Source: Johnny Haglund/Getty Images
brought up on mainframe computers and PCs, Salkowitz argues they are not hampered in their mindsets and the way they think and develop new ideas. They have grown up with mobile devices and it is these that will provide the foundation for entrepreneurship in the twenty-first century. It is
this fresh young cast of entrepreneurs whose ideas are changing the world. The next generation of Googles and Ubers may begin to emerge from this rising new young world.
Schumpeter: The other demographic dividend, The Economist, 7 October 2010.
Popular views of innovation
Science, technology and innovation have received a great deal of popular media coverage over the years, from Hollywood and Disney movies to best-selling novels (see Figure 1.3). This is probably because science and technology can help turn vivid imaginings into a possibility. The end result, however, is a simplified image of scien- tific discoveries and innovations. It usually consists of a lone professor, with a mass of white hair, working away in his garage and stumbling, by accident, on a major new discovery. Through extensive trial and error, usually accompanied by dramatic experiments, this is eventually developed into an amazing invention. This is best demonstrated in the blockbuster movie Back to the Future. Christopher Lloyd plays the eccentric scientist and Michael J. Fox his young, willing accomplice. Together, they are involved in an exciting journey that enables Fox to travel back in time and influence the future.
Cartoons have also contributed to a misleading image of the innovation process.
Here, the inventor, usually an eccentric scientist, is portrayed with a glowing light-
Figure 1.3 The popular view of science
Models of innovation
bulb above his head, as a flash of inspiration results in a new scientific discovery. We have all seen and laughed at these funny cartoons.
This humorous and popular view of inventions and innovations has been rein- forced over the years and continues to occur in the popular press. Many industrial- ists and academics have argued that this simple view of a complex phenomenon has caused immense harm to the understanding of science and technology.
Models of innovation
Traditional arguments about innovation have centred on two schools of thought.
On the one hand, the social deterministic school argued that innovations were the result of a combination of external social factors and influences, such as demo- graphic changes, economic influences and cultural changes. The argument was that when the conditions were right, innovations would occur. On the other hand, the individualistic school argued that innovations were the result of unique individual talents and such innovators are born. Closely linked to the individualistic theory is the important role played by serendipity; more on this later.
Over the past 10 years, the literature on what drives innovation has tended to divide into two schools of thought: the market-based view and the resource-based view. The market-based view argues that market conditions provide the context that facilitates or constrains the extent of firm innovation activity (Porter, 1980, 1985;
Slater and Narver, 1994). The key issue here, of course, is the ability of firms to recognise opportunities in the marketplace. Cohen and Levinthal (1990) and Trott (1998) would argue that few firms have the ability to scan and search their environ- ments effectively.
The resource-based view of innovation considers that a market-driven orientation does not provide a secure foundation for formulating innovation strategies for mar- kets that are dynamic and volatile; rather a firm’s own resources provide a much more stable context in which to develop its innovation activity and shape its mar- kets in accordance with its own view (Conner and Prahalad, 1996; Eisenhardt and Martin, 2000; Grant, 1996; Penrose, 1959; Prahalad and Hamel, 1990; Wernerfelt, 1984, 1995). The resource-based view of innovation focuses on the firm and its resources, capabilities and skills. It argues that when firms have resources that are valuable, rare and not easily copied they can achieve a sustainable competitive advantage – frequently in the form of innovative new products. Chapter 6 offers a more detailed overview of the resource-based theory of the firm.
Serendipity
Many studies of historical cases of innovation have highlighted the importance of the unexpected discovery. The role of serendipity or luck is offered as an explana- tion. As we have seen, this view is also reinforced in the popular media. It is, after all, everyone’s dream that they will accidentally uncover a major new invention leading to fame and fortune.
On closer inspection of these historical cases, serendipity is rare indeed. After all, in order to recognise the significance of an advance, one would need to have some
prior knowledge in that area. Most discoveries are the result of people who have had a fascination with a particular area of science or technology and it is following extended efforts on their part that advances are made. Discoveries may not be expected, but in the words of Louis Pasteur, ‘chance favours the prepared mind’.
Linear models
It was US economists after the Second World War who championed the linear model of science and innovation. Since then, largely because of its simplicity, this model has taken a firm grip on people’s views on how innovation occurs. Indeed, it domi- nated science and industrial policy for 40 years. It was only in the 1980s that man- agement schools around the world began seriously to challenge the sequential linear process. The recognition that innovation occurs through the interaction of the sci- ence base (dominated by universities and industry), technological development (dominated by industry) and the needs of the market was a significant step forward (see Figure 1.4). The explanation of the interaction of these activities forms the basis of models of innovation today. Students may also wish to note that there is even a British Standard (BS7000), which sets out a design-centred model of the process (BSI, 2008).
There is, of course, a great deal of debate and disagreement about precisely what activities influence innovation and, more importantly, the internal processes that affect a company’s ability to innovate. Nonetheless, there is broad agreement that it is the linkages between these key components that will produce successful innova- tion. Importantly, the devil is in the detail. From a European perspective, an area that requires particular attention is the linkage between the science base and techno- logical development. The European Union (EU) believes that European universities have not established effective links with industry, whereas in the United States uni- versities have been working closely with industry for many years.
As explained above, the innovation process has traditionally been viewed as a sequence of separable stages or activities. There are two basic variations of this model for product innovation. First, and most crudely, there is the technology- driven model (often referred to as technology push) where it is assumed that scien- tists make unexpected discoveries, technologists apply them to develop product ideas and engineers and designers turn them into prototypes for testing. It is left to manufacturing to devise ways of producing the products efficiently. Finally, market- ing and sales will promote the product to the potential consumer. In this model, the marketplace was a passive recipient for the fruits of R&D. This technology-push
Figure 1.4 Conceptual framework of innovation
Needs of the market Consumers express their needs and wants through the consumption
of products Technology development,
dominated by organisations Creation of new
knowledge, dominated by universities and large science-based organisations
Technological developments Science and
technology base
Models of innovation
model dominated industrial policy after the Second World War (see Figure 1.5).
Whilst this model of innovation can be applied to a few cases, most notably the pharmaceutical industry, it is not applicable in many other instances; in particular where the innovation process follows a different route.
It was not until the 1970s that new studies of actual innovations suggested that the role of the marketplace was influential in the innovation process (von Hippel, 1978).
This led to the second linear model, the market-pull model of innovation. The cus- tomer need-driven model emphasises the role of marketing as an initiator of new ideas resulting from close interactions with customers. These, in turn, are conveyed to R&D for design and engineering and then to manufacturing for production. In fast-moving consumer goods industries the role of the market and the customer remains powerful and very influential. The managing director of McCain Foods argues that knowing your customer is crucial to turning innovation into profits:
It’s only by understanding what the customer wants that we can identify the innova- tive opportunities. Then we see if there’s technology that we can bring to bear on the opportunities that exist. Being innovative is relatively easy – the hard part is ensuring your ideas become commercially viable.
(Murray, 2003)
Simultaneous coupling model
Whether innovations are stimulated by technology, customer need, manufacturing or a host of other factors, including competition, misses the point. The models above concentrate on what is driving the downstream efforts rather than on how innova- tions occur (Galbraith, 1982). The linear model is able to offer only an explanation of where the initial stimulus for innovation was born, that is, where the trigger for the idea or need was initiated. The simultaneous coupling model shown in Figure 1.6 Figure 1.5 Linear models of innovation
Technology push
Market pull
User Manufacturing
Marketing Research and development
Manufacturing Marketing User Research and
development
Figure 1.6 The simultaneous coupling model Manufacturing
Marketing Research and
development
suggests that it is the result of the simultaneous coupling of the knowledge within all three functions that will foster innovation. Furthermore, the point of commencement for innovation is not known in advance.
Architectural innovation
Henderson and Clark (1990) divide technological knowledge along two new dimensions: knowledge of the components and knowledge of the linkage between them, which they called architectural knowledge. The result is four possible types of innovation: incremental, modular, radical and architectural innovation.
Essentially, they distinguish between the components of a product and the ways they are integrated into the system, that is, the product architecture, which they define as innovations that change the architecture of a product without changing its components. Prior to the Henderson and Clark model, the radical/incremental dimension suggests that incumbents will be in a better position if the innovation is incremental, since they can use existing knowledge and resources to leverage the whole process. New entrants, on the other hand, will have a large advantage if the innovation is radical because they will not need to change their knowledge background. Furthermore, incumbents struggle to deal with radical innovation both because they operate under a managerial mindset constraint and because, strategically, they have less of an incentive to invest in the innovation if it will cannibalise their existing products.
Kodak illustrates this well. The company dominated the photography market over many years and, throughout this extended period, all the incremental innova- tions solidified its leadership. As soon as the market experienced a radical innova- tion – the entrance of digital technology – Kodak struggled to defend its position against the new entrants. The new technology required different knowledge, resources and mindsets. This pattern of innovation is typical in mature industries.
This concept is explored further in Chapter 7.
Interactive model
The interactive model develops this idea further (see Figure 1.7) and links together the technology-push and market-pull models. It emphasises that innovations occur as the result of the interaction of the marketplace, the science base and the organisa- tion’s capabilities. Like the coupling model, there is no explicit starting point. The use of information flows is used to explain how innovations transpire and that they can arise from a wide variety of points.
Whilst still oversimplified, this is a more comprehensive representation of the innovation process. It can be regarded as a logically sequential, though not necessar- ily continuous, process that can be divided into a series of functionally distinct but interacting and interdependent stages (Rothwell and Zegveld, 1985). The overall innovation process can be thought of as a complex set of communication paths over which knowledge is transferred. These paths include internal and external linkages.
The innovation process outlined in Figure 1.7 represents the organisation’s capabili- ties and its linkages with both the marketplace and the science base. Organisations that are able to manage this process effectively will be successful at innovation.
Models of innovation
At the centre of the model are the organisational functions of R&D, engineering and design, manufacturing and marketing and sales. Whilst, at first, this may appear to be a linear model, the flow of communication is not necessarily linear.
There is provision for feedback. Also, linkages with the science base and the mar- ketplace occur between all functions, not just with R&D or marketing. For exam- ple, as often happens, it may be the manufacturing function that initiates a design improvement that leads to the introduction of either a different material or the eventual development by R&D of a new material. Finally, the generation of ideas is shown to be dependent on inputs from three basic components (as outlined in Figure 1.4): technological developments; the needs of the marketplace; the science and technology base. Recent research confirms the validity of this concept today.
Research by Stefano et al., (2012) updates the debate on the sources of innovation.
They show and confirm that:
● the market is a major source of innovation;
● firm competences enable firms to match technology with demand; and
● external and internal sources of innovations are important.
All of which are necessary for value creation and capture.
Innovation life cycle and dominant designs
The launch of an innovative new product into the market is usually only the begin- ning of technology progress. At the industry level, the introduction of a new tech- nology will cause a reaction: competitors will respond to this new product, hence technological progress depends on factors other than those internal to the firm. We need to consider the role of the competition. Product innovation, process innova- tion, competitive environment and organisational structure all interact and are closely linked together. Abernathy and Utterback (1978) argued there were three different phases in an innovation’s life cycle: fluid, transitional and specific. This concept will be discussed in detail in Chapter 7, but at this stage we need only to recognise that one can consider innovation in the form of a life cycle that begins with a major technological change and product innovation. This is followed by the
Technology push
Market
pull Needs in society
and the marketplace Latest sciences and technology
advances in society
Idea R&D Manufacturing Marketing Commercial product
Figure 1.7 Interactive model of innovation
emergence of competition and process innovations (manufacturing improvements).
As the life cycle proceeds, a dominant design usually emerges prior to standardisa- tion and an emphasis on lowering cost. This model can be applied to many con- sumer product innovations over the past 20–30 years, such as VCRs, CD players and mobile phones. The so-called sailing ship effect can sometimes enable old tech- nologies to have new life (see Illustration 1.6).
Open innovation and the need to share and exchange knowledge (network models)
Innovation has been described as an information–creation process that arises out of social interaction. Chesbrough (2003), adopting a business strategy perspective, presents a persuasive argument that the process of innovation has shifted from one of closed systems, internal to the firm, to a new mode of open systems involving a range of players distributed up and down the supply chain. Significantly, it is Chesbrough’s emphasis on the new knowledge-based economy that informs the concept open innovation. In particular, it is the use of cheap and instant information flows that places even more emphasis on the linkages and relationships of firms. It is from these linkages and the supply chain in particular that firms have to ensure that they have the capability to fully capture and utilise ideas.
Furthermore, the product innovation literature, in applying the open innovation paradigm, has been debating the strengths and limitations of so-called user toolkits, which seem to ratchet up further this drive to externalise the firm’s capabilities to capture innovation opportunities (von Hippel, 2005).
Authors such as Thomke (2003), Schrange (2000) and Dodgson et al. (2005) have emphasised the importance of learning through experimentation. This is sim- ilar to Nonaka’s work in the early 1990s, which emphasised the importance of learning by doing in the ‘knowledge creating company’ (Nonaka, 1991). However, Dodgson et al. argue that there are significant changes occurring at all levels of the innovation process, forcing us to reconceptualise the process with emphasis placed on the three areas that have experienced most significant change through the intro- duction and use of new technologies. These are: technologies that facilitate cre- ativity, technologies that facilitate communication and technologies that facilitate
Illustration 1.6
The ‘sailing ship effect’
The so-called ‘sailing ship effect’ often has been stated as though there is no doubt that it really took place at the end of the nineteenth century.
The notion is that the substitution threat of new radical technologies (steamships) may lead to a renewed spurt of innovation in an old and estab- lished technology (sailing ships). Recently,
Mendonça (2013) reviewed the field of maritime history and shows that the effect is nowhere to be found, even in the very case from which it derives its name. Mendonça says the modernisation of the sailing trader occurs before, not after, the steamship had become an effective competitor.
Doing, using and interacting (DUI) mode of innovation
manufacturing. For example, they argue that information and communication technologies have changed the way individuals, groups and communities interact.
Mobile phones, email and websites are obvious examples of how people interact and information flows in a huge osmosis process through the boundaries of the firm. When this is coupled with changes in manufacturing and operations tech- nologies, enabling rapid prototyping and flexible manufacturing at low costs, the process of innovation seems to be undergoing considerable change (Chesbrough, 2003; Dodgson et al., 2005; Schrange, 2000). Models of innovation need to take account of these new technologies, which allow immediate and extensive inter- action with many collaborators throughout the process from conception to com- mercialisation.
Table 1.6 summarises the historical development of the dominant models of the industrial innovation process.
Doing, using and interacting (DUI) mode of innovation
Researchers have recognised for many years that in low and medium technology (LMT) intensive industries the traditional science and technology model of inno- vation is not applicable and cannot explain continued product and process innova- tions (see Arrow, 1968; Bush, 1945; Fitjar and Rodriguez-Pose, 2013; Maclaurin, 1953; Pavitt, 2001). Further, in the classic article by Pavitt (1984: 343–73) he spelt out, in his typology of firms, that ‘LMT industries are characterised by pro- cess, organisational and marketing innovations, by weak internal innovation capa- bilities and by strong dependencies on the external provision of machines, Table 1.6 The chronological development of models of innovation
Date Model Characteristics
1950/60s Technology-push Simple linear sequential process; emphasis on R&D; the market is a recipient of the fruits of R&D
1970s Market-pull Simple linear sequential process; emphasis on marketing; the market is the source for directing R&D;
R&D has a reactive role
1970s Dominant design Abernathy and Utterback (1978) illustrate that an innovation system goes through three stages before a dominant design emerges
1980s Coupling model Emphasis on integrating R&D and marketing 1980/90s Interactive model Combinations of push and pull
1990 Architectural
innovation Recognition of the role of firm-embedded knowledge in influencing innovation
1990s Network model Emphasis on knowledge accumulation and external linkages
2000s Open innovation Chesbrough’s (2003) emphasis on further
externalisation of the innovation process in terms of linkages with knowledge inputs and collaboration to exploit knowledge outputs