Open Innovation in the Twenty-First Century
Open Innovation in the Twenty-First Century
Abstract and Keywords
This chapter reviews the core ideas behind Open Innovation, discusses what it is and is not, and shows how it can deliver more value to organizations and to society. Outside-in Open Innovation strengthens the current business and current business model, while inside-out Open Innovation searches for alternative businesses and business models. The chapter explores the connection between technology development and the business model, and examines the use of Open Innovation in intellectual property and in services. However, Open Innovation is not a panacea. Its boundary conditions and limitations must also be acknowledged. As with Chapter 1, the processes of generation in innovation must also be supported by equal attention to innovation dissemination and innovation absorption within the firm, in order for organizations to create and capture value from Open Innovation. Finally, Open Innovation is moving beyond collaborations between two actors, to a broader ecosystem focus that connects many actors together.
Innovation processes need to change if we are to close the gap between the promise of exponential technology, and the lagging economic results we are seeing. Not long ago, innovation was a largely internal affair. The journey from the laboratory to the marketplace took place largely within the four walls of the firm. Think of Bell Labs, IBM Research, or Xerox PARC. Each of them created important technological breakthroughs. And each breakthrough was commercialized through the company’s own businesses.
In recent years, though, this ‘do it all yourself’ approach is increasingly hard to sustain. It costs a lot of money to support each of the many processes needed to achieve success in the market. It takes a long time to complete the journey, at a time when the world is changing more and more rapidly. And it places all the risk squarely on your own shoulders. This unpromising combination of cost, time, and risk has caused many organizations to rethink their approach to innovation. There is an alternative approach that offers a better combination of lower internal cost, faster time to market, and shared risk. It is an approach known as Open Innovation.
Open Innovation is a recent phenomenon. As recently as 2003, if you had done a Google search on that term, you would not have found any useful responses. Today that Google search would return hundreds of millions of responses. Two recent surveys of large companies in North American and Europe found that 78 percent of them were practicing at least some elements of this process.1 Open Innovation has gone from nowhere to nearly everywhere in just over a decade.
Open Innovation is based on the fundamental idea that useful knowledge is now widespread throughout society. No one organization has a monopoly on great ideas, and every organization, no matter how effective internally, needs to engage deeply and extensively with external knowledge networks and communities. An organization that practices Open Innovation will utilize external ideas and technologies as a common practice in their own business (p.29) (outside-in Open Innovation) and will allow unused internal ideas and technologies to go to the outside for others to use in their respective businesses (inside-out Open Innovation).
What evidence is there that Open Innovation actually works? Let’s recap some of the evidence presented in the previous chapter. Many individual companies such as Procter & Gamble have proudly proclaimed their success with their version of Open Innovation called Connect and Develop.2 Another consumer products firm, General Mills, analyzed sixty new product introductions in a twelve-month period. They found that those which had a substantial contribution from Open Innovation outsold the ones that did not by more than 100 percent.3 In the industrial sector, a recent study of 489 projects inside a large European manufacturer found that projects involving significant Open Innovation collaboration achieved a better financial return for the company than projects that did not.4
Research of large numbers of companies also supports the value of Open Innovation. A number of studies employing the Community Innovation Survey have found that organizations with more external sources of knowledge achieve better innovation performance than those with fewer sources, controlling for other factors.5 A recent survey of 125 large firms also found that firms that employed Open Innovation were getting better innovation results.6
Yet I believe that most of us don’t really understand Open Innovation very well. We don’t agree on what it means, we don’t know how best to use it, we don’t think hard enough about its problems and its limits, and therefore we aren’t getting the most out of it. That’s a key goal of this book: to bring a more complete understanding of Open Innovation to the world, and help us all get the most we can out of this exciting concept.
Also, a lot has changed in Open Innovation since 2003. I will examine the most important developments and what they mean for industry, innovation, and policy. One theme that will emerge is that Open Innovation has spread well beyond collaborations and partnerships between two organizations (though that remains an important part of its operation) to a much broader canvas of supply chains, networks, ecosystems and public-private partnerships. Open Innovation isn’t just about the firm anymore. It’s also about the surrounding environment in which innovation occurs. For Open Innovation to thrive, we need to build ecosystems of innovating organizations. And to harness these ecosystems to enhance productivity growth, we need to go further, and build an innovation infrastructure to support an Open Innovation society.
Let’s start by defining Open Innovation. Just as Eskimos have dozens of words for ‘snow’, there are multiple meanings to the term ‘Open Innovation’. In my own view, the Open Innovation paradigm is best understood as the antithesis of the traditional vertical integration model, where internal innovation activities lead to internally developed products and services that are then distributed by the firm. I term the vertically integrated model a Closed Innovation model. Put into a single sentence, Open Innovation is a distributed innovation process based on purposively managed knowledge flows across organizational boundaries, using pecuniary and non-pecuniary mechanisms in line with the organization’s business model.7 This is an admittedly academic definition. But it basically means that innovation is generated by accessing, harnessing, and absorbing flows of knowledge across the boundary of the firm, either flowing in or going out. However, this definition is not universally accepted, a point I will return to later.
In this definition of Open Innovation, we assume that firms can and should use external ideas as well as internal ideas, and internal and external paths to market, as they look to advance their innovations. Open Innovation processes combine internal and external ideas together into platforms, architectures, and systems. Open Innovation processes utilize business models to define the requirements for these architectures and systems. The business model utilizes both external and internal ideas to create value, while defining internal mechanisms to claim some portion of that value.
Outside-In and Inside-Out Open Innovation
There are two important kinds of Open Innovation: outside-in Open Innovation and inside-out Open Innovation. The outside-in part of Open Innovation involves opening up a company’s own innovation processes to many kinds of external knowledge inputs and contributions. It is this aspect of Open Innovation that has received the greatest attention, both in academic research and in industry practice. A lot has been written about technology scouting, about crowdsourcing, about open source technology, and licensing in or acquiring technology. Many scholars and industry people think that is all that Open Innovation is about. But that’s incomplete. There is a second branch (p.31) of those knowledge flows that is also a critical part of the concept. Inside-out Open Innovation requires organizations to allow unused and under-utilized knowledge to go outside the organization for others to use in their businesses and business models. This could result in licensing out a technology, or spinning off a new venture, or contributing a project to an open commons, or forming a new joint venture with outside parties (Box 2.1). In contrast to the outside-in branch of Open Innovation, this portion of the model is less well understood, both in academic research and also in industry practice. As we’ll see in a later chapter, it is this second branch of Open Innovation that provides the path to discovering new business models for unused or underused internal ideas and technologies.
What Open Innovation is Not
Notice what Open Innovation is not: it is not (only) about crowdsourcing, where someone looking for a breakthrough concept or solution submits a problem for a group or crowd to solve. Open Innovation is not (only) about managing one’s suppliers better. And Open Innovation isn’t (only) about open source software, and the open source methods inspired by open source software.
This last item deserves more discussion, as it is a very common misconception. The open source approach to Open Innovation ignores the business model and takes no account of the inside-out half of the Open Innovation model. It also treats intellectual property (IP) as a barrier to innovation, ideally one that should be eliminated. The work of Eric von Hippel, for example, (p.33) analyzes ‘open and distributed innovation’, using the example of open source software as the motivating example for his analysis.8,9 And he is far from alone in this.
There is an irony in this, because of a schism that has arisen in open source software itself. Within that community, there has been a strong disagreement between the ‘free software’ people and the ‘open software’ people. The free software people were people like Richard Stallman and others who thought ‘software should be free’. Projects like the GNU operating system were constructed using a copy-left approach, meaning that any use of the GNU code must itself be shared with the rest of the GNU development community. This is very much akin to the belief that IP is unnecessary and indeed, unhelpful to innovation. Users can be expected to freely reveal their knowledge within the community, because they benefit directly from innovation advances as users of that innovation. Business models similarly have no role to play in his conception. Whatever capital organizations may require to scale their innovations, and how that capital may earn a return once it is employed, is completely ignored.
On the other hand, there is a separate branch of open source software that uses the term ‘open software’, which allows companies that use open software code to make additions to that code without having to share those additions back with the software community. Linux is a software project organized along these lines. Companies like Google and Amazon, which make extensive use of Linux, have developed a variety of extensions to that code that have deliberately been kept private, and are not shared back with the Linux community. Open software enables companies to build upon open or shared code, but to invest in proprietary extensions if they so wish.
Linus Torvalds, the creator of Linux, is squarely in the ‘open’ camp (rather than the ‘free’ camp). In fact, he is rather dismissive of Richard Stallman’s evangelism for ‘free software’:
‘He’s too inflexible, too religious…. I certainly am of the opinion that open source started working a lot better once it got away from the Free Software Foundation politics and values, and more people started thinking about it as a tool than a religion. I’m definitely a pragmatist.’
Torvalds’ pragmatism is akin to my definition of Open Innovation, in which a company utilizes a business model to support investment in a project and allows that company to scale that project over time. IP is not only allowed in my view of Open Innovation, it actually enables companies to collaborate and (p.34) coordinate together, confident in the knowledge that they will be able to enjoy some protection from direct imitation by others in the community. This will allow firms to invest capital to scale their innovations, should they prove to be successful, and earn a return on that capital.11
Both views of Open Innovation share the insight that being open is a powerful generative mechanism to stimulate a lot of innovation. Von Hippel rightly notes that users are a powerful source of innovation in the early stages of a new product. The differences between ‘free’ and ‘open’ become apparent once the initial stage of a new product is over and the innovation begins to gain traction in the market. At this point, hobbyists give way to companies that come into the market to commercialize these innovations, business models are created, and capital investments have to be made to grow volume sufficiently to spread throughout the society. As we saw in the previous chapter, the real social benefit of an innovation requires more than its generation, it also needs wide dissemination and absorption. While Linux was created by Linus Torvalds and a small community of volunteers early on, it is sustained today by the participation of companies like IBM, Google, Red Hat, and Amazon, who have built business models around Linux and have driven its usage in the enterprise.12 The Open Innovation folks like me think you can have and should have legal regimes and business models to enable that process, whereas the free (or the ‘open and distributed innovation’) people don’t regard this as necessary.
Now you know what Open Innovation is, what it is not, and why it’s not just a glorified version of open source software. Let’s turn now to see how it works, and how that has evolved since the idea was introduced in 2003.
How Open Innovation Works
My 2003 book Open Innovation13 is credited by Wikipedia14 and other observers for being the first sustained analysis of this new approach to innovation. That book was based on close observation of a small number of companies’ innovation practices. It found a number of cases where what these companies were doing was contrary to the prevailing wisdom about innovation at that time. The prevailing wisdom of the time derived from the work of Michael Porter and Alfred Chandler, two very influential Harvard Business School professors.
Porter’s work argued that firms would innovate more effectively by creating or increasing entry barriers, to keep other firms out of the industry.15 Chandler (p.35) argued that managing R&D was done best by managing internal R&D to create economies of scale and scope. In both professors’ views, the real action was inside the firm, and the outside world was not fundamentally a part of the innovation process.16
In my 2003 book, I showed that this conception was no longer a valid description of the innovation activities of many leading industrial companies. In order to understand what these companies were doing, we needed to move past Porter and Chandler, to a new approach. It is helpful to visualize this transformation via ‘before’ and ‘after’ diagrams of an innovation process (see Figures 2.1 and 2.2 below).
Open Innovation, when properly understood, is able to explain phenomena that the earlier closed model of innovation could not.17,18 Open Innovation began from close observation of what companies actually are doing. Then I would step back and reflect on what they were doing in relation to what I’d read as a PhD student and what we were teaching our students. Professor Michael Porter’s work on business and corporate strategy was very powerful and influential when it first appeared in the 1980s and the 1990s, and remains popular to this day. It is really a model of closed innovation, where you figured out what your key strategic assets were and you either went for low cost or went for differentiation or you found a niche. You were constantly looking for (p.37) ways to compete against the other guy. In my observations of what was going on in the industry labs it was clear that a lot of Porter’s model was happening, but there was a lot of other stuff going on that Porter’s model didn’t really explain very well. These anomalies were what led me to the concept of Open Innovation.
I spent a significant amount of time at Xerox and its Palo Alto Research Center. Some of my research there tracked thirty-five projects that started inside of Xerox’s labs and got to a certain level of development, but then internal funding for all these projects was stopped. I was curious as to what happened to these projects subsequently because in many cases Xerox proactively encouraged the employees working on them to leave and take them to the external market. Why? Because once these people left the lab, that budget was freed up to be redeployed in the lab for something that was more strategic and promising for Xerox’s core business.
One of the things I discovered was that most of the thirty-five projects, when they went outside, subsequently failed. And that was what Xerox expected. Since they didn’t see the value of continuing the project, they assumed that there wasn’t much value to be realized. But I found a fascinating anomaly: a few of the projects that went outside succeeded brilliantly, and actually became publicly traded companies. In fact, if you added up the market value of those publicly traded spinoff entities, it more than exceeded the value of Xerox’s own market value. I can assure you that no one inside Xerox ever expected that! It is also a result that Michael Porter and Alfred Chandler would have a very hard time explaining.
So that really made me think how to better understand this, and how would you innovate effectively, whether in a large corporation like Xerox or in a small corporation or startup. How would you think about an innovation system that was more open? In the example of Xerox, their core innovation processes were doing a good job of commercializing certain technical projects that really fit well with their business model. But there were also had these other projects that didn’t fit with the core but when they exited to the outside they found different business models that made them much more attractive as standalone entities.
I have come to think of these misfit projects as ‘false negatives’, projects that lacked value in the context of the company’s current business model, but might have significantly more value if commercialized through a different business model. The root of the problem is that innovation involves a substantial degree of both market and technical uncertainty. When evaluating projects under these conditions, managers will exercise their best judgment, (p.38) but will sometimes commit evaluation errors. These can be ‘false positives’: projects that looked highly promising, and were launched into the market, where they promptly failed. Or they can be ‘false negatives’: projects that were stopped during the innovation process, because they were judged to be unpromising. But some of these projects that manage to continue outside the organization go on to become successful, hence the false negative label. (This concept of false negatives is also something not discussed in the previous research on innovation processes.)
Open Innovation treats false negatives as a consequence of a mismatch between a potential technology and the company’s business model. This mismatch means that the false negative project needs to be managed through processes that explore alternative business models internally, or to spin off the technology outside the firm, to allow the nascent venture to locate a different business model. We will look at such processes more closely in Chapter 5. These false negatives are at the root of the inside-out part of the Open Innovation model.
A second set of new insights from Open Innovation lies in the treatment of intellectual property. In the closed model, companies historically accumulated intellectual property to provide design freedom to their internal staff. The primary objective was to obtain freedom to operate, and to avoid costly litigation. As a result, most patents are actually worth very little to these companies, and the vast majority are never used by the business that holds them.19 In Open Innovation, intellectual property represents a new class of assets that can deliver additional revenues to the current business model, and also point the way towards entry into new businesses and new business models. Open Innovation implies that companies should be both active sellers of IP (when it does not fit their own business model) and active buyers of IP (whenever external IP does fit their own business model).
To assess the value of this insight, consider your own organization and evaluate its patent utilization rate. Think of all the patents that your company owns. Then ask yourself, what percentage of these patents are actually used in at least one of your businesses? Often people don’t even know the answer, because no one has ever asked the question. One fact is known: about two-thirds of all the issued patents in Europe are allowed to lapse before their twenty-year expiration date, because the company didn’t want to continue paying the renewal fees to keep the patent in force.20 In cases where large companies have taken the trouble to analyze their own patent usage, the percentage used is often quite low, between 10–30 percent.21 This means that 70–90 percent of a company’s patents are not used. In most companies, (p.39) these unused patents also are not offered outside for licensing either. If you have a low patent utilization rate, you might also benefit from opening up your patents to others for their use (on your terms, of course!).
The Business Model is Critical to Absorbing Innovation
As the Xerox PARC analysis and the IP discussion above show, the business model plays a critical role in the innovation process. As I reflected further upon this point, I realized that it warranted an entire book in its own right. This became the motivation for my second book, Open Business Models, published in 2006. Instead of treating the business model as fixed, as I did in the first book, I examined the implications of being able to innovate the business model itself. Making business models more adaptive might allow companies to obtain more value from innovation, from those false negative projects.
Had Xerox, for example, been willing to experiment with alternative business models, some of the value that resulted from 3Com, Adobe, VLSI Technology, and other spinoffs might have accrued directly to Xerox. And some of these experiments can even be done with ‘other people’s money’. If Xerox were willing to sell some of its technologies on an Original Equipment Manufacturer (OEM) basis, for example, those technologies might have become industry standards while being housed within Xerox. And the experiment would have been whether external companies were willing to buy the technology or not. In other cases, technologies that were licensed out went to companies that employed those technologies in very different business models. Xerox could have selectively emulated some of those models with other technologies still in its possession.
The book also presented a maturity model of business models, from commodity-type business models (offering undifferentiated products) to the highest, most valuable kind of business model, a platform business model. The platform models are more open, because they entice numerous third parties to innovate on your architecture, your system, your platform. And they often enable others to license unused technologies from you to place those into other business models. This makes continued investment in R&D more sustainable, and can even confer competitive advantage.
P&G, for example, is best known for its embrace of outside-in Open Innovation via its Connect and Develop initiative. But P&G also opens up its business model to license out many of its technologies for others to use. (p.40) This isn’t as weird as it might seem, because P&G is strategic about how, when, and on what terms it licenses those technologies. As Jeff Weedman of P&G put it to me:
The original view [of competitive advantage] was: I have got it, and you don’t. Then there is the view, that I have got it, you have got it, but I have it cheaper. Then there is I have got it, you have got it, but I got it first. Then there is I have got it, you have got it from me, so I make money when I sell it, and I make money when you sell it.22
Today, business model innovation is becoming a growing area of interest for many authors.23 While my book was among the first to link innovation results to the fit with the prevailing business model, this is an area that is developing rapidly. However, most organizations treat R&D activities quite separately from the design and improvement of business models. This has held back progress in this area.
The good news is that some pioneering thinkers in the entrepreneurship area have created a set of processes that have the capability to explore new business models with potentially false negative internal R&D projects. This is the Lean Startup movement, initiated by Eric Ries, advanced by Steve Blank, and from a design perspective, illustrated by the Business Model Canvas of Alex Osterwalder. Because of their collective work, we know now how to design and test potential new business models. What is not well known, though, is that Open Innovation can play a powerful role to advance these new explorations, particularly inside large companies. I’ll devote an entire chapter to this topic later in this book in Chapter 5.
Open Innovation: Shifting into Services
Another recent development in Open Innovation is the consideration of how innovation occurs in services. Most of the top forty economies in the OECD have half or more of their gross domestic product (GDP) from services. And many companies are witnessing a shift to services as well. Xerox now gets more than 25 percent of its revenues from services. IBM is another classic case, along with GE and Honeywell.
In some cases, what’s really happening is the business model is shifting, which can turn a product business into more of a service business. For example, a GE aircraft engine can be sold for tens of millions of dollars to (p.41) an airframe manufacturer. That same engine can also be leased on a so-called ‘power by the hour’ program to that airframe manufacturer. In the first case, it’s a product transaction. In the second case, it becomes a service. And, in the second case a hidden benefit for GE is all the aftermarket sales and service, spare parts, etc., that accrue during the thirty-year operating life of the engine. With a Power by the Hour offering, all that work—and revenue—comes back to GE.
More generally for services, innovation must negotiate a tension between standardization and customization. Standardization allows activities to be repeated many times with great efficiency, spreading the fixed costs of those activities over many transactions or customers. Customization allows each customer to get what they want, for high individual satisfaction. The problem is that standardization denies customers much of what they want, while customization complicates the efficiencies available from standardization.
The resolution to this dichotomy is to construct service platforms. These platforms invite others to build on top of your own offering (the platform), so that there are economies from standardization in the platform, along with customization via the participation of many others adding to the platform. Recall that a fundamental premise of Open Innovation is ‘not all the smart people work for you’. If that’s the case, there’s actually more value, not in coming up with yet another building block of technology, but rather in coming up with the architecture that connects these things together in useful ways that solves real problems before other people do. So that system architecture, that system integration skill to combine pieces together in useful ways, becomes even more valuable in a world where there are so many potential building blocks that can be brought together for the purpose.
Platform leadership to me is the business model side of systems integration.24 To get others to join your platform, you need to construct a business model that can inspire and motivate customers and developers and others to join the platform. You design your model in ways that they can make money and they can create business models that work for them, even while your business model works for you. Done well, their activities increase the value of your business to you, so their money makes your business more valuable. These ideas are explored further in my 2011 book, Open Services Innovation.25
In summary, Open Innovation is a powerful approach to improve the results one can obtain from innovation. It offers a number of insights when compared to more conventional ways of approaching innovation, as shown in Box 2.2. (p.42)
What are Open Innovation’s Problems? When Might it Fail?
So far, you might think that Open Innovation is wonderful. So if it is so great, why doesn’t everyone do it? And why hasn’t it resolved the gap between exponential potential and economic reality that we examined in Chapter 1? Two large sample surveys, done in 2013 and 2015, reveal that in large companies, nearly 80 percent of companies are practicing at least some elements of Open Innovation.27 But those same surveys showed that companies are not satisfied with their measures for managing Open Innovation. And, as we have already seen, Open Innovation means different things to different people.
It is high time to consider some of the problems involved with practicing Open Innovation. Academics are still publishing Open Innovation success (p.43) cases for the most part, or performing large scale statistical analyses that show an innovation benefit to Open Innovation.28 Some academics have done excellent work on crowdsourcing, to explore how best to construct a request for submissions, and whether or not to have submitting respondents collaborate or compete for the rewards.29 With a few notable exceptions,30 however, academics have ignored the very real problems of Open Innovation failures.
Meanwhile, inside companies one finds many who are trumpeting their successes with Open Innovation. The barriers they faced, the projects that failed, ‘the ones that got away’, are all swept under the rug. Many consulting firms now offer Open Innovation services for interested clients. They too are quick to trumpet positive results, while discreetly burying anything that didn’t work as expected. This shouldn’t surprise us, as these consultants do not want to embarrass their clients (and in the process, perhaps themselves). But we miss the chance to learn from negative experiences with Open Innovation, causing us to overlook its risks, its problems, and its true character.
In order to move beyond simply celebrating Open Innovation’s successes, we can start by considering some underlying conditions that need to be satisfied. At its root, Open Innovation is about generating, disseminating, and absorbing inflows and outflows of knowledge. This recalls Figure 1.5 that we considered in Chapter 1, only now we examine it in the context of an individual organization (Figure 2.3).
As in Chapter 1, it isn’t enough to simply discover or locate useful knowledge. That knowledge has to be disseminated to the right people and the right (p.44) places in the organization. And other people in the organization need to learn it, understand it, and potentially modify or extend it, in order to put it to work inside the organization. The best way to move knowledge from one person to another, even in this hyper-connected, always-on world, is to put people in close proximity, so that they interact enough to really share and transfer that knowledge. So one critical requirement for effective Open Innovation is a high level of education and skill in the workforce, combined with a reasonably high level of labor mobility from one organization to other organizations, to diffuse that knowledge broadly throughout society.
This is hard to do in some environments. In Japan, for example, there’s a two-tier labor market where many people join a company once they graduate college, and they stay with that company for most of their career. There’s a second tier in the market that’s much more temporary, with people moving from company to company. Those people are typically in lower status jobs. Within that first tier of the market, labor mobility in Japan remains very low even today. That really impairs Open Innovation because even if you bring in external ideas, it’s the same people that you had last year or the year before or the year before that, who are trying to embrace the new ideas. The idea might come in but the people with those ideas don’t come in, and don’t make the necessary modifications and adjustments to the new idea so that it works in the context of that company.
As we’ll see in a later chapter on the back end of Open Innovation (Chapter 4), internal siloes often frustrate Open Innovation, because useful internal knowledge gets trapped in specific functions, or hoarded by defensive managers. To break through these siloes, people also need to rotate between innovation groups and business units, in order to transfer a promising innovation project into a business unit. Such a transfer often requires making the modifications and adjustments to an initial idea to incorporate it into a business unit, and take it to market. And to take advantage of the inside-out branch of Open Innovation, one or more people often need to move with the project, for some extended period of time, to effectively transplant the project outside the originating department.
Another requirement for dissemination and absorption of new knowledge is the presence of internal R&D. Some consider Open Innovation to be a rationale for outsourcing R&D. But this misunderstands the nature of innovation. To really transfer knowledge effectively in a way companies can really make use of it, you need a certain amount of creative abrasion and a certain amount of dwell time for people who are working to apply that knowledge together.31 Open Innovation works best when you have people collaborating (p.45) side by side, with people that are sharing knowledge from one organization to another.32 These aren’t people from purchasing, but instead are very talented people from your own organization. A related requirement are people who operate in a boundary-spanning role to connect knowledge from difference sources, and find ways to mash them together. This is particularly useful to overcome organizational siloes that specialize knowledge within specific functions, and restrict its access to anyone outside of those functions. Such people are sometimes termed ‘T-shaped managers’.33 This is part of the absorption process.
A well-known phenomenon in R&D that can impair Open Innovation’s effectiveness is the Not Invented Here (NIH) syndrome. Organizations with strong technical histories often feature R&D personnel who are convinced that if they didn’t invent it themselves, it must not be important or must not be very good. This hubris arises typically in organizations with a solid history of good technical results, and non-technical people are not able to evaluate the capability of internal R&D very effectively on their own. Open Innovation depends on internal R&D staff at many critical stages of the innovation process, and so an organization with a strong NIH culture might find many ways to subvert the Open Innovation process.
One recent paper documented the impact of NIH upon Open Innovation quite clearly. Hila Lifshitz Assaf did her doctoral studies at Harvard Business School under the direction of Karim Lakhani. She studied the adoption of Open Innovation practices at NASA, and focused particularly upon the use of crowdsourcing to generate new ideas for NASA.34 One successful idea allowed NASA to significantly improve its ability to predict solar flares.
But Lifshitz Assaf’s work went beyond this successful idea. She looked at the impact that the idea had inside the engineering organization at the Johnson Space Control Center at NASA. Internal engineers were troubled by the result obtained from outside. Their sense of identity, their understanding of their role in the organization, seemed threatened by the Open Innovation outcome. I suspect that many R&D intensive organizations responded similarly to the practice of Open Innovation in their own company.
Another issue with Open Innovation has to do with whether and how the results of externally-obtained knowledge move through a company’s subsequent innovation process. Hosting a crowdsourcing challenge, and offering a prize to the winning submission, is just the beginning of the innovation journey for the hosting organization. Even excellent ideas must be adapted, modified, and customized to the specific context of the host organization. And this work must be done by internal staff, often technical staff in the (p.46) organization. At the same time, the externally-sourced idea must compete for attention and priority with other ideas and projects. The internally-sourced ideas and projects usually have champions who explain, justify, and promote them inside the organization. This advocacy is critically important to advance projects through the many hurdles that any innovation project must clear. By contrast, there is often no internal technical champion for an externally-sourced idea or project. Even if an award or prize has been paid, that does not assure the idea of continued internal support through those subsequent innovation hurdles.
A different constraint emerges in potential inside-out Open Innovation projects. Many companies under-utilize their library of patents and other know-how assets. It is quite possible that some shelved internal projects might find new life in a new market, if they were allowed the chance to pursue that opportunity outside the company. Yet there are real barriers to doing this, not because of the fear that those exploring the opportunity would be wasting the company’s time or resources. The real barrier is the fear that those explorers may succeed in finding a new market. Instead of celebrating this success, those inside the company who previously shelved the technology now look bad. As long as the project stays shelved, no one is at risk of being embarassed. But allowing the project out of the organization invites the possibility of appearing to look foolish. This behavioral response might be termed Fear of Looking Foolish, or FOLF (with a nod to the millenial notion of Fear of Missing Out, or FOMO).
Eric Chen and I looked at this issue in the pharmaceutical industry, when we explored the idea of recovering abandoned compounds.35 While every pharma asserts that its critical mission is to address unmet medical needs among patients, organizational siloes strongly inhibit the process to export an abandoned compound outside the company for another group to commercialize. One pharma with 7000 research scientists working on tens of thousands of compounds had exactly two people charged with outlicensing the company’s patented compounds. In some years, one compound might be licensed out, while in other years, no compounds were licensed out. Our interview subjects candidly admitted to us that FOLF was a major constraint to overcoming this.
There are more subtle problems that arise with Open Innovation as well. If one succeeds in fielding a successful call for solutions to a crowd or innovation community, one will likely attract a lot of submissions. It takes time to review all of these submissions, and the level of quality of most of them is often rather poor. Perhaps worse, if a great many more ideas enter into a company’s (p.47) innovation process, and the company has not invested in greater downstream capacity within the different support organizations (not just engineering, but also IT, procurement, finance, legal, etc.) to process these ideas, the wealth of new ideas can create bottlenecks and congestion that slow down the overall innovation process—instead of stimulating more innovation. Many companies that exhibit slow innovation processes do so precisely because they have overloaded the support resources that these groups need to do their work.
These are not easy issues to address. We will consider them in more depth in Chapter 4.
Open Innovation Today: Networks, Ecosystems, and Platforms
Open Innovation began as a series of case studies that examined collaborations between two organizations to open up the internal innovation process of the focal firm. Today, though, we see many instances in which the concept is being used to orchestrate a significant number of players across multiple roles in the innovation process. Put simply, designing and managing innovation communities is going to become increasingly important to Open Innovation’s future. This is true both for firms, and for the larger society in which these firms operate.
Many observers have noted how firms like Uber, Airbnb, and Amazon have developed quite valuable businesses by building and scaling platforms that connect customers for various goods and services with disparate suppliers of those goods and services. These are relatively pure forms of platforms, characterized by the platform owner not needing to own any of the assets being traded.
But Open Innovation goes well beyond these pure play examples. It is actually transforming a variety of consumer (B2C) and industrial (B2B) businesses, by extending their reach and focus to the surrounding ecosystem in which they operate. Playing close attention to one’s ecosystem can unlock new sources of growth for these firms. Ron Adner has a wonderful book that addresses this point at length, though not in the context of Open Innovation.36 Let me illustrate this point with two rather distinct examples of two different kinds of community level Open Innovation across a broad spectrum of innovation activities.
My first example comes from Taiwan Semiconductor Manufacturing Corporation (TSMC), a foundry operating in the semiconductor industry. TSMC provides manufacturing services from its manufacturing facilities (p.48) (foundries) to its clients, who design new semiconductor chips. The customers take these chip designs to TSMC, and TSMC fabricates the designs onto silicon wafers, and gives these back to its customers. The customers then package them into individual chips, and sell them. This saves TSMC’s customers from having to invest in expensive manufacturing plants to manufacture chips. Instead, they rely on companies like TSMC to do the fabrication work for them.
Designing chips is a complex process that requires customers to use a variety of design tools, such as reference designs and process recipes. With the growth of TSMC’s business ecosystem, many of the third-party companies who make these tools began to take steps to assure their customers that their offerings would run on TSMC’s processes. This expansion in third party tool offerings creates more design options for TSMC’s customers—a clear benefit. However, these new offerings also increase the complexity for TSMC’s customers to manage, and this complexity might cause new chips to require re-designs or other expensive modifications to be manufactured correctly—a clear risk.
TSMC has addressed this risk with its Open Innovation Platform (their term, not mine!).37 The Open Innovation Platform starts by combining the many design and manufacturing services of TSMC with those provided by many third-party companies, and then testing all these combinations together. TSMC then certifies to customers of those offerings that they can use these tools with confidence that the chip will turn out properly the first time through the process. TSMC’s Open Innovation Platform helps its customers get their designs manufactured on the first pass. This avoids very expensive ‘turns’ of the chip design, whereby the chip must be redesigned in order to be manufactured properly in volume. The result is faster time to market for TSMC’s customers, at a lower cost of design. So TSMC uses Open Innovation to manage a complex ecosystem of internal and external design sources, and provides a guarantee to its customers, provided they stick to these validated resources when designing their chips.
My second example comes from GE, and its recent ecomagination challenge.38 While GE has a very large energy business of its own, with revenues of nearly $40 billion annually, the company has noticed a great deal of venture capital and startup activity in green and renewable energy technologies. Recognizing its own limits, GE sought to establish a process to tap into the potential project ideas out there that had the potential to become promising new ventures in green and/or renewable energy.
But GE did this in an open way. Instead of doing all the work themselves, they enlisted four active VC firms who had already had experience investing in this space. Together, the four VCs and GE pledged a total of $200 million to (p.49) invest in attractive startup ventures. The ecomagination challenge was born. In July of 2010, the challenge was launched to the world, and everyone was invited to submit potential project ideas for consideration for startup investment.
In the process, more than 3800 venture proposals were received (they were expecting perhaps 400). As of this writing, twenty-three ventures have been funded, with five other projects receiving other awards, and even a People’s Choice award was given as well. While the ventures are quite young, the VCs and GE are all enthusiastic about the experience. GE’s level of enthusiasm has led them to adapt the model to the health care space (a Healthymagination challenge was launched in 2011) and also in China (a challenge was launched there as well).
And one need not be a large company to open up to the community in one’s innovation process. A small firm in Florida, Ocean Optics, has instituted a community innovation challenge on a much smaller scale.39
This is the future of Open Innovation, a future that is will be more extensive, more collaborative, and more engaging with a wide variety of participants. Just as no man is an island, no firm will be successful in an Open Innovation world if they restrict themselves to the prescriptions of Porter and Chandler. Instead, these companies must embrace the bountiful useful knowledge that exists all around them, and find ways to identify, harness, and deploy that knowledge to advance their business—before their competitors do so.
Open Innovation offers a great deal of opportunity, for the firms that embrace it and for the larger society that sustains it. To get the most out of Open Innovation, however, we will need to pay close attention to the boundary conditions that support or inhibit effective Open Innovation. As with the previous chapter, firms must do more than simply generate a new technology. Firms must also disseminate the technology widely, across the many siloes that infest most large organizations, and overcome the fear of looking foolish (FOLF). And these firms must absorb the technology, embedding it in a business unit, and a business model, in order to scale it. In the next chapter, we’ll examine the process for getting that technology out of basic scientific research. For those who want to get directly to Open Innovation results, you can skip to Chapter 4, where we will look at these issues in more depth. Chapter 8 will showcase some exemplary companies practicing Open Innovation, and will also consider some notable failure cases as well.
The innovation capabilities of organizations around the world will no longer stop at the boundaries of one’s own organization. Instead an organization’s Open Innovation practices will extend to suppliers, customers, partners, third parties, and the general community as a whole. This is the secret to (p.50) getting business results out of the Open Innovation process. As one R&D manager explained to me, ‘It used to be that the lab was our world; with Open Innovation, the world is now our lab.’
Chapter 2 review points:
1. Most companies used to use a Do-It-All-Yourself, or Closed model of innovation. Innovation in many companies today is more open.
2. Open Innovation uses inflows and outflows of knowledge across organizational boundaries to identify new opportunities, save time and money, and share innovation risks.
3. The generation, dissemination, and absorption of technology within the firm requires not only technology development, but also business model design and deployment. This parallels the innovation infrastructure we saw for the overall society in Chapter 1.
4. Open Innovation affects service industries, in addition to product and process industries. Service platforms can resolve the tensions between customization and standardization.
5. Open Innovation can be blocked by NIH attitudes, a lack of internal R&D capability, a lack of internal champions, a fear of looking foolish (FOLF), or congested support functions that lack the capacity to respond in a timely manner.
6. Open Innovation is moving beyond single collaborations between individual organizations, to networks and ecosystems of organizations, often collaborating through platforms
(1.) Brunswicker and Chesbrough, ‘A Fad or a Phenomenon: Results from a Survey on Open Innovation’, 2013, and Brunswicker and Chesbrough, ‘The Adoption of Open Innovation in Large Firms’, Research-Technology Management, 2018.
(2.) See L. Huston and N. Sakkab, ‘Inside Procter & Gamble’s new model for innovation: Connect and develop’, Harvard Business Review, 2006.
(3.) Personal conversation between Mike Helsel of General Mills and the author, October 15, 2014.
(4.) See Du. Leten and Vanhaverbeke, 2014.
(5.) See for example, Laursen and Salter, 2006.
(6.) Brunswicker and Chesbrough, ‘A Fad or a Phenomenon: Results from a Survey on Open Innovation’, 2013.
(7.) See H. Chesbrough and Marcel Bogers, in Chesbrough, Vanhaverbeke and West, New Frontiers in Open Innovation (Oxford University Press, 2014), p. 1.
(8.) Eric von Hippel, Democratizing Innovation, MIT Press, 2005. This book discusses Open Innovation in quite some detail, but does not cite my 2003 book at all. There also is no discussion of a business model anywhere in his book.
(9.) Jim Euchner of the IRI has usefully distinguished Open Innovation from what he calls ‘open source innovation’, with the latter corresponding to von Hippel’s treatment of the concept. See Euchner, ‘Two Flavors of Open Innovation’, RTM July–August 2010, pp. 7–8.
(10.) Torvalds’ frank comments are quoted in Steve Lohr’s book Go To (2001), p. 215.
(11.) In a paper with Ann Kristin Zobel and Ben Balsmaier (2016) we actually ran a test of whether IP protection impaired or enhanced innovation collaboration. Using data from photovoltaic solar panels, we examined the behavior of hundreds of (p.169) startup companies in this industry, and compared their collaborative activity before and after they received their first patent. The ‘free software’ camp would argue that collaboration is easier before startups stake out their IP claims in the form of patents. The ‘open software’ camp would disagree, arguing that having some IP protection allows companies to collaborate more, secure in the knowledge that they have at least some protection for their technology. In this instance, the empirical analysis supports the Open camp, rather than the Free camp.
(12.) It is worth noting, for example, that the Linux Foundation that governs the Linux kernel these days is comprised of companies like IBM, Intel, Oracle, Dell, Nokia, and others. Membership on the Board requires an investment of $500,000, well beyond the financial capacity of any hobbyist. These inconvenient facts are ignored by the ‘open and distributed’ adherents of Open Innovation.
(13.) H. Chesbrough, Open Innovation: The New Imperative for Creating and Profiting from Technology (Harvard Business School Press, 2003).
(15.) Michael Porter, Competitive Strategy (New York: Free Press), 1980; Michael Porter, Competitive Advantage (New York: Free Press), 1985.
(16.) Alfred Chandler, Scale and Scope: The Dynamics of Industrial Capitalism (Harvard University Press, 1990).
(17.) The entirety of chapter 1 of that book examines the experience of Xerox’s Palo Alto Research Center, and offers a different interpretation of the root cause of Xerox’s problems with PARC. Xerox was judged to be effective in utilizing PARC technologies that fit with Xerox’s copier and printer business model. The failure was that Xerox could not conceive of an alternate business model through which to commercialize technologies that did not comport with that model. By contrast, the profile of IBM in chapter 5 showed a company that did reconceive its business model in response to a life-threatening crisis.
(18.) One paradox posed in Open Innovation was the surprising ability of Cisco to keep up with Lucent and its Bell Labs in the 1990s. As the 2003 book noted, ‘Though they were direct competitors in a very technologically complex industry, Lucent and Cisco were not innovating in the same manner. Lucent devoted enormous resources to exploring the world of new materials and state of the art components and systems, to come up with fundamental discoveries that could fuel future generations of products and services. Cisco, meanwhile, did practically no internal research of this type.
Instead, Cisco deployed a rather different weapon in the battle for innovation leadership. It scanned the world of startup companies that were springing up all around it, which were commercializing new products and services. Some of these startups, in turn, were founded by veterans of Lucent, or AT&T, or Nortel, who took the ideas they worked on at these companies, and attempted to build companies around them. Sometimes, Cisco would invest in these startups. Other times, it simply partnered with them. And more than occasionally, it would later acquire them. In this way, Cisco kept up with the R&D output of perhaps the finest (p.170) industrial research organization in the world, without doing much internal research of its own’ (p. xviii).
(19.) While comprehensive evidence of these points is elusive, some elements are already documented in the literature. Lemley (2001: 11–12) cites studies that report a large fraction of patents are neither used, nor licensed by firms. Davis and Harrison (2001) report that more than half of Dow’s patents were un-utilized. Sakkab (2002) states that less than 10 percent of Procter & Gamble’s patents were utilized by one of P&G’s businesses.
(21.) These data are taken from H. Chesbrough, Open Business Models (Boston: Harvard Business School Press, 2006).
(22.) The quotation is from H. Chesbrough, Open Business Models (Harvard Business School Press, 2006), p. 201.
(23.) See Mark Johnson’s book, Seizing the White Space: Business Model Innovation for Growth and Renewal (Harvard Business School Press, 2010), Alex Osterwalder’s book, Business Model Generation (Wiley, 2010), and a special issue of Long Range Planning, 43 (2–3), 2010. that was dedicated entirely to academic articles on business models.
(24.) See Annabelle Gawer and Michael Cusumano’s excellent book on Platform Leadership (2002), for an indepth analysis of what it takes to build and sustain leadership within a platform. Geoffrey Parker and Marshall VanAlstyne’s Platform Revolution: How Networked Markets Are Transforming the Economy and How to Make Them Work for You (2016) updates this thinking for today’s digital era.
(27.) For details on these surveys, see Chesbrough and Brunswicker, 2013, and Brunswicker and Chesbrough, 2015. Our sample was restricted to firms with annual sales over $250 million, headquartered in either the US or Europe. So they cannot inform us about small firms’ use of Open Innovation, nor the use of Open Innovation in other parts of the world.
(28.) See Laursen and Salter, 2006 and Du. Leten and Vanhaverbeke, 2014, for two excellent large sample analyses that show a statistically significant benefit to the use of Open Innovation in firms.
(29.) See K. Boudreau and K. Lakhani, ‘How to manage outside innovation’, Sloan Management Review, 2009 for a good discussion of the benefits of competition vs. the benefits of collaboration in innovation communities that propose solutions to problems.
(30.) See Hila Lifshitz-Assaf’s excellent article on OI at NASA: ‘Dismantling knowledge boundaries at NASA: The critical role of professional identity in Open Innovation’, Administrative Science Quarterly 63.4 (2018): 746–82.
(p.171) (31.) Ikujiro Nonaka and Hiro Takeuchi (1995) established the importance of managing knowledge by getting team members to engage with one another extensively. This was particularly needed for experiential, or tacit, knowledge.
(32.) A nice recent analysis of the role of teams in Open Innovation initiatives can be found in Amy Edmondson and Jean-Francois Harvey’s 2017 book, Extreme Teaming. They were even kind enough to allow me to write the Foreword to this book!
(33.) Morten Hansen (2001) has done some excellent work on the importance of T-shaped managers. The base of the T refers to the person’s deep expertise in some domain of knowledge. But the cross of the T refers to the ability of that manager to engage with other experts from other domains of knowledge, and find connections between the domains.
(34.) See Lifschitz-Assaf, ‘Dismantling knowledge boundaries at NASA’, 2018.
(35.) See Chesbrough and Chen, 2013.
(36.) See Ron Adner, The Wide Lens (2012) for an insightful discussion of the role of complementers in the ecosystem in promoting a successful innovation, or inhibiting the success of an otherwise promising innovation.
(37.) See https://www.tsmc.com/english/dedicatedFoundry/oip/index.htm, last accessed March 21, 2019.