Dining out in the days of living in caves was not quite the simple matter it has become today. For a start, there was a minor difficulty of finding and gathering the roots and berries – or, being more adventurous, hunting and (hopefully) catching your mammoth. And raw meat isn't necessarily an appetizing or digestible dish so cooking it helps – but for that you need fire and for that you need wood, not to mention cooking pots and utensils. If any single individual tried to accomplish all of these tasks alone, they would quickly die of exhaustion, never mind starvation! We could elaborate but the point is clear – like almost all human activity, it is dependent on others. But it's not simply about spreading the workload – for most of our contemporary activities the key is shared creativity – solving problems together, and exploiting the fact that different people have different skills and experiences which they can bring to the party.

It's easy to think of innovation as a solo act – the lone genius, slaving away in his or her garret or lying, Archimedes‐like, in the bath before that moment of inspiration when they run through the streets proclaiming their “Eureka!” moment. But although that's a common image, it lies a long way from the reality. In reality, taking any good idea forward relies on all sorts of inputs from different people and perspectives.

For example, the technological breakthrough that makes a better mousetrap is only going to mean something if people can be made aware of it and persuaded that this is something they cannot live without – and this requires all kinds of inputs from the marketing skill set. Making it happen will require skills in manufacturing, in procurement of the bits and pieces to make it, and in controlling the quality of the final product. None of this will happen without some funding so that other skills related to gaining access to finance – and the understanding of how to spend the money wisely – become important. And coordinating the diverse inputs needed to turn the mousetrap into a successful reality rather than as a gleam in the eye will require project management skills, balancing resources against the clock, and facilitating a team of people to find and solve the thousand and one little problems which crop up as you make the journey.

As we saw in the last chapter, innovation is not a solo act but a multiplayer game. Whether it is the entrepreneur who spots an opportunity or an established organization trying to renew its offerings or sharpen up its processes, making innovation happen depends on working with many different players. This raises questions about team working, bringing the different people together in productive and creative ways inside an organization – a theme we discussed in Chapter 3. But increasingly it's also about links between organizations, developing and making use of increasingly wide networks. Smart firms have always recognized the importance of linkages and connections – getting close to customers to understand their needs, working with suppliers to deliver innovative solutions, linking up with collaborators, research centers, even competitors to build and operate innovation systems. In an era of global operations and high‐speed technological infrastructures populated by people with highly mobile skills, building and managing networks and connections becomes the key requirement for innovation. It's not about knowledge creation so much as knowledge flows. Even major research and development players like Siemens or GlaxoSmithKline are realizing that they can't cover all the knowledge bases they need and instead are looking to build extensive links and relationships with players around the globe.

This chapter explores some of the emerging themes around the question of innovation as a network‐based activity. And of course, in the twenty‐first century, this game is being played out on a global stage but with an underlying networking technology – the Internet – which collapses distances, places geographically far‐flung locations right alongside each other in time, and enables increasingly exciting collaboration possibilities. However, just because we have the technology to make and live in a global village doesn't necessarily mean we'll be able to do so – much of the challenge, as we'll see, lies in organizing and managing networks so that they perform. Rather than simply being the coming together of different people and organizations, successful networks have what are called emergent properties – the whole is greater than the sum of the parts. Box 7.1 gives an example.

7.1 The “Spaghetti” Model of Innovation

As we have showed in Chapter 2, innovation can be seen as a core process with a defined structure and a number of influences – as Figure 7.1 suggests. This is helpful in terms of simplifying the picture into some clear stages and recognizing the key levers we might have to work with if we are going to manage the process successfully. But like any simplification, the model isn't quite as complex as the reality. While our model works as an aerial view of what goes on and has to be managed, the close‐up picture is much more complicated. The ways knowledge actually flows around an innovation project are complex and interactive, woven together in a kind of “social spaghetti” where different people talk to each other in different ways, more or less frequently, and about different things. The image on the right in Figure 7.1 gives another perspective!

This complex interaction is all about knowledge and the ways it flows and is combined and deployed to make innovation happen. Whether it's our entrepreneur building a network to help him get his mousetrap to market or a company like Apple bringing out the latest generation iPod or phone the process will involve building and running knowledge networks. And as the innovation becomes more complex, the networks have to involve more different players, many of whom may lie outside the firm. By the time we get to big complex projects – like building a new aeroplane or hospital facility – the number of players and the management challenges posed by the networks get pretty large. There is also the complication that increasingly the networks we have to learn to deal with are becoming more virtual, a rich and global set of human resources distributed and connected by the enabling technologies of the Internet, broadband, and mobile communications and shared computer networks.

None of this is a new concept in innovation studies. Research going back to the work of Carter and Williams in the 1950s in the United Kingdom, for example, noted that “technically progressive” – innovative – firms were far more cosmopolitan than their “parochial” and inward‐looking counterparts [1]. Similar findings emerged from Project SAPPHO, from the “Wealth from knowledge” studies and from other work such as Allen's detailed study of innovation across the US space program during the 1960s and 1970s [2–4]. Andrew Hargadon's work on Thomas Edison and Henry Ford highlights the fact that they were not just solo geniuses but rather that they understood the network dynamics of innovation and built teams around them capable of creating and sustaining rich innovation networks [5]. In fact studies of early industries, such as Flemish weavers or gun making in Italy or the United Kingdom, suggest that innovation networks have been long‐established ways of creating a steady stream of successful new products and processes [6,7].

We should not forget the importance of managing this “knowledge spaghetti” within the organization. Recent years have seen an explosion of interest in “knowledge management,” and attention has focused on mechanisms to enable better flow such as communities of practice, gatekeepers, and recently social network analysis [8].

Networking of this kind is something that Roy Rothwell foresaw in his pioneering work on models of innovation, which predicted a gradual move away from thinking about (and organizing) a linear science/technology push or demand pull process to one which saw increasing interactivity. At first, this exists across the company with cross‐functional teams and other boundary‐spanning activities. Increasingly, it then moves outside it with links to external actors. Roy Rothwell's vision of the “fifth‐generation” innovation (see Box 7.2) is essentially the one in which we now need to operate, with rich and diverse network linkages accelerated and enabled by an intensive set of information and communication technologies [9].

7.2 Innovation Networks

A network can be defined as “a complex, interconnected group or system,” and networking involves using that arrangement to accomplish particular tasks. As we've suggested innovation has always been a multiplayer game, and we can see a growing number of ways in which such networking takes place. The concept of innovation networks has become popular in recent years, as it appears to offer many of the benefits of internal development, but with few of the drawbacks of collaboration. (We explore the theme of collaboration in more detail in Chapter 10.) Networks have been claimed by some to be a new hybrid form of organization that has the potential to replace both firms (hierarchies) and markets, in essence the “virtual corporation,” whereas others believe them to be simply a transitory form of organization, positioned somewhere between internal hierarchies and external market mechanisms. Whatever the case, there is little agreement on what constitutes a network, and the term and alternatives such as “web” and “cluster” have been criticized for being too vague and all‐inclusive [10].

Different authors adopt different meanings, levels of analysis, and attribute networks with different characteristics. For example, academics on the continent have focused on social, geographical, and institutional aspects of networks, and the opportunities and constraints these present for innovation [11]. In contrast, Anglo‐Saxon studies have tended to take a systems perspective and have attempted to identify how best to design, manage, and exploit networks for innovation [12]. Figure 7.2 presents a framework for the analysis of different network perspectives in innovation studies.

While there is little consensus in aims or means, there appears to be some agreement that a network is more than an aggregation of bilateral relationships or dyads, and therefore the configuration, nature, and content of a network impose additional constraints and present additional opportunities. A network can be thought of as consisting of a number of positions or nodes, occupied by individuals, firms, business units, universities, governments, customers or other actors, and links or interactions between these nodes. By the same token, a network perspective is concerned with how these economic actors are influenced by the social context in which they are embedded and how actions can be influenced by the position of actors.

7.3 Networks at the Start‐up

The idea of the lone inventor pioneering a path to market success is something of a myth – not least because of the huge efforts and different resources needed to make innovation happen. Say the name “Thomas Edison” and people instinctively imagine a great inventor, the lone genius who gave us so many twentieth‐century products and services – the gramophone, the light bulb, electric power, and so on. But he was actually a very smart networker. His “invention factory” in Menlo Park, New Jersey, employed a team of engineers in a single room filled with workbenches, shelves of chemicals, books, and other resources [32]. The key to their undoubted success was to bring together a group of young, entrepreneurial, and enthusiastic men from very diverse backgrounds – and allow the emerging community to tackle a wide range of problems. Ideas flowed across the group and were combined and recombined into an astonishing array of innovations [5].

While individual ideas, energy, and passion are key requirements, most successful entrepreneurs recognize the need to network extensively and to collect the resources they need via complex webs of relationships. They are essentially highly skilled at networking, both in building and in maintaining those networks to help build a sustainable business model.

Nowhere is this more clearly seen than in the case of social entrepreneurship where the challenge is to mobilize a wide range of supporting resources often at low or no cost – and to weave them into a network which enables the launch of a new idea. As Case Study 7.2 shows, this requires considerable network‐building and ‐managing skills.

7.4 Networks on the Inside …

“If only x knew what y knows …?” We can fill the x in with the name of almost any large contemporary organization – Siemens, Philips, GSK, Citibank – they all wrestle with the paradox that they have hundreds or thousands of people spread across their organizations with all sorts of knowledge. The trouble is that – apart from some formal project activities which bring them together – many of these knowledge elements remain unconnected, like a giant jigsaw puzzle in which only a small number of the pieces have so far been fitted together. This kind of thinking was behind the fashion for “knowledge management” in the late 1990s and one response, popular then, was to make extensive use of information technology to try and improve the connectivity. The trouble was that – while the computer and database systems were excellent at storage and transmission – they didn't necessarily help make the connections that turned data and information into useful – and used – knowledge. Increasingly firms are recognizing that – while advanced information and communications technology can support and enhance – the real need is for improved knowledge networks inside the organization.

It's back to the spaghetti model of innovation – how to ensure that people get to talk to others and share and build on each other's ideas. This might not be too hard in a three or four person business but is gets much harder across a typical sprawling multinational corporation. Although this is a long‐standing problem, there has been quite a lot of movement in recent years toward understanding how to build more effective innovation networks within such businesses. Research by Tom Allen during the US space program highlighted the importance of social networks and coined the term “technological gatekeeper.” His work also highlighted the importance of physical connections between people; the famous “Allen curve” shows that there is a strong negative correlation between physical distance and frequency of communication between people. Not for nothing did Steve Jobs reorganize the layout at Pixar so it was impossible for people not to bump into each other and spark conversations. BMW uses the same principles in the underlying architecture of its futuristic R&D Center in Munich.

Another important concept is that of communities of practice – a concept originally developed by Etienne Wenger and Jean Lave [33]. These are groups of people with common interests who collect and share experience (often tacit in nature) about dealing with their shared problem in a variety of different contexts. They represent deep pools of potentially valuable knowledge – for example, John Seeley Brown and Paul Duguid report on Xerox's experience in the world of office copiers [34]. Its technical sales representatives worked as a community of practice, exchanging tips and tricks over informal meetings. Eventually Xerox created the “Eureka” project to allow these interactions to be shared across their global network; it represents a knowledge store which has saved the corporation well over $100 million.

Case Study 7.3 and View 7.1 offer two examples.

7.5 Networks on the Outside

Creating and combining different knowledge sets has always been the name of the game both inside and outside the firm. But there has been a dramatic acceleration in recent years led by major firms like Procter and Gamble, GSK, 3M, Siemens, and GE toward what has been termed “open innovation.” The idea behind this – as we saw in Chapter 6 – is that even large‐scale R&D in a closed system like an individual firm isn't going to be enough in the twenty‐first century environment [35]. The “Chesbrough's Principles of Open Innovation” in Box 7.3 outlines some key characteristics of open innovation.

Knowledge production is taking place at an exponential rate, and the OECD countries spend close to $1 trillion on R&D in the public and private sector – a figure which is probably an underestimate since it ignores the considerable amount of “research,” which is not captured in official statistics [36]. How can any single organization keep up with – or even keep tabs on – such a sea of knowledge? And this is happening in a widely distributed fashion – R&D is no longer the province of the advanced industrial nations such as USA, Germany, or Japan but is increasing most rapidly in the newly growing economies such as India and China. In this kind of context, it's going to be impossible to pick up on every development and even smart firms are going to miss a trick or two [28].

The case of Procter and Gamble provides a good example of this shift in approach. In the late 1990s, there were concerns about their traditional inward‐focused approach to innovation. While it worked there were worries – not least the rapidly rising costs of carrying out R&D. Additionally, there were many instances of innovations that they might have made but which they passed on – only to find someone else doing so and succeeding. As CEO Alan Lafley explained “Our R&D productivity had levelled off, and our innovation success rate – the percentage of new products that met financial objectives – had stagnated at about 35 percent. Squeezed by nimble competitors, flattening sales, lacklustre new launches, and a quarterly earnings miss, we lost more than half our market cap when our stock slid from $118 to $52 a share. Talk about a wake‐up call (HBR March 2006).”

They recognized that much important innovation was being carried out in small entrepreneurial firms, or by individuals, or in university labs, and that other major players such as IBM, Cisco, Eli Lilly, and Microsoft were beginning to open up their innovation systems. As a result, they moved to what they have called “connect and develop” – an innovation process based on the principles of “open innovation.”

Lafley's original stretch goal was to get 50% of innovations coming from outside the company; by 2006, more than 35% of new products had elements that originated from outside, compared with 15% in 2000. Over 100 new products in the past 2 years came from outside the firm and 45% of innovations in the new product pipeline have key elements that were discovered or developed externally. They estimate that R&D productivity has increased by nearly 60% and their innovation success rate has more than doubled. One consequence is that they increased innovation while reducing their R&D spend, from 4.8% of turnover in 2000 to 3.4%.

Central to the model is the concept of mobilizing innovation networks. As Chief technology Officer Gilbert Cloyd explained, “It has changed how we define the organization … We have 9000 people on our R&D staff and up to 1.5 million researchers working through our external networks. The line between the two is hard to draw … . We're … putting a lot more attention on what we call 360‐degree innovation.” But this is not simply a matter of outsourcing what used to happen internally. As Vice President Larry Huston comments, “People mistake this for outsourcing, which it most definitely is not … Outsourcing is when I hire someone to perform a service and they do it and that's the end of the relationship. That's not much different from the way employment has worked throughout the ages. We're talking about bringing people in from outside and involving them in this broadly creative, collaborative process. That's a whole new paradigm.”

Enabling external networking involves a number of mechanisms. One is a group of 80 “technology entrepreneurs” whose task is to roam the globe and find and make interesting connections. They visit conferences and exhibitions, talk with suppliers, visit universities, scour the Internet – essentially a no‐holds‐barred approach to searching for new possible connections.

They also make extensive use of the Internet. An example is their involvement as founder members of a site called Innocentive (www.innocentive.com) originally set up by the pharmaceutical giant Eli Lilly in 2001. This is essentially a web‐based market place where problem owners can link up with problem solvers – and it currently has around 250,000 solvers available around the world. The business model is simple – companies such as P&G, Boeing, and DuPont post their problems on the site and if any of the solvers can help they pay for the idea. Importantly, the solvers are a very wide mix, from corporate and university lab staff through to lone inventors, retired scientists and engineers, and professional design houses. Jill Panetta, InnoCentive's chief scientific officer, says more than 30% of the problems posted on the site have been cracked, “which is 30 percent more than would have been solved using a traditional, in‐house approach.”

Other mechanisms include a website called Yourencore that allows companies to find and hire retired scientists for one‐off assignments. NineSigma is an online marketplace for innovations, matching seeker companies with solvers in a marketplace similar to InnoCentive. As Chief Technology Officer, Gil Cloyd comments, “NineSigma can link us to solutions that are more cost efficient, give us early access to potentially disruptive technologies, and facilitate valuable collaborations much faster than we imagined.” And yet2com looks for new technologies and markets across a broad frontier, involving around 40% of the world's major R&D players in their network.

The challenge in open innovation – as we saw in Chapter 6 – is less about understanding the concept than in developing mechanisms that can enable its operation in practice. Approaches like Procter and Gamble's “Connect and develop” provide powerful templates but these are only relevant for certain kinds of organization – in other areas new models are being experimented with. For many, this involves the construction of different kinds of shared platforms on which different partners can collaborate to create new products and services – such as the BBC Backstage project. This was an ambitious five‐year program to open up the BBC's data and publishing information to outsiders, inviting them to “use our stuff to build your stuff.” It operated via an online platform and a series of linked physical events where ideas could be pitched, explored, and developed further; a wide range of external developers participated and over 500 prototypes for new products and services emerged. In a similar fashion, the UK's public sector mapping organization, Ordnance Survey, began opening up their approach to sharing geographical information to a wide variety of partners. The latest version is an online/offline program – Geovation – which invites external entrepreneurs and developers to use OS information to build novel applications in the geographical information space [37].

Others have gone further down the road toward creating open‐source communities in which cocreation among different stakeholders takes place. Google's support for the Android platform is a good example; the expectation is that the collective innovation across such a space allows for rapid acceleration and diffusion of innovation. Case Study 7.4 looks at examples of opening up the innovation game.

The logic of open innovation is that organizations need to open up their innovation processes, searching widely outside their boundaries and working toward managing a rich set of network connections and relationships right across the board [38]. Their challenge becomes one of improving the knowledge flows in and out of the organization, trading in knowledge as much as goods and services. To assist in this process a new service sector of organizations offering various kinds of brokering and bridging activity has begun to emerge. Examples include mainstream design houses like IDEO and? what if! which help to link clients with new ideas and connections on the technology and market side, technology brokers aiming at match‐making between different needs and means (both web‐enabled and on a face‐to‐face basis) and intellectual property transfer agents like the Innovation Exchange which seek to identify, value, and exploit internal IP which may be underutilized.

Needless to say the challenge of open innovation cannot be met by a single approach and there has been considerable experimentation over the past 20 years. In Chapter 11, we look in more detail at some of the parameters involved in choosing an appropriate open innovation strategy.

Research Note 7.1 looks at some different models for open innovation.

7.6 Networks into the Unknown

Much of the time the challenge in innovation is one of “doing what we do, but better” – continuously improving products and services and enhancing our processes. The scope here is enormous – both in terms of incremental modifications and additions of features and enhancements and in delivering on cost savings and quality improvements. Taken on their own, these may not be as eye‐catching as the launch of a radically new product, but the historical evidence is that continuous incremental innovation of this kind has enormous economic impact. It's the glacier model rather than the violently fast‐running stream – but in the long run, the impact on the economic geography is significant.

But as we have seen when discontinuous events occur existing players often perform badly and it is the new entrant firms who succeed. Part of the problem is the commitment to existing networks by established players. Long‐term relationships are recognized as powerful positive resources for incremental innovation [26] but under some circumstances “the ties that bind may become the ties that blind” [5]. For example, Christensen showed in his work on disruptive innovation that when new markets emerge they do so at the fringe of existing ones and are often easy to ignore and dismiss as not being relevant. Under these conditions, organizations need a different approach to manage innovation – much more exploratory, and engage in developing new networks [39].

Research suggests the challenge facing firms in building new networks can be broken down into two separate activities: identifying the relevant new partners and learning how to work with them. Once the necessary relationships have been built, they can then be converted into high‐performing partnerships. It's a little like the recipe for effective team working (forming, storming, norming, and performing), except that here it is a three‐stage process: finding, forming, and performing [21].

Finding refers essentially to the breadth of search that is conducted. How easy it is to identify the right organizations with which to interact? Finding is enabled not only by the scope and diversity of current operations but also by capacity to move beyond the dominant mental models in the industry. But it is also hindered by a combination of geographical, technological, and institutional barriers (see Table 7.3). Forming refers to the attitude of prospective partners. How likely is a linkup and what are the advantages or barriers?

When these two aspects are set against each other, four separate approaches can be identified [21]. See Figure 7.3.

• Zone 1 represents the relatively straightforward challenge of creating new networks with potential partners that are both easy to find and keen to interact. Although this is where traditional business relationships are formed, it also contains examples of uncertain projects even if the partners are known to each other.
  For example, Lego's decision to develop its next‐generation Mindstorms product involved using a network of lead users of the first‐generation product. Lego's experience after the first Mindstorms product had been that the enthusiastic user community was an asset, despite its approaches such as hacking into the old software and sharing this information on the web. As described by Lego Senior Vice President Mads Nipper, “We came to understand that this is a great way to make the product more exciting. It's a totally different business paradigm.”
• Zone 2 places the emphasis on new network partners. The barriers here are typically geographical, ethnic, and institutional, and the challenge is to locate the appropriate organizations from among many prospective partners. It is here that scouts and other boundary spanning agents can play a key role – as in P&G's Connect and Develop model.
• Zone 3 is where the potential partners are easy to find but may be reluctant to engage. This might occur for ideological reasons, or because of institutional or demographic barriers. An illustration of this approach can be seen in the Danish pharmaceutical company, Novo Nordisk. Faced with long‐term changes in the business environment toward greater obesity and rising health care costs associated with diabetes (its core market), Novo Nordisk realized that it needed to start exploring opportunities for discontinuous innovation in its products and offerings. Its “Diabetes 2020” process involved exploring radical alternative scenarios for chronic disease treatment and the roles which a player like Novo‐Nordisk could play. As part of the follow‐up from this initiative, in 2003, the company helped to set up the Oxford Health Alliance, a nonprofit collaborative entity which brought together key stakeholders – medical scientists, doctors, patients, and government officials – with views and perspectives which were sometimes quite widely separated. To make it happen, Novo Nordisk made clear that its goal was nothing less than the prevention or cure of diabetes – a goal which if it were achieved would potentially kill off the company's main line of business. As Lars Rebien Sørensen, the CEO of Novo Nordisk, explained:

  “In moving from intervention to prevention – that's challenging the business model where the pharmaceuticals industry is deriving its revenues! … We believe that we can focus on some major global health issue – mainly diabetes – and at the same time create business opportunities for our company.”

• Zone 4 covers potential partners who are neither easily identified nor necessarily keen to engage. One approach is gradually to reduce the reluctance of prospective partners by breaking down the institutional or demographic barriers that separate them – essentially pushing the prospective relationship into zone 2. The example of BBC Backstage (described in Chapter 5) offers a good illustration of this approach.

So far, we have considered the “finding” and “forming” aspects of novel networks – the third question posed is how to make them effectively perform. Challenges in this connection include keeping the network up‐to‐date and engaged, building trust and reciprocity, positioning within the network, and decoupling from existing networks.

7.7 Managing Innovation Networks

Throughout the book, we have seen the growing importance of viewing innovation as something which needs to be managed at a system level and which is increasingly inter‐organizational in nature. The rise of networking, the emergence of small firm clusters, the growing use of “open innovation” principles, and the globalization of knowledge production and application are all indicators of the move to what Rothwell called a fifth‐generation innovation model. This has a number of implications for the ways in which we deal with the practical organization and management of the process [9].

The basic model that we have been using throughout the chapter is still relevant, but the ways in which the different phases are enabled now need to be build on an increasing network orientation. For example, networking provides a powerful mechanism for extending and covering a richer selection environment and can bring into play a degree of collective efficiency in picking up relevant signals. Strategies like “Connect and develop” are predicated on the potential offered by increasing the range of connections available to an enterprise.

Configuring Innovation Networks

Whatever the purpose in setting it up, actually operating an innovation network is not easy – it needs a new set of management skills. A network can influence the actions of its members in two ways: Through the flow and sharing of information within the network and through differences in the position of actors in the network, which causes power and control imbalances. Therefore, the position an organization occupies in a network is a matter of great strategic importance and reflects its power and influence in that network. Sources of power include technology, expertise, trust, economic strength, and legitimacy. Networks can be tight or loose, depending on the quantity (number), quality (intensity), and type (closeness to core activities) of the interactions or links. Such links are more than individual transactions and require significant investment in resources over time.

Much depends on being clear about the type of network and the purposes it is set up to achieve. For example, there is a big difference between the demands for an innovation network working at the frontier where issues of intellectual property management and risk are critical, and the one where there is an established innovation agenda as might be the case in using supply chains to enhance product and process innovation. We can map some of these different types of innovation network on to a simple diagram (Figure 7.4), which positions them in terms of:

• how radical the innovation target is with respect to current innovative activity.
• the similarity of the participating companies.

Different types of networks have different issues to resolve. For example, in zone 1, we have firms with a broadly similar orientation working on tactical innovation issues. Typically, this might be a cluster or sector forum concerned with adopting and configuring “good practice” manufacturing. Issues here would involve enabling them to share experiences, disclose information, develop trust and transparency, and build a system level sense of shared purpose around innovation.

Zone 2 activities might involve players from a sector working to explore and create new product or process concepts – for example, the emerging biotechnology/pharmaceutical networking around frontier developments and the need to look for interesting connections and synthesis between these adjacent sectors. Here, the concern is exploratory and challenges existing boundaries but will rely on a degree of information sharing and shared risk‐taking, often in the form of formal joint ventures and strategic alliances.

In zones 3 and 4, the players are highly differentiated and bring different key pieces of knowledge to the party. Their risks in disclosing can be high so ensuring careful IP management and establishing ground rules will be crucial. At the same time, this kind of innovation is likely to involve considerable risk and so putting in place risk and benefit sharing arrangements will also be critical. For example, in a review of “high value innovation networks” in the United Kingdom, researchers from the Advanced Institute of Management Research (AIM) [40] found the following characteristics were important success factors:

• Highly diverse: network partners from a wide range of disciplines and backgrounds who encourage exchanges about ideas across systems.
• Third‐party gatekeepers: science partners such as universities but also consultants and trade associations, who provide access to expertise and act as neutral knowledge brokers across the network.
• Financial leverage: access to investors via business angels, venture capitalists firms, and corporate venturing, which spreads the risk of innovation and provides market intelligence.
• Proactively managed: participants regard the network as a valuable asset and actively manage it to reap the innovation benefits.

Summary

In this chapter, we have looked at the particular challenges in setting up and running networks designed to enable innovation. We have reviewed the different – and often confusing – discussion of different types and models of networks and focused on what can be termed “engineered” networks, established and operated specifically to enable innovation. The chapter has looked at networks at the early stages of developing an entrepreneurial idea, at networks within organizations and at the increasingly important theme of external networks, which enable and facilitate the move to more open models of innovation. We also look at the particular case of finding, forming, and getting new networks with strange partners to perform to support innovation. Finally, we look at the question of how networks are set up, operated, and sustained.

Further Reading

Aalbers and Dolfsma (2015) offer a helpful review of the field in their book Innovation networks: Managing the networked organization (Routledge) while Keeley and colleagues (2013) discuss this as one of their Ten types of innovation (Wiley). The work of Andrew Hargadon has highlighted the importance of brokers going back to the days of Edison and Ford. (Hargadon, A. (2003). How breakthroughs happen. Boston, Harvard Business School Press.). One of the strong examples of this approach today is IDEO the design consultancy, which Kelley has described in detail (Kelley, T., J. Littman, et al., The art of innovation: Lessons in creativity from Ideo, America's leading design firm. 2001, New York, Currency.). Conway and Steward ((1998) Mapping innovation networks. International Journal of Innovation Management2(2): 165–196.) look at the concept of innovation networks and this theme is also picked up by Swan, N. et al., Knowledge management and innovation: networks and networking. Journal of Knowledge Management, 1999. 3(4): 262.). Learning networks are discussed in Bessant et al. “Constructing learning advantage through networks,” Journal of Economic Geography, September, 2012 and their use in sectors, supply chains and regional clusters in Morris, B. et al., Using learning networks to enable industrial development: Case studies from South Africa. International Journal of Operations and Production Management, 2006. 26(5): 557–568. Innovation networks of various forms feature in several reports from AIM – the Advanced Institute for Management Research (www.aimresearch.org).

Internal knowledge networks are a topic of increasing interest and Tom Allen has produced a fascinating update to his pioneering work together with Gunter Henn, the famous German architect (“The organization and architecture of innovation,” Elsevier, 2007, Oxford). Jonah Lehrer also provides a readable review of much new work around knowledge flows and structures in creative organizations (“Imagine: How creativity works,” Canongate, Edinburgh, 2012). Much of the “open innovation” literature deals with the challenges of establishing and working with rich external networks and useful sources include Henry Chesbrough, Wim Vanhaverbeke, and Joel West, eds., Open Innovation: Researching a New Paradigm. Oxford: Oxford University Press, 2006, Oliver G., “Opening up the innovation process: toward an agenda,” R&D Management, 2006. 36, 3 and Perkmann, M. and Walsh, K, “University–industry relationships and open innovation: Towards a research agenda,” International Journal of Management Reviews, 2007. 9, 4. Paul Sloane's 2011, “A guide to open innovation and crowdsourcing,” Kogan Page, London offers a good review of the moving frontier towards engaging wide participation and this theme is also picked up in “Open collective innovation” and “Open healthcare innovation,” reports available from AIM.

Case Studies

You can find a number of additional downloadable case studies at the companion website, including these topics:

• learning networks in action
• Liberty Global and Lufthansa Systems mobilizing internal networks for innovation
• Procter and Gamble and their “Connect and develop” approach and of 3M and their work with “lead user” networks
• Supply chain learning
• Local Motors, Threadless, and Lego that highlight the use of external communities for innovation

You can also find a wide range of tools to help work with concepts introduced during this chapter, again at the companion website.

References

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3. 3. Langrish, J., et al., Wealth from knowledge. 1972, London: Macmillan.
4. 4. Rothwell, R., The characteristics of successful innovators and technically progressive firms. R&D Management, 1977. 7(3): 191–206.
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