dealing with discontinuous innovation: the...

36 Int. J. Technology Management, Vol. 42, Nos. 1/2, 2008

Copyright © 2008 Inderscience Enterprises Ltd.

Dealing with discontinuous innovation: the European experience

John Bessant Imperial College, London, SW7 2AZ, UK E-mail: [email protected]

Abstract: Recent research has drawn attention to problems with innovation management under conditions of discontinuity. For example, at certain times, the close interaction with players within the value network may act as a filter which blocks firms seeing the salience of new signals about emerging, but very different potential, technical or market trajectories. There is also the well-known issue of ‘not invented here’ suggesting that under conditions in which significant shifts occur in the technological trajectory existing incumbents often fail to capitalise or even to adopt. The problem is not simply one of missing important signals about emerging shifts in innovation trajectories in the environment. In a number of cases the information was available to the enterprise but its decision making and resource allocation processes failed to deal adequately with the new information. These and other experiences suggest that whilst firms can learn capabilities around what might be termed ‘steady state’ innovation conditions they need to extend these capabilities to deal with the uncertainties arising from discontinuous shifts in their technological, market or regulatory environments. This paper discusses some of the challenges around building such capability and presents some case study-based illustrations of experiments in progress.

Keywords: discontinuous innovation; search routines; open innovation.

Reference to this paper should be made as follows: Bessant, J. (2008) ‘Dealing with discontinuous innovation: the European experience,’ Int. J. Technology Management, Vol. 42, Nos. 1/2, pp.36–50.

Biographical notes: John Bessant is a Professor of Innovation and Technology Management at Imperial College, London. He also received a Senior Fellowship of the Advanced Institute for Management Research which he was awarded in 2003. In 2003, he was elected a Fellow of the British Academy of Management and in 2006 appointed a Fellow of the Sunningdale Institute.

1 Introduction

Much recent interest has been shown in the concept of discontinuous or disruptive innovation and has highlighted the managerial challenges posed when conditions move beyond a ‘steady state’ in terms of market, technology or other dimensions (Birkinshaw et al., 2004; Burgelman et al., 2004; Danneels, 2004). For example, Christensen’s extensive work explored the issue of new market emergence around a set of technological parameters which offered different performance characteristics to those required by a mainstream market (Christensen, 1997). This model offered a plausible

Dealing with discontinuous innovation 37

explanation for the problems he observed across several industries including computer disk drives, mechanical excavators and steel mini-mill technology. In later work he extended both the range of sectors where such disruption appeared to occur but also to include a second set of circumstances, again market-led, which could trigger such shifts in industry structure (Christensen and Raynor, 2003). Whereas his early model stressed disruption from below (a simpler and cheaper technology displaces an established but over sophisticated one) his later model also included the case of ‘new market’ disruption where the focus is on hitherto, unmet or unimagined needs in the market or a segment of it.

Christensen’s model offers a strongly demand-linked explanation, where the role of technological advance is of limited significance. It is not the radical nature of the technology but rather its recombination into a new bundle whose performance characteristics are valued by a different market groups which leads the disruption. But there are also cases where radical technological step-change has led to discontinuous conditions across industries – for example, the shift from grinding to float glass, the move from ice harvesting to refrigeration technology and in valves to solid state electronics (Utterback, 1994). In these cases a similar pattern emerges of change in the players and their relative market position can also be observed.

A significant number of innovations that ultimately transform an industry often do not originate from the industry’s leaders (Cooper and Schendel, 1988; Foster, 1986; Henderson and Clark, 1990; Utterback, 1994). The problem is that existing incumbents may find that their commitment to incremental exploration of an established trajectory may lock then into this mode and militate against their ability to move in more radical directions, Henderson (1993) suggested that

“ in some circumstances extensive experience with a technology may be a substantial disadvantage ( ). Large established firms have an advantage over entrants in the pursuit of incremental innovation because incremental innovation builds upon their existing knowledge and capabilities, but these assets can simultaneously reduce substantially the effectiveness of their attempts to exploit radical innovation” (p.251).

The difficulty is compounded by the fact that shifts which create discontinuous conditions and precipitate a new fluid phase may come from multiple directions (Phillips et al., 2006). And the innovation management challenge lies less in the absolute scale of novelty or dislocation but rather in the firm’s experience of these conditions as something which takes it beyond its normal operating envelope. Since such conditions do not emerge every day – they are essentially discontinuous – established firms are often unable to deal with them effectively even though they may have very sophisticated routines for managing the steady state innovation process.

Tushman and Anderson studied such shifts across a wide rage of industries over an extended time period and noted that under some conditions major technological shifts could be ‘competence destroying’ – at which point new entrants would dominate the new industries enabled by radical technology (Tushman and Anderson, 1987). But, under other conditions the radical technologies were ‘competence enhancing’ and strengthened the hand of existing incumbents. Importantly, this suggests that disruption is not always a ‘changing of the guard’ between existing incumbents and new entrants – a view finding increasing support across a number of studies. For example, Methé et al. (1997) found that industry incumbents and diversifying entrants could be credited with many major innovations in the telecommunications and medical device industries while

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Klepper and Simons (2000) found that nearly all dominant US manufacturers of television sets previously were dominant producers of radios and that they took the lead in television product and process innovations. Chandy and Tellis (2000) found that after World War II, incumbents actually introduced the majority (75%) of radical product innovations within the two product classes they studied. Recent work by Markides explores the strategic advantages offered by ‘fast followership’ in this context (Markides, 1997).

Much seems to depend on the firm’s ability to pick up on and respond effectively to weak signals which often came ‘out of left field’. There is a challenge to incumbent firms around their capability to deal with both ‘steady state’ innovation (where the rate of change in key market and technological conditions follows a continuous path) and ‘discontinuous’ innovation where this is subject to radical upheaval – a change in the ‘rules of the game’. As Tushman and O’Reilly point out, developing such ‘ambidextrous’ capability is not easy and many firms resolve the tension by creating separate organisations to deal with the discontinuous challenge (Buckland et al., 2003). At the least it requires incumbent firms to review their routines for dealing with ‘steady state’ and to modify these or possibly create completely new ones to deal with the discontinuous challenge.

2 Routines for steady state and discontinuous innovation conditions

Organisations across a wide range of sizes, sectors, geographical locations, etc. have evolved a series of behaviours which help them deal with the challenge of innovation. Trial and error learning eventually gives rise to the accumulation of knowledge about successful behaviours which then become organisational ‘routines’ which build into ‘the way we do things around here’ – the innovation culture and its attendant organisational structures, policies and procedures (Cohen et al., 1996; Nelson and Winter, 1982; Pavitt, 2002). Significantly some bundles of routines are demonstrably more effective than others under particular conditions and give rise to a degree of competitive advantage which is often difficult to imitate because of its firm specific nature and the lengthy learning processes required to absorb and embed them.

This convergence of experience around successful innovation management routines has given rise to a ‘good practice’ model for ‘steady state’ innovation which embeds some key guidelines or design principles for effective innovation management (Dodgson, 2000; Ettlie, 1999; Shavinina, 2003). Their adoption still requires extensive configuration to suit particular circumstances but the emergent model provides a starting point for such organisational development. In particular it can be used as a structured framework against which organisations can begin a process of audit and consequent organisational development activity (Chiesa et al., 1996; DTI, 1994; Johne and Snelson, 1988).

Under discontinuous conditions, however, these routines may prove ineffective. The context is much closer to the ‘fluid’ phase in Abernathy and Utterback’s innovation life-cycle model (Abernathy and Utterback, 1975; Utterback, 1994). This phase is one in which new options become explored by many players, all learning fast but all trying to elaborate the technology into a form which can become widely adopted. It is characterised by coexistence of old and new technologies and by rapid improvements of


both (Foster, 1986; Tushman and Anderson, 1987).1 Eventually there is a crystallisation of a ‘dominant design’ – not always the best in purely technological terms2 but one which becomes the innovation standard and sets up a technological trajectory (Dosi, 1982). The establishment of the dominant design then gives way to a phase of consolidation innovation, first around stabilising the product concept and later around the processes which create and deliver it. Eventually it moves from the mature phase into a new period of fluidity and the cycle repeats itself associated with a new technology.3

Whilst Abernathy and Utterback’s model is predicated upon technological change being the driver it plays equally well to the emergence of new market conditions of the kind highlighted by Christensen. Arguably discontinuities emerge and trigger a fluid phase in which there is an extended search in new and unfamiliar space. Under these conditions existing incumbents and new entrants are equally in the dark – no one knows the nature of the technological or market trajectory – the ‘dominant design’ – and so considerable experimentation, fast failure and rapid learning needs to take place. Essentially the problem facing ‘steady state’ archetype organisations is one of systematic search within known or ‘knowable’ selection environments. By contrast discontinuous innovation requires a much open ended and agile approach to managing and emergent field where search strategies are difficult to predict in advance (McKelvey, 2004).

New entrants have the agility to handle these high levels of ambiguity but at the same time lack the resource base to sustain much in the way of blind alleys or other short-term failures. By contrast existing incumbents have a resource-based resilience which can carry them through the exploration – but may lack the motivation, especially when their internal systems militate against changing the rules of the game as a result of sunk costs, reluctance to cannibalise, cognitive and perceptual barriers, etc. (Tripsas and Gavetti, 2000).

Under these conditions we would expect winners and losers on both sides and that the evidence around discontinuous shifts shows a proportion of existing incumbents which falter but others which thrive. This in turn focuses attention on what they actually do to preserve and enhance their position. What additional or complementary routines do they put in place to enable successful management of discontinuous technological, market and other changes?

Working ‘out of the box’ in this way requires a new set of approaches to organising and managing innovation – for example, how the firm searches for weak signals about potential discontinuities, how it makes strategic choices in the face of high uncertainty, how it resources projects which lie far outside the mainstream of its innovation operations, etc. Established and well proven routines for ‘steady state’ conditions may break down here – for example, an effective ‘stage gate’ system would find it difficult to deal with high risk project proposals which lie at the fringes of the firm’s envelope of experience. Developing new behaviours more appropriate to these conditions – and then embedding them into routines – requires a different kind of learning – ‘generative learning’ (Senge, 1990) or ‘double loop’ (Argyris and Schon, 1970).

The problem is further compounded by the networks of relationships the firm has with other firms. Typically, much of the basis of innovation lies at a system level involving networks of suppliers and partners configuring knowledge and other resources to create a new offering. Discontinuous innovation is often problematic because it may involve building and working with a significantly different set of partners than those the firm is accustomed to working with. Whereas ‘strong ties’ – close and consistent relationships with regular partners in a network – may be important in enabling a steady

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stream of continuous improvement innovations, evidence suggests that where firms are seeking to do something different they need to exploit much weaker ties across a very different population in order to gain access to new ideas and different sources of knowledge and expertise (Philips et al., 2004).

Table 1 offers two opposing ‘archetypes’ which we might associate with these two forms – ‘steady state’ and ‘discontinuous’. It highlights the ‘design principles’ around which new or modified routines will have to emerge to deal with discontinuous challenges. But unlike ‘steady state’ conditions, there is not a well codified ‘best practice’ model – nor even well established practices of any kind. Rather firms find themselves in the ‘preroutine’ stage of capability development, using trial and error experimentation to approach practices which work and may become routinised in the future.

Table 1 Two archetypes of innovation organisation

Type 1 – steady state Type 2 – discontinuous

Operates within mental framework based on clear and accepted set of rules of the game

No clear rules – these emerge over time High tolerance for ambiguity

Strategies path dependent Path independent, emergent, probe and learn

Clear selection environment Fuzzy, emergent selection environment

Selection and resource allocation linked to clear trajectories and criteria for fit

Risk taking, multiple parallel bets and tolerance of (fast) failure

Operating routines refined and stable Operating patterns emergent and ‘fuzzy’

Strong ties and knowledge flows along clear channels

Weak ties and peripheral vision important

3 Searching under discontinuous conditions

Table 1 highlights a number of challenges to the development of effective innovation management routines to deal with discontinuous conditions, and in the remainder of this paper we will concentrate particularly on those which relate to search behaviour. It is clear that a degree of potential advantage is associated with the capability to pick up early and weak signals about the emergence of discontinuities. To do this firms need to extend and enhance their peripheral vision (Day and Schoemaker, 2004) and extend their (re)search activities into new and unexpected areas. This is often difficult to justify not least because of the difficulty of deciding where to focus such alterative search activity. It is a little like the story of the drunk searching for his keys under the lamp-post because it is better illuminated. Clearly he needs to extend his search to the dark areas beyond – but how does he choose a particular direction in which to begin his search from 360’ of such darkness?

Whilst it is clear that the ‘exploitation/exploration’ question is not new and has led to the development of firm-specific approaches to resolving the tension between them, we would argue that this old question is now challenges by a significantly different context within which firms operate (March, 1991). Changes along several core environmental dimensions mean that the incidence of discontinuities is likely to rise – for example in response to a massive increase in the rate of knowledge production and the consequent


increase in the potential for technology-linked instabilities. But there is also a higher level of interactivity amongst these environmental elements – complexity which leads to unpredictable emergence (for example, the rapidly growing field of Voice over Internet Protocol (VoIP), communications is not developing along established trajectories towards a well defined end-point. Instead it is a process of emergence. The broad parameters are visible – the rise of demand for global communication, increasing availability of broadband, multiple peer-to-peer networking models, growing technological literacy amongst users – and the stakes are high, both for established fixed-line players (who have much to lose) and new entrants (such as Skype, recently bought by eBay for $2.6 billion). The dominant design is not visible yet – instead there is a rich fermenting soup of technological possibilities, business models and potential players from which it will gradually emerge).

Table 2 summarises some of the key changes in the context within which search behaviour is located. Arguably these require firms to pay more attention to the limits of their current models and adds an element of urgency to the need to extend and develop new routines.

Table 2 Changing context for search behaviour

Context change Indicative examples

Acceleration of knowledge production OECD estimates that close to $1 trillion is spent each year (public and private sector) in creating new knowledge – and hence extending the frontier along which ‘breakthrough’ technological developments may happen.

Global distribution of knowledge production Knowledge production is increasingly involving new players especially in emerging market fields like the BRIC nations – so the need for search routines to cover a much wider search space increases.

Market fragmentation Globalisation has massively increased the range of markets and segments so that these are now widely dispersed and locally varied – putting pressure on search routines to cover much territory, often far from ‘traditional’ experiences – such as the ‘bottom of the pyramid’ conditions in many emerging markets (Prahalad, 2006).

Market virtualization Increasing use of internet as marketing channel means different approaches need to be developed. At the same time emergence of large-scale social networks in cyberspace pose challenges in market research approaches – for example, My Space currently has over 80 million subscribers. Further challenges arise in the emergence of parallel world communities as a research opportunity – for example, Second Life now has over 6 million ‘residents’.

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Table 2 Changing context for search behaviour (continued)

Context change Indicative examples

Rise of active users Although von Hippel has long identified the active role which users can pay in innovation there has been an acceleration in the ways in which this is now taking place – for example, the growth of Linux has been a user-led open community development (Von Hippel, 2005). In sectors like media the line between consumers and creators is increasingly blurred – for example, You Tube has around 100 million videos viewed each day but also has over 70,000 new videos uploaded every day from its user base.

Development soft technological and social infrastructure

Increasing linkages enabled by information and communications technologies around the internet and broadband have enabled and reinforced alternative social networking possibilities. At the same time the increasing availability of simulation and prototyping tools have reduced the separation between users and producers (Gann, 2004; Schrage, 2000).

4 Methodology

In the following section we give some illustrative examples drawn from a continuing programme of research on this question: how do firms experiment towards building capabilities aligned with the second – ‘discontinuous innovation’– archetype?

This work is based on longitudinal case studies of firms participating in ‘learning networks’ (Bessant and Tsekouras, 2001) and acting as a community of practice, a ‘colaboratory’ for articulating key research issues around discontinuous innovation, sharing experiences and developing and implementing experiments to develop new routines for dealing with it. The first of these – the Discontinuous Innovation Forum – was established in 2003 and involved 25 firms in UK (Phillips et al., 2006). The model is now being used in a parallel programme involving around 60 firms in UK, Denmark and Germany with further extension into Sweden, Norway, France. The Netherlands, Finland and Australia planned for 2007. The experience of firms in these networks highlights the extensive nature of experimentation around finding routines for dealing with discontinuous innovation.

The underlying model is one of cooperative experience sharing supported by a mixture of qualitative and quantitative research carried through by academic partners in the participating countries. Case studies of the member firms are constructed via a common interview framework and the results feedback at both national level and in international workshops, providing a check on face validity and an opportunity to explore and expand on issues raised. Future research plans include a quantitative survey across the participating firms to check the incidence of emerging patterns and the key directions along which routines are being constructed.

The research is focusing on key stages within the innovation process, with each cycle of workshops, case studies and elaboration workshop dealing with a particular theme.


During 2006 emphasis was placed on the question of search – how do firms explore their environments and pick up weak and early signals about potential discontinuities? The current phase (2007) is dealing with the second question of strategic selection – how firms are tackling the question of allocating resources and making strategic commitments to high risk and often discontinuous projects which go against the ‘steady state’ trajectory of the business. The third phase, envisaged for late 2007 and 2008 will deal with the question of implementation routines – how to carry through radically different projects.

5 Results

This paper reports on early results from the first – search – phase of the work. The full set of results is presented elsewhere and we will briefly summarise them here, drawing out some common themes around the European experience (Bessant and Von Stamm, 2007). A general observation is experimentation and learning towards new routines is extensively focused on the emerging ‘open innovation’ agenda – and in dealing with some of the questions (like intellectual property management) which this raises. Whilst all the firms involved were essentially trying out new approaches, there was a degree of convergence in their actins and experiences. Amongst these common themes were the following:

• Drivers for undertaking such experiments varied but in most cases it was a proactive move to try and develop capability to avoid being taken by surprise or ‘blindsided’ by rapid developments on the edge of their radar screens. This picks up on an extensive and growing literature which highlights the vulnerability of existing incumbents and stresses the need for development of new capabilities (Christensen and Raynor, 2003; Day and Schoemaker, 2006; Foster and Kaplan, 2002; Tushman and O’Reilly, 1996).

• A common first step was the creation of slack resources to focus on the extended search task – for example, establishing a special unit or team or designating a new role for an established group. Most of the participants in the ‘colaboratories’ came from such new groupings.

• Another common set of approaches sought to (re)create entrepreneurial capability through setting up specialist venture units, corporate venture funds, etc. – and at the limit to consider spinning these off as separate entities.

• Many experiments were along pathways already established as ‘mainstream’ exploration routines – for example, the use of futures and forecasting methods. But there was also a degree of stretching the boundaries of these and modifying them to suit more open-ended search behaviour – for example, cross-sectoral forecasting.

• The cross-sector nature of the colaboratories reinforced an approach to experimenting with ideas and approaches from outside the sector – for example, the use of advanced market research tools by some of the less consumer-facing firms or of prototyping methods by service businesses.

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• Whilst many search experiments were essentially variations on established routines a number of new approaches were also being developed involving approaches and technologies which would simply not have been possible in earlier models – for example, the use of interactive ‘web 2.0’ approaches or advanced user involvement in codesign.

• Whilst there is still wide variation in the ways in which they were deployed there was convergence around 12 core ‘strategies’ shaping experiments towards new search routines. Table 3 summarises these and we offer some illustrative examples.

A flavour of these approaches can be gained from the following examples.

Table 3 Search strategies for discontinuous innovation

Search strategy Mode of operation

Sending out scouts Dispatch idea hunters to track down new innovation triggers

Exploring multiple futures Use futures techniques to explore alternative possible futures; and develop innovation options from that

Using the web Harness the power of the web, through online communities and virtual worlds for example, to detect new trends

Working with active users Team up with product and service users to see the ways in which they change and develop existing offerings

Deep diving Study what people actually do, rather than what they say they do

Probe and learn Use prototyping as mechanism to explore emergent phenomena and act as boundary object to bring key stakeholders into the innovation process

Mobilise the mainstream Bring mainstream actors into the product and service development process

Corporate venturing Create and deploy venture units

Corporate entrepreneurship and intrapreneuring

Stimulate and nurture the entrepreneurial talent inside the organisation

Use brokers and bridges Cast the ideas net far and wide and connect with other industries

Deliberate diversity Create diverse teams and a diverse workforce

Idea generators Use creativity tools and techniques

5.1 Sending out scouts

The role of scouts or ‘idea hunters’, who can be full or part time, is to search actively for new ideas to trigger the innovation process. They could be searching for technological triggers, emerging markets or trends, competitor behaviour, etc., but what they have in common is a remit to seek things out, often in unexpected places. For example:


• Procter and Gamble’s Connect and Develop open innovation approach sets a target of sourcing 50% of innovation inspiration from outside the company. It employs around 80 ‘technology entrepreneurs’, scouts, licenced to roam the world with a wide remit to find and bring back interesting new ideas.

• O2 has a trend-scouting group of about ten people who interpret externally identified trends into O2’s specific business context. Once a year the group meets with the board to discuss and select ideas.

• BT has a scouting unit in Silicon Valley which assesses some 3000 technology opportunities a year in California. The four-man operation looks at more than 1000 companies per year and then targets the small number of cases where there is a direct match between BT’s needs and the Silicon Valley Company’s technology.

5.2 Using the web

In its simplest form this search strategy is a passive information resource to be searched – an additional space into which the firm sends its scouts. Increasingly there are professional organisations who offer focused search capabilities to help with this hunting – for example, in trying to pick up on emerging cool trends among particular market segments. But the internet can also be used as a multidirectional information marketplace – for example, Eli Lilly’s www.innocentive.com used as a match making tool, connecting those with scientific problems with those being able to offer solutions.

We have also found companies that use websites as ‘online laboratories’ for conducting experiments or prototype testing. An example of the former is Second Life (www.secondlife.com), an online role playing game with over 6 million users and rising fast. Here people assume alternate identities represented by avatars and interact in an alternative online world – in the process creating a powerful laboratory for testing out ideas. Since by definition Second Life is the result of people projecting their aspirations and interests in a different space it offers significant scope for early warning about or even creating new trends.

Examples discussed in the workshops included:

• Lego has set up the Lego Factory website where users can build their own model online and then have the ‘ready to assemble set’ sent out to them (http://factory.lego.com). A benefit was seen to be that is supports direct communication with users that could be difficult to identify otherwise, such as train enthusiasts. In this way LEGO receives feedback from its most advanced users and can use this information to enhance mainstream products.

• Under development at Webasto (a German automotive component maker) is a ‘department store for ideas’ where company employs can list their ideas and in a future step, external solvers can contribute in finding technical solutions to the posted ideas.

• BMW makes use of the web to enable a Virtual Innovation Agency – a forum where suppliers from outside the normal range of BMW players can offer ideas. These can be both product related and also process-related – for example, a recent suggestion was for carbon recycling out of factory waste.

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5.3 Working with active users

With the advent of powerful new tools there is huge scope for engaging users in active cocreation of products and services. For example, the internet has enabled the open source movement to develop high quality software as a cooperative process, whilst tools like rapid prototyping, simulation and computer-aided design help create the spaces where active users can interact with professional designers (Von Hippel, 2005).

Participating companies also pointed out that users at the fringes of the mainstream tend to be more tolerant of failure and prepared to accept that through mistakes they can get to something better. This makes them an ideal target group for the ‘perpetual beta testing’ approach increasingly used in software development and other online products.

Examples from participating companies include:

• When LEGO originally launched the Mindstorms RCX – the programmable Lego toys – within a few days the most advanced users had cracked the code and developed their own updated versions. These advanced users produced variants of the product that were superior to the original. In 2006 LEGO was launching a radical new Mindstorms product – an NXT. This time it invited some leading users to participate directly in the development. In recognition of the success of this programme, Lego stated in January 2006 that it was looking for 100 more citizen developers (http://mindstorms.lego.com).

• This kind of approach is being explored by the British Broadcasting Corporation (BBC) – a major producer of broadcast media now trying to deal with the discontinuous challenges of the new digital media environment. One experiment, BBC Backstage, is trying to do with new media development what the open source community did with software development. The model is deceptively simple – developers are invited to make free use of various elements of the BBC’s site, such as live news feeds, weather and TV listings, to integrate and shape innovative applications. The strap line is ‘use our stuff to build your stuff’. Since the site launched in May 2005 it has already attracted interest of hundreds of software developers (www.bbcbackstage.com).

• Webasto went through a systematic approach to understand what lead users are and how to identify them. It identified four aspects that really drive people’s propensity to innovate: cognitive complexity, team expertise, general knowledge, willingness to help. Based on this information it developed a questionnaire and sent it out to up to 5000 people. About 20% returned the questionnaires, and eventually a lead user group of between 10 and 30 was selected. The lead users committed to come for an entire weekend, and without pay.

5.4 Probe and learn

This strategy is aimed at addressing the problem that it is often difficult to imagine a radically different future, and even harder to predict how things will actually develop. In order to get a better understanding of the most promising direction companies have started to use an approach we have called ‘probe and learn’. Rather than fully developed products prototypes and concepts are put out into the market and consumer reactions are carefully watched and monitored. Through this process, emergent trends and potential designs can be explored and refined in a continuing learning process.


Probe and learn strategies allow firms to devise experiments to explore alternative hypotheses – for example, looking for opportunities in the segments of the market they are not active or strong in. If an incumbent wishes to anticipate disruptive threats, it should test out some alternative radical hypotheses and carry out such experiments at the fringes of its existing business.

An example is the Danish pharmaceutical firm Novo Nordisk which is making extensive use of probe and learn approaches in trying to understand the possible evolution of new diabetes-related services and care pathways which may represent an important new direction for this traditional pharmaceutical firm with its emphasis on drugs and delivery systems. Much of this work is going on in laboratories where very different conditions apply – for example, in Africa where the need is for holistic solutions involving education, clinics and treatment centres and prevention methods – all delivered from a very low cost base.

6 Emerging conclusions

This paper has outlined continuing research around the theme of discontinuity and the approaches which firms are experimenting with in order to develop capability to detect and react to early warning signals in their environments. These approaches do not yet have the character of ‘routines’ but are rather indicators of emerging patterns and trajectories around which such routines may form. As with routines themselves there is a high degree of firm-specificity in the ways in which experiments are being carried out but there appear to be interesting shared learning effects arising from the cross-sectoral make-up of the ‘colaboratories’ (e.g. sharing of future scenario work to explore potential collaborations or exchanging experience and running joint workshops around new tools such as lead-user methods).

As part of firm-level capabilities building, these experiments indicate a degree of convergence. They are, of course, highly contingent with fast-moving sectors like media and telecoms requiring much greater levels of market and technology research commitment than sectors like food or automotive. Nevertheless there is a general pattern of commitment of ‘slack resources’ to create a learning capacity and the use of this to deploy and test multiple mechanisms around the search question. Arguably this reflects a growing preoccupation with a context which is increasingly driving a more ‘open’ innovation model and challenging existing innovation management structures and processes.

At its heart this process of experimenting towards new routines is, of course, the embodiment of dynamic capability view of innovation – not simply learning and putting in place routines but also being able to modify, adapt and, at the limit, create new ones.

Acknowledgements

The research described in this paper was funded by the Engineering and Physical Sciences Research Council and the Economic and Social Research Councils of the UK under the AIM – Advanced Institute for Management Research – initiative and their support is gratefully acknowledged. I would also like to thank the two anonymous reviewers who provided very helpful comments on an earlier draft.

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Notes

1 It is here that the so-called ‘sailing ship’ effect can often be observed, in which a

mature technology accelerates in its rate of improvement as a response to a competing new alternative – as was the case with the development of sailing ships in competition with newly-emerging steamship technology. (Cooper and Schendel, 1988; Gilfillan, 1935).

50 J. Bessant

2 The example of video recorders is a demonstration of this in which the technically superior

Betamax system was unable to achieve the dominant position of the VHS approach. For more details see Tushman and Moore (1988).

3 A good example of this can be seen in the case of bicycles which went through an extended period

of fluidity in design options before the dominant diamond frame emerged which has characterised the industry for the past century (Walsh et al., 1992).

dealing with discontinuous innovation: the...

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