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OPEN INNOVATION
New Product Development Essentials from the PDMA
Edited byCharles H. Noble
Serdar S. DurmusogluAbbie Griffin
Cover Design: C. WallaceCover Illustration: Vector Swirl © iStock.com/antishock
This book is printed on acid-free paper.
Copyright © 2014 Product Development and Management Association. All rights reserved
Published by John Wiley & Sons, Inc., Hoboken, New JerseyPublished simultaneously in Canada
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Library of Congress Cataloging-in-Publication Data:
ISBN 978-1-118-77077-1 (cloth); ISBN 978-1-118-77078-8 (ebk); ISBN 978-1-118-77085-6 (ebk); ISBN 978-1-118-94716-6 (ebk)
Printed in the United States of America10 9 8 7 6 5 4 3 2 1
To three amazing ladies who’ve made me who I am: Stephanie, Dolores, and Jenny—CN
To Tansu, my little angel—SD
To Ken for supporting me in all my research and publication endeavors for over a decade—AG
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Contents
Introduction: The Journey into Open Innovation xiiiCharles H. NobleSerdar S. Durmusoglu
Part 1: Open InnOvatIOn In the Fuzzy FrOnt end 1
1 De‐bottleneCking oPen innovation: turning Patent‐baseD teChnology network analysis into value 3Manfred StadlbauerGerhard Drexler
1.1 Methods of Patent Analysis and Data Mining 3
1.2 Patent Analytics for Identifying Open Innovation Partners 12
1.3 Nanotechnology Case Study 18
1.4 Conclusion 24
2 oPen Foresight workshoPs For oPPortunity iDentiFiCation 27Christiane RauFiona SchweitzerOliver Gassmann
2.1 Corporate Foresight Workshops and Processes 28
2.2 Opening Up the Foresight Process 30
2.3 Stages of Opening Up the Foresight Process 32
2.4 Pitfalls to Avoid 45
2.5 Keys to Success 46
2.6 Conclusion 50
vi COnTenTS
Part 2: Open InnOvatIOn In the develOpment Stage 53
3 keePing uP with the virtual voiCe oF the Customer—soCial meDia aPPliCations in ProDuCt innovation 57Anna DubielTim Oliver BrexendorfSebastian Glöckner
3.1 Introduction 57
3.2 The Voice of the Virtual Customer 59
3.3 The Social Media Phenomenon 59
3.4 Social Media in New Product Development 62
3.5 Success Factors 76
3.6 Conclusion 78
4 PreDiCtion, PreFerenCe, anD iDea markets: how CorPorations Can use the wisDom oF their emPloyees 81Peter Koen
4.1 Introduction 81
4.2 Virtual Stock Markets in Corporations: Prediction, Preference, and Idea Markets 83
4.3 How Well Do Prediction, Preference, and Idea Markets Work in Corporations? 89
4.4 Implementing a Stock Market in Corporations 95
4.5 Choosing a Virtual Stock Market Software Platform 100
COnTenTS vii
4.6 Conclusions 103
About the Contributor 105
5 Catalyzing taCit knowleDge exChange with visual thinking teChniques to aChieve ProDuCtive oPen innovation Collaborations 107Karen A. KreutzKim D. Benz
5.1 Introduction 107
5.2 Visual Thinking Introduction 109
5.3 Visual Thinking and Open Innovation Endeavors 114
5.4 Understanding the Tacit Knowledge Exchange Challenges 117
5.5 Using Visual Thinking in OI Teams 122
5.6 Conclusions 129
6 user Collaboration through Private online Communities 135 Thomas TrochTom De Ruyck
6.1 Introduction 135
6.2 From Crowd‐Everything to Co‐Everything 136
6.3 Crowdsourcing, Co‐creation, and Structural Collaboration 137
6.4 Private Online Communities 138
6.5 How to Get Started with Private Online Communities 153
6.6 Conclusion 169
viii COnTenTS
Part 3: Open InnOvatIOn wIth unIverSItIeS 173
7 Collaborative innovation aCross inDustry‐aCaDemy anD FunCtional bounDaries: how ComPanies innovate with interDisCiPlinary FaCulty anD stuDent teams 175Jelena SpanjolMichael J. ScottStephen MelamedAlbert L. PageDonald BerghPeter Pfanner
7.1 Introduction 176
7.2 The IPD Model: Resolving Major Open Innovation Challenges 177
7.3 Concept Prototypes: Virtual and Physical 194
7.4 Conclusion 199
Appendix A 200
Appendix B 201
Appendix C 212
Appendix D 214
Appendix E 218
About the Contributors 222
8 oPen innovation: a Framework For Collaborative ProDuCt DeveloPment between inDustry anD universities 225Aruna Shekar
8.1 Introduction 225
8.2 Open Innovation Program 226
COnTenTS ix
8.3 A Framework for Open Innovation between University and Industry 227
8.4 An Example of an Open Innovation Project 234
8.5 What Industry Partners Can Expect from Open Innovation Projects 237
8.6 Challenges in University‐Industry Collaborations 239
8.7 Company Feedback from Industry Partners 240
8.8 Keys to Success 240
8.9 Pitfalls to Avoid 242
8.10 Benefits of the Open Innovation Program 243
8.11 Conclusions 243
About the Contributor 244
Appendix A 246
Appendix B 248
Appendix C 253
Appendix D 254
Part 4: Open InnOvatIOn FOr really BIg InItIatIveS 257
9 oPen innovation as a DisCovery solution For ConFronting the extraorDinary Challenge 259Christopher W. Miller
9.1 Surfing on Innovation Impact Waves: The Source of the Really Big Problem 260
9.2 Process, Purpose, and Payoff 260
9.3 Conclusion 276
x COnTenTS
Part 5: BeSt practIceS and advIce FOr Open InnOvatIOn 279
10 how to work with small ComPanies to exPanD your oPen innovation CaPabilities 281Donna RainoneMike RainoneLouise Musial
10.1 Introduction 281
10.2 Definitions 282
10.3 Background of Open Innovation 283
10.4 Two Paths: The Intraprenurial Organization versus the Outsourced Organization 284
10.5 How to Build Entrepreneurship within a Large Corporation 288
10.6 Why Working With Small Companies Is Important 293
10.7 Conclusion 295
11 boosting oPen innovation by leveraging big Data 299Gerhard DrexlerAndrej DuhAndreas KornherrDean Korošak
11.1 Open Innovation and Big Data 299
11.2 Big Data Applications in Today’s World 306
11.3 Big Data Analytics in Action 308
11.4 Keys to Success and Pitfalls to Avoid 313
11.5 Conclusions 315
COnTenTS xi
12 ameriCan ProDuCtivity anD quality Center best PraCtiCes stuDy: using oPen innovation to generate iDeas 319Christopher W. MillerG. Anne OrbanBecky PartidaAndrea StroudPaige Leavitt
12.1 Open Innovation Best Practices Study 320
12.2 Open Innovation Best Practices 321
12.3 Eleven Best Open Innovation Practices 322
12.4 Open Innovation Enablers 333
12.5 Conclusion 337
inDex 339
xiii
IntroductIon
the Journey Into open InnovatIon
The idea of cultivating firm innovation has long been associated with secrecy, fear of competition, and a general distrust of any entity outside the corporate walls. In this view (shown in Figure 1), product concepts are developed across various
organizational functions, but it is a “hard‐walled” process in which input from outside the firm is not sought or valued, and concepts are jealously guarded from leaks to the outside world.
Figure 1: A Typical Closed Approach to Innovation
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The term “Open Innovation” is generally credited to Henry Chesbrough from his 2005 book and prior writings1, though its origins and concepts certainly appear in earlier thinking. Chesbrough’s definition highlights the breaking down of traditional walls and veils of secrecy surrounding the organizational innovation process. As he describes it formally, “[Open Innovation is] . . . the use of purposive inflows and outflows of knowledge to accelerate internal innovation and expand the markets for the external use of innovation, respectively.” In somewhat simpler terms, this is “punching holes in the funnel” that historically depicts the innovation process, allowing good ideas, technologies, materials, and other knowledge to flow in, and viable ideas, concepts, and technologies that aren’t going to be commercialized by the firm to be passed out through
xiv InTrOduCTIOn: THe JOurney InTO OPen InnOvATIOn
licenses, joint ventures, and other approaches. Figure 2 illustrates this general concept. More than ever, the benefits of Open Innovation (OI) are being explored and under its umbrella can be found increasingly popular techniques such as consumer co‐creation, crowdsourcing, idea competitions, collaborative design, and other approaches.
despite the recent focus on this approach, elements of OI have in fact been in existence for centuries. Consider the following:
■ In 1714, the British government, through an Act of Parliament, offered the Longitude Prize to anyone who could develop a practical method for the precise determination of a ship’s longitude. The winner was John Harrison, who received £14,315 for his work on chronometers.
■ In 1795, napoleon offered a 12,000‐franc prize to drive innovation in food preservation, spurring a French brewer and confectioner named nicholas Appert to develop an effective canning process to avoid spoilage.
■ In 1919, new york City hotel owner raymond Orteig offered a $25,000 reward to the first allied aviator(s) to fly nonstop from new york City to Paris or vice versa. It was a relatively unknown individual, Charles Lindbergh, who won the prize in 1927 in his aircraft, Spirit of St. Louis, and made history.
■ In recent years, the X PrIZe Foundation sponsored a space competition and offered a $10,000,000 prize for the first nongovernment organization to launch a reusable manned spacecraft into space twice within two weeks.
■ eli Lilly pioneered the modern idea of crowdsourcing in 2001 when they began to post research questions openly (online) to scientists and other outsiders to augment their own r&d efforts. From this effort, they developed and spun off a new company, InnoCentive, to offer crowdsourcing to other companies.
■ The use of “beta invitations” has been practiced for decades in the video game industry. In this model, which could be considered a form of OI crowdsourcing, a software developer releases a “beta” (or early, likely flawed) version to users for
Figure 2: A General View of Open Innovation
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testing and commentary. This results in many expert hours of development being applied in a short time, thereby improving the product quickly and cost‐effectively.
While these principles have been sporadically tried in the past, the recent move to focus thinking around the term “Open Innovation” has increased attention and has helped explore the full breadth of the concept with its many dimensions and implications.
despite the hoopla and the calls for many goods and service firms to pursue this approach, there are certainly hurdles and cautions to consider. The loss of control is a fundamental worry, manifesting itself in many ways—in that competitors can have more insight into your early stage product pipeline and in that the same core ideas may be shared with others. There is also a valid concern that allowing users to enter into your innovation process creates an expectation with them that their ideas will be valued and implemented, which may not always be the case, resulting in disappointment. Last is the potentially more daunting worry that “great” ideas can’t come from a crowd, which inherently produce compromise and mediocrity.
Idea sifting also can be an overwhelming challenge for firms pursuing this approach with gusto. For example, the community‐driven innovation site “Quirky” has, as of this writing, almost 700,000 individuals who have contributed somehow to various product innovation processes—through raw ideas, branding suggestions, design insights, and so on. All of that enormous energy has culminated in only just over 400 products reaching the marketplace to this point. The vast majority of ideas and refinements are rejected, either by the community or, in a more organizationally taxing way, by the firm’s own marketing, design, and manufacturing experts. This illustrates the skill shift seemingly required in firms pursuing Open Innovation—from technical expertise in personal product development to screening and sifting through potentially thousands of inputs for a few with “radical” potential. Therefore, it seems fairly clear that cost savings should not be the main driver for the firm embarking down the path to Open Innovation.
despite these cautions, the general focus on Open Innovation is growing at breakneck speed. A recent report showed that 61 percent of firms were growing or expanding their OI efforts with the focus on partner networks, ideation programs, problem/solver networks, and co‐creation programs.2 Interestingly, this study also showed that the drive for OI is largely coming from the CeO level with mid‐level and functional management much less likely to be in a championing position. Perhaps you are one of those middle‐ or even higher‐level managers who have been tasked by a well‐intentioned CeO to explore this “Open Innovation thing” and this is one of your first steps down that path. If so, you have come to the right place!
This book is not a theoretical treatise on the conceptual underpinnings of Open Innovation, nor is it proposing an untested agenda for further development. In the chapters within, you will find clear and usable tools and ideas to help you implement the principles of Open Innovation in your firm. The authors have taken their lumps and achieved their victories, and share both here. We are fortunate to have insights here from an exceptionally talented group of innovators and appreciate their willingness to share this knowledge. This is a collection of stories of the OI journey, not all of which may apply to your particular situation, but which will inspire you shake up your own approaches to maximizing your innovation potential.
InTrOduCTIOn: THe JOurney InTO OPen InnOvATIOn xv
xvi InTrOduCTIOn: THe JOurney InTO OPen InnOvATIOn
In this book, we consider applications of OI principles in all phases of the new product development process—from idea generation to evaluation, development, and delivery (i.e., launch). The views and techniques offered come from authors with diverse and exciting experiences. This exploration is useful in understanding the full breadth and potential of an incredibly rich concept in Open Innovation. We summarize these insights in several ways, including a model of Open Innovation which highlights the contributing perspectives of this book. We think you will enjoy the offerings here, as a source of thought‐provoking ideas for your own OI applications.
Why Open Innovation?As described in various previous writings in the area, there are many reasons to consider the route of Open Innovation. Briefly, these include the value of bringing in new, outside perspectives on innovation challenges, the ability to profit from ideas that weren’t necessarily initiated within the company, increasing speed through development to market, and the ability of smaller firms to effectively scale up innovation resources to match those of larger competitors.3 Many companies seek OI for both “inbound” and “outbound” innovation benefits. From an inbound perspective, OI can complement traditional, internal r&d. On the outbound side, OI principles are used to find creative markets and earning opportunities from developed ideas that aren’t put through a traditional development pipeline.
There are numerous examples of Open Innovation successes in the popular press, including efforts such as Heineken’s “Ideas Brewery,” an OI portal which asks for creative solutions to specific problems. In one effort to better understand the beer needs of 60+‐year‐old consumers, winning entries including fruitier and sweeter brews to suit more senior tastes, added iron (an important mineral for the elderly), and easier‐opening packaging concepts.4
In a more unusual setting, the u.S. department of defense launched a major OI program in 2010 to design the next‐generation infantry fighting vehicle through a series of design challenges. Their goals were to achieve a broader range of ideas and to be able to develop a final product at a lower cost. In developing the Fast Adaptable next‐Generation Ground vehicle (“FAnG”) program, three independent challenges were created. The program was launched in 2013 and received widespread participation from those trying to design key components of the vehicle, likely motivated by the $4 million in prize money at stake. To date, the first round of the competition has received over 200 submissions and the military is extremely impressed with their quality and is looking to continue the approach.5
despite these successes, Open Innovation has also been shown to be, at times, hazardous or at least not particularly worthwhile. For example, Mountain dew recently launched an Apple‐flavored product variation and decided to build consumer support by running a crowdsourcing competition (titled “dub the dew”) to let people name the new beverage. not surprisingly, particularly given their youthful and somewhat
PerSPeCTIveS On OPen InnOvATIOn xvii
irreverent target market, the crowd decided to show their wit with “Top 10” name submissions including “Hitler did nothing wrong,” “Gushing Granny,” and “diabeetus.” Clearly, the potential for loss of corporate control was striking here. In the end, the company cancelled the contest and used the quite unimaginative “Apple Mountain dew” as the final product name.6
In another recent effort, Mcdonald’s decided to use the Twitter hashtag #McdStories to encourage customers to share their Mcd’s experiences. unfortunately, the results were not the collection of shining brand championing they were hoping for, but included public comments such as, “One time I walked into Mcdonalds and I could smell Type 2 diabetes floating in the air and I threw up,” and “I lost 50lbs in 6 months after I quit working and eating at Mcdonald’s.”7
Clearly, Open Innovation is not a panacea and can present challenges that must be carefully managed. That challenge became the genesis for this book—to offer battle‐tested insights on the most effective ways to apply OI ideas across a variety of situations and industries—and to discuss both the key success factors and pitfalls encountered. This is the general format our authors follow in the chapters ahead, helping you to capture the benefits of Open Innovation for your situation.
Perspectives on Open InnovationGassmann, enkel, and Chesbrough (2010) have offered an interesting view on the various perspectives which can be taken to consider OI, many of which are represented in this book.8 These include a structural perspective, considering outsourcing and innovation development alliances, a user perspective which examines how users are integrated into the innovation process, supplier perspectives which consider the role of those partners in OI, process perspectives which consider both inside‐out and outside‐in processes, institutional perspectives which study innovation norms within an industry, and a cultural perspective examining how firms learn to embrace outside influences on a critical process, among other perspectives. These views are most interesting in how they examine the complexity of Open Innovation, both as a process and as an example of organizational change for many firms. This suggests that implementing Open Innovation is not simply a change in process, but can represent a deeper, cultural change, a more committed level of partnering with suppliers, the seeking out of new types of allies, and a general openness in thinking that may create discomfort for many. While the diversity of industries and OI situations makes a comprehensive step‐by‐step guide for all cases impossible, this book offers a range of ideas that will greatly facilitate instituting a new regime of Open Innovation in your firm.
next, we offer a brief summary of the various chapters in this book. As we lay out, these stories align nicely with the major steps in any innovation and product development process. This mapping of chapters on steps in the Open Innovation process is shown in Figure 3.
xviii InTrOduCTIOn: THe JOurney InTO OPen InnOvATIOn
Essential Tools for Open InnovationThis book presents 12 chapters to help your firm implement Open Innovation, organized into 5 parts based on where in the product development process the chapter will provide the most utility. Part 1 starts at the left side of Figure 3, offering insights into essential tools for OI in the discovery phase, frequently referred to as the fuzzy front end of product innovation. The flow of subsequent parts moves generally from left to right in Figure 3, with the concluding part providing information on Open Innovation best practices and overall advice.
In Part 1, the book opens with the introduction of tools that you can use for technology mapping and subsequently identifying potential partners for co‐development projects. In particular, the authors, Stadlbauer and drexler, show how emerging technologies can be identified with the use of patent analytics, locate the inventors or firms advancing those technologies, and then, from those that are in close geographic proximity, select the OI partner that best complements your technology capabilities. In their chapter, the authors first make a case for why patents portray the most immediate picture of the technology landscape compared to other sources such as the academic literature. They then summarize traditional patent analytics methods, followed by demonstrations of their method, which is the use of social network analysis in this endeavor. The chapter ends with an illustration of this method as applied to the nanotechnology industry. We think that applying this method in your own firm will be straightforward after reading this chapter.
In Chapter 2, Open Foresight Workshops for Opportunity Identification, rau and colleagues distinguish between “foresighting” versus “forecasting”: foresight aims to identify several potential futures, while forecasting is done in order to provide estimates of the one most probable future. They then describe four different stages of “open” foresight workshop designs for collaborative opportunity identification. The authors provide the specific benefits gained at each stage when your firm purposefully opens its foresight processes. These benefits include the diversity of insights and perspectives gained, attractiveness of partners, identification of blind spots, trust and relationships
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Figure 3: The Structure of this Book
eSSenTIAL TOOLS FOr OPen InnOvATIOn xix
built, and sensitization to trends. rau and colleagues then illustrate how certain companies opened their foresight processes and highlight what steps you can take to open your firm’s foresight processes by pointing out specific activities.
Part 2 contains four chapters about various ways to use OI in the development stages—the stages after the fuzzy front end is completed. Our authors show how social media, crowdsourcing, and other types of collaborative processes can improve product innovation efforts.
In Chapter 3, dubiel and colleagues introduce several important social media applications and cluster them into three levels with respect to their potential uses in your firm’s product development process: listening to, dialoging with, and fully integrating customers. These levels range from passive involvement to very active, such as designing proprietary social media content. This chapter’s deep content focus is on introducing the netnography process, which is an effective method of using ethnography on the Internet. you will read about several successful implementations of idea/design/solution contests administered by major corporations such as Mcdonald’s and Smart as well as acquire a step‐by‐step process for executing such a contest for augmenting your own product innovation efforts.
This section continues with a chapter about prediction, preference, and idea crowdsourcing markets, where the author, Koen, first describes the main factors influencing the accuracy of each of these markets. Subsequently, suggesting you keep in mind these factors, he presents different implementation processes for each market type. The chapter concludes with a list of virtual stock market software providers and suggestions on how to choose the right software to effectively open your product innovation process to the crowd.
next, Kreutz and Benz focus on why and how to employ visual thinking techniques when your employees are partnering with experts outside of your firm or with other firms. Simply put, integrating the tacit knowledge outsiders carry can be daunting because of unfamiliarity with each other’s thought worlds and lack of trust. To achieve smooth tacit knowledge transfer, the authors first provide an overview of visual thinking, including the two main types: graphic group processes and knowledge modeling. The authors then explain when to use the two different types of visual thinking techniques and how tacit knowledge is obtained, organized, and presented with these processes.
Part 2 closes with Chapter 6, by Troch and de ruyck, which provides insights into incorporating customers into your new product development process by using private online communities. In addition to explaining why firms should open up their product innovation processes to potential and current customers via private online communities, they provide a process for doing so. The authors then describe when to use different methods and compare them. Finally, they provide examples and lay out a blueprint for setting up a private user community for your firm.
Part 3 introduces how to implement OI endeavors with universities as partners. First, Spanjol and colleagues share more than a decade of experience at the university of Illinois at Chicago with their interdisciplinary new product development course, in which, so far, over a thousand new product concepts have been generated for partnering firms. The authors present the process followed in a very detailed manner, along with the activities, methods, and deliverables for each step. Chapter 7 will be most helpful for large firms.
The second chapter in Part 3, Chapter 8, provides an overview of similar practices at Massey university, but focuses on smaller firm–university collaborations. In this chapter, Shekar also presents a blueprint for a joint university–company journey and specifies
xx InTrOduCTIOn: THe JOurney InTO OPen InnOvATIOn
the roles for each stakeholder (i.e., students, supervisors/professors at the university, the industry partner, and the advisory board) in such partnerships. In addition to presenting a project that went through this process, the chapter is full of other useful material such as a sample project agreement and a nondisclosure agreement.
Our book continues with a chapter on depicting OI for really big initiatives. The author, Miller, first talks about innovation impact waves. These are the unintended consequences of innovations, which have created more problems to be solved, even in the face of solving other important problems. The author first identifies the stages and processes for solving “really big” problems and then presents six separate cases where these processes have been applied successfully. This chapter is full of examples of how a wide variety of stakeholders can be brought together and become focused on working swiftly and harmoniously to generate product solutions. even if your firm is not facing a “really big” problem, the cases may provide hints for enhancing your OI initiatives in general.
The final part of this book concludes with three chapters that portray best practices and overall advice for OI. The first of these, rainone and colleagues, is a thought piece on the reasons for working with small firms to enhance your innovation muscle. In this chapter, the executives of a small firm present the lessons they have learned during successful OI collaborations. Based on decades of product development support their firm has provided to numerous large enterprises, the authors describe what characteristics you should look for in an OI partner and then best practices when working with small firms, including a timeline for going from initial engagement with an OI partner until the completion of the first set of tasks.
next, drexler and colleagues prescribe what senior managers and executives should demand to see periodically so that they stay on top of their game in managing their firm’s OI practices. This is especially important considering the emergence of Big data in the last few years. The authors argue that firms react in two ways to garner the right information from Big data. The first is to have a data scientist who constantly looks over the huge amount of data firms now gather on a continuous basis. The second is to have a structured way of having these data presented to managers to get a quick snapshot of the current situation. They call this your “daily cup of information,” a sheet that you can carefully look into every morning while sipping your coffee before you start your workday. The authors argue that this cup of collective intelligence, gleaned through the analysis of Big data, should have an update on specific components related to your business, namely, technology, trends, customers, markets, gap analysis, and competitors.
Finally, Miller and colleagues present the results of the American Productivity and Quality Center’s 2013 best practices study for utilizing OI to generate ideas. They define 11 specific best practices associated with the Open Innovation strategies, roles, processes, measurement, and improvement. For each best practice, they provide concrete examples from best‐practice firms. The chapter closes with five key enablers that firms trying to improve Open Innovation performance also need to implement.
We hope you will have an enjoyable read and also that this work inspires you to open your own processes to achieve enhanced product innovation results.
Charles H. nobleSerdar S. durmusoglu
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about the edItorsCharles H. Noble (Phd, Arizona State university; MBA, Babson College; BS, Boston College) is currently Proffitt’s Professor of Marketing and director of the Marketing Phd Program at The university of Tennessee in Knoxville. He also serves as the vice Chair for the Product development and Management Association (PdMA), and as a member of the Faculty research network of the Center for Services Leadership at Arizona State university. His research interests focus generally on design and development processes, as applied to both products and services. He has published in many leading journals including the Journal of Marketing, Strategic Management Journal, Journal of the Academy of Marketing Science, Journal of Product Innovation Management, Sloan Management Review, IEEE Transactions on Engineering Management, and many others. Charles has consulted for many organizations, primarily in the airline, retailing, consumer packaged goods, and commercial real estate sectors.
Serdar S. Durmuşoğlu is an Associate Professor of Marketing at the School of Business Administration, university of dayton. He earned his Phd in Marketing from Michigan State university. He also holds an MBA from Purdue university in West Lafayette, Indiana, and a Bachelor’s degree in Mathematics from Boğaziçi university in Istanbul, Turkey. dr. durmuşoğlu’s main research interests are product innovation strategies and decision making, the effect of information technology on new product development, and Open Innovation. His work has been published in the Journal of Product and Inno-vation Management and Industrial Marketing Management, among others.
Abbie Griffin holds the royal L. Garff endowed Chair in Marketing at the david eccles School of Business at the univer sity of utah, where she teaches MBAs marketing. Professor Griffin obtained her BS Che from Purdue university, MBA from Harvard Business School, and Phd in Management of Technology from MIT. Her re search investigates means for measur ing and improv ing the process of new product development. Her latest research can be found in the book titled Serial Innovators: How Individuals in Large Organizations Create Breakthrough New Products. A video trailer about the book can be found at www.abbiegriffin.org. She was the editor of the Journal of Product Innovation Management, the leading academic journal in the areas of product and technology development from 1998 to 2003. The Product development and Management Association named her as a Crawford Fellow in 2009, and she currently serves as the vice President of Publications for the Association. Professor Griffin is an avid quilter, hiker, and swimmer.
Endnotes 1. Chesbrough, Henry (2005), Open Innovation: The New Imperative for Creating and
Profiting from Technology, Boston: Harvard Business review Press.
2. Forrester (2012), “Open Innovation expands new Product Opportunities,” white paper (www.forrester.com).
3. See, Chesbrough, Henry (2007), “Why Companies Should Have Open Business Models,” MIT–Sloan Management Review, 48 (2); and Lindegaard, Stefan (2010), The Open Innovation Revolution: Essentials, Roadblocks, and Leadership Skills, Hoboken, nJ: Wiley.
4. www.ideaconnection.com/open‐innovation‐success/Heineken‐s‐Global‐Search‐for‐Beer‐Concepts‐for‐Senior‐00457.html.
5. www.ideaconnection.com/open‐innovation‐success/Crowdsourcing‐to‐Create‐a‐disruptive‐Approach‐to‐Buil‐00429.html.
6. http://searchenginewatch.com/article/2277410/Crowdsourcing‐Gone‐ Wrong‐How‐Brands‐Can‐Avoid‐Messy‐Marketing‐Mistakes.
7. http://searchenginewatch.com/article/2277410/Crowdsourcing‐Gone‐ Wrong‐How‐Brands‐Can‐Avoid‐Messy‐Marketing‐Mistakes.
8. Gassmann, Oliver, ellen enkel, and Henry Chesbrough (2010), “The Future of Open Innovation,” R&D Management, 40 (3), 213–221.
xxii ABOuT edITOrS
Part 1Open InnOvatIOn In
the Fuzzy FrOnt end
2 OPen InnOvatIOn In the Fuzzy FrOnt end
The fuzzy front end of innovation is that messy, chaotic part of the innovation pro-cess before a product concept has been ideated or developed. this part of the process seeks new opportunities for the firm—whether they derive from a tech-
nology capability, a specific market insight, or changing trends in customer needs or competitors. the goal for this stage is to find an interesting problem to solve, invent the solution, or find someone else who already has invented that solution, and eliminate the technical, market, and competitive unknowns sufficiently to move the project forward into the firm’s formal development process. Part 1 contains two chapters, which pro-vide information that will allow you to spot opportunities that arise from technology, market, and general trends.
■ Manfred Stadlbauer and Gerhard drexler focus on finding and using sources of tech-nology capabilities that are external to the firm in Chapter 1. this chapter shows how to use the patent literature and social network analysis to find areas of technology in the early stages of development, uncover interconnections between those new technologies and other technologies, locate firms and individuals active in those technologies, and map their geographic location to help determine who might make appropriate technology development partners.
■ Christiane rau, Fiona Schweitzer and Oliver Gassmann present methods for using open foresight workshops to identify new opportunities for the firm. rather than being merely technology‐driven opportunities, these methods allow the firm to investigate at the overall market and general trends level. Chapter 2 shows firms how they can implement these types of workshops in “closed” or internally executed forms, but then also shows firms how to move step‐by‐step to using them in more and more open ways.
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1De‐bottlenecking open innovation:
turning patent‐baseD technology network
analysis into value
Manfred StadlbauerTechmeter
Gerhard DrexlerMondi Uncoated Fine Paper
1.1 Methods of Patent Analysis and Data MiningOpen Innovation is a paradigm that combines internal and external ideas into processes whose requirements are defined by specific business models. Firms spend significant effort sourcing and integrating external knowledge and ideas from customers, suppliers, universities, and research organizations, and also competitors. Thus, competitive intelli-gence and technology forecasts are high on the agenda of leading‐edge enterprises. Fur-thermore, in the fast‐paced and complex world we face, the need to solve problems and develop new products as quickly and efficiently as possible is of paramount importance.
One of the challenges of starting new innovation initiatives is the need to see beyond the current time horizon in order to identify the most promising future technologies and products. In addition, acquiring the tangible and intangible assets required for meeting these challenges often exceeds a company’s resources, and successful product development is usually realized through the joint contribution of several disciplines, including engineering, marketing, design, and manufacturing.
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The practice‐oriented approach we present in this chapter is about the applica-tion of novel tools and techniques for the support of some of the most crucial steps in Open Innovation, namely the identification of both new opportunities and prospec-tive internal and external partners. Starting from the exploration of ideas and enriching them with quantitative data derived from internal and external networks and compe-tence maps, this chapter describes how promising new technologies and best‐in‐class candidates for co‐development can be identified.
The first part reviews extant methods of patent analysis and data mining. classical methods of patent monitoring are time consuming and only reveal what someone is definitively looking for. More sophisticated approaches involve a number of analytical methods that have been made possible by recent progress in information technology.
Subsequently, the second part of the chapter provides an insight into novel methods for patent analytics with a special focus on Open Innovation. It covers topics such as patent dynamics, emerging technology analysis, geographic proximity, and collabora-tion networks. each example is described briefly and supported by flow charts and spe-cial graphics. This second section shows how state‐of‐the‐art patent analysis holds the potential to assist throughout the whole innovation chain.
Finally, the third part of the chapter is a case study from the nanotechnology industry. Depicting a number of real‐case results demonstrates how the emerging land-scape of nanotechnology can be evaluated by means of advanced patent analysis, how the most dynamic technologies are identified, and how collaboration networks are visu-alized and utilized for identifying prospective external collaboration partners.
Patents as a Lead Indicator of InnovationIn the search for cutting‐edge global innovation trends, one may consider a variety of different information sources, each of them having advantages and disadvantages. among the most important sources are scientific publications such as the academic literature and conference papers as well as interview panels, direct conversations and workshops with internal experts, consumers, or experts from customers and suppliers. another important source for trend scouting is the patent literature.
compared to alternatives for deriving information about technology trends, the patent literature offers a range of specific benefits that makes it a preferred source. For example, the patent literature is indisputably very current and accurate. earlier than other publications such as scientific publications from the academic literature, or marketing communications such as Internet appearance or sales brochures, patent applications pro-vide signals of emerging technology trends. This is because of a patent’s requirement of novelty at the point of filing. any other earlier publication would prohibit the granting of a patent. For that reason, patent applications are always filed substantially earlier than scientific publications and even well before any marketing communication is put in place. consequently, patent applications are a very early indicator of technology changes. Figure 1.1 illustrates patents as the lead trend indicator compared to scientific publications.
In addition to the lead time gained, patents are very structured, making them more accurate than other alternatives. With the patent publication, there is a technology classification from the patent classification scheme [such as the International Patent
MeThODS OF PaTenT analySIS anD DaTa MInIng 5
classification, (IPc)], date, information about authors (inventors), and assignees (Faust and Schedl, 1984). The formal features of the patent literature are summarized in Table 1.1.
In conclusion, while a trend analysis based on the academic literature or Internet sources shows delayed results and challenges in the structured analysis, patents offer a significant lead time, as well as structured metadata on technology area, inventors, assignees, and citations. Furthermore, the patent literature utilizes a standardized “review scheme” and, due to the costs of patent maintenance, there is a significant quality barrier to filing.
In contrast to the abovementioned advantages of patent analysis over other sources for forecasting technology trends, in the recent past, patent analysis presented several draw-backs. The most prominent drawback is the vast amount of time required for interpretation. Studying the patents, assembling all the technical details into a holistic picture, and learning the relevant information about technology trends from it, used to be very time consuming.
addressing the earlier drawbacks of patent analysis, a number of patent analysis tools have evolved, from standard document‐search systems to tools attempting to derive metadata such as technology trends from the large amount of data inherent to patents. For example, patent classification schemes such as the International Patent classification (IPc) scheme are hierarchical indexing schemes for categorizing techno-logically similar patents. Table 1.2 shows an example of this hierarchy for a tree down to
Figure 1.1: Information from Patent Literature as Lead Trend Indicator
Pu
blic
ato
n F
req
uen
cy
Time
PatentApplications
ScientificPublications
MarketingPresentations,Internet
Table 1.1: Outline—Formal Features of Patent Literature
Accessibility Very easy, e.g., from patent offices such as the U.S. Patent Office, European Patent Office*, Japan Patent Office, etc.
Technology Classification Yes, built‐in via patent classification
Time Accuracy Yes, due to the requirement of novelty when filing a patent, i.e., no prior printed publication allowed
Information Density High: structured technology classification, technology description, inventors, assignees, citations
Reviewed Yes
*EPO Patent Database: http://worldwide.espacenet.com
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three levels. There is a main category, in this example “D,” describing a patent class at its highest level. In this particular case it stands for “paper.” Then there is a second level, in this case “D21,” which is a subcategory of paper, to be specific, paper‐making. yet there is a third level, which is shown as well, “D21h,” which is about pulp compositions. So the full tree for “D21h” reads “Paper → Paper‐Making → Pulp compositions.” There are fur-ther, more detailed levels (typically there are five or six levels of granularity, depending on the particular classification scheme), which provide a very suitable database search field for performing a more semantic search for patents. The results obtained from such classification‐based searches are independent of the keywords used in the patents. Search options exist for full‐text search in the title/abstract or the full publication, the patent classification, the date, the inventor, and the assignee.
Network Analysis Tools and Relevant Featuresnetwork analysis tools are commonly used in the field of sociology. Due to the high degree of interconnections of the data to be investigated, they also turn out to be a powerful accelerator for preparing a comprehensive picture of the patent literature. They allow visualizing some of the most essential information, such as co‐inventor net-works, citation networks, and technology clusters (Rastogi et al., 2008; Sternitzke et al., 2008). Many network analysis tools are available, ranging from commercial to free pub-licly licensed software. Table 1.3 provides a short overview of some of the many software
Table 1.2: Sample International Patent Classification Scheme
D Paper(Level 1)
. D21 Paper→ Paper‐Making; Production of Cellulose(Level 2)
. . D21H Paper→ Paper‐Making; Production of Cellulose→Pulp Compositions(Level 3)
Table 1.3: Some Examples of Suitable Network Analysis Tools
Gephi
www.gephi.orgWide range of input formats, including .csvDirect access to possible databases (existing databases can be directly connected and visualized by graphs)
Cuttlefish
cuttlefish.sourceforge.net/Some common input formats (e.g., .cxf, .net, .graphml)Direct access to possible databases
Pajek
pajek.imfm.siWide range of input formats, including .net, .paj, .dat (UCINET), .ged, .bs, .mac, .mol
UCINET
www.analytictech.com.dat input formatCommercial Software
