (level 3).

1

See Khurana and Rosenthal (1997, 1998)Koen et al. (2001).

# Springer Nature Switzerland AG 2021 S. Biazzo, R. Filippini, Product Innovation Management, Management for Professionals, https://doi.org/10.1007/978-3-030-75011-4_9

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9 Managing the Development Portfolio

Portfolio Management Portfolio Analysis & Project Selection

Portfolio Planning

Project Portfolio Plan

Project Classification

Intelligence & Discovery Product Ideas

Portfolio Visualizazion

Approved Projects

Product & Technology Roadmaps

Development Scheduled Projects

Fig. 9.1 Portfolio management: transforming new product ideas into development projects

9.1

Project Classification

Managing a portfolio of development projects is metaphorically similar to putting together a jigsaw puzzle; what makes this activity difficult is the fact that it usually requires to assemble several oddly shaped pieces. Therefore, it is essential to “simplify the puzzle” and define a limited number of project types or categories to be managed. A useful metaphor that succeeds in highlighting the critical role of project types is the “bin” concept proposed by Oosterwal2: a project, to be included in the portfolio, must fit into a bin of well-defined dimensions, i.e. it must belong to a specific type characterized by a particular combination of complexity, effort and lead time. Cooper and Edgett use the notion of strategic buckets3 to classify projects: a bucket is an “envelope of resources” that define project categories in terms of size and complexity. Project types represent the backbone of a portfolio management system: in order to be evaluated and then possibly included in the development portfolio, each potential new project must be classified along three basic dimensions: complexity, effort (person-hours of critical development resources) and lead time. As far as complexity is concerned, the crucial variable to be analysed and assessed is the novelty level of the expected output; novelty drives complexity as it increases the number of design decision with high unknowns. In order to characterize the overall project complexity, it is appropriate to structure the evaluation according to the logic of mediating assessments4 by identifying critical subsystems that must be independently assessed and deriving the final classification from a series

2 The importance of project classification has been well highlighted by Wheelwright and Clark (1992a, b, c); the bin metaphor, which echoes the well-known strategic bucket concept of Cooper et al. (2001), was elaborated by Oosterwal (2010). 3 Cooper and Edgett (2010). 4 On the usefulness of structuring complex decision-making processes using mediating assessments, see Kahneman et al. (2019).

9.2 Portfolio Visualization and Project Selection

161

of intermediate analyses. By adopting a mediating assessment approach, the classification process can be more accurate, fact-based and reliable (see Case Study 9.1). Three or four project types are generally used, following or adapting the wellknown novelty levels proposed by Wheelwright and Clark5; the four categories illustrated below are characterized by increasing complexity, lead time and effort. • Maintenance: these are the simplest projects that result in manufacturing efficiency improvement, quality problems reduction or supply-chain costs optimization. • Derivative: projects involving changes aimed at incrementally improving current products or at generating product variants derived from an existing platform to attack new market segments. • Platform: projects aimed at creating the next generation of a product line based on a new common platform. • Breakthrough: projects that create a whole new product line for the company and are typically characterized by radical product and process technology changes. With a sharp classification, a company’s product development strategy can thus be delineated by highlighting the distribution of the company’s investments in the different project categories. The standardization of project types generates two fundamental benefits: on the one hand, it facilitates communication processes related to project selection and planning; on the other hand, it provides a useful conceptual framework to visualize the company’s innovation ambition and operationalize the innovation strategy by distributing investments among different project types.

9.2

Portfolio Visualization and Project Selection

The inclusion of new projects in the portfolio entails a prioritization and selection problem, mainly when exploration processes (Chap. 4) are robust and generate a “well-stocked supermarket” of new product ideas. The problem is to optimize investments in such situations, choosing product development opportunities consistent with the company’s strategic priorities and innovation ambitions; portfolios must be managed with considerable forethought as the potential options are often greater than the available resources. To this end, portfolio matrices are valuable tools with which it is possible to clearly and concisely visualize the spectrum of initiatives in which the company has invested and intends to invest. A classic form of portfolio visualization is the matrix linking project effort (total person-hours of core development resources) with the expected financial results (using, for example, the net present value). An example of such a matrix is illustrated

5

See Wheelwright and Clark (1992a, b, c); Ulrich et al. (2012).

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9 Managing the Development Portfolio

Project type C

€ P1

Project type B Project type A

P2 Net Present Value

P3? P5 P6

P7?

P4

Effort

h

Fig. 9.2 A portfolio matrix: effort versus financial impact

in Fig. 9.2, where it has been assumed that the company has classified projects into three types—A, B, C, in descending order of complexity; projects P3 and P7 are highlighted with a question mark as the company’s management has judged unsatisfactory the NPV/effort ratio. Portfolio approaches that exclusively adopt financial criteria for project analysis and selection have substantial limitations and have been frequently criticized in the literature.6 In the context of innovation and new product development, the uncertainty in profitability forecasting is significant and worsens as the output novelty level increases. Multi-year financial projections may hide such an amount of variance that this kind of quantitative project evaluations may lose their meaning even though they are apparently objective. Therefore, it is important to complement the financial dimension by adopting a multidimensional analysis and considering a combination of qualitative factors. In this perspective, another useful visual representation and evaluation method of the development portfolio is the matrix in Fig. 9.3, highlighting the consistency between technological novelty and perceived market novelty. A variant of the novelty matrix involves the intersection of technology knowledge and market knowledge bases that are required by new projects: the most complex and risky initiatives require completely different technical expertise compared to the status quo and target entirely different markets which have several unknowns (Fig. 9.4).7

6 7

Christensen et al. (2008); Cooper et al. (2001). See Day (2007)

9.2 Portfolio Visualization and Project Selection

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Project type C Projects without a leverage effect

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cy en ist ns

ne zo

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Fig. 9.3 Novelty level matrix Project type C New to the company

Project type B

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Fig. 9.4 Technology-market knowledge matrix

New to the company

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9 Managing the Development Portfolio

In order to visualize projects in the matrices in Figs. 9.3 and 9.4, it is necessary to develop qualitative measurement scales for the matrix axes. For example, to position a project in the axis of the “market knowledge base”, we can identify several evaluation factors (such as the “company’s knowledge of customer needs and decision processes”) to be assessed with a 5-level Likert scale; the project’s position in the “market knowledge base” will be obtained by adding the scores of the evaluation factors. Generally, members of an interfunctional team assign these evaluations. A fourth way of visualizing the portfolio focuses on multidimensional project scoring. Scoring tools aim to evaluate a project with an overall score that takes several factors into account. As an example, a well-known simple tool is the RWW8 (real-win-worth) method. RWW is structured around three key dimensions, which are, in turn, articulated in specific evaluation questions. • Real: the soundness and feasibility of the idea (is it real?). Have customer needs been clearly identified? Is the market size attractive? Is the product idea clear? Is it feasible with the available skills? • Win: the probability of success in the market (can we win?). Do we know the market better than the competition? Does the product have clear elements of differentiation from the competition? Is the timing of the launch appropriate? • Worth: the project’s motivation (is it worth doing?). Are revenue forecast higher than costs? Is there alignment with the company’s strategic priorities? (e.g. is the project aimed at regaining market share or entering a new segment of importance to the company’s growth plans?). The easiest way to use RWW is to associate a binary result with each question (0–1) and then add up the results to arrive at an overall evaluation score for the project. RWW is an additive scoring model that produces a single list of project priorities. On the contrary, scoring-based visualization matrices identify two axes of evaluation that must be conceptually orthogonal to each other; the project’s global score is the multiplication of the two axes’ evaluations. A high score in one dimension does not compensate for a low score in the other (as happens in additive scoring models such as RWW). RWW method and the above-described matrices can be put together “on the table”: they support the portfolio’s decision process and allow to have a common language. Competitive attractiveness and technical feasibility are the most frequently used orthogonal scoring dimensions.9 Each scoring dimension can be broken down into several factors to be assessed individually, and the overall score is simply the average of the factor ratings.

8

Day (2007); Terwiesch and Ulrich (2009). An interesting scoring tool based on the dimensions of feasibility and attractiveness has been developed by Mitchell et al. (2014). 9

9.2 Portfolio Visualization and Project Selection

165

• Competitive attractiveness dimension includes factors such as the level of differentiation from the competition; the sustainability of the competitive advantage; the uniqueness of the benefits offered to customers; the profitability levels. • Technical feasibility dimension includes factors such as the project’s technical challenge (project objectives that represent a radical change from current products) and technical capability (the availability of knowledge and expertise to tackle the project). Likert 1–5 scales can be used to assess individual factors in each dimension, in which scores are anchored to specific statements that illustrate their meaning. For example, for the factor “level of competitive differentiation”, a 1–5 scale could be formulated with a linguistic anchor at each score or at the extreme scores: • 1 ¼ no product attributes differ from the competition. • 5 ¼ many relevant product attributes are superior to the competition. Another example of a 1–5 scale, concerning the factor “technical challenge”, is the following: • 1 ¼ significant changes with solutions not yet tested in products. • 5 ¼ modest changes with known and widely tested technical solutions. According to the average score obtained in the two dimensions, the development projects can thus be placed in the attractiveness—feasibility matrix10 (Fig. 9.5). The figure also shows the curve representing the points where the project’s overall score (attractiveness multiplied by feasibility) is 9. This curve divides the diagram into two areas: projects above this line are of high strategic interests as they have an overall opportunity—feasibility score higher than the average value 9. Finally, development projects can be mapped by focusing on “risk”, as illustrated by the matrix in Fig. 9.6. Market risk can be determined by considering several factors (which, as usual, can be assessed using qualitative 5-point Likert scales), for example: • • • •

market novelty and lack of commercial knowledge; competition intensity; weakness of the brand; complexity of commercial initiatives to be undertaken (e.g. building a distribution channel from scratch). Technological risk can be assessed by taking into account:

10

See Mitchell et al. (2014).

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9 Managing the Development Portfolio

5 High Strategic Interest

Technical Feasibility

3

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1 1

3

5

Fig. 9.5 Attractiveness—feasibility matrix

• • • •

rate of technological change; difficulty in acquiring the know-how needed to carry out the project; depth and breadth of company knowledge gaps; barriers such as patents or certification requirements.

The technology and market risk matrix highlights the problem of consistency between the project’s risk profile and its potential benefits. The portfolio matrices presented above allow visualizing innovation strategy from different perspectives: • The first matrix (Fig. 9.2) focuses on return on investments and promotes a financial view of innovation efforts. • The second, third and fourth matrixes (Fig. 9.3, 9.4, and 9.5) provide a strategic perspective in portfolio analysis, highlighting the potential competitive and market impact of development projects compared to the needed technological effort. • The fifth matrix (Fig. 9.6) stresses the assessment of project risks, a perspective which does not emerge explicitly in the other visualizations.

9.3 Project Portfolio Planning

High

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Is there any consistency between TECHNOLOGICAL RISK and the strategic importance of know-how acquired during the project?

HIGH RISK

Technological Risk

Low

Is there any consistency between MARKET RISK and the strategic importance of the project’s commercial objectives?

LOW RISK

Low

Market Risk

High

Fig. 9.6 The technology and market risk matrix

No single matrix alone can provide all the information needed for a comprehensive and robust assessment. Therefore, these perspectives should be combined to examine the development portfolio through different observation lenses and make analysis and project selection more effective. Moreover, it is crucial to define how management arrives at a shared project positioning assessment. A frequently adopted process has two fundamental phases: a first phase in which top managers, with the support of future project managers and functional experts, independently evaluate each development project; a second phase focuses on the sharing and discussion of individual scores, to reach a consensus in the formulation of judgements.

9.3

Project Portfolio Planning

The primary planning tool is the project portfolio plan (PPP), which visualizes the project schedule and the expected loading of development resources. PPP is typically a quarterly plan11 as its purpose is to give a high-level visual summary of start

11 A project portfolio plan with a granularity of less than a quarter—e.g. monthly—is only appropriate for development projects with very short lead times (less than a year).

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Fig. 9.7 An example of a project portfolio plan

and end-dates of all projects in the portfolio and ensure a macro-level (medium to long-term) balance between available and planned workload. Figure 9.7 shows a project portfolio plan with two product lines (A and B); relevant events in the sector (e.g. a trade fair) are also highlighted, to focus the attention on the synchrony between product development activities and the external environment. For each project, critical resources’ workload (estimated in terms of quarterly full-time equivalents) is displayed. In the example, five organizational units of development resources are considered; in order to verify the PPP’s feasibility, it is necessary to check the compatibility in each quarter between available resources and total workload. In the example of Fig. 9.7, there are two project categories: platform projects (PLAT) and derivative projects (DER) and two product lines (A and B). As far as product line A is concerned, the platform project PLAT_1 will introduce three different product models into the market. Afterwards, two derivative projects will introduce two high-end extensions (DER_1-3000; DER_1-4000) based on the new PLAT_1 platform.

9.3 Project Portfolio Planning

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A fixed launch cadence12 characterizes the project portfolio plan illustrated in Fig. 9.7: a platform project is launched every 2 years and a derivative project every year. Wheelwright and Clark13 first highlighted the importance of having a rhythmic structure on portfolio planning; subsequently, the idea of cadence in the introduction of new products onto the market was taken up and emphasized in the lean product development literature.14 The regular pace of project launches (the so-called takt-time of the project portfolio) creates an orderly and stable development environment. The project portfolio takes on the characteristics of a “development factory”, i.e. a system capable of generating a constant flow of new products. Ward proposed a method to establish a portfolio cadence15: 1. Determine the demand time for each project class—how often should a specific type of project be launched in the market? For example, it might be deemed necessary to implement a new “platform project” every 4 years. This cadence can be changed over time, depending on the evolution of the industry’s life cycle. 2. Identify project types (paragraph 8.1) with standard lead times. 3. Define the cadence time, the actual time interval between the launch of two successive projects of the same type. For example, if the company can achieve a 2-year development lead time for platform projects—which have a 4-year demand time—it might be possible to adopt a 2-year launch strategy to differentiate itself from the competition. Implementing a cadenced portfolio is extremely complex as it requires considerable process management (Chap. 5) and project management skills (Chap. 7). Maintaining a “takt time” in portfolio planning is a challenging objective (see Case Study 9.1). Case Study 9.1 (by Silvia Modino and Mauro Lentoni). Olimpia Splendid, a leading Italian company in the HVAC (heating, ventilation and air conditioning) industry, has recently teamed up with consultancy CONSIDI to transform its portfolio management and product development process in a lean and agile perspective. This change in the development system allowed a reduction in project development time and increased its ability to (continued) The concept of cadence (steady streams sequencing) was introduced in the seminal work of Wheelwright and Clark (1992a, b, c) and taken up many years later in the lean product development strand (Oosterwal, 2010; Ward & Sobek II 2014). 13 See Wheelwright and Clark (1992a, b, c). 14 See Ward and Sobek II (2014) and Oosterwal (2010). 15 Ward and Sobek II (2014). 12

Fig. 9.8 The definition of the thermodynamics subsystem BIN

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Fig. 9.9 Cadence in the project portfolio plan

Case Study 9.1 (continued) launch many successful projects than before through a carefully designed development cadence. The ability to manage a cadenced portfolio is based on identifying welldefined project types, which in Olimpia Splendid are referred to as “BINs”. Four BINs have been defined at increasing complexity and innovation levels: BIN 1, BIN 2, BIN 4 and BIN 6. The following steps were implemented to perform this classification. 1. Identification of the critical subsystems that constitute the product: thermodynamics, mechanical components, controls, aesthetics, certifications, customization modules. 2. Detection of the key parameters which define the complexity of each identified subsystem. For example, the thermodynamics subsystem was characterized by the following parameters: efficiency, energy yield, noise, product dimension. 3. Definition of a scale of complexity for each parameter identified. For example, for thermodynamics subsystem efficiency, the three complexity levels were: no efficiency variation, increase in efficiency with actual parameters far from the limits, increase in efficiency with actual parameters already close to the limits. 4. Definition of each subsystem BIN: The subsystem’s different parameters are progressively related to each other through a cascade of BIN matrices (Fig. 9.8). Each crossing of the matrix represents an intermediate evaluation of whole subsystem complexity, which considers two parameters; for example, in the first matrix that links efficiency to energy yield, energy yield reduction with no efficiency variation is a BIN 1, while energy yield reduction with an increase in efficiency with actual parameters far from the limits is BIN 2. (continued)

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Case Study 9.1 (continued) 5. Definition of the overall project BIN through the combination of all subsystem BINs. Generally, the product BIN is equal to the BIN of the most critical subsystem; however, there may be variations to this rule to consider global complexity assessments. For example, when several subsystems are classified with the same BIN (e.g. BIN 4), the final product BIN may be one level higher (e.g. BIN 6). The BIN classification of each subsystem entails a significant advantage: the opportunity to identify the most critical aspects of the project immediately. This approach has generated a mindset change since it became clear that to deliver the product on time, the development team should focus their attention and effort on the most critical subsystems (the ones that generally have some parameters already close to the maximum acceptable limit) and start working on them as soon as possible in order to avoid delays and problems in late development stages. Once defined the BIN system’s architecture, a software application was created to facilitate the classification of different projects. Moreover, a standard high-level Gantt was generated; this Gantt is modular and parameterizable based on each subsystem’s complexity. Thanks to the BIN standardization, each phase was dimensioned in terms of lead time and workload. Through the implementation of the BIN system, it was, therefore, possible to create a project portfolio plan (Fig. 9.9) based on the concept of cadence and flow, respecting the limitation of workload across the organization by avoiding situations of oversaturation. A second planning tool is the product generation roadmap or product segment map.16 An example is illustrated in Fig. 9.10 and refers to the outputs of the A-line projects shown in the project portfolio plan in Fig. 9.7; the y-axis represents market segmentation (in the example, low-end and high-end product performances). The product generation roadmap visualizes the product life cycle (phase-in, phase-out), the role of development projects in changing the product portfolio, and those competing products against which the company wants to compete. A third planning tool is the technology roadmap,17 which is designed to highlight the product’s technological evolution, crossing three perspectives: subsystems or modules with their different component technologies and product generations. Let us assume that the product A-line of our case example can be characterized by three 16

For an in-depth look at the visualization of product development project outputs see Wheelwright and Sasser Jr (1989) (product development map) and Ulrich et al. (2020) (Product Segment Map). 17 For an in-depth discussion of technology roadmapping see Moehrle et al. (2013); Phaal et al. (2004a, b); Dissel et al. (2009).

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Fig. 9.10 Product generation roadmap (A-Line)

key modules: sensors, user interface and diagnostic system. Figure 9.11 shows the technological contents of the products that will be developed in the PLAT_1 and DER_1 projects; moreover, the first hypotheses of the technological changes that could be implemented in the future platform project after PLAT_1 were also displayed. Portfolio analysis, selection and planning are key innovation management activities as project options very often exceed the available resources; the adverse effects of inadequate portfolio management are manifold. First of all, there is the risk of lacking product competitiveness in certain target market segments, generated by a lack of vision in project planning and resource allocation. Furthermore, the inability to effectively manage the overall resource load, caused by the lack of an aggregated project launch plan (too many projects running, with no clear priorities) has a strong negative impact on projects’ lead time and organizational climate. Finally, the lack of shared and formalized evaluation criteria also increases the likelihood that projects will be selected in an overly subjective and emotional way or based on organizational politics, leading to the development portfolio’s strategic inconsistency.

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9 Managing the Development Portfolio COMPONENT TECHNOLOGIES

SUBSYSTEMS

Sensors

Accelerometer Proximity sensor Brightness sensor

User Interface

Full Touch

Diagnos c system

Cloud system for maintenance management

Smart sensors?

Touch 3D

Multiple Gestures User Interface?

AI-based Diagnostic System

New products PLAT_1 & DER_1

Existing products

New Future Plaorm

PRODUCT GENERATIONS

Fig. 9.11 An example of a Technology Roadmap

A blurred strategic vision in allocating investments may lead to a severe dissipation of product development efforts, with highly detrimental effects on innovation ambitions and performance.

References Christensen, C. M., Kaufman, S. P., & Shih, W. C. (2008). Innovation killers. How financial tools destroy your capacity to do new things. Harvard Business Review, 86(1), 98–105. Cooper, R. G., & Edgett, S. J. (2010). Developing a product innovation and technology strategy for your business. Research-Technology Management, 53(3), 33–40. Cooper, R. G., Edgett, S. J., & Kleinschmidt, E. J. (2001). Portfolio management for new products. Basic Books. Day, G. S. (2007). Is it real? Can we win? Is it worth doing? Harvard Business Review, 85(12), 110–120. Dissel, M. C., Phaal, R., Farrukh, C. J., & Probert, D. R. (2009). Value roadmapping. ResearchTechnology Management, 52(6), 45–53. Kahneman, D., Lovallo, D., & Sibonya, O. (2019). A structured approach to strategic decisions. Reducing errors in judgment requires a disciplined process. MIT Sloan Management Review, 67–73. Spring. Khurana, A., & Rosenthal, S. R. (1997). Integrating the fuzzy front end of new product development. Sloan Management Review, 38(2), 103–120. Khurana, A., & Rosenthal, S. R. (1998). Towards holistic front ends in new product development. Journal of Product Innovation Management, 15(1), 57–74. Koen, P., Ajamian, G., Burkart, R., Clamen, A., Davidson, J., D’Amore, R., Elkins, C., Herald, K., Incorvia, M., Johnson, A., Karol, R., Seibert, R., Slavejkov, A., & Wagner, K. (2001). Providing

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clarity and a common language to the “fuzzy front end”. Research-Technology Management, 44 (2), 46–55. Mitchell, R., Phaal, R., & Athanassopoulou, N. (2014). Scoring methods for prioritizing and selecting innovation projects. In Management of Engineering & Technology (PICMET), IEEE 2014 Portland International Conference. Moehrle, M. G., Isenmann, R., & Phaal, R. (2013). Technology Roadmapping for strategy and innovation. Charting the route to success. Springer. Oosterwal, D. (2010). The lean machine: How Harley-Davidson drove top-line growth and profitability with revolutionary lean product development. AMACOM. Phaal, R., Farrukh, C. J., & Probert, D. R. (2004a). A framework for supporting the management of technological knowledge. International Journal of Technology Management, 27(1), 1–15. Phaal, R., Farrukh, C. J., & Probert, D. R. (2004b). Technology roadmapping—A planning framework for evolution and revolution. Technological Forecasting and Social Change, 71 (1), 5–26. Terwiesch, C., & Ulrich, K. T. (2009). Innovation tournaments: Creating and selecting exceptional opportunities. Harvard Business Review Press. Ulrich, K. T., Eppinger, S. D., & Filippini, R. (2012). Progettazione e sviluppo prodotto. McGrawHill. Ulrich, K. T., Eppinger, S. D., & Yang, M. C. (2020). Product design and development (7th ed.). McGraw-Hill. Ward, A. C., & Sobek, D. K., II. (2014). Lean product and process development. Lean Enterprise Institute. Wheelwright, S. C., & Clark, K. B. (1992a), Creating project plans to focus product development. Harvard Business Review, March–April, 3–14. Wheelwright, S. C., & Clark, K. B. (1992b). Competing through development capability in a manufacturing-based organization. Business Horizons, 35(4), 29–43. Wheelwright, S. C., & Clark, K. B. (1992c). Revolutionizing product development: Quantum leaps in speed, efficiency, and quality. Simon & Schuster. Wheelwright, S. C., & Sasser, W. E., Jr. (1989). The new product development map. Harvard Business Review, 67(3), 112–125.

Product Innovation and Business Models

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Abstract

The product and its accompanying services are the core elements of a company’s value proposition, and product innovation plays a central role in creating a sustainable competitive advantage. However, the ability to unlock the transformative and revenue-generating potential of new products lies, in certain situations, in the change of other components of the firm’s “way of being” in the competitive arena. In other words, the ability to capture the value of product innovation depends on the business model in which the product is embedded. We will address this topic with an emphasis on product innovations in the current era of digital transformation.

10.1

Innovation and Digital Transformation

The dynamic of innovation is nowadays strongly dependent on digital transformation, artificial intelligence (AI) and big data. The concept of disruptive innovation proposed by Christensen (e.g. capturing new customers with low-end products; see Chap. 2) is now manifesting itself in new and different forms.1 We can characterize digital transformation according to two scenarios: a. new organizational forms based on integrated digital systems to move from traditional B2B or B2C to forms of direct relationships with customers (D2C); b. intelligent and connected products (ICP). (a) There are several examples of companies that, through the adoption of digital technologies, have created new organizational forms that have gone beyond the 1

See Downes and Nunes (2013); McGrath (2020).

# Springer Nature Switzerland AG 2021 S. Biazzo, R. Filippini, Product Innovation Management, Management for Professionals, https://doi.org/10.1007/978-3-030-75011-4_10

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traditional way of organizing transactions with customers, trying to have a direct relationship with customers (D2C). Most of these companies operate their business online, as Amazon, Alibaba, Airbnb, Booking and many others. These organizations are not simple examples of e-commerce. They do not compete directly with traditional companies, but they create a new model of managing the relationship with customers offering a new and higher value, a customer experience. These players can grow their business thanks to accumulating and elaborating data and using AI to recognize customer needs in a completely new way, offering better services to customers and suppliers of third parties. Software and digital technologies are the core business in these companies. Iansiti and Lakhani2 state that these companies use their capabilities in data analytics and AI, and their ability to generate network and learning effects, to increase their scope and the depth of interactions with their customers. This new way of organizing the business model is becoming more frequent in service industry. However, several manufacturing companies are moving from traditional B2B or B2C business model to a customer-centric approach, powering a D2C model. Vibram, for example, a B2B manufacturing company since 1937, produces high-performance rubber soles. Recently it created a new exciting opportunity of interacting with its final users using a set of digital technologies (apps, site, platforms), offering a new type of shoes and bags in the global consumer market, having a direct relationship with users and collecting big data from their behaviour.3 (b) Another new form of organizing business revolves around intelligent and connected products (ICP). ICP is the third level of product evolution: (1) purely physical products are at the first evolutionary level; (2) intelligent products (characterized by data collection on-board and ex-post analysis) represent the second level; (3) the third level is that of intelligent and connected products, which are capable of sending and receiving data and creating the so-called internet of things (IoT). Let’s consider a few examples. Babolat offers a new connected tennis experience: “Tracking your game now becomes possible with Babolat’s breakthrough innovations; join the Babolat Tennis Community with a product for everyone4”. The tennis racket, equipped with several sensors, is connected to the smartphone with a dedicated App. The player can check his/her game, move to the next level, share performance, join the community. Using smart rackets, players can live a novel connected tennis experience. Unox produces a new line of intelligent and connected ovens for restaurants. Ovens are connected with Unox, which can analyse big data, improve the product and help customers to solve problems. Ovens can catch data from Unox—for example, receive an updated version of the software. Connected ovens allow restaurant chains and fast-food chains to monitor and check the different ovens’ operative

2

See Iansiti and Lakhani (2020). https://eu.vibram.com. 4 www.babolatplay.com. 3

10.2

Business Model: The Company’s “Way of Being” in the Competitive

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behaviour around cities and countries. By Apps, cooking and technical assistance, Unox communicates its value saying “you will never cook alone”. Urban mobility, especially in big cities, is being transformed by electric connected bikes or scooters. In Paris, for example, there are more than 15,000 shared electric scooter. People can find the closest scooter using an App and a QR code on the scooter and leave the scooter wherever they arrive. Using the shared scooter fleet is a very convenient and valuable way of moving. At the same time, the municipal administration can get many traffic data, having the possibility to organize bike path and bus route better. Connected and intelligent products will be the future of many industries, to mention a few: house automation, health care, agriculture, transport, automotive. ICPs require several digital technologies to be adopted, like sensors, cloud computing, artificial intelligence and big data analytics. ICPs are one of the so-called Industry 4.0 technologies,5 which include cyber-physical systems, intelligent robotics, 3D printing and augmented reality. Developing an ICP is a tough challenge. In several cases, ICPs move up customer expectations and needs because people can’t imagine having at their disposal such type of innovative and intelligent products. ICPs often stress a company’s business model, which doesn’t fit with the new market value proposition that smart products can offer. This chapter will highlight how important it is to check the coherence between ICPs and business models to maximize both the value for the company and customers.

10.2

Business Model: The Company’s “Way of Being” in the Competitive Environment

In recent years, there has been growing attention in management and academic literature on the business model concept, and many definitions have been formulated. Here are some of them. • A business model consists of four interconnected elements: the value proposition to the customers, the profit formula (how the company manages to create value for itself while creating value for customers), key resources and key processes.6 • The essence of a business model lies in defining how the company delivers value to customers, persuades them to pay for that value and converts those payments into profit; it reflects management’s assumptions about what customers want and how the company can best organize the satisfaction of those needs, achieve revenue and make a profit.7

5

See Kagermann et al. (2013); Deloitte (2015). Johnson et al. (2008). 7 Teece (2010). 6

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• A business model fulfils the following functions: to articulate the value proposition; to identify market segments and revenue generation mechanisms; to define the structure of the value chain to create and distribute the offer and complementary resources needed to support its position in the value chain; to estimate the cost structure and potential profits; to describe the role of the company in the value network linking suppliers and customers.8 • A business model defines the conditions of doing business and sheds light on the gap analysis between needed resources and existing resources and on the search to increase the profitability of the enterprise.9 Despite some differences, a common theme emerges: a business model systemically describes the logic by which an organization creates, distributes and captures value by interacting with the surrounding ecosystem.10 From the perspective of the sustainability of competitive advantage, the effectiveness of a business model is not only linked to internal consistency, or to the degree of novelty of the ‘logic of doing business’ defined by the model. Effectiveness is also related to the relationship between the business model and the competitive and social environment in which the company is immersed; a relationship that refers, for example, to barriers to imitation by other companies, to the intensity of competitive pressure, or entry barriers. A business model reflects the company’s strategy, the result of fundamental, not easily reversible, competitive positioning choices that are made over time. Then, the business model determines the boundaries of the decision space available for operational choices that define the details of the functioning of the enterprise’s way of being in a specific competitive arena (e.g. in the case of a business model centred on product rental, such choices may concern the types of service to be offered, contractual options and pricing strategies). The ability to capture value from product innovation does not depend on rethinking the business model only when the new product’s success is entirely consistent with the current business model or requires incremental changes within the boundary of the company’s “way of being” in the competitive environment. Intelligent and connected products represent an ambitious innovation challenge, as they unavoidably require strategic and business model radical changes. Remaining confined to the marginal adjustments allowed by the established business model can cause even the most innovative, unique and perfectly responsive products to fail in the market. However, decisions on which business model elements to change or innovate are very complex, particularly when product innovation is significant. It can lead to endless discussions that sometimes divide those in the company who have different languages and mental models. Therefore, it is useful to have a framework that allows

8

Chesbrough (2010). Eisenmann (2014). 10 Osterwalder and Pigneur (2010); see also Amit and Zott (2001); Shafer et al. (2005). 9

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Business Model Canvas: A Visualization Tool

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us to analytically discuss what and how we need to change in the company’s business model. This framework is the Canvas, which we will see briefly in the next paragraph.

10.3

Business Model Canvas: A Visualization Tool

For the business model concept to be effectively used in strategic analysis and innovation, it is necessary to have a framework that allows the various constituents of the company’s “way of being” to be explained and represented synthetically. There is no doubt that the most widespread and internationally used conceptual scheme is the Business Model Canvas (briefly, the Canvas) by Osterwalder and Pigneur, developed with the collaboration of several professionals in 2004.11 Canvas is a visual framework that describes and holistically examines the business model of an organization or enterprise. Canvas reminds us of oil painting, and the authors decided to use this term to evoke the image of the blank surface on which a business model is visualized, analysed and innovated. The Canvas is a model, a conceptual tool useful to capture the essence of a complex system, understand its functioning and facilitate the communication between the decision-makers. It contains nine fundamental, interdependent blocks or constructs to describe a current or future business model. The Canvas is centred on a visual approach to summarize how a company creates, distributes and captures value (Fig. 10.1). The sequence with which the nine blocks of the Canvas must be analysed must follow a precise path, aimed at “telling” the basic logic of the company’s way of “doing business”. The right part of the Canvas represents how value is offered to established and new customer segments, identifying sales channels and types of relationships with the different segments. From this combination of elements comes the revenue stream for the company. The left-hand side of the Canvas highlights the means and resources used to create customer value. These elements include key processes, human resources (and their skills), financial resources needed and key partners. These elements, of course, define the company’s cost structure. From a practical point of view, it is important to use the Canvas as a classic “visual management” tool; therefore, it is good to print it on a large board to physically interact with it through post-it notes or markers. The Canvas makes a complex concept such as the business model visible and “manipulable”; by defining a common language, it is a tool that favours the activities of analysis and critical discussion of the status quo and the creative processes of strategic innovation. Through the Canvas it is possible to illustrate both the general framework and the interdependencies among the nine elements of the business model visually; the format is suitable to be used in different business contexts both to reconstruct and critically analyse the current business model (current state) and to trigger a discussion on new and alternative models (future state).

11

Osterwalder and Pigneur (2010).

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Fig. 10.1 Visualizing the business model: the Canvas (Osterwalder and Pigneur, 2010 and Srategyzer AG, licenced under CC BY-SA 4.0)

In the following, we will exemplify some consequences on business model building blocks resulting from innovations driven by Industry 4.0 technologies (including ICP).

Customer Segments What are the customer segments that the company’s offer is aimed at? This Canvas element defines the different groups of people or organizations that a company wants and can reach and serve. The various segments are reached through specific channels, require proper types of relationships and create diverse revenue streams. Intelligent robotics and additive manufacturing can foster mass customization strategies to fully satisfy customers who require tailor-made solutions and can unlock imagination to create new value propositions (e.g. product co-creation processes). ICP innovations make it possible to reach new and valuable customer segments, as in the case of smart and connected ovens that meet the needs of restaurant and fast-food chains that are very sensitive to productivity and open to digital innovations.

Value Propositions For each specific segment, what is the value proposition for customers? The value is delivered through the set of “products” (goods and services) that a company

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Business Model Canvas: A Visualization Tool

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proposes to customers seeking to satisfy their needs and differentiate itself from its competitors. Value can be created in multiple ways, for example, through the novelty of fulfilled needs, customized solutions, increased productivity of customer activities, accessibility, ease of use, etc. Intelligent and connected products offer new value for customers: the product becomes, in effect, a digital platform that enables the development of new services and substantial savings for the customer. For example, by reducing product failures, shutdowns or malfunctions. In some cases, the revenue-generating mechanism can be radically changed, adopting the product-as-a-service model, where an integrated rental-services contract replaces the product’s sale. In the case of products that are used intermittently, such as in city biking, the product-sharing model could be adopted, where customers only pay for the product’s use. In the case of Industry 4.0 innovations in business processes, the offered value can be increased by lead time compression, cost reduction or more flexibility to customer demand.

Channels How do you interact with customers in offering your value proposition? Communication, distribution and sales channels are the company’s interface with its customers. They play a fundamental role in customer experience. Channels describe how a company communicates with and reaches out to its customer segments to bring value, before and after the sale. Communication and connection with customers can benefit from digital technologies by facilitating a two-way relationship, moving from a push sales system to a pull system in which the customer has a proactive role in developing the ‘product-service’. Companies moving from traditional B2B or B2C sales systems to D2C systems use new channels based on digital technologies, and this shift has substantial consequences on resources, internal processes and key partners (the left part of the Canvas).

Customer Relationships What kind of relationship is established with customers? It can range from a personal relationship to an automated one, from an ongoing to sporadic. Like channels, relationships are essential because they have a considerable influence on the customer experience and loyalty. An intelligent and connected product enables a systematic and robust relationship to be established with the customer; for example, the volume of data on connected ovens allows new forms of relationship with users to be developed and maintained. In D2C contexts, the traditional relationships between company and consumer grow radically.

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Revenue Streams What value is each customer segment willing to pay? How and with which pricing mechanisms does the business model generate value? Revenues may derive from different types of transactions: sale of goods, cost per use, rental, leasing, licencing. In all cases, revenues correspond to the value offered, the relationships established and the channels used, consistent with customer expectations. The transformation of physical products into digital platforms opens up significant opportunities to reach new customer segments and obtain additional revenue streams. Even higher revenues than those from traditional after-sales services can be achieved, for example, by switching to performance-based contracting models. In the field of 4.0 innovations in manufacturing, a faster and more flexible response to the customer, including product customization, allows for a premium price and thus an increase in revenue streams.

Key Resources What is the infrastructure needed to create, capture and distribute value? What are the key resources required for the specific business model? Which core capabilities are demanded? Changes in the value offered, the channels and the type of relationship with customers require specific and different key resources. They may concern human and managerial resources but also financial and intellectual resources. A critical factor often pointed out by companies regarding the adoption of 4.0 technologies in products and processes is the skills in big data analytics and a lack of “data culture” in management. These new competencies need to be combined and integrated with lean management and continuous improvement skills, which are essential components to exploit the potential of digitalization fully.12

Key Activities What are the crucial activities and processes that the enterprise must have to realize its value proposition, reach markets and maintain customer relationships? What does a company need to “know how to do” very well to sustain its business model? Moving from a business based solely on the sale of products to one that is more focused on digitization-related services entails redefining various business activities (e.g. the entire sales process must be reorganized, as must service and warranty services), or creating new activities and organizational units (e.g. processing and managing big data relating to product use and ongoing interaction with users). At the same time, cost analysis and pricing activities will have to be reorganized.

12

See, for example, the empirical research in Agostini and Filippini (2019).

10.3

Business Model Canvas: A Visualization Tool

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Key Partnerships Which partners are needed to support the business model consistent with the innovations introduced? No single company has all the resources and skills required to implement the new value proposition, so it is necessary to develop deep relationships with a network of external actors who can complement the company’s activities and skills. System integrators and IoT solution providers play a key role in implementing product and service innovations related to 4.0 technologies. There is a wide range of specialist skills to be integrated, and a ‘4.0 value proposition’ must be based on an ‘ecosystem’ of companies (see, for example, General Electric’s Digital Ecosystem). The network is often global, especially for partnerships of a digital nature where physical location loses its relevance as an element influencing relationships’ quality. The real-time exchange of data and information with suppliers improves coordination in the value network, reduces organizational costs and allows the best involvement of partners’ resources and skills.

Cost Structure Traditional business models often focus all attention on cost reduction. With smart, connected products and innovations based on 4.0 technologies, business models are strongly focused on value development and premium pricing strategies. In ICP and IOT systems, the cost of cloud connections does not have a high impact on business costs. Several costs can be reduced by less maintenance, improved quality and increased productivity. Cost structure modifications can come from a “use-oriented” servitization business model, where the product becomes an asset to be managed as it is no longer sold to customers but leased (see the Hilti case in the next paragraph). Innovations based on Industry 4.0 technologies applied to products and processes can significantly affect several building blocks of the company’s “way of being” in the competitive environment. The great challenge is to coherently integrate the transformations of the multiple components of the new business model to generate a profitable and sustainable business formula (see Case Study 10.1). The Canvas is a useful tool to analyse and define a business model consistent with the potential offered by 4.0 technologies. Innovating the business model provides the company considerable advantages over competitors that adopt the same technologies without changing the “way of doing business”. Moreover, it raises barriers to imitation; the “recipe” of a business model is not transparent to the outside world and is much more difficult to replicate than a single product or process innovation.

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Case Study 10.1 RECOLD is an innovative company in the field of air conditioning systems for civil and industrial buildings. It has developed considerable know-how in this field and has applied digital technologies to its chillers, transforming them into intelligent and connected objects (ICP). RECOLD can constantly monitor numerous performance parameters and optimize their operation and maintenance, through a suite of Cloud-based Analytics applications. The company’s value proposition has changed to include preventive and predictive maintenance services and offer customers a range of tips to optimize chillers’ energy efficiency. Changes to the business model were necessary, particularly in the sales area (which no longer simply sells a physical product) and in the organization of service and maintenance services; new commercial agreements were also defined with external service network partners. The company is planning to use its know-how to enter the field of ship air conditioning, modifying its products accordingly with a view to “repositioning” (see Chap. 2). A ship travelling the seas has, even more than a building, the need to prevent problems or failures in the air conditioning system. The new connected products recently developed by the company constitute an excellent base and opportunity to enter the new market segment; simultaneously, RECOLD’s management is aware of the need to critically review the business model, to understand its suitability for the new market. To this end, the Canvas was used to reconstruct the crucial elements of the current business model; the business model visualization was then adopted to analytically examine, for each of the model blocks, the changes that needed to be made to deliver value to new customers and differentiate in the competitive environment. The analysis was also guided by the questions proposed in Teece’s framework: how does the product solve customer problems? How big is the market? What are the differentiating elements of the value proposition? What is the state of the industry? Is there a dominant design? What are the opportunities for patent protection of the offer?

10.4

Business Model Innovation

Business model innovation has attracted increasing attention in recent years, both in practice and in management research, as a critical source of sustainable competitive advantage,13 as it is more difficult to imitate than product and process innovation. A new business model changes the value proposition, the customer relationship system and channels. At the same time, competencies, resources, activities and 13 On the concept of business model innovation, see Chesbrough (2010); Amit and Zott (2012); Bertels et al. (2015); Foss and Saebi (2017).

10.4

Business Model Innovation

187

Current business model

?

Fig. 10.2 Product innovation, business model innovation and success (adapted from Csik, 2014)

partnerships network must be innovated; such innovations in organizational routines could generate a competitive advantage as they are hardly visible and accessible from the outside.14 As we pointed out in the introductory paragraph, product success is not exclusively linked to the quality of the new value proposition (see Chap. 7), but it also relies on transforming other elements of the business model (Fig. 10.2). In digital innovations (D2C and ICP) where the customer is at the centre, the possibility of making product innovation profitable and different from competitors is strongly conditioned by innovation in the way value is delivered to customers, and in changing the system of activities and resources employed by the company. Innovations based on 4.0 technologies significantly accentuate the need for business model innovation. The link between product innovation, market success and the business model is certainly not a recent one. A well-known example is the Haloid-Xerox model 914, the first automatic plain-paper copier launched in 1959. The prevailing business models at the time were of the “razor & blade” type (a metaphor evoking Gillette’s business model of the early 1900s): sell the photocopiers with very modest margins but achieve high markups in the supply of consumables (among which was special paper); the average price of the photocopiers was around $300, and 90% were used for less than 100 photocopies per day. The 914 model was technologically revolutionary: it produced high-quality photocopies using plain paper, with an unprecedented speed (7 copies per minute); but there was a problem due to the very high production cost ($2000). Xerox’s initial attempts to bring the innovation to market with the traditional business model failed. The very high initial investment for the machine’s purchase was not perceived to be

14

See Amit and Zott (2012); Teece (2010); Girotra and Netessine (2014); Frankenberger et al. (2013). See also the BCG survey showing the financial benefit got from companies adopting an innovative business model (Lindgardt et al., 2009).

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of any value. The well-known consultancy firm Arthur D. Little, commissioned by IBM (one of Xerox’s potential customers) to analyse the proposal, concluded: “although admirably suited to particular applications, the Model 914 has no future in the copier market”.15 In September 1959, Haloid-Xerox decided to offer the 914 photocopier adopting an innovative business model: rental, direct distribution channels and total control of maintenance and consumables supply. The success was overwhelming, with revenues and margins beyond all expectations. Within 15 years, the small HaloidXerox ($30 million in sales) had grown into a $3 billion company, later known as “The Copier Company”. Another historical example is the case of Rolls-Royce’s Civil Aviation division (aircraft engines), where the effect of product innovation had paradoxical consequences at the beginning of the 1990s: the constant improvement in engine reliability had caused demand for spare parts to plummet.16 This was a serious problem from a profitability point of view; product innovation was progressively wiping out the biggest profitability source: the spare parts business. Maintaining the status quo, excellence in product innovation processes would paradoxically worsen its profitability year after year and make the investment in research and development unsustainable. In 1993, Rolls-Royce began to completely reorganize its global structure for engine maintenance, repair and overhaul (acquiring infrastructures all over the world) and to systematically offer airlines, as part of the engine sales contract, a form of maintenance contract called “power-by-the-hour”: a fixed cost for each hour of flight. In 2011, power-by-the-hour maintenance services, enhanced by big data analytics technologies (key to analysing carrier behaviour and engine problems), exceeded 50% of the division’s total turnover.17 As illustrated in the first paragraph, recent advances in the field of digital transformation will undoubtedly offer, in a wide range of sectors, enormous opportunities for innovation enabling the creation of new and original value propositions. Still, the ability to fully capture the value of these innovations will depend on changing business models. The following example of a manufacturer of sheet metal machineries highlights the business model changes resulting from the introduction of a smart and connected product.

15

Chesbrough and Rosenbloom (2002). See Smith (2013). 17 Maintenance services are now offered with a wide range of options (Total Care, Lessor Care, Corporate Care and Select Care). 16

10.5

10.5

Product and Business Model Innovation: The Case of a Connected Product

189

Product and Business Model Innovation: The Case of a Connected Product

The evolution of physical products into the virtual digital space, towards smart and connected products can lead to significant competitive advantages, but this requires substantial innovation in the business model’s components to fully capture all the benefits of bringing new products to the market. PRESBEND is a manufacturer of bending machines. Its customers are companies that make bent sheet metal components for use in many types of products, such as refrigerators, lifts, electrical cabinets or air conditioners. The machines are equipped with complex technology (mechanical, electrical, hydraulic, electronic and software), with many sensors and transducers on board. The price can reach several hundred thousand euros; the sector is highly concentrated, with only a few manufacturers. International markets are served by subsidiaries responsible for sales, installation, technical assistance and maintenance of the machines at the customer’s premises. It is not always possible for the subsidiary to resolve machine malfunctioning problems, so it is necessary to call on the expertise of the parent company, with which it communicates by telephone, Skype, e-mail or by sending photos of the parts of the machine that need intervention. The speed of solving a problem or failure is decisive to the customer. For example, a downtime in sheet metal machinery can bring entire assembly lines of a household appliance to a halt. It is often the case that an experienced technician has to fly to the customer to diagnose the fault and repair the machine. Therefore, it was essential to ensure highly effective preventive maintenance to minimize downtime. Monitoring the machine during machining requires sensors to control many parameters, such as temperatures, pressures, flow rates of oil circuits, electrical currents or vibrations. Some cameras can record information on the status of machining operations. The high speed of data transmission via the cloud has made it possible for all this information to be available immediately. PRESBEND set up a new organizational unit, called the Supervision Centre, to analyse this massive amount of data coming from each machine in real-time and pursue several objectives: prevent possible machine faults (predicting stoppages or breakdowns); give indications on the maintenance work to be carried out by the customer or the branch to optimize machine productivity; solve problems and repair remotely where possible; prevent stoppages and breakdowns. Remote control work is very complex, as big data has to be interpreted. For example, to understand whether the primary circuit’s temperature shows elements of concern, it is necessary to have established standard values. In this way, reading the temperature diagram makes it possible to move from data to the information needed to take an action. After a few months of work and some satisfactory simulations, the project team presented the smart and connected machines project to top management. There was a great deal of satisfaction, and everyone expected great results from this 4.0 innovation; however, some managers wondered what other parts of the company

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could or should be changed to capture all the possible benefits from these connected machines. The team engineers did not ask themselves this question, as they were concentrated on machine’s design. To facilitate the discussion, the marketing manager explained the Canvas as a working tool to make visible the fundamental elements of a company’s way of being and to discuss possible or necessary changes. The team members were initially puzzled; it was the first time they had approached the topic of product innovation in a broader perspective, with a strategic approach. But as they reasoned together, the potential and usefulness of the tool quickly emerged. During the discussion, ideas and observations were written down on the Business Model Canvas (an A0 sheet of paper hanging on the wall) (Fig. 10.3). As the discussion progressed, a new horizon opened up for the engineers who had developed the project: the focus of innovation was no longer on the machine but the customer value; and, as a result, the business model had to be transformed. The meeting ended with the CEO summarizing the nine components of the business model, highlighting the main drivers of change and the innovations that would need to be implemented in line with the new value proposition offered by connected machines. Customer Segments The company has two market segments: the so-called subcontractors (suppliers who carry out bending operations on behalf of other companies) and the large industrial groups in various sectors (domestic appliances, lifts, etc.). This second group is very sensitive to productivity and systematically monitors its machinery’s performance with indicators such as OEE (overall equipment effectiveness). Machine stoppages or malfunctions have severe repercussions on the operation of downstream plants. These companies have a strong technical culture, including digital technologies, and are therefore open to this kind of innovation. ICPs will expand this market segment by acquiring customers who have plants in various countries around the world. The marketing manager was responsible for drafting a development programme for this type of customer. Value Propositions Merely stating that the connected machine offers a “better service” (by improving, for example, preventive maintenance) does not explain to the customer the real value provided, which is economic: the increase in productivity and OEE, which can be achieved by reducing troubleshooting times, fewer stoppages, minimizing disturbances and losses in efficiency due to preventive maintenance. A small cross-functional team, called the Value Team, was asked to define the new value’s meaning and how it should be communicated and presented to customers. Channels The main change concerns the ways and means by which value is communicated to the customer. Salesforce should not focus on the technical explanation of the new machine, but on the benefits that the customer can achieve, also using videos or simulations. For example, it is possible to demonstrate how the

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detection of oil overheating can be followed up with an adjustment or repair, preventing a breakdown. The absence of a certain number of stoppages per year will generate a productivity gain and therefore, an economic advantage, clearly defined and illustrated through a quantitative example so that customers can appreciate the value offered. Branches will also have to change their role, moving away from being “local mechanic” to become consultants and partners in developing customer’s diagnostic skills. Customer Relations Customer relations are changing radically, and assistance must be continuous and personalized. Customer loyalty can increase not only through the productivity benefits offered but also through the quality of interactions; PRESBEND aims to increase customer knowledge of machine functioning and their problem-solving skills. At the same time, the switching costs for the customer of a possible change of machine supplier are increased. The Value Team was given the task of drawing up a programme regarding channels and customer relations. Revenue Streams PRESBEND expects an increase in revenues from the expansion of the segment of large industrial groups that understand the benefits of adopting these machines. These customers have production facilities in several countries, and interconnection capabilities are considered very important. The basic product is sold already connected, and extensions of the range of services can be offered for a fee. Key Resources To be effective and fast, the Supervision Centre will have to be organized with people with data analysis skills. Subsidiaries will have to change how they interact with the parent company and customers, acting as active intermediaries for troubleshooting. On the systems and software side, the company must acquire big data analytics technologies. Key Activities Marketing and sales processes involving the branches will have to be updated according to connected machines’ new value potential. The research and development unit will have to interact with the Supervision Centre to understand what changes and improvements need to be made and what ideas may emerge to design new products. A small inter-functional team (sales and R&D) was set up to identify the primary business process re-engineering needs. Key Partners Providers of ICT systems, cloud and data analytics are strategic to ensure effective communication with customers and quick problem-solving. The IT manager was asked to set up a programme. Cost Structure The new business model is based on revenue and margin growth rather than cost-saving. The connection systems will not entail any particular extracosts; warranty costs, which today are relatively high, can be reduced by the online support.

References

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The CEO recommended that the implications of the planned changes in the business model should be investigated and concrete proposals and work programmes presented at the next meeting. The change would have to involve the company’s entire organizational structure; speed and coordination between business areas were considered a strategic factor to make the most of the opportunities offered by the new machines. This case is presented as an example to show the extent of business models’ changes resulting from products using new digital technologies in an IoT perspective, and the Canvas’s usefulness to accompany change. The example refers to a real situation; however, it has been modified and simplified for privacy reasons. The digital transformation of products and processes will strongly characterize innovation processes in the most diverse sectors. Companies will have to focus on finding the connection between digital innovation and business model transformations to face the increasingly hard global competition challenges.

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