Where do innovations come from? There’s a good chance that asking that question will conjure images like that of Archimedes, jumping up from his bath and running down the street, too enthused by the desire to tell the world that he forgot to get dressed. Or Newton, dozing under the apple tree until a falling apple helped kick his brain into thinking about the science of gravity. Or James Watt, also asleep, until woken by the noise of a boiling kettle. Such “Eureka” moments are certainly a part of innovation folklore – and they underline the importance of flashes of insight that make new connections. They form the basis of the cartoon model of innovation that usually involves thinking bubbles and flashing light bulbs. And from time to time, they do happen – for example, Percy Shaw’s observation of the reflection in a cat’s eye at night led to the development of one of the most widely used road safety innovations in the world. Or George de Mestral, who noticed the way plant burrs became attached to his dog’s fur while returning home from a walk in the Swiss Alps. This provided him with the inspiration behind Velcro fasteners.

But of course there is much more to it than that – as we saw in Chapter 2. Innovation is a process of taking ideas forward, revising and refining them, weaving the different strands of “knowledge spaghetti” together toward a useful product, process, or service. Triggering that process is not just about occasional flashes of inspiration – innovation comes from many other directions, and if we are to manage it effectively, we need to remind ourselves of this diversity. This chapter explores some of the many sources of innovation.

5.1 Where Do Innovations Come From?

A quick review of the contents of anyone’s house will throw up a wide range of innovations – and the chances are that these will have been the result of many different kinds of trigger. Figure 5.1 indicates a wide range of stimuli that could be relevant to kick-starting the innovation journey, and we will explore some of the important sources in this chapter.

It’s important to remember that a wide variety of sources means that we will need similarly diverse approaches to search for key innovation signals – something which is also discussed in this chapter.

5.2 Knowledge Push

Around the world, approximately $1500 billion is spent every year on research and development (R&D). All the activity in laboratories and science facilities in the public and private sector isn’t for the sheer fun of discovery. It’s driven by a clear understanding of the importance of R&D as a source of innovation. Although there have always been solo researchers, from a very early stage, the process of exploring and codifying at the frontiers of knowledge has been a systematic activity involving a wide network of people sharing their ideas. In the twentieth century, the rise of the large corporate research laboratory was a key instrument of progress; Bell Labs, ICI, Bayer, BASF, Philips, Ford, Western Electric, and Du Pont (all founded in the early 1900s) are good examples of such “idea powerhouses.” Their output wasn’t simply around product innovation – many of the key technologies underpinning process innovations, especially around the growing field of automation and information/communications technology, also came from such organized R&D effort.

Now we are in a new era in which R&D is becoming more open and distributed and the large central laboratory is giving way to networks of collaborating groups inside and between firms. This involves some big changes; for example, the giant Philips research complex at Eindhoven in the Netherlands, established a hundred years ago, has moved away from white-coated armies of company researchers in a corporate laboratory to operating as a science campus on the site involving many different research groups. Some work directly for Philips, others are independent small firms, and others are joint ventures. But the underlying idea is still the same; generate ideas and they will provide the basis for a steady stream of innovations.

This model of “knowledge push” has a strong track record. In the twentienth century, the rise of the modern large corporation brought with it the emergence of the research laboratory as a key instrument of progress. Bell Labs, ICI, Bayer, BASF, Philips, Ford, Western Electric, and Du Pont – all were founded in the early 1900s as powerhouses of ideas [1]. They produced a steady stream of innovations that fed rapidly growing markets for automobiles, consumer electrical products, synthetic materials, industrial chemicals – and the vast industrial complexes needed to fight two major wars. Their output wasn’t simply around product innovation – many of the key technologies underpinning process innovations, especially around the growing field of automation and information/communications technology, also came from such organized R&D effort. Table 5.1 gives a few examples of knowledge-push innovations, each of which has been the source of a wave of subsequent innovative activity.

Organized R&D of this kind involved a systematic commitment of specialist staff, equipments, facilities, and resources targeted at key technological problems or challenges. The aim was to explore, but much of that exploration was elaborating and stretching trajectories, which were established as a result of occasional breakthroughs. So the leap in technology, which the invention of synthetic materials like nylon or polyethylene represented, was followed by innumerable small scale developments around and along that path. The rise of “big Pharma” – the huge global pharmaceutical industry – was essentially about big R&D expenditure but much of it is spent on development and elaboration punctuated by the occasional breakthrough into “blockbuster” drug territory.¹ While there are spectacular success stories (the top 20 drugs in the United States in 2011 had earned nearly $320 billion), the real value from such R&D investment comes in the systematic improvement across a broad frontier of products and the processes that created them.

It’s a story of occasional breakthrough punctuated by long periods of incremental innovation, consolidating around that idea. We can see it play out in the semiconductor and computer industries that have become linked to a long-term trajectory, which followed from the early “breakthrough” years of the industry. Moore’s Law (named after Gordon Moore, one of the founders of Intel) essentially sets up a trajectory that shapes and guides innovation based on the idea that the size will shrink and the power will increase by a factor of 2 every two years.² This affects memory, processor speed, display drivers, and various other components which in turn drives the rate of innovation in computers, digital cameras, mobile phones, and thousands of other applications.

As given in Chapter 1, the chemical industry moved from making soda ash (an essential ingredient in making soap, glass, and a host of other products) from the earliest days where it was produced by burning vegetable matter through to a sophisticated chemical reaction that was carried out on a batch process (the Leblanc process), which was one of the drivers of the Industrial Revolution. This process dominated for nearly a century but was in turn replaced by a new generation of continuous processes that used electrolytic techniques and which originated in Belgium where they were developed by the Solvay brothers. Moving to the Leblanc process or the Solvay process did not happen overnight; it took decades of work to refine and improve the process and to fully understand the chemistry and engineering required to get consistent high-quality output.

Another good illustration is the camera. Originally invented in the late nineteenth century, the dominant design gradually emerged with an architecture which we would recognize – shutter and lens arrangement, focusing principles, back plate for film or plates, and so on. But this design was then modified still further – for example, with different lenses, motorized drives, flash technology – and, in the case of George Eastman’s work, to creating a simple and relatively “idiot-proof” model camera (the Box Brownie), which opened up photography to a mass market. This pattern stabilized for an extended period in the twentieth century; however, by the 1980s, we saw another surge in the research around new imaging technologies and the product changed dramatically with the growth of digital cameras and then a host of other imaging devices such as phones and tablets. Although the core players in the industry have shifted positions, the underlying process of innovation driven by scientific research remains the same, and there are still plenty of patents being registered around this. (The recent legal battles between Apple and Samsung are one illustration of the strategic importance of such knowledge in playing out the innovation game.)

This idea of occasional breakthroughs followed by extended periods of exploring and elaboration along those paths has been studied and mapped by a number of writers [2,3]. It’s a common pattern and one that helps us deal with the key management question of how and where to direct our search activity for innovation – a theme we will return to in Chapter 6. It forms the basis of much R&D strategy in big corporations – and also opens up space for individual inventors to spot new niches and different directions.

Knowledge push has long been a source of innovative start-ups where entrepreneurs have used ideas based on their own research (or that of others) to create new ventures. This model underpins the success of many high-tech regions – for example, Silicon Valley and Route 128 in the United States, “medical valley” around the city of Nuremburg in Germany, or the Cambridge area in the United Kingdom, where giant technology businesses such as ARM (whose chips are at the heart of most mobile phones) were founded as spin outs from the university. (We discuss this in more detail in Chapter 12.)

5.3 Need Pull

Knowledge creation is a field of possibilities for innovation. But – as we saw in Chapter 2 – simply having a bright idea is no guarantee of adoption. The American writer Ralph Waldo Emerson is supposed to have said “build a better mousetrap and the world will beat a path to your door,” – but the reality is that there are plenty of bankrupt mousetrap salesmen around!³ Knowledge push creates a field of possibilities – but not every idea finds successful application and one of the key lessons is that innovation requires some form of demand if it is to take root. Bright ideas are not, in themselves, enough – they may not meet a real or perceived need and people may not feel motivated to change.

We need to recognize that another key driver of innovation is needed – the complementary pull to the knowledge push. In its simplest form, it is captured in the saying that “necessity is the Mother of invention” – innovation is often the response to a real or perceived need for change. Basic needs – for shelter, food, clothing, security – led early innovation as societies evolved, and we are now at a stage where the need pull operates on more sophisticated higher level needs but via the same process. In innovation management, the emphasis moves to ensuring we develop a clear understanding of needs and finding ways to meet those needs. For example, Henry Ford was able to turn the luxury plaything that was the early automobile into something which became “a car for Everyman,” while Procter and Gamble began a business meeting needs for domestic lighting (via candles) and moved across into an ever-widening range of household needs from soap to nappies to cleaners, toothpaste, and beyond. Their “Pampers” brand of nappies illustrates this process well; its origins in the 1950s lay in the experience of one of their researchers, Vic Mills, who was babysitting his newborn grandson and became frustrated at the amount of time and trouble involved in washing cloth nappies. They began a development program and the product eventually came to market in 1961; it is still a major contributor to the business, with around $10 billion in global sales in 2015 and 41% of the world market share.

View 5.1 gives another example drawn from the world of domestic tableware.

Just as the knowledge-push model involves a mixture of occasional breakthroughs followed by extensive elaboration on the basic theme, searching around the core trajectory, so the same is true of need. “Occasionally, it involves a ‘new to the world’ idea that offers a new way of meeting a need” – but mostly it is elaboration and differentiation. Various attempts have been made to classify product innovations in terms of their degree of novelty and, while the numbers and percentages vary slightly, the underlying picture is clear – there are very few “new to the world” products and very many extensions, variations, and adaptations around those core ideas [4,5]. Figure 5.2 indicates a typical breakdown – and we could construct a similar picture for process innovations.

Understanding buyer/adopter behavior has become a key theme in marketing studies since it provides us with frameworks and tools for identifying and understanding user needs [7]. (We return to this theme in Chapter 10.) Advertising and branding play a key role in this process – essentially using psychology to tune into – or even stimulate and create – basic human needs [4]. Much recent research has focused on detailed ethnographic studies of what people actually do and how they actually use products and services – using the same approaches which anthropologists use to study strange new tribes to uncover hidden and latent needs [8,9].

Case Study 5.1 gives an example of Hyundai’s efforts to understand its customers, showing how a major corporation builds in such techniques to develop a rich understanding of latent and potential user needs.

Need-pull innovation is particularly important at mature stages in industry or product life cycles when there is more than one offering to choose from – competing depends on differentiating on the basis of needs and attributes and/or segmenting the offering to suit different adopter types. There are differences between business to business markets (where emphasis is on needs among a shared group, e.g., along a supply chain) and consumer markets where the underlying need may be much more basic – food, shelter, and mobility – and appeal to a much greater number of people. Importantly, there is also a “bandwagon” effect – as more people adopt so that the innovation becomes modified to take on board their needs – and the process accelerates [10].

It is also a key source of opportunity for entrepreneurial start-ups. Identifying a need that no one has worked on before or finding novel ways to meet an existing need lie behind many new business ideas. For example, Jeff Bezos picked up on the needs (and frustrations) around conventional retail and has built the Amazon empire on the back of using new technologies to meet these in a different way. Air BnB (“I need to find somewhere to stay”), NextBike, Zipcar (“I need easy short-term access to transport”), and WhatsApp (“I need to communicate with my friends”) are other well-known examples.

A good source of opportunity for entrepreneurs is to look at the underlying need which people have for goods and services – and then to ask if there are different ways of expressing or meeting this need. For example, the huge industry around selling drills and screws and other devices to the domestic market is not about a desire for owning power tools but reflects a more basic need – how can I put a picture or photograph on the wall? Maybe there are other ways of meeting this need and new business opportunities behind that?

It’s also important to recognize that innovation is not always about commercial markets or consumer needs; social innovation is also important. Whether it’s providing health care or clean water in developing countries or more effective education or social services in established industrial economies, the need for change is clear and provides an engine for increasing innovation. Some examples of major social innovations that grew out of meeting needs are the kindergarten (providing childcare when both parents are working), the National Childbirth Trust (providing education and information to new parents about all aspects of childbirth), the Open University (providing access to higher education to those for students once excluded by the barriers of wealth and work), and the Big Issue (providing employment and identity to homeless people).

5.4 Making Processes Better

Of course needs aren’t just about external markets for products and services – we can see the same phenomenon of need pull working inside organizations, as a driver of process innovation. “Squeaking wheels” and other sources of frustration provide rich signals for change – and this kind of innovation is often something that can engage a high proportion of the workforce who experiences these needs first hand. The successful model of “kaizen,” which underpins the success of firms such as Toyota, is fundamentally about sustained, high involvement incremental process innovation along these lines [11], and we can see its application in the “total quality management” movement in the 1980s, the “business process re-engineering” ideas of the 1990s and the current widespread application of concepts based on the idea of “lean thinking” [12–14]. Case Study 5.2 provides an example.

This kind of process improvement is of particular relevance in the public sector, where the issue is not about creating wealth but of providing value for money in service delivery. Many applications of “lean” and similar concepts can be found that apply this principle – for example, in reducing waiting times or improving patient safety in hospitals, in speeding up delivery of services such as car taxation and passport issuing, and even in improving the collection of taxes!

Once again, we can see the pattern – most of the time such innovation is about “doing what we do better,” but occasionally it involves a major leap. The example of glassmaking (Case Study 5.3) provides a good illustration – for decades, the need to produce smooth flat glass for windows had been met by a steady stream of innovations around the basic trajectory of grinding and polishing. There is plenty of scope for innovation in machinery, equipment, working practices, and so on – but such innovation tends to meet with diminishing returns as some of the fundamental bottlenecks emerge – the limits of how much you can improve an existing process. Eventually, the stage is set for a breakthrough – like the emergence of float glass – which then creates new space within which incremental innovation along a new trajectory can take place.

It’s also important to recognize that innovation is not always about commercial markets or consumer needs. There is also a strong tradition of social need providing the pull for new products, processes, and services. A recent example has been the development of innovations around the concept of “micro-finance” – see Case Study 5.4.

5.5 Crisis-driven Innovation

Sometimes, the increase in the urgency of a need or the extent of demand can have a forcing effect on innovation – the example of wartime and other crises supports this view. For example, the demand for iron and iron products increased hugely in the Industrial revolution and exposed the limitations of the old methods of smelting with charcoal – it created the pull that led to developments like the Bessemer converter. In a similar fashion, the emerging energy crisis with oil prices reaching unprecedented levels has created a significant pull for innovation around alternative energy sources – and an investment boom for such work. The origins of “lean thinking” – an approach that has revolutionized manufacturing and large parts of public and private sector services – lie in the experience of Japanese manufacturers like Toyota in the immediate postwar period. Faced with serious shortages of raw materials, energy, and skilled labor, it was impossible to apply the resource-intensive methods associated with mass production and instead they were forced to experiment and develop an alternative approach – which became known as “lean” because it implied a minimum waste philosophy [13]. Case Study 5.5 gives some other examples of crisis-driven innovation.

5.6 Whose Needs? The Challenge of Underserved Markets

When considering need pull as a source of innovation, we should remember that one size doesn’t fit all. Differences among potential users can also provide rich triggers for innovation in new directions. Disruptive innovation – a theme to which we will return later – is often associated with entrepreneurs working at the fringes of a mainstream market and finding groups whose needs are not being met. It poses a problem for existing incumbents because the needs of such fringe groups are not seen as relevant to their “mainstream” activities – and so they tend to ignore them or to dismiss them as not being important. But working with these users and their different needs creates different innovation options – and sometimes what has relevance for the fringe begins to be of interest to the mainstream. Clayton Christensen in his many studies of such “disruptive innovation” shows this has been the pattern across industries as diverse as computer disk drives, earth moving equipment, steel making, and low cost air travel [15].

For much of the time, there is stability around markets where innovation of the “do better” variety takes place and is well managed. Close relationships with existing customers are fostered and the system is configured to deliver a steady stream of what the market wants – and often a great deal more! (What he terms “technology overshoot” is often a characteristic of this, where markets are offered more and more features which they may not ever use or place much value on but which comes as part of the package).

But somewhere else there is another group of potential users who have very different needs – usually for something much simpler and cheaper – which will help them get something done. For example, the emergent home computer industry began among a small group of hobbyists who wanted simple computing capabilities at a much lower price than that was available from the mini-computer suppliers. In turn, the builders of those early PCs wanted disk drives, which were much simpler technologically but – importantly – much cheaper and so were not really interested in what the existing disk drive industry had to offer. It was too high tech, massively overengineered for their needs and, most importantly, much too expensive.

Although they approached the existing drive makers, none of them was interested in making such a device – not surprisingly since they were doing very comfortably supplying expensive high-performance equipment to an established mini-computer industry. Why should they worry about a fringe group of hobbyists as a market? Steve Jobs described in an interview their attempts to engage interest, “…So we went to Atari and said, ‘Hey, we’ve got this amazing thing, even built with some of your parts, and what do you think about funding us? Or we’ll give it to you. We just want to do it. Pay our salary, we’ll come work for you.’ And they said, ‘No.’ So then we went to Hewlett-Packard, and they said, ‘Hey, we don’t need you. You haven’t got through college yet.’”

Consequently, the early PC makers had to look elsewhere – and found entrepreneurs willing to take the risks and experiment with trying to come up with a product which did meet their needs. It didn’t happen overnight, and there were plenty of failures on the way – and certainly, the early drives were very poor performers in comparison with what was on offer in the mainstream industry. But gradually the PC market grew, moving from hobbyists to widespread home use and from there – helped by the emergence and standardization of the IBM PC – to the office and business environment. And as it grew and matured so it learned and the performance of the machines became much more impressive and reliable – but coming from a much lower cost base than mini-computers. The same thing happened to the disk drives within them – the small entrepreneurial firms who began in the game grew and learned and became large suppliers of reliable products which did the job – but at a massively lower price.

Eventually, the fringe market that the original disk drive makers had ignored because it didn’t seem relevant or important enough to worry about grew to dominate – and by the time they realized this it was too late for many of them. The best they could hope for would be to be late entrant imitators, coming from behind and hoping to catch up.

This pattern is essentially one of disruption – the rules of the game changed dramatically in the marketplace with some new winners and losers. Figure 5.3 shows the transition where the new market and suppliers gradually take over from the existing players. It can be seen in many industries – for example, think about the low-cost airlines. Here the original low cost players didn’t go head to head with the national flag carriers who offered the best routes, high levels of service, and prime airport slots – all for a high price. Instead, they sought new markets at the fringe – users who would accept a much lower level of service (no food, no seat allocation, no lounges, no frills at all) but for a basic safe flight would pay a much lower price. As these new users began to use the service and talk about it, so the industry grew and came to the attention of existing private and business travellers who were interested in lower cost flights at least for short haul because it met their needs for a “good enough” solution to their travel problem. Eventually, the challenge hit the major airlines who found it difficult to respond because of their inherently much higher cost structure – even those – such as BA and KLM, which setup low-cost subsidiaries that found they unable to manage with the very different business model low cost flying involved.

Low-end market disruption of this kind is a potent threat – think what a producer in China might do to an industry like pump manufacturing if they began to offer a simple, low-cost “good enough” household pump for $10 instead of the high-tech, high-performance variants available from today’s industry at prices 10–50 times as high? Or how manufacturers of medical devices like asthma inhalers will need to respond once they have come off-patent – a challenge already being posed in markets such as generic pharmaceuticals? This kind of “reverse innovation” is beginning to happen – for example, GE began making a simple ultrasound scanner for use in their Indian markets where the need was for something low cost, robust, and portable so it could be taken out by midwives in visiting remote villages. But the basic package was also of considerable interest in many other markets, and the product has become a best seller – in the process changing the company’s orientation toward product design [16]. Case Study 5.6 gives some examples of frugal innovation.

So how might an organization begin to think about frugal innovation? There are some core principles that help make up the mind-set:

• Simplify – not dumbing down but distilling the key necessary functions
• Focus on value – avoid overshoot, avoid waste
• Don’t reinvent the wheel – adopt, adapt, re-use, recombine ideas from elsewhere
• Think horizontally – open up the innovation process, engage more minds on the job
• Platform thinking – build a simple frugal core and then add modules
• Continuous improvement – evolve and learn, best is the enemy of better

It is also important to recognize that similar challenges to existing market structures can happen through “high end” disruption – as Utterback points out [17]. Where a group of users require something at a higher level than the current performance, this can create new products or services, which then migrate to mainstream expectations – for example, in the domestic broadband or mobile telephone markets.

Disruptive innovation examples of this kind focus attention on the need to look for needs, which are not being met, or poorly met or sometimes where there is an overshoot [18]. Each of these can provide a trigger for innovation – and often involve disruption because existing players don’t see the different patterns of needs. This thinking is behind, for example, the concept of “Blue Ocean strategy” [19] that argues for firms to define and explore uncontested market space by spotting latent needs, which are not well-served. Case Study 5.7 gives some examples of Blue Ocean strategy.

Overserved markets might include those for office software or computer operating systems where the continuing trend toward adding more and more features and functionality has possibly outstripped users’ needs for or ability to use them all. Linux-based open office applications such as “LibreOffice” or “Apache Office”represent simpler, “good enough” solutions to the basic needs of users – and are potential disruptive innovations for player like Microsoft.

Central to this idea is the role of entrepreneurs – by definition established players find it difficult to look at and work with the fringe since it is not their core business or main focus of attention. But entrepreneurs are looking for new opportunities to create value and working at the fringe may provide them with such inspiration. So the pattern of disruptive innovation is essentially one where entrepreneurs play a role in changing and reshaping business and social markets through often radical innovation. Smart organizations look to defend themselves against disruption to their world by setting up small entrepreneurial units with the licence to explore and behave exactly as free agents, challenging conventional approaches and looking at the edges of what the business does.

5.7 Emerging Markets

One powerful source of ideas at the edge comes from what are often termed “emerging markets” – countries such as India, China, and those in the Latin American and African regions. These are huge markets in terms of population and often very young in age profile, and while there may be limited disposable income they represent significant opportunities. The writer C.K. Prahalad first drew attention to this idea in his book “The fortune at the bottom of the pyramid” arguing that nearly 80% of the world’s population lived on less than $2/day but could represent a huge market of unserved needs for goods and services. Since its publication in 2005, there has been an explosion of interest in exploring the innovation opportunities in meeting the needs of this significant population involving billions of people. Table 5.2 gives some examples of this challenge.

Developing solutions which meet these needs requires considerable innovation and reconfiguration but there is a huge potential market. As the Chief Technology Officer of Procter and Gamble commented in a Business Week interview, “… We’ve put more emphasis on serving an even broader base of consumers. We have the goal of serving the majority of the world’s consumers someday. Today, we probably serve about 2 billion-plus consumers around the globe, but there are 6 billion consumers out there. That has led us to put increased emphasis on low-end markets and in mid- and low-level pricing tiers in developed geographies. That has caused us to put a lot more attention on the cost aspects of our products…”

Prahalad’s original book contains a wide range of case examples where this is beginning to happen in fields as diverse as health care, agriculture, and consumer white goods and home improvements [20]. Subsequently, there has been significant expansion of innovative activity in these emerging market areas – driven in part by a realization that the major growth in global markets will come from regions with a high BoP profile.

Significantly the different conditions in BoP markets force a new look and enable the emergence of very different innovation trajectories. Case Study 5.8 gives an example of a revolutionary approach to eye care and this is described in more detail on the website. Such approaches radically improved productivity while maintaining the key levels of quality; in the process they open up the possibilities of low-cost health care for a much wider set of people. Such models have been applied to a variety of health areas, including elective surgery for hip and knee replacement, maternity care, kidney transplants, and even heart bypass surgery where Indian hospitals are now able to offer better quality care at a fraction of the cost of major hospitals in Europe or the USA!

The idea of “reverse innovation” where innovations migrate back from these emerging markets is of growing interest – for example, General Electric developed a simple low-cost version of its ultrasound scanner for use in the emerging market context of rural India. Designed to be easy to use and rugged enough for traveling midwives to carry round on their bicycles from village to village, the unit was not only very successful in those markets but attracted considerable attention elsewhere in the world. While maternity care in major economies is currently delivered in highly specialized hospitals and clinics using sophisticated machinery there is a clear demand for something simpler and GE have found this to be a surprising growth market. In 2009, they announced their intention to spend at least $3 billion to develop 100 low-cost health-care innovations, targeted at emerging economies but with potential for such reverse innovation [21].

Importantly it isn’t just the case that fringe markets trigger simpler and cheaper innovations. Sometimes the novel conditions spawn completely new trajectories. For example, the emergence of “mobile money” was in Africa where the security risks of carrying cash meant that people began to use the mobile phone system to provide an alternative way of moving money around. Systems like M-PESA have now grown in sophistication and widespread application in emerging markets such as Africa and Latin America – but are also offering a template for existing markets back in the industrialized world.

5.8 Toward Mass Customization

Arguably Henry Ford’s plant, based on principles of mass production, represented the most efficient response to the market environment of its time. But that environment changed rapidly during the 1920s, so that what had begun as a winning formula for manufacturing began gradually to represent a major obstacle to change. Production of the Model T began in 1909 and for 15 years or so it was the market leader. Despite falling margins, the company managed to exploit its blueprint for factory technology and organization to ensure continuing profits. But growing competition (particularly from General Motors with its strategy of product differentiation) was shifting away from trying to offer the customer low cost personal transportation and toward other design features – such as the closed body – and Ford was increasingly forced to add features to the Model T. Eventually, it was clear that a new model was needed and production of the Model T stopped in 1927.

The trouble is that markets are not made up of people wanting the same thing – and there is an underlying challenge to meet their demands for variety and increasing customization. This represents a powerful driver for innovation – as we move from conditions where products are in short supply to one of mass production so the demand for differentiation increases. There has always been a market for personalized custom made goods – and similarly custom configured services – for example, personal shoppers, personal travel agents, personal physicians, and so on. But until recently, there was an acceptance that this customization carried a high price tag and that mass markets could only be served with relatively standard product and service offerings [22].

However a combination of enabling technologies and rising expectations has begun to shift this balance and resolve the trade-off between price and customization. “Mass customization” (MC) is a widely used term that captures some elements of this [23]. MC is the ability to offer highly configured bundles of nonprice factors configured to suit different market segments (with the ideal target of total customization – that is, a market size of 1) – but to do this without incurring cost penalties and the setting up of a trade-off of agility vs. prices.

Of course there are different levels of customizing – from simply putting a label “specially made for (insert your name here)” on a standard product right through to sitting down with a designer and cocreating something truly unique. Table 5.3 gives some examples of this range of options.

Until recently, the vision of mass customization outran the capabilities of manufacturing and design technologies to deliver it. But increasing convergence around this area and falling costs have meant that the frontier has now been reached. With simple user-friendly computer design tools and new manufacturing technologies such as 3-D printing, it now becomes possible to design and make almost anything and to do so at an increasing economic cost. While it might once have seemed a science fiction fantasy, it is now possible to design and print clothing, shoes, jewellery, furniture, toys, spare parts – essentially any three-dimensional shape. An increasing number of online service businesses are appearing, offering to translate individual ideas into physical products, and hobby users can install 3D printers and computer-aided design linked to their computers for under $5000. Recently, Microsoft released a scanning program for mobile phones that allows the users to take 3D pictures and create design information from them for feeding into 3D printers.

This trend has important implications for services, in part because of the difficulty of sustaining an entry barrier for long. Service innovations are often much easier to imitate, and the competitive advantages that they offer can quickly be competed away because there are fewer barriers to entry or options for protecting intellectual property. The pattern of airline innovation on the transatlantic route provides a good example of this – there is a fast pace of innovation but as soon as one airline introduces something like a flat bed, others will quickly emulate it. Arguably the drive to personalization of the service experience will be strong because it is only through such customized experiences that a degree of customer “lock on” takes place [25]. Certainly, the experience of Internet banking and insurance suggests that, despite attempts to customize the experience via sophisticated web technologies, there is little customer loyalty and a high rate of churn. However, the lower capital cost of creating and delivering services and their relative simplicity makes cocreation more of an option and there is growing interest in such models involving active users in the design of services – for example, in the open source movement around software or in the digital entertainment and communication fields where community and social networking sites such as Facebook, Flickr, and YouTube have had a major impact.

Once again, we should be clear that this is not simply a trend in the commercial market place; social innovation is increasingly about trying to match particular needs of different groups in society with solutions that work for them. Customizing solutions for the delivery of public services to different groups is becoming a major agenda item, particularly as governments and service providers recognize that “one size fits all” is not a model which applies well. In the wider not-for-profit space, these technologies are opening up significant innovation opportunities; for example, an organization called Field Ready is using 3D printing to create urgently needed spare parts and medical devices for applications in disaster situations.

View 5.2 gives an example of Living Labs as a way of engaging with user needs:

5.9 Users as Innovators

Understanding what it is that customers value and need is critical in pursuing a customization strategy and it leads, inevitably to the next source of innovation in which the users themselves become the source of ideas. Although need pull represents a powerful trigger for innovation, it is easy to fall into the trap of thinking about the process as a serial one in which the user needs are identified and then something is created to meet those needs. The assumption underpinning this is that users are passive recipients – but this is often not the case. Indeed history suggests that users are sometimes ahead of the game – their ideas plus their frustrations with existing solutions lead to experiment and prototyping and create early versions of what eventually become mainstream innovations. Eric von Hippel of Massachusetts Institute of Technology has made a lifelong study of this phenomenon and gives the example of the pickup truck – a long-time staple of the world automobile industry. This major category did not begin life on the drawing boards of Detroit but rather on the farms and homesteads of a wide range of users who wanted more than a family saloon. They adapted their cars by removing seats, welding new pieces on, and cutting off the roof – in the process prototyping and developing the early model of the pickup. Only later did Detroit pick up on the idea and then begin the incremental innovation process to refine and mass produce the vehicle [26]. A host of other examples support the view that user-led innovation matters – for example, petroleum refining, medical devices, semiconductor equipment, scientific instruments, and a wide range of sports goods and the Polaroid camera. Case Study 5.9 gives some examples of user-led innovation.

Importantly, active and interested users – “lead users” – are often well ahead of the market in terms of innovation needs. In Mansfield’s detailed studies of diffusion of a range of capital goods into major firms in the bituminous coal, iron and steel, brewing, and railroad industries, he found that in 75% of the cases it took over 20 years for the complete diffusion of these innovations to major firms [31]. As von Hippel points out, some users of these innovations could be found far in advance of the general market [32].

One of the fields where this has played a major role is in medical devices where active users among medical professionals have provided a rich source of innovations for decades. Central to their role in the innovation process is that they are very early on the adoption curve for new ideas – they are concerned with getting solutions to particular needs and prepared to experiment and tolerate failure in their search for a better solution. One strategy – which we will explore later – around managing innovation is thus to identify and engage with such “lead users” to cocreate innovative solutions. Case Study 5.10 gives an example of lead users at work in innovation.

Sometimes user-led innovation involves a community which creates and uses innovative solutions on a continuing basis. Good examples of this include the Linux community around operating systems or the Apache server community around web server development applications, where communities have grown up and where the resulting range of applications is constantly growing – a state which has been called “perpetual beta” referring to the old idea of testing new software modules across a community to get feedback and development ideas [33]. A growing range of Internet-based applications make use of communities – for example, Mozilla and its Firefox and other products, Propellerhead and other music software communities, and the emergent group around Apple’s i-platform devices like the i-Phone [34].

Within some communities, users will freely share innovations with peers, termed “free revealing.” For example, online communities for open source software, music hobbyists, sports equipment, and professional networks. Participation is driven mostly by intrinsic motivations, such as the pleasure of being able to help others or to improve or develop better products, but also by peer recognition and community status. The elements valued are social ties and opportunities to learn new things rather than concrete awards or esteem. Such knowledge sharing and innovation tend to be more collective and collaborative than idea competitions [35].

5.10 Using the Crowd

Not everyone is an active user, but the idea of the crowd as a source of different perspectives is an important one. Sometimes people with very different ideas, perspectives, or expertize can contribute new directions to our sources of ideas – essentially amplifying. Using the wider population has always been an idea, but until recently, it was difficult to organize their contribution simply because of the logistics of information processing and communication. But using the Internet, new horizons open up to extend the reach of involvement as well as the richness of the contribution people can make.

In 2006, journalist Jeff Howe coined the term crowdsourcing in his book The Power of Crowds. Crowdsourcing is where an organization makes an open call to a large network to provide some voluntary input or perform some function. The core requirements are that the call is open, and that the network is sufficiently large, the “crowd”. Crowd sourcing of this kind can be enabled via a number of routes – for example, innovation contests, innovation markets, innovation communities – which we will discuss in detail in Chapter 10. But it is worth commenting here that opening up to the crowd can not only amplify the volume of ideas but also the diversity and evidence is emerging that it is particularly this feature that makes the crowd a useful additional source of innovation.

Research Note 5.1 describes this approach in more detail.

Public sector applications of this idea are growing as citizens act as user-innovators for the services which they consume. “Citizen-sourcing” is increasingly being used; an example is the UK website fixmystreet.com in which citizens are able to report problems and suggest solutions linked to the roads infrastructure. The approach also opens up significant options in the area of social innovation – for example, the crisis response tool “Ushahidi” emerged out of the Kenyan post-election unrest and involves using crowd sourcing to create and update rich maps which can help direct resources and avoid problem areas. It has subsequently been used in the Brisbane floods, the Washington snow emergency and the aftermath of the Tsunami in Japan.

Innovation contests are growing in popularity; a recent McKinsey report cited in the Wall St Journal suggested that more than 30,000 significant prizes are awarded every year worth $2 billion. The total value of the 219 largest prizes on offer has tripled in the past 10 years and most contests are now specifically targeted. And while there is big prize money available some organizations are seeing the value in “crowdsourcing” simpler innovation challenges. For example, the French food supplier Petit Navire offers a prize of €5000 for anyone coming up with new uses for their canned tuna fish. KLM – Royal Dutch Airlines and Schiphol Airport in Amsterdam offer €10,000 for new ideas in baggage handling. And Hershey Chocolate Co. offers a $25,000 prize for ideas to stop chocolate from melting on the way to stores [36].

Increasing interest is being shown in such “crowdsourcing” approaches to cocreating innovations – and to finding new ways of creating and working with such communities. The principle extends beyond software and virtual applications – for example, Lego makes extensive use of communities of developers in its Lego Factory and other online activities linked to its manufactured products [37]. Adidas has taken the model and developed its “mi Adidas” concept where users are encouraged to cocreate their own shoes using a combination of website (where designs can be explored and uploaded) and in-store mini-factories where user created and customized ideas can then be produced. Such models offer considerable promise, but there is a risk; in 2016, the crowdsourcing manufacturer Quriky filed for bankruptcy having failed to create a sustainable business model for the approach [38].

User engagement provides a powerful new resource for the “front end” of innovation. One example is Goldcorp – a struggling mining company that threw open its geological data and asked for ideas about where it should prospect. Tapping into the combined insights of 1200 people from 50 countries helped them find 110 new sites, 80% of which produced gold. The business has grown from $100 million in 1999 to over $9 billion today. Companies like Svarowski have recruited an army of new designers using “crowdsourcing” approaches – and in the process have massively increased their design capacity.

The approach also opens up significant options in the area of social innovation – for example, the crisis response tool “Ushahidi” emerged out of the Kenyan post-election unrest and involves using crowd sourcing to create and update rich maps which can help direct resources and avoid problem areas. It has subsequently been used in the Brisbane floods, the Washington snow emergency, and the aftermath of the Tsunami in Japan.

Case Study 5.11 provides some examples of what might be termed “open collective innovation.”

Another important feature of crowdsourcing across user communities is the potential for dealing with the “long tail” problem – that is, how to meet the needs of a small number of people for a particular innovation. By mobilizing user communities around these needs it is possible to share experience and cocreate innovation; an example is given on the website where communities of patients suffering from rare diseases and their careers are brought together to enable innovation in areas which lie at the edge of the mainstream health system radar screen.

5.11 Extreme Users

An important variant that picks up on both the lead user and the fringe needs concepts lies in the idea of extreme environments as a source of innovation. The argument here is that the users in the toughest environments may have needs which by definition are at the edge – so any innovative solution that meets those needs has possible applications back into the mainstream. An example would be antilock braking systems (ABS) which are now a commonplace feature of cars but which began life as a special add-on for premium high performance cars. The origins of this innovation came from a more extreme case, though – the need to stop aircraft safely under difficult conditions where traditional braking might lead to skidding or other loss of control. ABS was developed for this extreme environment and then migrated across to the (comparatively) easier world of automobiles [33].

Looking for extreme environments or users can be a powerful source of stretch in terms of innovation – meeting challenges, which can then provide new opportunity space. As Roy Rothwell put it in the title of a famous paper, “tough customers mean good designs” [39]. For example, stealth technology arose out of a very specific and extreme need for creating an invisible aeroplane – essentially something which did not have a radar signature. It provided a powerful pull for some radical innovation which challenged fundamental assumptions about aircraft design, materials, power sources, and so on, and opened up a wide frontier for changes in aerospace and related fields [40]. The “bottom of the pyramid” concept mentioned earlier also offers some powerful extreme environments in which very different patterns of innovation are emerging.

For example, in the Philippines, there is little in the way of a formal banking system for the majority of people – and this has led to users creating very different applications for their mobile phones where pay as you go credits become a unit of currency to be transferred between people and used as currency for various goods and services. In Kenya, the MPESA system (described earlier) is used to increase security – if a traveler wishes to move between cities he or she will not take money but instead forward it via mobile phone in the form of credits, which can then be collected from the phone recipient at the other end. This is only one of hundreds of new applications being developed in extreme conditions and by underserved users – and represents a powerful laboratory for new concepts which companies such as Vodafone are working closely to explore [41]. The potential exists to use this kind of extreme environment as a laboratory to test and develop concepts for wider application – for example, Citicorp has been experimenting with a design of ATM based on biometrics for use with the illiterate population in rural India. The pilot involves some 50,000 people, but as a spokesman for the company explained, “we see this as having the potential for global application.”

5.12 Prototyping

We’ve emphasized the importance of understanding user needs as a key source of innovation. But one challenge is that the new idea – whether knowledge push or need pull – may not be perfectly formed. Innovations are made rather than born – and this means we need to think about modifying, adapting, and configuring the original idea. Feedback and learning early on can help shape it to make sure it meets the needs of the widest group and has features which people understand and value. For this reason, a core principle in sourcing innovation is to work with potential users as early as possible and one way of doing this is to create a simple prototype. It serves as a “boundary object,” something everyone can get around and give their ideas and in the process innovation becomes a shared project.

It enables a move from vague notions, hunches, half-formed ideas toward something more workable, providing a series of stepping-stones, bridges, scaffolding – essentially playing with ideas about the problem. It forms the core of the approach taken by companies such as Dyson where “…prototypes allow you to quickly get a feel for things and uncover subtle design flaws …”

Prototyping offers some important features to support sourcing innovative ideas:

• It creates a “boundary object,” something around which other people and perspectives can gather; a device for sharing insights into problem dimensions as well as solutions
• It offers us a stepping stone in our thought processes, making ideas real enough to see and play with them but without the lock-in effect of being tied into trying to make the solutions work – we can still change our minds
• It allows plurality – we don’t have to play with a single idea, we can bet on multiple horses early on in the race rather than trying to pick winners
• It allows for learning – even when a prototype fails we accumulate knowledge which might come in helpful elsewhere
• It suggests further possibilities – as we play with a prototype, it gives us a key to open up the problem, break open the shell, and explore more deeply
• It allows us to work with half-formed ideas and hunches – enables a “conversation with a shadowy idea”
• It allows for emergence – sometimes we can’t predict what will happen when different elements interact. Trying something out helps explore surprising combinations

Prototyping has always been an important part of innovation – even when the solution trajectory is clear there is plenty of room for using test pieces to refine the product and get the bugs out. It is extensively used to improve the product concept – for example, beta testing of software or pilot projects, which are deliberately setup to explore and learn rather than provide the finished product or service. And it has an increasingly important role to play at the fuzzy front end of the innovation process.

It is of particular value to entrepreneurs trying to start new ventures. The “lean start-up” method, for example, argues that the process needs to be one of the fast learning and modifying of the original idea. By putting a “minimum viable product” out into the marketplace, it becomes possible to test and adapt the idea, and it may well be that there is a need to “pivot” around that idea to a new way of delivering it. This prototype doesn’t have to be perfect, but it provides a live experiment to help learn about what things in the new venture need to change [42]. We will return to this theme in Chapter 9.

5.13 Watching Others – and Learning From Them

Another important source of innovation comes from watching others – imitation is not only the sincerest form of flattery but also a viable and successful strategy for sourcing innovation. For example, reverse engineering of products and processes and development of imitations – even around impregnable patents – is a well-known route to find ideas. Much of the rapid progress of Asian economies in the postwar years was based on a strategy of “copy and develop,” taking Western ideas and improving on them [43]. For example, much of the early growth in Korean manufacturing industries in fields like machine tools came from adopting a strategy of “copy and develop” – essentially learning (often as a result of taking licenses or becoming service agents) by working with established products and understanding how they might be adapted or developed for the local market. Subsequently, this learning could be used to develop new generations of products or services [43,44].

A wide range of tools for competitor product and process profiling has been developed, which provide structured ways of learning from what others do or offer [45].

One powerful variation on this theme is the concept of benchmarking [46]. In this process, enterprises make structured comparisons with others to try and identify new ways of carrying out particular processes or to explore new product or service concepts. The learning triggered by benchmarking may arise from comparing between similar organizations (same firm, same sector, etc.), or it may come from looking outside the sector but at similar products or processes. For example, Southwest Airlines became the most successful carrier in the United States by dramatically reducing the turnaround times at airports – an innovation which it learned from studying pit stop techniques in the Formula 1 Grand Prix events. Similarly, the Karolinska hospital in Stockholm made significant improvements to its cost and time performance through studying inventory management techniques in advanced factories [47].

Benchmarking of this kind is increasingly being used to drive change across the public sector, both via “league tables” linked to performance metrics, which aim to encourage fast transfer of good practice between schools or hospitals, and also via secondment, visits and other mechanisms designed to facilitate learning from other sectors managing similar process issues such as logistics and distribution. One of the most successful applications of benchmarking has been in the development of the concept of “lean” thinking, now widely applied to a many public and private sector organizations [48]. The origins were in a detailed benchmarking study of car manufacturing plants during the 1980s, which identified significant performance differences and triggered a search for the underlying process innovations that were driving the differences [49,50].

5.14 Recombinant Innovation

Another easy assumption to make about innovation is that it always has to involve something new to the world. The reality is that there is plenty of scope for crossover – ideas and applications which are commonplace in one world may be perceived as new and exciting in another. This is an important principle in sourcing innovation where transferring or combining old ideas in new contexts – a process called “recombinant innovation” by Andrew Hargadon – can be a powerful resource [51]. The Reebok pump running shoe, for example, was a significant product innovation in the highly competitive world of sports equipment – yet although this represented a breakthrough in that field it drew on core ideas which were widely used in a different world. Design Works – the agency which came up with the design brought together a team which included people with prior experience in fields like paramedic equipment (from which they took the idea of an inflatable splint providing support and minimizing shock to bones) and operating theatre equipment (from which they took the microbladder valve at the heart of the pump mechanisms). Many businesses – as Hargadon points out – are able to offer rich innovation possibilities primarily because they have deliberately recruited teams with diverse industrial and professional backgrounds and thus bring very different perspectives to the problem in hand. His studies of the design company, IDEO, show the potential for such recombinant innovation work [9,52].

Nor is this a new idea. Thomas Edison’s famous “Invention Factory” in New Jersey was founded in 1876 with the grand promise of “a minor invention every ten days and a big thing every six month or so.” They were able to deliver on that promise not because of the lone genius of Edison himself but rather from taking on board the recombinant lesson – Edison hired scientists and engineers (he called them “muckers”) from all the emerging new industries of early twentienth-century USA. In doing so, he brought experience in technologies and applications such as mass production and precision machining (gun industry) telegraphy and telecommunications, food processing and canning, automobile manufacture, and so on. Some of the early innovations that built the reputation of the business – for example, the teleprinter for the NYSE – were really simple cross-over applications of well-known innovations in other sectors [51].

One of the key characteristics of “open innovation” is its emphasis on knowledge flows in and out of organizations and this creates a considerable scope for recombinant innovation. Examples of established knowledge from one sector being applied elsewhere include the use of ground management systems for aircraft handling in the United Kingdom air traffic control system – this uses software originally developed in Formula 1 motor racing by the Maclaren racing team. Case Study 5.12 gives some examples of recombinant innovation.

Recombinant innovation is also possible within large organizations where opportunities to use knowledge created in one area and applied in another can be exploited. For example, Dupont scientists were working in the 1960s on fibers, which were similar to nylon but had much greater strength – an idea which had potential for the tire cords used in one of their core business areas. In 1965, Stephanie Kwolek developed a process for making aramide fibers which the company called “Kevlar” – it had the property of being five times stronger than its equivalent weight in steel. However, the tire makers were initially slow to adopt and so the technology was offered to other divisions, finding new markets in bullet-proof vests, helmets, ropes, boats – and eventually the tire market itself.

In many ways, recombinant innovation involves a core principle understood by researchers on human creativity. Very often original – breakthrough – ideas come about through a process of what Arthur Koestler called “bisociation” – the bringing together of apparently unrelated things, which can somehow be connected and yield an interesting insight [53]. The key message here for managing innovation is to look to diversity to provide the raw material, which might be combined in interesting ways – and realising this makes the search for unlikely bedfellows a useful strategy.

5.15 Design-led Innovation

“Market? What market! We do not look at market needs. We make proposals to people.”

– Ernesto Gismondi, Chairman of Artemide, quoted in Verganti

One increasingly significant source of innovation is what Roberto Verganti calls “design-driven innovation.” Examples include many of the recent successful Apple products, where the user experience is one of surprise and pleasure at the look and feel, the intuitive beauty of the product. This emerges not as a result of analysis of user needs but rather through a design process which seeks to give meaning shape and form to products – features and characteristics which they didn’t know they wanted. But it is also not another version of knowledge or technology push in which powerful new functions are installed – in many ways design-led products are deceptively simple in their usability. Apple’s i-pod was a comparative latecomer to the mp3 player market yet it created the standard for the others to follow because of the uniqueness of the look and feel – the design attributes. Its subsequent success with I pad and I phone owes a great deal to the design ideas of Jonathan Ive, which bring a philosophy to the whole product range and provide one of the key competitiveness factors to the company.

As Verganti points out, people do not buy things only to meet their needs – there are important psychological and cultural factors at work as well [54]. He suggests that we need to ask about the “meaning” of products in people’s lives – and then develop ways of bringing this into the innovation process. For example, Apple’s i-phone changed the meaning of the phone from a communication device to the core of a highly interactive social system, while Nintendo’s Wii changed the meaning of computer gaming from a largely solitary activity to an interactive family pursuit. This is the role of design – to use tools and skills to articulate and create meaning in products – and increasing services as well. He suggests a map (see Figure 5.4) in which both knowledge/technology push and market pull can be positioned – and where design-driven innovation represents a third space around creating radical new concepts which have meaning in people’s lives.

The increasing importance of design as a source of innovation also engages with the world of services. Joseph Pine used the term “experience economy” to describe the evolution of innovation from meeting needs toward creating experiences [55]. In an increasingly competitive world, differentiation comes increasingly from such “experience innovation,” especially in services where fulfilling needs takes second place to the meaning and psychological importance of the experience. For example, the restaurant business moves from emphasis on food as an essential human need toward increasingly significant experience in innovation around restaurants as systems of consumption involving the product, its delivery, the physical and cultural context, and so on. Increasingly service providers such as airlines, hotels, or entertainment businesses are differentiating themselves along such “experience innovation” lines [56]. And the model is being widely used in public sector services such as health care [57,58].

5.16 Regulation

Photographs of the pottery towns around Stoke on Trent in the Midlands of the United Kingdom taken in the early part of the twentienth century would not be of much use in tracing landmarks or spotting key geographical features. The images in fact would reveal very little at all – not because of a limitation in the photographic equipment or processing but because the subject matter itself – the urban landscape – was rendered largely invisible by the thick smog that regularly enveloped the area. Yet, 60 years later, the same images would show up crystal clear – not because the factories had closed (although there are fewer of them) but because of the continuing effects of the Clean Air Act and other legislation in the United Kingdom. They provide a clear reminder of another important source of innovation – the stimulus given by changes in the rules and regulations that define the various “games” for business and society. The Clean Air Act didn’t specify how, but only what had to change – achieving the reduction in pollutants emitted to the atmosphere involved extensive innovation in materials, processes, and even in product design made by the factories.

Regulation in this way provides a two edged sword – it both restricts certain things (and closes off avenues along which innovation had been taking place) and opens up new ones along which change is mandated to happen [59]. And it works the other way – deregulation – the slackening off of controls – may open up new innovation space. The liberalization and then privatization of telecommunications in many countries led to rapid growth in competition and high rates of innovation, for example.

Given the pervasiveness of legal frameworks in our lives we shouldn’t be surprised to see this source of innovation. From the moment we get up and turn the radio on (regulation of broadcasting shaping the range and availability of the programs we listen to) to eating our breakfast (food and drink is highly regulated in terms of what can and can’t be included in ingredients, how foods are tested before being allowed for sale, etc.) to climbing into our cars and buckling on our safety belt while switching on our hands free phone devices (both the result of safety legislation) the role of regulation in shaping innovation can be seen [60].

Regulation can also trigger counter innovation – solutions designed to get round existing rules or at least bend them to advantage. The rapid growth in speed cameras as a means of enforcing safety legislation on roads throughout Europe has led to the healthy growth of an industry providing products or services for detecting and avoiding cameras. And at the limit changes in the regulatory environment can create radical new space and opportunity. Although Enron ended its days as a corporation in disgrace due to financial impropriety it is worth asking how a small gas pipeline services company rose to become such a powerful beast in the first place. The answer was its rapid and entrepreneurial take up of the opportunities opened up by deregulation of markets for utilities like gas and electricity [61].

Case Study 5.13 gives an example of government control driving innovation.

5.17 Futures and Forecasting

Another source of stimuli for innovation comes through imagining and exploring alternative trajectories to the dominant version in everyday use. Various tools and techniques for forecasting and imagining alternative futures are used to help strategy making – but can also be used to stimulate imagination around new possibilities in innovation. For example, Shell has a long history of exploring future options and driving innovations, most recently through its Game changer program [62]. Sometimes, various “transitional objects” are used, such as concept models and prototypes in the context of product development, to explore reactions and provide a focus for different kinds of input, which might shape and cocreate future products and services [63,64].

Chapter 9 explores this theme and the related toolkits in detail. Research Note 5.2 discusses the theme of futures thinking.

5.18 Accidents

Accidents and unexpected events happen – and in the course of a carefully planned R&D project, they could be seen as annoying disruptions. But on occasions accidents can also trigger innovation, opening up surprisingly new lines of attack. The famous example of Fleming’s discovery of penicillin is but one of many stories in which mistakes and accidents turned out to trigger important innovation directions. For example, the famous story of 3M’s “Post-it” notes began when a polymer chemist mixed an experimental batch of what should have been a good adhesive but which turned out to have rather weak properties – sticky but not very sticky. This failure in terms of the original project provided the impetus for what has become a billion dollar product platform for the company. Henry Chesbrough calls this process “managing the false negatives” and draws attention to a number of cases [65]. For example, in the late 1980s, scientists working for Pfizer began testing what was then known as compound UK-92,480 for the treatment of angina. Although promising in the lab and in animal tests, the compound showed little benefit in clinical trials in humans. Despite these initial negative results, the team pursued what was an interesting side effect, which eventually led to UK-92,480 becoming the blockbuster drug Viagra.

Case Study 5.14 gives some examples of “accidental” innovations.

The secret is not so much recognizing that such stimuli are available but rather in creating the conditions under which they can be noticed and acted upon. As Pasteur is reputed to have said, “chance favours the prepared mind!” Using mistakes as a source of ideas only happens if the conditions exist to help it emerge. For example, Xerox developed many technologies in its laboratories in Palo Alto, which did not easily fit their image of themselves as “the document company.” These included Ethernet (later successfully commercialized by 3Com and others and PostScript language (taken forward by Adobe Systems). Chesbrough reports that 11 of 35 rejected projects from Xerox’s labs were later commercialized with the resulting businesses having a market capitalization of twice that of Xerox itself.

Part of the answer is undoubtedly to create an environment in which there is space and time to experiment and fail. It’s not coincidence that all of those discoveries in Case Study 5.14 took place in contexts where the individuals concerned could explore, experiment, and accept failure without fear of being penalized.

But another part of the story is recognizing the role of timing in “accidental” innovation. We can see many of these innovations as an extreme version of the “knowledge push” model in which we create something new for which there is no apparent need or where the intended need isn’t met. It’s only later as an alternative need emerges that the real potential of the innovation comes through – and this different need often comes from a very different direction.

For example, metallurgist Harry Brearly was working hard in his lab in 1912 trying to improve the design of guns. He needed an alloy that wouldn’t erode over time as bullets spinning fast along grooved barrels rubbed against their walls – but his efforts proved fruitless. After months next to a growing pile of steel scrap representing failed efforts, he noticed one particular piece that had managed to retain its original shine rather than oxidizing. He explored this 12% chromium alloy a little further and found it also resisted marks and scratches as well; not very useful in gun-making but “stainless steel” had an impressive future elsewhere!

In 1942, Harry Coover was working in Eastman Kodak labs trying to perfect material for a precision gun sight. But the cyanoacrylate he experimented with was a bitter disappointment – sticking annoyingly to everything it touched. But six years later in trying to use it for cockpit canopies, he suddenly realized that the incredibly strong bonding powers could have a different application – and Superglue was born. The final version of his product hit the market 16 years after his original experiments.

One last aspect of accidents and unexpected events – shocks to the system which fundamentally change the rules provide not only a threat to the existing status quo but also a powerful stimulus to find and develop something new. The tragedy of the 9/11 bombing of the Twin Towers served to change fundamentally the public sense of security – but it has also provided a huge stimulus to innovate in areas such as security, alternative transportation, fire safety and evacuation, and so on [60].

Summary

Innovations don’t just appear perfectly formed – and the process is not simply a spark of imagination giving rise to changing the world. Instead innovations come from a number of sources and these interact over time. Sources of innovation can be resolved into two broad classes – knowledge push and need pull – although they almost always act in tandem. Innovation arises from the interplay between them.

There are many variations on this theme – for example, “need pull” can include social needs, market needs, latent needs “squeaking wheels,” crisis needs, and so on.

It’s clear that opportunities for innovation are not in short supply – and they arise from many different directions. The key challenge for innovation management is how to make sense of the potential input – and to do so with often limited resources. No organization can hope to cover all the bases so there needs to be some underlying strategy to how the search process is undertaken. One way is to impose some dimensions on the search space to help us frame where and why we might search for innovation triggers. That is the theme of the next chapter which explores how we might mobilize search strategies for innovation.

Further Reading

In this chapter, we’ve looked at the many ways in which the innovation process can be triggered – and the need for multiple approaches to the problem of searching for them. The management challenge lies in recognizing the rich variety of sources and configuring search mechanisms which balance the “exploit” and “explore” domains, providing a steady stream of both incremental (do what we do, better) ideas and more radical (do different) stimuli – and doing so with limited resources.

The long-running debate about which sources – demand pull or knowledge push – are most important is well covered in Freeman and Soete’s work that brings in the ideas of Schumpeter, Schmookler, and other key writers (The economics of industrial innovation. 3rd ed 1997, Cambridge: MIT Press). Public sector and social innovation are important emerging areas where user needs are central to design and delivery of innovation; good discussions can be found in the work of Christian Bason (Leading public sector innovation 2011, London: Policy Press) and Robin Murray and colleagues (The open book of social innovation 2010, London: The Young Foundation). Particular discussion of fringe markets and unmet or poorly met needs as a source of innovation is covered by Christensen (Seeing what’s next 2007, Boston: Harvard Business School Press) and Ulnwick (What customers want: Using outcome-driven innovation to create breakthrough products and services 2005, New York: McGraw-Hill.), while the “bottom of the pyramid” and extreme user potential is explored in Prahalad’s work (The fortune at the bottom of the pyramid 2006, New Jersey: Wharton School Publishing) and in the idea of “jugaad innovation” (Jugaad innovation: Think frugal, be flexible, generate breakthrough innovation 2012, San Francisco: Jossey Bass.). The website Next Billion (www.nextbillion.net) provides a wide range of resources and information about “bottom of the pyramid” and extreme user activity including video and case studies.

User-led innovation has been researched extensively by Eric von Hippel (The democratization of innovation 2005, Cambridge, Mass.: MIT Press and Free innovation, 2016, MIT Press) and his website (http://web.mit.edu/evhippel/) provides an excellent starting point for further exploration of this approach. Frank Piller, Professor at Aachen University in Germany, has a rich website around the theme of mass customisation with extensive case examples and other resources (http://www.mass-customization.de/); the original work on the topic is covered in Joseph Pine’s book (Mass customisation: The new frontier in business competition 1993, Cambridge, Mass.: Harvard University Press). Andrew Hargadon has done extensive work on “recombinant innovation” (How breakthroughs happen 2003, Boston: Harvard Business School Press) and Mohammed Zairi provides a good overview of benchmarking (Effective benchmarking: Learning from the best 1996, London: Chapman and Hall). The “Future of the automobile” project offers a famous example of this approach in practice (The machine that changed the world 1991, New York: Rawson Associates). Roberto Verganti’s book (Design driven innovation, 2010, Harvard Business School Press) is complemented by a detailed discussion of design management in the context of innovation by Pascal Le Masson and colleagues from the Ecole des Mines in Paris (Strategic management of innovation and design 2010, Cambridge: Cambridge University Press). Several useful books summarise the challenges and opportunities in opening up innovation to the crowd, see for example Harhoff, D. and K. Lakhani, eds. Revolutionizing Innovation: Users, Communities, and Open Innovation. 2016, MIT Press: Boston. and Ramaswamy, V., The Power of Co-Creation: Build It with Them to Boost Growth, Productivity, and Profits. 2010, New York: Free Press.

Case Studies

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

• A case study of Spirit, a Russian company which draws on the extensive knowledge base built up during the Cold War around voice recognition technology to provide solutions for major global companies like Cisco and Oracle. And the case of Dyson demonstrates a similar theme, using a science-based approach to rethink appliances like washing machines, cooling fans and hand driers.
• Case studies of Philips, Kodak, and Cerulean that offer examples of disruptive innovation challenges and responses.
• Case study of MPESA and the development of mobile money solutions in East Africa.
• Case studies of Lego, Adidas and Threadless which illustrate the move toward mass customization.
• Case study of Kodak which has been able to reuse its strong knowledge base in coating photographic film (which became redundant as the industry moved to digital images) in the field of high speed, high volume printing. There is also a case study of Fujifilm which made a similar move away from photography, deploying its deep knowledge base to enter new fields in skincare.

References

1. 1. Freeman, C. and L. Soete, The economics of industrial innovation. 3rd ed. 1997, Cambridge: MIT Press.
2. 2. Dosi, G., Technological paradigms and technological trajectories. Research Policy, 1982. 11, 147–62.
3. 3. Tushman, M. and P. Anderson, Technological discontinuities and organizational environments. Administrative Science Quarterly, 1987. 31(3), 439–65.
4. 4. Trott, P., Innovation management and new product development. 5th ed. 2011, London: Prentice-Hall.
5. 5. Booz, A.a.H.C., New product management for the 1980s. 1982, Booz, Allen and Hamilton Consultants.
6. 6. Griffin, A., PDMA research on new product development practices. Journal of Product Innovation Management, 1997. 14, 429.
7. 7. Kotler, P., Marketing management, analysis, planning and control. 11th ed. 2003, Englewood Cliffs, NJ: Prentice Hall.
8. 8. Goffin, K. and R. Mitchell, Innovation management. 2nd ed. 2010, London: Pearson.
9. 9. Kelley, T., J. Littman, and T. Peters, The art of innovation: Lessons in creativity from Ideo, America’s leading design firm. 2001, New York: Currency.
10. 10. Rosenberg, N., Inside the black box: Technology and economics. 1982, Cambridge: Cambridge University Press.
11. 11. Imai, K., Kaizen. 1987, New York: Random House.
12. 12. Davenport, T., Process innovation: Re-engineering work through information technology. 1992, Boston, MA.: Harvard University Press. 326.
13. 13. Womack, J. and D. Jones, Lean solutions. 2005, New York: Free Press.
14. 14. Bessant, J., High involvement innovation. 2003, Chichester: John Wiley & Sons.
15. 15. Christensen, C., S. Anthony, and E. Roth, Seeing whats next. 2007, Boston: Harvard Business School Press.
16. 16. Immelt, J., V. Govindajaran, and C. Trimble, How GE is disrupting itself. Harvard Business Review, 2009 (October).
17. 17. Utterback, J., High end disruption. International Journal of Innovation Management, 2007.
18. 18. Ulnwick, A., What customers want: Using outcome-driven innovation to create breakthrough products and services. 2005, New York: McGraw-Hill.
19. 19. Kim, W. and R. Mauborgne, Blue ocean strategy: How to create uncontested market space and make the competition irrelevant. 2005, Boston, MA: Harvard Business School Press.
20. 20. Prahalad, C.K., The fortune at the bottom of the pyramid. 2006, NJ: Wharton School Publishing.
21. 21. Govindarajan, V., C. Trimble, and P. Dubois, Reverse innovation: Create far from home, win everywhere. 2012, Boston: Harvard Business School Press.
22. 22. Brown, S., et al., Strategic operations management 2nd ed. 2004, Oxford: Butterworth Heinemann.
23. 23. Pine, B.J., Mass customisation: The new frontier in business competition. 1993, Cambridge, MA: Harvard University Press, p. 333.
24. 24. Lampel, J. and H. Mintzberg, Customizing, customization. Sloan Management Review, 1996. 38(1), 21–30.
25. 25. Vandermerwe, S., Breaking through: Implementing customer focus in enterprises. 2004, London: Palgrave Macmillan.
26. 26. Von Hippel, E., The sources of innovation. 1988, Cambridge, MA: MIT Press.
27. 27. Bessant, J., Tim craft and AMS. 2002: http://www.innovation-portal.info.
28. 28. Bessant, E., Megan Grassell and Yellowberry. 2015: http://www.innovation-portal.info.
29. 29. Habicht, H., P. Oliveira, and V. Scherbatuik, User innovators: When patients set out to help themselves and end up helping many. Die Unternehmung – Swiss Journal of Management Research, 2012. 66(3), 277–94.
30. 30. Bessant, J., K. Moeslein, and C. Kunne, Opening up healthcare innovation: Innovation solutions for a 21st century healthcare system. 2012, AIM-Advanced Institute of Management Research: London.
31. 31. Mansfield, E., Industrial research and technological innovation: An econometric analysis. 1968, New York: Norton.
32. 32. Von Hippel, E., Lead Users: A source of novel product concepts. Management Science, 1986. 32(7), 791–805.
33. 33. Von Hippel, E., The democratization of innovation. 2005, Cambridge, MA: MIT Press.
34. 34. Piller, F., Mass Customization: Ein wettbewerbsstrategisches Konzept im Informationszeitalter. 4th ed. 2006, Frankfurt: Gabler Verlag.
35. 35. Dahlander, L. and M. Wallin, A man on the inside: Unlocking communities as complementary assets. Research Policy, 2006. 35(8), 1243–59.
36. 36. Lee_Hotz, R., Need a breakthrough? Offer prize money!, Wall St Journal 2016: online.
37. 37. Moser, K. and F. Piller, Special issue on mass customisation case studies: Cases from the international mass customisation case collection. International Journal of Mass Customisation, 2006. 1(4).
38. 38. Fixson, S. and M. Tucker, A case study of crowdsourcing gone wrong. Harvard Business Review, 2016. Online version, December 15.
39. 39. Rothwell, R. and P. Gardiner, Tough customers, good design. Design Studies, 1983. 4(3), 161–9.
40. 40. Rich, B. and L. Janos, Skunk works. 1994, London: Warner Books.
41. 41. Corbett, S., Can the cellphone help end global poverty? New York Times. 2008: New York.
42. 42. Ries, E., The Lean Startup: How Today’s Entrepreneurs use continuous innovation to create radically successful businesses. 2011, New York: Crown.
43. 43. Hobday, M., Innovation in East Asia – The challenge to Japan. 1995, Cheltenham: Edward Elgar.
44. 44. Kim, L., Imitation to innovation: The dynamics of Korea’s technological learning. 1997, Boston: Harvard Business School Press.
45. 45. Belliveau, P., A. Griffin, and S. Somermeyer, The PDMA Tool-Book for new product development: Expert techniques and effective practices in product development. 2002, New York: John Wiley & Sons.
46. 46. Camp, R., Benchmarking – the search for industry best practices that lead to superior performance. 1989, Milwaukee, WI: Quality Press.
47. 47. Kaplinsky, R., F. den Hertog, and B. Coriat, Europe’s next step. 1995, London: Frank Cass.
48. 48. Womack, J. and D. Jones, Lean thinking. 1996, New York: Simon and Schuster.
49. 49. Womack, J., D. Jones, and D. Roos, The machine that changed the world. 1991, New York: Rawson Associates.
50. 50. Bessant, J., Benchmarking in the automobile industry. 2010: http://www.innovation-portal.info.
51. 51. Hargadon, A., How breakthroughs happen. 2003, Boston: Harvard Business School Press.
52. 52. Hargadon, A. and R. Sutton, Technology brokering and innovation in a product development firm. Administrative Science Quarterly, 1997. 42, 716–49.
53. 53. Koestler, A., The act of creation. 1964, London: Hutchinson.
54. 54. Verganti, R., Design-driven innovation. 2009, Boston: Harvard Business School Press.
55. 55. Pine, J. and J. Gilmore, The experience economy. 1999, Boston: Harvard Business School Press.
56. 56. Voss, C., A. Roth, and D. Chase, Experience, service operations strategy, and services as destinations: Foundations and exploratory investigation. Production and Operations Management, 2008. 17, 247–66.
57. 57. Bessant, J. and L. Maher, Developing radical service innovations in healthcare: the role of design methods. International Journal of Innovation Management, 2009. 13(4), 555.
58. 58. Bessant, J., Lynne Maher interview – Using patient experience to drive innovation. 2010: http://www.innovation-portal.info.
59. 59. Blind, K., Special issue on innovation and regulation. International Journal of Public Policy, 2007. 2(1).
60. 60. Dodgson, M., D. Gann, and A. Salter, In case of fire, please take the elevator. Organization Science, 2007.
61. 61. Hamel, G., Leading the revolution. 2000, Boston, MA.: Harvard Business School Press.
62. 62. de Geus, A., The living company. 1996, Boston, MA: Harvard Business School Press.
63. 63. Schwartz, P., The art of the long view. 1991, New York: Doubleday.
64. 64. Fahey, L. and R. Randall, Learning from the future. 1998, Chichester: John Wiley & Sons.
65. 65. Chesborough, H., Managing your false negatives. Harvard Management Updates, 2003. 8(8).