1. Introduction ± on the need for innovation
Situations for innovation management: towards a contingency model
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1. Introduction ± on the need for innovation
Situations for innovation management: towards a contingency model
The need for firms to become more innovative has probably never been greater. Today concepts such as the new economy, new technologies, hyper-competition and clock speed are used to explain that the dynamics of competition and markets has never been greater. Thus, there is a large focus on the concept of innovation management in firms. This paper aims at investigating this, but first let us establish the need for innovation. First and foremost, there is a lot of talk these days about market dynamics in an economy where tangible, technological assets are no longer the primary foundation for competition and/or building a firm. In recent years the notion of intellectual capital has begun to rise in management circles, among both researchers of management and managers. A stream of papers, conferences, seminars, and lately books (Stewart, 1997; Edvinson and Malone, 1997; Kaplan and Norton, 1996), goes to show that ``intellectual capital'' is an alternative way of viewing the assets and value creation of the firm. This coincides with the emergence of ``knowledge intensive firms'', i.e. firms that base their activities, products/services and value on knowledge of their employees and external partners. Charles Handy quotes a McKinsey report concluding that in 2000 70 per cent of all jobs will have been knowledgebased rather than based on manual labor, whereas 50 years ago the situation was the oppposite (Handy, 1995) Furthermore, new (information) technologies are arising every day that make entirely new ways of working and organising possible. For instance, Savage speaks of the possibility of ``fifth generation organisation'' based on ideas of networking and new information technology (Savage, 1990). Using the same ideas, Martin discusses the notion of ``cybercorp'' as an entirely new way of managing and organising firms (Martin, 1997) In general, there seems to be agreement that an entirely new competitive situation has arisen. This is nicely summarised by D'Aveni under the concept of ``hyper-competition'' (D'Aveni, 1994). Hyper-competition, according to D'Aveni, is a competitive situation where the key competitive success
Anders Drejer
The author Anders Drejer is Senior Lecturer at the Center for Industrial Production, Aalborg University, Aalborg, Denmark. Keywords Innovation, Competitive advantage Abstract The need for firms to become more innovative has probably never been greater. Today concepts such as the new economy, new technologies, hyper-competition and clock speed are used to explain that the dynamics of competition and markets has never been greater. Thus, there is a large focus on the concept of innovation management in firms. Discusses innovation management, understood as being the activities that firms undertake in order to yield new solutions within products, production and administration. The main contribution is a discussion of how a general framework for innovation management can be tailored to individual situations/different firms. Electronic access The research register for this journal is available at http://www.emeraldinsight.com/researchregisters The current issue and full text archive of this journal is available at http://www.emeraldinsight.com/1460-1060.htm
European Journal of Innovation Management Volume 5 . Number 1 . 2002 . pp. 4±17 # MCB UP Limited . ISSN 1460-1060 DOI 10.1108/14601060210415135
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Situations for innovation management: towards a contingency model
European Journal of Innovation Management Volume 5 . Number 1 . 2002 . 4±17
Anders Drejer
competencies as defined by Lowe (1995). This corresponds to the thinking behind Miles and Snow's seminal strategy model (1978), where strategy is seen as a process of solving three independent problems; the entrepreneurial problem (choices within the product-market domain), the engineering problem (choices related to operations), and the administrative problem (choices related to administration). Miles and Snow's model (1978) of what they refer to as ``organisational adaptation'' is a widely quoted conceptual model regarding integration mainly between technology and organisation. The model is usually also referred to as a model for ``strategic adaptation'' by others (e.g. Stacy, 1999). The model is based mainly on conceptual thinking, but also on a number of case studies. The purpose of the model is to describe and diagnose existing organisational behaviours and to prescribe alternative directions for change when necessary. The model is based on the following three basic ideas: (1) Organisations can act to create (or choose) their environment. (2) Management's strategic choices shape the organisation's structure and processes. (3) On the other hand, once chosen, structure and process constrain strategy.
factor is the ability to constantly develop new products, processes or services, providing the customer with increased functionality and performance (D'Aveni, 1994). In a hypercompetitive environment, firms cannot count on a sustainable competitive advantage, but must continuously develop themselves in new directions. There are also increased technological pressures on firms. It has become accepted that technological life cycles in some industries seem to be decreasing compared with earlier (Dussage et al., 1992; Foster, 1986). This builds pressure on firms to constantly innovate (Kiernan, 1995). Much of this thinking stems from the electronics industry ± for instance, the new generation of SEGA video games that your six-year-old plays with contains as much computing power as the Cray supercomputers of the mid-1970s (Kiernan, 1995). Even though this situation does not have to be equally dynamic in other industries, it seems as if the belief in the technology dynamics creed is so strong that firms simply will follow that creed and, thereby, inflect the dynamics to themselves without the need (Noori, 1990). Either way, many authors agree on the need for firms to move technology up on the corporate agenda (Clarke, 1991) and make it a strategic issue (Bhalla, 1987; Betz, 1989; Jones and Smith, 1997; Drejer, 1996).
These basic ideas follow the work of authors such as Galbraith (1979) and Mintzberg (1994) and should not be too hard to comprehend. The ideas describe a change in attitude towards strategy in the school of product/market focused strategic management as opposed to the school of strategic planning, where the environment was assumed to be given. Miles and Snow describe strategy as the idea of strategic choice, i.e. that organisational structure is only partially given by the environmental conditions, which implies that top management has an important role to play as the primary link between the corporations and their environment. Thus, the effectiveness of organisational adaptation hinges on top managers' perceptions of the environmental conditions, and the decisions they make concerning how the organisations should cope with these conditions. The complex and dynamic process of strategic adaptation is broken down into three major problems,
2. A framework for innovation management The introduction has emphasised the need for firms to offer new products faster and faster as well as developing the underlying competencies dynamically in order to be able to compete in different markets in the nottoo-distant future. Thus, there is a need for a dynamic view of strategy in terms of both the external product-market perspective and internal competence perspective, see Drejer and Riis (2001) where the term ``focus competencies'' is proposed to denote identified competencies that need to be developed into tomorrow's core competencies. It would be sensible, however, to expect that not all firms should be innovative in the same manner. Innovation needs to be directed at products, markets, production competencies as well as administrative 5
Situations for innovation management: towards a contingency model
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itself is reserved for the results of the process of innovation, hopefully amply managed by innovation management. A further note on innovations: many have noted that innovation is more than just invention (e.g. Roberts, 1981), thereby emphasising that ideas need to be put into practice and inventions need to be commercialised in order to speak of innovation. In our fairly broad perception of innovation to cover more than just product innovation, it is probably necessary to say that idea/ inventions need to be implemented in the products, production or administrative competencies of the firm. Finally, there is the issue of how new an innovation should be. According to the strictest of definitions, innovations should be new to the world (e.g. Urabe et al., 1988). However, this ignores the idea of parallel development of technologies in different industries ± i.e. precursor technology development ± not to mention the difficulties experienced by any firm struggling to implement something new to the firm itself. A suitable compromise between views seems to be to say that an innovation should be new to the firms and its industry. So what are the activities that constitute innovation management? Notwithstanding the enormous differences between individual firms ± the very starting-point for this paper ± the author has identified five important activities that together define innovation management in its proper context. The first three activities define innovation management per se, whereas the last two define the context of innovation management. The activities are: (1) Technological integration. This refers to the integration between technologies and the product-markets of the firm (Iansiti, 1997) and emphasises the importance of satisfying the customer with the innovations of any firm. In other words, technology development (production and administration) needs to be integrated with product development (Drejer, 2001) also at the strategic level. (2) The process of innovation. By this is meant the cross-functional (business) process of activities that create innovations across the departments of the firm. Obviously, no one department is responsible for innovation and it is, thus, necessary to see how departments together create
which management must continually solve ± the entrepreneurial, the engineering, and the administrative problems. According to Miles and Snow (1978), these problems typically occur simultaneously. However, within this context, they will be treated as sequential: (1) The entrepreneurial problem has to do with defining the organisation's domain: often in terms of a specific product or service and a target market or market segment. In mature and ongoing organisations, attempts to modify the products or markets may be constrained by the organisation's existing manufacturing and management technologies/competencies. (2) The engineering problem involves the creation of a system that puts into actual operation management's solution to the entrepreneurial problem. The creation of such a system requires management to select appropriate technologies for manufacturing and distribution of the products or services, and to form new information, communication and control linkages to ensure proper operation of this technology. (3) The administrative problem is primarily that of reducing uncertainty within the organisation, i.e. rationalising and stabilising those activities that successfully solved problems faced by the organisation during the entrepreneurial and engineering phases. Furthermore, solving the administrative problem also involves formulating and implementing those processes that will enable the organisation to continue to evolve (innovation). Miles and Snow's model gives us an idea of some domains for innovation, i.e. the areas in which innovation could be focused, as well as the notion that these areas do not exist on their own but are related to one another. 2.1 How to create innovations The real issue now is how to create the desired innovations? It was Peter Drucker (1985) who first said that innovation is not just an outcome, but a process. In order to avoid confusion, the author will propose to call the set of managerial activities that together attempt to control the process of innovation ``innovation management''. Thereby, we can safely say that ``innovation'' 6
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innovations (see Cooper (1995) for one of the seminal accounts of this subject). (3) Strategic technology planning. This refers to the planning of technology and/or competence projects with the aim of maintaining a balanced portfolio of technologies and/or competencies (see Bhalla (1987) or Drejer and Riis (2001)). (4) Organisational change. Innovation is closely related to organisational change. No matter how small or large the innovation, it will affect the organisation with needs for new knowledge, new markets, new employees and so on. Thus, it is difficult to speak of innovation without considering organisational change. (5) Business development. Of course, innovation should be seen as a means for creating new and improved business for the company. That is innovation can both drive and be driven by business development as the second very critical contextual element of innovation management.
This is a relatively well-known idea that has been around since the late 1960s (Bhalla, 1987), where the Boston Consulting Group made empirical studies of the life cycles of technologies. It was found that technologies seem to have a life cycle much like the wellknown product life cycle, where the curve of performance measured as a function of either time or resources used for developing the technology will show an S-curved shape (Bhalla, 1987; Drejer, 1996). But how is technological dynamics related to knowledge and learning? In order to answer that we need to go beyond the empirical pattern of technological diffusion and see how the S-curve comes about. As summarised by Blackmon, ``. . . technological change is used to describe changes in knowledge that increase the volume of output or allow a qualitatively superior output from a given amount of resources . . . It is one of the key forces shaping organisational environments and thus in driving organisational evolution . . .'' (Blackmon, 1996, p. 6). Based on the early case studies and many others to follow, Anderson and Tushman proposed that technological change ``. . . constitutes an evolutionary system punctuated by discontinuous change . . .'' (Anderson and Tushman, 1990). A more recent refinement aimed at explaining technological change has been made in the form of the technology cycle model (Tushman and Rosenkopf, 1992). In this model, it is proposed that technological change is characterised by socio-cultural evolutionary processes of variation, selection and retention (Rogers, 1962). The model explains the S-curve phenomenon by dividing the life cycle into four elements; technological discontinuity, era of ferment, dominant design, and era of incremental improvement (Tushman and Rosenkopf, 1992). The technological discontinuity ± a major product or process breakthrough-provides a source of variation either by substituting an old technology or rendering possible a new one. This initiates an era of ferment in which many different variations compete. Furthermore, there will be technological rivalry between an old and the new technology. At some point, a dominant design emerges, as one variation ``wins'' the selection process. This initiates the era of discontinuous improvement of the dominant design that, eventually, leads to a new technological discontinuity. A
A thorough discussion of the framework for innovation management has been omitted for reasons of space. However, the reader is referred to Drejer (2001) for such a discussion.
3. The traditional perspective on contingency Innovation is closely related to technological dynamics in the literature. In fact sometimes management of technology is used together with management of innovation (Burgelman et al., 1989; Lowe, 1995). Even though the definitions based on Miles and Snow's model above contradict that technological dynamics is the only key to contingency factors of innovation management, we find it necessary to start this paper by discussing technological changes and the traditional perspective on contingency that results from them. Technologies evolve over time; some even say that technologies go through a life cycle (e.g. Rogers, 1962; Bhalla, 1987), passing from birth, low growth in performance plotted against resources or time, a period of stable, high growth, to, finally, a period of stagnation and replacement by a new technology. Technologies change over time. 7
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need not be made explicit because of the emergence of a dominant design. It was observed that the degree of process innovations in the car industry increased after the emergence of the dominant design (and, thus, decrease of product innovations) (Abernathy, 1978). This corresponds to observations that it can be difficult to transfer mature technologies due to the high degree of experiences and tacit knowledge related to those technologies. We take it that ± even though technical knowledge about the technology may be explicit ± knowledge about the technology's integration with other technologies and systems as well as knowledge about the commercial effects of the technology may even become more tacit. In summary, it can be expected that the type of problems encountered by firms working with a given technology will be significantly different before the emergence of a dominant design rather than after. In the first stage, problems will be of a technical character ± related to getting some sort of knowledge about the technology itself ± whereas later, as the technical problems are solved, problems will be of a more organisational character related to the use and integration of the technology. Therefore, management of technology will be different as technologies evolve. This has given rise to one of the most popular distinctions between environmental situations in the literature ± the distinction between creative destruction and technology exploitation. The distinction can be attributed to Joseph Schumpeter (Freeman, 1982; Drejer, 1996), who in his work switched interest from the large, bureaucratic organisations exploiting existing technologies to small, entrepreneurial organisations creating new technologies and, in that process, entirely new markets, competencies, and so on. Where one situation is stable and calls for one kind of innovation management, the other is dynamic and calls for an entirely different form of innovation management. However, the distinction may be too simple. Consider the following points: . Many firms are, today, based on much more than one technology and/or technologies that in themselves are systems of several technologies. Thus, the effect of one technology shift will be muzzled and diminish in importance compared with the days when
technological discontinuity is fundamentally different from other types of environmental change, as a discontinuity represents a dramatic break with existing practice ± and hence knowledge ± in an industry. Thus, technological changes are clearly very important for the core competencies of firms. The basic idea of technological dynamics and change is illustrated in Figure 1. Of course, the problems encountered and, hence, actual management of technology need to vary in the course of the technological life cycle. One of the bestknown accounts of the evolution of a technology ± the car ± documents several changes over a period spanning more than 70 years (Abernathy, 1978). For instance, it is documented how the emergence of a ``dominant design'' provides a standard around which organisations can converge. For instance, the dominant design of the car makes it possible for entirely new car-making nations to enter competition at a relatively late stage in the evolution of the car. We would say that this is because (some of) the knowledge regarding the car has become very explicit, whereas (some of) the knowledge prior to the dominant design was tacit knowledge on behalf of craftsmen making cars in very small batches. Abernathy (1978) describes in great detail how it was standardisation of parts and components that made it possible for Ford to massproduce cars ± an argument also made by Womack et al. (1990) in their account of the car industry. In all, some argue that the more knowledge developed about a technology, the more explicit this knowledge will be (Bohn, 1994). In the case of cars, the knowledge in question seems to be mainly the technical knowledge regarding cars, whereas knowledge about production systems, management, use of technologies Figure 1 Tushman and Rosenkopf's model for the technology cycle
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.
Schumpeter pinned his distinction down. In general, the IT-revolution of the 1980s and 1990s has created a tendency to more and more technologies being complex higher-order systems compared with the situation before WWII, when Schumpeter did his work. In general not all technology changes (of complex systems of technology) need to affect the entire system. Henderson and Clarke, for instance, distinguish between changes that affect components of a product and changes that affect the general idea ± or design concept ± of the product (Henderson and Clarke, 1990). Only a combination of those changes will lead to a situation of creative destruction.
then, what drives the development of such complex products? This is, indeed, very hard to say. In the case of cellular phones, it certainly seems as if it is not the end-users that drive development of new generations of cellular phones. But this does not have to mean that development is driven by technology push. In conclusion, we can say that it seems necessary to develop richer models for contingency of innovation management theory. Based on a firm empirical basis, Christensen (1998) discusses this in great detail. He concludes that there must be two kinds of technology changes from one life cycle to the next: (1) disruptive changes that create conditions like those envisioned by Schumpeter as creative destruction; and (2) sustainable changes that continue to support established firms and knowledge patterns in the industry (Christensen, 1998).
The two points above support the conclusion that not all technology changes from one S-curve to another need to be discontinuous. In some cases the overall effect will be less than creative destruction of the entire industry based on the technology in question. In other words, the traditional contingency model of discontinuous technological change versus technology exploitation of mature technologies also seems to be too simplistic a model to function as a contingency model for innovation management theory.
Whereas sustainable changes can be found to sustain established firms, disruptive changes lead to the demise of established firms in favour of newcomer firms. Christensen explains the difference between the two kinds of technological changes in terms of the S-curve. Sustainable changes continue along the same basic pattern as measured by the same performance measure, whereas disruptive changes start an entirely new S-curve (compared with earlier curves) that needs to be measured by another performance parameter. For instance, disc drives for computers have changed dramatically on several occasions, for instance in 1980, where a new kind of technology was part of enabling the personal computer (Christensen, 1998). However, it was difficult for established firms to foresee that, as their perception was driven by the old standard for performance (in that case capacity rather than size). Thus, new firms came to lead in the new market for personal computers. The typical example of the computerindustry would be that of IBM versus Apple Computers. Because Apple was driven by a value system that was about creating small computers for home use, its managers could see the value of a disc drive that was smaller than the generation before, albeit not performing quite as well. On the other hand,
4. Situations for innovation management The recent emergence of quite complex products consisting of, perhaps, mechanical components, electronics components, and software, not to mention interfaces to other IT products as well as a strong image part (of an expanded product concept), has given rise to many questions regarding the traditional idea of using the technological S-curve as a key to contingent use of innovation management theory. First of all, many of the new products, such as computers, cellular phones, and so on, are in effect complex technological systems of many technologies, each with individual life cycles. And how are many individual life cycles added in to one life cycle for the entire product per se? It seems as if the individual technologies and the complex products of which the technologies are a part need not develop according to the same logic. But, 9
Situations for innovation management: towards a contingency model
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IBM was driven by a value system that favoured making large computers for central computer departments in large firms and hence saw no value in a smaller disc drive. Unfortunately ± for IBM that is ± the market favoured the former option and an entirely new product was created. Interestingly, Christensen demonstrates exactly the same forces at play in an entirely different kind of industry, i.e. that of machinery for the building industry. Thus, the phenomenon does not need to be new at all and certainly not limited to IT-based industries. We have now established that there must be, at least, three situations for innovation management. We have the well-known situation of technology exploitation, i.e. after the dominant design has been established. This situation can, of course, be divided into a number of situations. This has been amply demonstrated by the equally well-known A.D. Little approach to technology investment (e.g. Bhalla, 1987), that distinguishes between monitoring/early adoption, selectively investing/follower, developing key technology, maintaining mature technology and divesting of obsolete technology as the life cycle nears another technology shift (Bhalla, 1987). Furthermore, we have established that changes of technology between life cycles can be either sustaining or disruptive rather than the traditional idea of a discontinuous technological change leading to creative destruction. Based on the discussions above, we can move beyond the popular distinction between creative destruction and technology exploitation and define three situations for innovation management: (1) Exploitation of existing technologies (2) Stable technological change (3) Disruptive technological change.
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with a number of case-studies from which we will draw selectively. The entire study is documented in a recent book by this author (Drejer, 2001) and must be presented selectively within this context for obvious reasons of space. 5.1 Managing innovation when exploiting existing technology The first situation corresponds to being on the smooth part of the technological S-curve, where technological progress is (relatively) easy to forecast and achieve and where things do not change discontinuously. This is wellknown in the literature. For instance, there is the A.D. Little model for investing in existing technologies (e.g. (Bhalla, 1987), where the development from dominant design to the next technology change is divided into three phases: (1) developing fast; (2) key to competitive advantage; and (3) mature. To each of these phases is attached advice on management of innovation: (1) monitor and invest selectively; (2) invest and develop; and (3) harvest and prepare to divest. Not surprisingly, this ties in nicely with a portfolio management thinking also known from product-market strategy (Bhalla, 1987). The literature also has cases of this kind of innovation management. The best-known, perhaps, is Abernathy's study of the automotive industry over some 60 years over the life cycle of the technology of cars (Abernathy, 1978). From dominant design ascribed to 1911 until 1978, Abernathy observed how the rate of innovation in the product gradually fell over time. However, this does not mean that the overall rate of innovation fell. Instead, the rate of process innovation increased over time, making the overall rate constant over time. Notwithstanding the many new car models and features of cars, this seems to be a reasonable explanation for many of the innovations in manufacturing technologies such as robotics, automation, and so on in the last 20-30 years. Furthermore, this author would like to speculate as to what happens even further down the road of the life cycle of an existing technology. Since 1978, there has been a vast focus on management and planning of manufacturing (such as Just-In-Time),
In the next section, we will discuss how innovation is managed in each of these three situations.
5. Managing innovation in the three situations In this section, we will discuss the actual management of innovation in each of the three situations discussed previously. This is based on a study of the literature combined 10
Situations for innovation management: towards a contingency model
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formulate some general conclusions regarding innovation management in the technology exploiting situation (Table I). What we expect to find in this situation is a kind of innovation management that is rather formalised and focused on process and administrative practices, as opposed to the popular notion of a chaotic, not managed process with emphasis on the product alone. There are not many changes within technology integration, the organisation or, for that matter, the market. Thus, the more reason for formalisation and systematic procedures for innovation management.
manufacturing strategy and philosophies of organising manufacturing (such as lean and agile manufacturing). Perhaps this corresponds to a third kind of innovation rising? The latter being administrative or managerial innovation? In the study made by this author, one of the case examples is the worlds second-largest manufacturer of pumps for water distribution, Grundfos. Grundfos is one of the four largest industrial firms in Denmark with annual sales of more than £700 millon and some 10,000 employees, half of whom work outside Denmark. With an annual production of 8 million pump units, Grundfos is one of the world's leading pump manufacturers, covering approximately 50 per cent of the world market for these pumps. In addition to pumps, Grundfos manufactures electric motors for the pumps and has a considerable production of electric motors for separate merchandising. Furthermore, Grundfos develops and sells state-of-the-art electronics for control pumps and pumps systems. The Grundfos Group is represented by 55 companies in 38 countries. Regarding innovation management, Grundfos has followed a path remarkably similar to the one outlined by Abernathy for the automative industry. The company was founded in 1945 by the father of its current CEO, who still manages the company, on the basis of several inventions within product technology and process technology. Since very early on, the integration of innovations in product and process technology has been considered paramount at Grundfos as witnessed by the establishment of a joint product development and (process) technology development facility in 1990. The development of massproduction facilities in 1955 is considered a landmark in Grundfos' history, which supports the notion that the rate of innovation over time changes from product to process technology. And, finally, in the last ten years, more and more emphasis has been put on the managerial side of the firm and its development. For instance, Grundfos has embraced the idea of total quality management and put tremendous efforts into business excellence, finally winning the national quality award in 1999. Grundfos now has its eye on the European Quality Award within the next five years. Based on the empirical and theoretical basis briefly discussed above, it has been possible to
5.2 Managing innovation when subject to sustainable changes The second situation corresponds to a situation where a series of technologies replace one another within the same type of S-curve, i.e. measured by the same performance parameter over time. Thus, the technologies can easily differ from one another, but many other things are constant over time. This is a new situation in the literature. Christensen, of course, has a discussion of this situation (Christensen, 1998) and seems to be seminal in that respect. Christensen's work is based on empirical work and aims at describing the situation itself rather than innovation management in that situation. However, a few conclusions on innovation management are made in Christensen's work ± mainly on how the sustainable situation differs from creative destruction. This is mainly with respect to the market that does not change preferences totally, as happens in disruptive technological changes, but rather does so slowly with the addition of new features to products from generation to generation. Thus, business development from scratch is not a strong feature of this kind of innovation management. Instead, focus is typically on developing the technologies of which the products consist in order to offer new generations of improved products as measured on the same performance parameter as the old products. So what we find within industries in this situation are products that get lighter, stronger, smarter, and so on over the years, often at a constant rate. Christensen's main empirical basis is that of the computer industry from the age of so-called mini-computers to the PC and its 11
Situations for innovation management: towards a contingency model
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Table I Innovation management in the technology exploiting situation Element
General characteristics
The innovation process
The process is formalised and documented in procedures inspired by the systematic stage-gate models (Cooper, 1993), with a clear linear progression clearly separated by formal gates Technology integration Technology integration is formalised as a part of the organisational diagram with departments or sub-departments for important technology areas Strategic technology planning Is an explicit and formal activity according to the traditional notion of an annual planning process with analysis, portfolio formulation and plans for technology development Takes its starting-point in the existing product-market strategy of the firm Organisational change Management attempts to trim the organisation and/or develop procedures and processes. Typically this is directed towards the administrative competencies of the firm Change is minor compared with the other case firms in Drejer (2001) Business development The organisation can no longer grow and prosper by means of technological leadership alone Focusing on the market has been singled out as the other important means for growth in the current strategic plans of the firm
In the author's study, an interesting case in mind is that of a mobile telephones producer, currently part of Siemens Mobile Phones, located in the northern part of Denmark. A mobile phone is a technology in itself, but that technology can be broken down into a set of technologies from which the overall system of a mobile phone is constructed. Sustainable innovation, then, takes place in this industry by changing elements of the overall system, the mobile phone, in order to improve the system. The performance parameter of this technology has been that of weight plus operation and stand-by time. The interested reader will know that Denmark ± in particular its northern part ± held a leader position in the emerging phase of mobile telephones and that there still is a ``telecom valley'' in northern Denmark with all the major players in the industry. The case company was one of two firms that started all that as an offspring from an existing radio communications company called SP Radio. The two firms, Cetelco and our case firm Dancall, started out making communications products for sea and land, but quickly joined forces in a common development company (DC Development) in order to develop the first mobile phones. This development was completed in the late 1980s and set the two firms ± along with the new offspring ± on the race for developing generation after generation of mobile phones. In the course of doing that the firm has experienced major
cousin, the laptop PC. It is in industries related to the major technological dynamics of information technology that we can find many examples of industries that exist in the sustainable situation. Having said that, Christensen also offers the example of building machinery ± an industry where the products show similar characteristics, albeit at a much slower rate. And it is the speed of technological changes that is the most defining feature of how innovation management should be carried out in the sustainable situation. If change is as slow as in the machinery industry, this situation roughly corresponds to the traditional technology exploitation situation, but this is altered with quick change. The faster the clock speed, the more dynamic innovation management needs to be and the larger the emphasis has to be on meeting deadlines and on time. Since the sustainable situation requires that technology integration is reconstructed with every technological change (new technologies emerge to offer better solutions to the same problem), this becomes a key point in innovation management in this situation. In turn, the continuous reconstruction of technology integration drives business development. Even though products or processes are to solve the same problem as earlier, new technologies may offer add-on features and new market opportunities, thus creating the need for constant awareness of business creation as an innovation management issue. 12
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management in the sustainable situation have been formulated (Table II). In the situation of sustainable change, it is necessary to innovate faster and constantly. Furthermore, we would expect that there would be a focus on product innovation and process innovation ± and not on administrative innovation. Therefore, many of the means for innovation management will have to be similar to the means in the technology exploiting situation. For instance, portfolio methods, technology planning, and many others have been found in the two cases of, respectively, technology exploitation and sustainable technology changes. What differs stems from the need to innovate fast and constantly. The empirical approaches have been found to be much more formalised and focused on meeting deadlines. Thus, project management and R&D management are much more a top management activity and done in a very formalised manner in this second situation.
growth and gone from 40 to almost 2,000 employees. Furthermore, the firm has been bought and sold several times, having had the names Armstrad, Bosch and Siemens in the process. It was not until the take-over by Siemens Mobile Phones in early 2000 that the manufacturing part of the original company was sold off to Flextronics, that now owns the single largest manufacturing firm in the region. Regarding innovation management, there are many interesting things to learn from this case. The first is the preoccupation with time. The clock speed in the mobile phones industry is extremely fast with new generations of products coming out every year based on new platforms every second year. Even if the industry, via the European Standardisation Organisation ETSI, so far has been able to agree on specifications for the next generation of products, the time frames are so small that planning for deadlines and timing are absolutely essential in the industry. In fact, timing is much more important than getting the latest technology into the products ± if a technology is not mature enough (developed in time) for one generation of products, the technology is simply assigned to the next generation. We see here that sustainable innovation is not the major, one-off innovation of which we are so used to thinking. Rather, the products (in this case) develop constantly and in a rather organic fashion, as technology integration is reconstructed from productmarket to technology and back once every year or every second year. In order to survive these conditions, innovation management needs to be relatively formalised and focused on risks that can jeopardise the timing of development efforts. In the case company, organisational change, furthermore, has been quite large partly because of the growth of the industry. But another important factor that has created organisational change has been the need for employees with new kinds of knowledge from generation to generation of the overall technology. Since the speed of change has been so great, there has been no time to educate the existing workforce and the case company has been forced to change major parts of its employees at several occasions. Based on the empirical and theoretical basis discussed above, general conclusions regarding the elements of innovation
5.3 Managing innovation when subject to disruptive changes The third, and last, situation actually corresponds to the stereotype of creative destruction with which we are so familiar and innovation is normally associated with the products of the firm. What happens is that the technology on which the products are based changes disruptively, leaving the field open for an entirely new kind of products and rendering the old products obsolete with one stroke and destroying entire industries in the process. Because of the surprising nature of such changes, established firms in the old industry rarely see the change coming and go under as a result of creative destruction. The creative part of this process is that a new industry is created with new firms taking advantage of the new situation. This situation is so well-known and discussed that we will not focus on it to the same extent as the other two. However, let us discuss some interesting aspects of disruptive technological change. Christensen's empirical evidence (1998) clearly shows that disruptive technological change favours new firms, whereas sustainable change favours established firms. But Christensen also points to some interesting evidence of disruptive change, namely the fact that established firms often have the technologies of the next/new industry at hand ± sometimes 13
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Table II Innovation management in the sustainable technology change situation Element
General characteristics
The innovation process
Formalised into a procedure, albeit not a a stage-gate model Focus in the procedure is on timing and planning of activities over time Activities are clearly bound by available time Technology integration Difficult when it comes to establishing a new integration ± and thus balance ± that must be created with each new generation of products Products are seen as configurations of technologies that change over time, thereby affecting the market Strategic technology planning Is explicit and formalised into procedures The process is also concerned with getting knowledge workers involved in an organisational process of sharing knowledge about technologies and their use Organisational change A large amount of organisational change is going on at employee level because of the constant change in knowledge and technologies over time Another factor is the growth often associated with markets of this kind ± the market for mobile phones has grown rapidly in the last ten years Business development Always central. Business development is related to the constant change of the technology integration balance, where it is crucial to make sure that each new generation of products is in line with rival products and the needs of the market
1990, Principia has gone through all the stages through which a new firm, according to the models of new firms, has to go. First, the entrepreneurs developed a product ± an aluminium bicycle frame ± for their own use (there's market research for you) and learned how to design and construct in aluminium in the process. Later they had to develop process technologies and learn how to produce their products ± and build a manufacturing facility in the process. At the same time, marketing efforts were being designed and undertaken. This is the typical story, even including a bankruptcy in 1992, and will not be presented in its entirety here. Today, the company is the world's leading manufacturer of high-end competition bicycle frames and enjoys a niche position that seems relatively well protected. Based on the empirical and theoretical basis discussed above, the following general conclusions regarding the elements of innovation management in the disruptive situation have been formulated (Table III).
having developed them years before ± but fail to see how the technologies can be applied to create a new industry. This was the case, when Steven Jobs and Steve Wozniak developed the Apple computer and later Apple II. The first was based on existing components, whereas the other was based on technologies developed elsewhere and offered to IBM. For instance, the 5.25-inch disc drive was developed at Xerox's Palo Alto Research Center and offered to IBM as well as Apple. Only the latter saw the potential in the new technology and made the modern PC industry possible in the process. According to Christensen (1998) a certain kind of blindness seems to occur in established firms. Resources, business intelligence, marketing, and attention overall are directed towards the existing customers and it is hard to analyse/imagine a market that is not there just yet. Thus, we are left with the popular notion of the newly established entrepreneurial firm. This is a kind of firm that the author is sure most readers love and cannot help but admire for their courage and commitment to making decisions. In the study mentioned earlier (Drejer, 2001) one of the cases is that of Principia in Denmark, a company that has been an integral part of the revitalisation of the competition bicycle industry, when it changed from steel to aluminium some ten years ago. From being an against-all-odds adventure founded by three tri-athletes in
6. Conclusions In this paper, we have tried to find a better key to relating theory to the practice of actually managing innovation. This is to say that the way theory can be divided into convenient and distinct schools of thought does not necessarily correspond to the way 14
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Table III Innovation management in the disruptive technology change situation Element
General characteristics
The innovation process
Is an implicit activity in the thinking of a very small number of key individuals applying and building tacit knowledge and experiences in the process Technology integration The innovators are themselves representatives of the customers, thereby having a unique (albeit often tacit) understanding of the market side of integration From that the ways to fulfil the needs of the customer are deducted and technologies found. Some iteration can be expected ± not all needs can be fulfilled Strategic technology planning Is not a formal activity at all Deals with integrating product development with the development of other technologies, most often process and production technologies Organisational change Firms in this situation either experiences total turn-around or developing an entirely new firm Either way, the firm must identify and build the necessary competencies for its existence and success Business development Closely related to technology integration, since this is used as a means for making sure that the needs of the customers are formulated and translated into technological needs for innovation management
Other changes take place within the same set of assumptions and beliefs, thereby sustaining established firms and competencies ± those changes we call sustainable. But that is just one way of reformulating the traditional distinction between technology exploitation and change ± the other lies in the detailed discussion of each of the three situations. This paper does not allow for a detailed discussion of each of the three situations. Further research must go into that ± preferably by means of case studies of firms in each situation. In this paper, we have merely scratched the surface of each of the three situations based on a recent book by this author (Drejer, 2001). However, I will assert that a detailed discussion will reveal that each of the three situations will reveal that each of them requires methods, models, theories and so on from several of the four schools of thought discussed in the introduction to this paper. Perhaps not surprisingly to some, this still represents a large step ahead for the pragmatic application of theory to innovation management in practice. Further research may help to evolve existing theory even further in that direction. One thing that will further complicate matters is the evolution of firms in their environment over time. For instance, firms in a disruptive situation almost always evolve as the situation stops being disruptive over time ± due to the maturing of the underlying technology. In other words, firms may tend to
managing innovation is practised in organisations. This is not to say that existing theoretical schools of thought have no value. For one thing such schools of thought (for an example of schools of thought related to management of technology see Drejer, 1996), are rooted in different times and, furthermore, based on different basic assumptions about technology, organisations and management. Thus, they have an academic value and usefulness that should not be overlooked. However, the practical value of such schools of thought about theory depends on the formulation of good contingency factors to ease the translation from theory (schools of thought) to practice (a pragmatic use of theories, models and methods based on the situation at hand). I have asserted to the reader that a reformulation of the traditional distinction between technology exploitation and discontinuous technological changes (leading to creative destruction) might prove a step towards good contingency factors. First, we have managed to distinguish between ± at least ± three situations, because a technological change from one S-curve to another can be a different thing to different firms. Some technological changes go against the assumptions on which firms base their knowledge of the market, customers and the products. Hence, it becomes almost impossible for established firms to survive such changes ± those we call disruptive. 15
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be in different situations at different points in time ± and hence need different forms of technology management at different points in time. Apart from emphasising the dynamics of the world, this points towards the need for a very pragmatic view of innovation management theory as something that needs to be applied differently at different points in time and/or in different firms. This paper basically calls for a very dynamic view of the application and practice of innovation management theory, while at the same time insisting that some contingency factors can and must be identified and described. It seems a difficult balance to reach, but I believe that it is possible to push further along this route in research. This paper, furthermore, highlights another point. Innovation management is not just innovation management. It needs to be done differently in different situations (and different firms, of course). The proposal of three situations for innovation management is one step towards a contingency model for innovation management, something that the author believes is very much called for. This paper has been a first step towards such a contingency model, but should not be the last step. Much more research is needed, of course, especially of the empirical kind. We need case studies and empirical examples of innovation management in order to understand how it is ± and needs to be ± done in practice. And we need further theoretical studies and formulations of models for innovation management. Let us begin!
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Bohn, R.E. (1994), ``Measuring and managing technological knowledge'', Sloan Management Review, Fall, pp. 61-73. Burgelman, R.A. and Sayles, L.R. (1989), Inside Corporate Innovation, The Free Press, New York, NY. Christensen, C.M. (1998), Innovators' Dilemma, Harvard Business School Press, Cambridge, MA. Clarke, K. (1991), ``Pathways to technology strategy: technological configurations, stability and change'', Technology Analysis and Strategic Management, No. 1. Cooper, R.G. (1993), Winning at New Products, Perseus Books, Cambridge, MA. Cooper, R.G. (1995), ``Developing new products on time, in time'', Research-Technology Management, Vol. 38 No. 5, September/October, pp. 49-57. D'Aveni, R.A. (1994), Hyper-competition ± Managing the Dynamics of Strategic Maneuvering, The Free Press, New York, NY. Drejer, A. (1996), ``Frameworks for the management of technology: towards a contingent approach'', Technology Analysis and Strategic Management, No. 1, March, pp. 9-20. Drejer, A. (2001), The Innovative Firm, (in Danish), Bùrsen Bùger. Drejer, A. and Riis, J.O. (2001), ``New dimensions of competence development in industrial enterprises'', The International Journal of Manufacturing Technology and Management, Vol. 2 Nos 1-7, pp. 660-82. Drucker, P.F. (1985), Innovation and Entrepreneurship, Harper & Row, London. Dussage, P., Hart, S. and Ramanantsoa, B. (1992), Strategic Technology Management, Wiley & Sons, New York, NY. Edvinson, L. and Malone, T. (1997), Interllectual Capital, HarperCollins, New York, NY. Foster, R.N. (1986), Innovation ± the Attacker's Advantage, Summit Books, Oklahoma City, OK. Freeman, C. (1982), The Economics of Industrial Innovation, Pinter, London. Galbraith, J. (1979), Designing Complex Organizations, Addison-Wesley, Reading, MA. Handy, C. (1995), The Age of Unreason, Arrow Business Books, London. Henderson, R.M. and Clark, K.B. (1990), ``Architectural innovation'', Administrative Science Quarterly, Vol. 35, pp. 9-30. Iansiti, M. (1997), ``Technology integration: managing technological evolution in a complex environment'', Research Policy, Vol. 24, pp. 521-42. Jones, O. and Smith, D. (1997), ``Strategic technology management in a mid-corporate firm: the case of other controls'', Journal of Management Studies, Vol. 34 No. 4, pp. 511-36. Kaplan, R.S. and Norton, D.P. (1996), The Balanced Scorecard ± Translating Strategy to Action, Harvard Business School Press, Cambridge. Kiernan, M.J. (1995), Get Innovative or Get Dead!, Random House, London. Lowe, P. (1995), Management Technology, Chapman & Hall, London. Martin, J. (1996), Cypercorp, Amacom, New York, NY. Miles, R.E. and Snow, C.C. (1978), Organizational Strategy, Structure, and Process, McGraw-Hill, New York, NY.
References Abernathy, W.J. (1978), The Productivity Dilemma, John Hopkins University Press, Baltimore, MD. Anderson, P. and Tushman, M.L. (1990), ``Technological discontinuities and dominant designs ± a cyclical model of technological change'', Administrative Science Quarterly, Vol. 35, pp. 604-33. Betz, F. (1989), Managing Technology, Englewood Cliffs, NJ. Bhalla, S.K. (1987), The Effective Management of Technology, Batelle Press, Columbus, OH and Addison Wesley, Reading, MA. Blackmon, K. (1996), ``Absorptive capacity and technological changes'', PhD thesis, University of Miami, Miami.
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Mintzberg, H. (1994), The Rise and Fall of Strategic Planning, Prentice-Hall, New York, NY. Noori, H. (1990), Managing the Dynamics of New Technology, Prentice-Hall, Englewood Cliffs, NJ. Roberts, E.K. (1981), Generating Effective Corporate Innovation, The Free Press, New York, NY. Rogers, E.M. (1962), The Diffusion of Innovations, The Free Press, New York, NY. Savage, C.M. (1990), Fifth Generation Management, Digital Press, Woburn, MA. Stacy, R. (1999), Stategic Management and Organizational Dynamics, Pitman, London.
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Stewart, T. (1997), Intellectual Capital ± the New Wealth of Organizations, Nicholas Brealey Publishing, London. Tushman, M.L. and Rosenkopf, L. (1992), ``Organisational determinants of technological change'', in Staw, B.J. and Cummings, L.L. (Eds), Research in Organizational Behavior, Vol. 14, JAI Press, Greenwich, CT, pp. 311-47. Urabe, K., Child, J. and Tagono, T. (1988), Innovation and Management, Walter de Gruyter, Amsterdam. Womack, J.P., Jones, D.T. and Ross, D. (1990), The Machine that Changed the World, Van Nostrand Reinhold, New York, NY.
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The service imperative
Innovation as the core competency of a service organisation: the role of technology, knowledge and networks
The increasing importance and growth of services as a major global industry (Shugan, 1994) have been of interest to academics and practitioners alike. There is a consensus that economic growth, a higher disposable income and technological advances have contributed to the rapid growth of service-sector enterprises (Mattsson, 1995; Patterson, 1995), and have substantially increased their economic importance. According to GroÈnroos (2000), today firms compete on the basis of services, and not on the basis of physical products. The competitive advantage of services has become increasingly evident, as there is little to differentiate competing products from the customer's perspective. For example, to a customer, there is no apparent difference between a Sony television and a JVC television; it is the service offered by the retail store that manifests true value. The global dissemination of knowledge through information technology (IT) has limited benefit with regard to product differentiation. Advances in IT have reduced the life-cycle of products and, in addition, have revolutionised the way in which business is conducted in the new economy. Billions of people worldwide are currently connected to the Internet, and exponential growth in this international network means that millions more are being connected annually. The Internet enables customers to engage in a higher degree of self-service (Hallowell, 2001). Moreover, the nature of business today demands that firms interact with their customers and business partners using technology to provide services instantaneously across international borders. Essentially therefore, service encounters relate to ``high-touch'' (traditional face-to-face interaction) and ``high-tech'' (those encounters that take place over a long distance via a technology interface). Thus advances in technology have meant that the provision of services has become the business imperative in today's competitive marketplace. Moreover, services have become the uncompromisable core component of business and, from a management perspective, they have evolved to assume a strategic function. A firm's service function concerns and interacts with almost every activity or component of the firm. These
Jay Kandampully The author Jay Kandampully is Associate Professor at the UQ Business School, The University of Queensland, Ipswich, Australia. Keywords Service, Core competences, Innovation, Networks Abstract Services lie at the very hub of the economic activity of all societies, and interlink closely with all other sectors of the economy. The exponential growth of services internationally has not only intensified competition, but has also simultaneously posed a challenge and an opportunity for the managers of services. This study examines the factors underlying the growth of services, and emerging views on what constitutes a ``resource'' for service organisations. To this end, the roles of technology, knowledge and networks are examined as interdependent factors. It is argued here that today's ``resources'' are the culmination of various advances in knowledge. Technology facilitates the maintenance of networks with customers and partners inside and outside the firm. The network of relationships renders the firm's capabilities ``amorphous'' in nature. This study suggests that this amorphous knowledge represents the true ``resource'' in a service firm, and ultimately provides the creative potential for ``innovation'' ± the so-called ``core competency''. However, innovation per se does not benefit the firm unless it manifests superior value in the customer-driven marketplace. Moreover, this study argues that service innovation results only when a firm is able to focus its entire energies to think on behalf of the customer. Electronic access The research register for this journal is available at http://www.emeraldinsight.com/researchregisters The current issue and full text archive of this journal is available at http://www.emeraldinsight.com/1460-1060.htm European Journal of Innovation Management Volume 5 . Number 1 . 2002 . pp. 18±26 # MCB UP Limited . ISSN 1460-1060 DOI 10.1108/14601060210415144
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ultimately improve its efficiency and effectiveness. Hence, it can be argued that the value of a resource is dependent on present information or knowledge. The important words here are ``present knowledge'', as new knowledge has the ability to transform anything in this world (including humans) into a resource. This also implies that resources deemed valuable today might have limited value tomorrow if new knowledge develops a superior substitute. In the past, Ohmae (1989, p. 153) points out, there were gross inefficiencies ± some purposeful, some not ± in the flow of information around the world. For example, although the Chinese developed the knowledge of looming in the thirteenth century, it was the British who built that knowledge into a commercial business in the eighteenth century. However, with the increase in knowledge, its global dissemination (through networks and non-restrictive media such as the Internet), and its creative adaptation, many existing resources will diminish in value. For example, the value of natural rubber decreased in the world market following the invention of synthetic rubber made from crude oil. Similarly, the production of semi-conductors (high knowledge component product) was previously the economic strength of computing science in Taiwan and Korea. Today semi-conductors represent just another mass-production item. Moreover, in this age of technology, Porter (1985, p. 166) argues that a firm is actually a collection of technologies, and it is the technologies embodied in a firm's knowledge, manifested as product or service, that proffer a potential competitive advantage. It is therefore the knowledge that has the potential to add value to the offer of a product or service by a firm. The true focus has thus shifted from natural resources (physical) to knowledge resources (mental). There are numerous factors that have contributed to this paradigm shift, one of the most important of which is IT. The advent of computers in the workplace dates back to the early 1950s. However, because computers were predominantly utilised to hasten paper-based processing, they failed to effect any fundamental changes in the business process. It was not until the 1990s ± with the coming together of low-cost computers and IT in the form of a universally accessible phenomenon
include people, process, or physical evidence (both tangible and intangible evidence representative of the firm from the customer's perspective); internal and external customers; and the various networks, alliances and partners. External relationship networks have become an essential prerequisite if a firm is to achieve the capabilities and knowledge required to serve the holistic needs of customers. Service leaders successfully introduce products and services to the market far in advance of customer expectation. Moreover, in the customer's mind, a firm maintains its market leadership position by continuing to operate at the cutting-edge and by extending conventional parameters. Service firms today are expected to delight customers with their creativity and innovation. Thus, in operational terms, innovation can be translated as a firm's foresight to ``think for the customer'' by creating services that ``drive'' the marketplace (offer superior value to the customer). The ongoing dominance of services in the developed and developing economies around the world has raised a challenging question for service enterprises ± as to what constitutes ``resource''. This is a fundamental issue, which will invariably affect strategic decisions and subsequent management activities in service organisations.
``Resource'' in the new millennium The study of resources has been a focus of interest to economists for many years. A firm's or a nation's resources have consistently been recognised as important, and many studies have been conducted to determine ways of rendering them more effective (Andrews, 1971). However, the conceptual definition as to what constitutes a firm's or a country's ``resources'' has changed dramatically with the advent of technology. Today it incorporates a spectrum of components never previously considered in economic or management theory (Pilzer, 1990). Moreover, Barney (1991, p. 101) expands the common notion of a firm's resources to encompass ``all assets, capabilities, organisational processes, firm attributes, information, knowledge, etc.'', and indicates how such resources enable the firm to conceive of, and implement, strategies that 19
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(Internet) ± that computers had a transforming impact (Mendelowitz, 1999). It is, indeed, the advance of technology through mechanisation and mass production that has given rise to the economic prosperity of Western countries following the technological revolution in industry in the early part of the twentieth century. In economic terms, technology directly cuts costs; more importantly, however, its most radical impact has been on conceptual thinking, in terms of the designation of ``resources'' by a firm or country. This can be likened to the hunter-gatherers of the past, for whom land did not manifest itself as a resource until the human mind developed the methods and the know-how (technology) of farming (Pilzer, 1990). The creative utilisation of distance and time, referred to as the ``death of distance'' through the impact of technology, possibly constitutes the single most-important economic force that will shape society and the service industry in the first half of this century (The Economist, 1995). Services today are allpervasive, and we are dependent on those services to maintain our lives. For example, services such as: telephone, television, radio, taxi, bus, electricity, water, sewerage, security, restaurant, library, gym, bank, grocer, post, hairdressing, health care, and so on, are required by almost every citizen. In fact, technology and its capacity to affect every aspect of our lives have always been major determinants of human progress (Pilzer, 1990). It is proposed here that, on a macro level, the ``resources'' of the service organisation can be attributed to three interrelated factors of modern business, namely: technology, knowledge, and networks. The following sections will discuss these three factors individually and will examine how they contribute to ``service innovation'' ± the core competency of any firm.
example, the automobile industry. Fifteen years ago, we were able to attend to minor engine problems in our cars: adjusting the carburettor, for example. Today's technology has replaced carburettors with fuel-injectors, and we are obliged to take our cars to mechanics for tuning ± we no longer have a choice. Similarly, when we buy a washingmachine or dishwasher, our concerns now extend to the various support services provided by the seller in the event of something going wrong. The service component not only has become an integral part of most manufactured products but also has become the source of sustainable and strategic competitive advantage (GroÈnroos, 2000, p. 6). In this hyper-competitive environment, it is imperative that firms understand the values that customers attribute to the service package ± a combined product and service offering (Kandampully and Duddy, 1999a, p. 54). Technology has similarly augmented the knowledge required in almost every type of labour in industry. Knowledge ± through training ± has become a prerequisite for success in the job market. For example, secretaries who were once required to type and answer the telephone are now expected to demonstrate equal proficiency in various computer programs, and to possess the aptitude to learn new programs when these are introduced. Moreover, the increasing use (and incessant update) of technology in almost every field has added a knowledge component to every manual job, and has required firms to seek employees who are willing and able to update their knowledge on an ongoing basis. In addition, technology displaces low-skilled labour from the traditional workplace and offers new opportunities for skilled labour with higher levels of knowledge. Within this new technology paradigm, experience is of limited value because new knowledge is essential to make oneself productive with the adoption of new technology. Thus, knowledge and the increasing service component have significant implications for both the labour market (in terms of ongoing learning) and for the industry (in terms of continuous upskilling). In the past, labour represented, and was considered by management to be, the inevitable cost incurred in the production of goods and services. However, under the present extended definition of ``resources'',
Impact of technology on services Advances in technology have directly influenced the growth and importance of services, in terms of independent serviceofferings, and as components of product and service packages. Service has become a business essential in manufacturing (Zeithaml and Bitner, 1996, p. 10). Consider, for 20
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As the foundation of economies shifts from natural resources to intellectual assets, managers will be compelled to examine not only the knowledge underlying their organisation's success and competitive advantage but also, more importantly, the management of this knowledge (Hansen et al., 1999). Moreover, in an age in which business operates within networks and alliances, international boundaries pose no real limitation. Historically, many countries and industries prohibited the emigration of skilled workers (for example, carpet-weavers in Persia, paper and pottery craftsmen in China, silk-weavers in India). In those days, a worker's skill in a particular trade or craft represented specialist knowledge, capability and competence. Today, however, even if a particular worker's knowledge is deemed valuable to the company, it is seldom accorded the status accorded to a physical asset in the firm's book of accounts. Moreover, in the present everchanging world of global business, technology, competence, and capability, each, in its own way, is a manifestation of a firm's knowledge assets operating at different levels of the organisation (Boisot, 1998, p. 4). According to Drucker (1993, p. 38), knowledge represents a key personal and primary economic resource. He argues that traditional factors of production ± such as land, labour and capital ± have become secondary. He asserts that ``knowledge is the only meaningful resource today''. Hence, a worker with knowledge commands a leading role and status, as his or her knowledge represents the firm's single greatest asset. Moreover, the aptitude of the worker and the firm to seek new and up-to-date knowledge (the concept of the ``learning organisation'') is the only means of sustaining the value of the firm's knowledge resource. However, this new primacy of knowledge requires managers to rethink the fundamental practices of management. Webber (1993) asserts that managers not only must invest in the necessary information tools (to support and enhance the productivity of the knowledge workers), but also need to nurture a partnering relationship with them. In essence, a firm's strategy for knowledge management should reflect its competitive strategy (Hansen et al., 1999). In this competitive environment, knowledge is progressively being perceived as the core driver of
labour is valued not in terms of physical assistance, but in terms of mental contribution. The labour within an organisation or country is no longer a designated cost but a valuable resource. The true economic value of a person is primarily attributed to his or her knowledge and creative skills. This view is highlighted by Moody (1991) in the New York Times Magazine with his assertion that ``Microsoft's only factory asset is the human imagination''. Hamel and Prahalad (1989, p. 67) suggest that managers nurture and develop competitive intelligence at every level of the organisation in order to build the firm's competitive advantage. A similar view is held by SONY's chairman, Morita (1988), who indicated that it is not the manual labour of employees that allows a company to dominate the global market, but the contributions of the employees' minds. More recently, it has been recognised that the contribution of the human mind (knowledge) will play a major role in tomorrow's service industries (Peters, 1994). Indeed, talent-based enterprises have become commonplace in the innovative world of business. Business success will depend on an organisation's ability to imagine and/or create a need (Pilzer, 1990). Thus, it can be argued that innovation in services reflects the creativity of the human mind (knowledge). It is, indeed, progress into the unknown ± through new knowledge ± that will enable an organisation to attain wealth and the allimportant competitive advantage (Kelley, 1997). It is the people within a service organisation that create and innovate an organisation's service offer. According to Peters and Austin (1994, p. 98), irrespective of where technology leads, service differentiation comes from people and their contribution to the infinite field of knowledge.
Contribution of knowledge Developing, using and leveraging knowledge are essential for all organisations and/or countries to sustain economic progress. ``Knowledge is indisputably the primary basis for value-added in today's companies'', claims management consultant Peters (1994). It has become an accepted fact that, in the new millennium, we will encounter advances in technology-information-knowledge services. 21
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benefit of the customer ± by creating strategic alliances both horizontally and vertically (internal and external relationships) with individuals and firms (Peppers and Rogers, 1997). Horizontal strategy, according to Porter (1985, p. 319), is the essence of corporate strategy as it seeks to gain competitive advantage by creating links among distinct but interrelated businesses. It is suggested here that the core competency of the firm (as valued by the customer) is creatively developed by the firm's ability to nurture enduring relationships with various parties inside and outside the organisation. The collective competency of the firm is thus derived from the various networks of stakeholders of the firm ± for example: customer, employee, retailer, supplier, and shareholder (see Figure 1, Kandampully and Duddy, 1999b). Although various other stakeholders can be included in the network, the above five stakeholders (partners) constitute those participants that are essential to a service firm's basic operation. Through network partners, the firm essentially aims to enhance the value of its offerings ± to the benefit of customer, firm and stakeholder simultaneously. Developed as networks, the various relationships that the firm nurtures and maintains frequently constitute the life source for many leading-edge firms (Kandampully and Duddy, 1999a); indeed, most large and small projects invariably involve numerous alliances and partners. This is particularly
competitiveness; more importantly, knowledge extends beyond individuals, groups, or corporations to mutually supporting groups (Gummesson, 1999, p. 132). It is this extended network of relationships that, Gummesson argues, will reap the creative potential of knowledge. Products and services offered in the marketplace today have become increasingly complex, with most organisations offering not one product or service, but a collection of products and services (Albrecht and Zemke, 1985). Hence, most companies are nothing but a ``chain of services'' (Quinn et al., 1990). It is the firm's service package that augments the value of both product and service offerings (Chase and Garvin, 1990). Moreover, it is the specific configuration of the different components in the firm's service package (competence) that communicates added value to the customer. Management literature attributes a firm's competitive advantage to the firm's capabilities or core competencies (Prahalad and Hamel, 1990; Stalk et al., 1992; Teece and Piscano, 1994). A firm's core competency is dependent on its capacity to combine core skills creatively (Prahalad, 1993), from both within and outside the organisation. However, ``what matters is the creative bundling'' of a firm's core competency (Prahalad, 1993) and, thus, the need for a focus on the factors that signal value to the customer.
Contribution of networks of relationships
Figure 1 Service relationships
In this competitive global market, customer focus requires a firm to gain a comprehensive understanding of the buyer's entire value chain (holistic needs), not only as it is of today, but also as it will evolve over time (Slater and Narver, 1994, p. 22). Moreover, in most cases, customers' holistic requirements frequently extend beyond that capable of being effectively fulfilled by a single firm's product or service (Kandampully and Duddy, 1999b). Thus, firms which understand customers' holistic needs will be able to mix and match various products and services commensurate with customers' specific needs. If customers require products or services that are not within the realm of a firm's core competency, the firm should find ways to procure those competencies ± for the 22
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pertinent to services, as networks are endemic to most service businesses (Heskett et al., 1990, p. 160). The competitive advantage of Federal Express over its competition was attributed to advanced technology networks that offered customers the means of ``tracking'' their package during transit. Today's service organisations traverse conventional boundaries. Firms that seek assistance and enter into alliances with various individuals and suppliers do so, not as a cost-saving exercise, but to seek out specialist know-how to extend their core competency. In modern business, the term ``out-sourcing'' has been accorded a new meaning and has subsequently been replaced with ``out-partnering'' (Peters, 1994). The experts inside and outside the firm can therefore essentially be deemed the firm's ``competency-contributing partners'', because it is with their assistance that the design and delivery of the service are realised. Most often, the experts inside and outside the firm undertake projects that require them to work in very close relationships. It is technology that renders it possible for these amorphous networks of expertise to come together in cyberspace and work in very close relationships, although they might be thousands of miles apart physically. Technology thus acts as an unparalleled tool that makes it possible for service firms to extend their core capacity (competency or capability) and to forge networks of relationships across the globe (Figure 2). Thus the firm's core competency is represented by the knowledge base, realised through the effective use of internal and external partnerships utilising technology. It is argued here that it is this continuously updated ``amorphous knowledge resource'', resulting from the network of partners, that represents the firm's core competency. Moreover, it is the firm's subsequent ability to remain at the forefront that nurtures the firm's image as a service leader, and that provides the feature that differentiates the firm from its competition. The recognition of the non-conforming (amorphous) nature of knowledge provides firms with the mindset to seek for sources of knowledge beyond the obvious. Peters (1994) argues that corporations are becoming amorphous as they expand their resource base to people and firms around the world. For example, call centres are a booming business in India, as
Figure 2 Core competency in services
firms such as General Electric and British Airways set up their call centres in India to handle a daily barrage of customer enquiries that originate in North America and Europe (Landler, 2001). Thus resourcing services through networks beyond national boundaries has become a common feature in the global marketplace. Moreover, the ongoing dependence on network relationships, and the effective maintenance of such networks, will dictate the core survival strategy of tomorrow's service firms. Furthermore, the ability of a service firm to interact with its customer, and the ability to maintain an ongoing relationship with that customer, have become increasingly important strategies. This relationship imperative, referred to as ``relationship marketing'' in marketing literature, has gained widespread acceptance with practitioners and academics alike. One of the many benefits associated with the adoption of relationship marketing is its potential to gain timely information on the changing needs, expectations and spending patterns of customers. Customer information thus plays a significant role in the amorphous structure of the firm's knowledge resource. For example, booking 355,000 hotel rooms across the planet gives Marriott the opportunity to collect the world's most extensive store of information about the characteristics, habits and preferences of people who travel (Wired, 23
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industry. For example, the displacement of the multimillion-dollar music records industry by the introduction of CDs stands as testimony to this phenomenon. Moreover, innovated products and services indirectly destroy the demand for the old, as the latter prove less valuable to the customer. Innovation or creativity per se are of limited significance in today's evolving business continuum, as it is the value of the innovation as perceived by the customer that renders an advantage to a product or service. Service innovation results when a firm is able to focus its entire energies to think on behalf of the customer ± for an outcome that surpasses customers' present expectation of superior value. Innovation, however small, has a compounding (cumulative) strength that is capable of creating the new and of distorting the old. Innovation, therefore, nurtures a culture in which there are fewer hindrances to the creation of a synergy of thoughts and actions on behalf of the customer. This, of course, is conceptually and philosophically alien from conventional business wisdom. Entertaining the old (mindset) inevitably affects the present and future actions of a firm, and hence it is imperative to eradicate the old simultaneously with the introduction of the new. As Peters (1997) suggests, it is essential to destroy the old so as to give way to new thoughts and subsequent new action. Moreover, every enterprise should systematically undertake the tasks of creation, preservation and destruction of their philosophy, systems and processes. This new mindset also recognises the fact that the firm's extrinsic requirement (enhancement of customer value) is the allimportant factor in the firm's intrinsic preferences. The firm might thus choose to use various technologies and to forge networks of relationships to extend its competency (knowledge) base, and to offer higher value to the customer. The focus on customer-perceived value might require the firm to forgo their intrinsic ego and to seek competencies outside the firm. A firm might thus join in partnership with other enterprises ± including those they might previously have viewed as competitors. The 13-partner ``Star Alliance Network'' in the airline industry, for example, illustrates the numerous benefits to be gained by competing airlines, and by their customers, as a result of operating within a
2000). This in-depth customer information proves invaluable for the firm to ``think for the customer'' and to create products and services that manifest superior value to the customer, thus gaining ultimate advantage in the marketplace. The growing importance of relationships and alliances can be attributed to the global accessibility of the IT digital networks that link individuals and organisations around the world. The collective impact of various factors ± including the availability of low-cost computers, recent advances in digital communications, applications of the easy-touse graphical-interface Web-browsers and the evolution of the Internet as a universally accessible phenomenon ± has enhanced the accessibility and exchange of knowledge. From a global perspective, it is the accessibility of knowledge, and how that knowledge is creatively transformed and marketed, that provides an individual firm or a country with its competitive advantage. The Internet offers access to the global marketplace, in which border and time pose no limitations for the amorphous extension of the firm's competency ± the only limitation being human imagination.
Service innovation: the core competency Success stories of firms and individuals in various parts of the world are often featured in business magazines and books. In most cases, their advances in their chosen fields have not been the result of hard work, but can be assigned to their capacity to utilise creatively the benefits of advances in technology, new knowledge, and networks of relationships. Technology thus serves firms as they create and maintain networks of relationships in the pursuit of new knowledge. Thus the incessant focus of firms will be on knowledge ± the ``resource'' that, with its creative potential for innovation, offers the firm its core competency. Service leaders have not only developed new services as collective packages but, in the process, have created new markets ± often initiating the growth of a new industry. Today's managers are not concerned about the challenges caused by the short life-cycle of products and services but, rather, by the possibility of the disappearance of an entire 24
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challenges previously posed by distance and time, and to convert them into potential opportunities. Time differences can be creatively utilised to serve internal and external customers around the clock. Many US firms strategically locate their support services across international borders ± with the aim of providing support services during off-business hours. For example, India is being recognised as the ``back office'' of the world (Landler, 2001). Marquee businesses ± such as Nordstrom, Visa, Xerox, General Electric, Reebok, AT&T, Motorola, Cisco, Thomas Cook, and British Airways ± provide their firm's support services (such as computer help-desks, accountants, call centres, transcribers, and so on) from India. This conceptual shift ± in recognising the value of people and their knowledge as a resource ± thus broadens the global opportunity for individuals, firms and countries, and has major implications for gaining success in the marketplace. This quantum shift in the attitude of firms demands that they reassess what constitutes ``resource'' for them, and demands that they reassess what has to be done to attract, nurture and manage the ever-changing knowledge-resource pool. In fact, it is this knowledge-resource pool that will be attractive to both internal and external customers.
network. Star Alliance Network partners enjoy the facilities to serve their customers with more than 815 destinations in more than 130 countries in a reputable and customerservice-led environment. This unparalleled world-class service would have been an impossible dream for any one airline operating alone.
Conclusion and discussion Firms undertake a myriad projects. However, creative innovation necessitates that these projects and actions be synchronised to produce value-enhancement for the customer ± the firm's ultimate goal. In the competitive marketplace, it is those factors that render greater value to customers that command demand. Hence, customer-focused firms are amenable to new and better ways of doing things for the benefit of their customers. Technology, knowledge and networks thus represent a unique set of factors that can fuel innovation in service organisations. It is the combined effect of technology, knowledge and network that gives a firm the ability to focus its amorphous resource on the future (as yet unexpressed) needs of customers ± the true innovative feature. Customers today expect firms to delight them with creativity. Hence, continuous and creative innovation undertaken by a firm on behalf of the customer is, indeed, the only strategy that can sustain the long-term success of the firm. However, service innovation initiates increasing expectations among customers and, hence, can constitute a selfcreated challenge. In fact, it is this selfinflicted challenge ± to excel beyond the norm ± that has made Steven Spielberg, Michael Jordan, Disney, CNN, Microsoft, and Marriott unchallenged leaders in their various marketplaces. Their passion for delighting fans and customers far beyond expectations has propelled them to unchallenged heights of recognition. In today's global marketplace, the factors that constituted success in the past might be of limited relevance in the future. It is not just the capabilities and knowledge base of a firm that have assumed amorphous states but, more importantly, the practice of conducting business itself. The quantum advances in technology, communication and digital science have enabled firms to transcend the
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Gummesson, E. (1999), Total Relationship Marketing: Rethinking Marketing Management from 4Ps to 30Rs, Butterworth-Heinemann, Oxford. Hallowell, R. (2001), ``Scalability: the paradox of human resources in e-commerce'', International Journal of Service Industry Management, Vol. 12 No. 1, pp. 34-43. Hamel, G. and Prahalad, C.K. (1989), ``Strategic intent'', Harvard Business Review, May-June, pp. 63-76. Hansen, M.T., Nohria, N. and Tierney, T. (1999), ``What's your strategy for managing knowledge?'', Harvard Business Review, March-April, pp. 106-16. Heskett, J.L., Sasser, W.E. and Hart, C.L. (1990), Service Breakthroughs, Free Press, New York, NY. Kandampully, J. and Duddy, R. (1999a), ``Competitive advantage through anticipation, innovation and relationships'', Management Decision, Vol. 37 No. 1. Kandampully, J. and Duddy, R. (1999b), ``Relationship marketing: a concept beyond the primary relationship'', Marketing Intelligence & Planning, special issue on Relationship Marketing, Vol. 17 No. 7, pp. 315-23. Kelley, K. (1997), ``New rules for the new economy'', Wired, September, p. 140. Landler, M. (2001), ``Hi, I'm in Bangalore (but I dare not tell)'', New York Times, 22 March. Mattsson, J. (1995), ``Services management: a holistic, multi-disciplinary and customer driven research agenda'', New Zealand Journal of Business, Vol. 17 No. 2, pp. 118. Mendelowitz, A.I. (1999), ``It's a small world after all: the global economy in the networked age'', 34th Otago Foreign Policy School, Dunedin. Moody, F. (1991), ``Mr Software'', New York Times Magazine, 25 August, p. 56. Morita, A. (1988), Made in Japan: Akio Morita and SONY, Signet Books, New York, NY, p. 165. Ohmae, K. (1989), ``Managing in a borderless world'', Harvard Business Review, May-June, pp. 152-61. Patterson, P.G. (1995), ``Services management 1995-2000 and beyond: comment'', New Zealand Journal of Business, Vol. 17 No. 2, pp. 19-25. Peppers, D. and Rogers, M. (1997), ``The $15,000 rug'', Marketing Tools, May, pp. 4-7.
Peters, T. (1994), Crazy Times Call for Crazy Organizations: Tom Peters Seminar, Macmillan, London, p. 10. Peters, T. (1997), The Circle of Innovation, Hodder & Stoughton, London. Peters, T. and Austin, N. (1994), A Passion for Excellence, The Leadership Difference, HarperCollins, London. Pilzer, P.Z. (1990), Unlimited Wealth: The Theory and Practice of Economic Alchemy, Crown Publishers, New York, NY. Porter, M.E. (1985), Competitive Advantage: Creating and Sustaining Superior Performance, Free Press, New York, NY. Prahalad, C.K. (1993), ``The role of core competencies in the corporation'', Research Technology Management, Vol. 36 No. 6, November-December, pp. 40-7. Prahalad. C.K. and Hamel, G. (1990), ``The core competence of the corporation'', Harvard Business Review, May-June, pp. 79-81. Quinn, J.B., Doorley, T.L. and Paquette, P.C. (1990), ``Technology in services: rethinking strategic focus'', Sloan Management Review, Winter, pp. 79-87. Shugan, S.M. (1994), ``Explanation for the growth of services'', in Rust R.T. and Oliver, R.L. (Eds), Service Quality: New Directions in Theory and Practice, Sage Publications, Newbury Park, CA, pp. 223-40. Slater, S.F. and Narver, J.C. (1994), ``Market orientation, customer value, and superior performance'', Business Horizons, Vol. 37, March-April, pp. 22-8. Stalk, G., Evans, P. and Shulman, L.E. (1992), ``Competing on capabilities: the new rules of corporate strategy'', Harvard Business Review, March-April, pp. 57-69. Teece, D. and Piscano, G. (1994), ``The dynamic capabilities of firms: an introduction'', Industrial and Corporate Change, Vol. 3 No. 4, pp. 537-56. Webber, A.M. (1993), ``What's so new about the new economy?'', Harvard Business Review, JanuaryFebruary, pp. 24-42. Wired (2000), ``The Wired index: 40 companies driving the future'', 8.06, June, pp. 229-64. Zeithaml, V.A. and Bitner, M.J. (1996), Services Marketing, McGraw-Hill, New York, NY, pp. 174-6.
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I. Introduction
Strategic issues in managing innovation's fuzzy front-end
Most activities in a new product development (NPD) process are performed in a probabilistic setting. Uncertainty particularly characterizes the early stages of the NPD process, since companies have difficulty forecasting whether they will succeed in developing a new product and, if a product is developed, whether they will accomplish the desired marketing objectives. Uncertainty can be particularly troublesome in the case of radical innovations in dynamic markets versus incremental innovations in stable market situations. Wood and Brown (1998) note, for example, that the path from nascent technology to full-scale production presents numerous managerial challenges that must be overcome for a company to develop new products involving new technologies. It is evident, however, that some organizations clearly surpass competitors in identifying promising ideas and preparing them for development. As several studies note, those organizations that excel in managing the ``upfront or fuzzy front-end (FFE)'' phase are more likely to win the innovation race (e.g. Cooper, 1988, 1998; Dwyer and Mellor, 1991; McGuinness and Conway, 1989). The FFE is that period between when an opportunity is first considered and when it is judged ready for development (Kim and Wilemon, 1999). Managers of successful products expend considerably more dollars and effort on the FFE than those in less successful companies (Cooper and Kleinschmidt, 1988). Though FFE importance varies according to the product and its market, a ``core competence'' in FFE management can be an obvious competitive advantage for companies required to develop important new products. Many firms, unfortunately, acknowledge serious weaknesses in the predevelopment steps of their innovation process (Khurana and Rosenthal, 1997). In fact, data on resources spent from the NewProd research studies show that limited time and money are devoted to these early, critical steps (Cooper and Kleinschmidt, 1988). To achieve high performance in the FFE, many issues need to be addressed, for example: . What activities must be accomplished in the FFE? . What skills and experiences are required by those involved?
Jongbae Kim and David Wilemon
The authors Jongbae Kim is Associate Professor at the School of Management, Silla University, Korea. David Wilemon is with the Innovation Management Program, School of Management, Syracuse University, Syracuse, New York, USA. Keywords Fuzzy logics, New product development, Teams, Project management, Innovation Abstract A product is more likely to be successfully developed and marketed when the ``upfront or fuzzy front-end (FFE)'' activities are understood and carefully managed. A framework is developed to illuminate several factors affecting FFE performance. Using this framework, several strategic issues involved in managing the FFE are identified and managerial recommendations are advanced. Electronic access The research register for this journal is available at http://www.emeraldinsight.com/researchregisters The current issue and full text archive of this journal is available at http://www.emeraldinsight.com/1460-1060.htm
European Journal of Innovation Management Volume 5 . Number 1 . 2002 . pp. 27±39 # MCB UP Limited . ISSN 1460-1060 DOI 10.1108/14601060210415153
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Strategic issues in managing innovation's fuzzy front-end
European Journal of Innovation Management Volume 5 . Number 1 . 2002 . 27±39
Jongbae Kim and David Wilemon . .
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What is the FFE project leader's role? What are the responsibilities of senior management? What is the best way to motivate FFE project teams for high FFE performance? How can FFE project teams gain the cooperation and support of functional groups and garner management support? What contribution can an innovation network or alliance offer?
The strategic concerns examined in the next section are derived from this framework. First, identifying the scope of FFE activities and setting FFE performance priorities are related to both the ``FFE idea'' and ``FFE performance.'' Second, the issues of assigning, organizing and motivating the FFE project team and defining the role of the project leader are related to the construction of the ``project team.'' Third, those concepts relating to internal and external factors usually originate with ``senior management,'' ``functional groups,'' and various ``external organizations.'' Both internal and external factors are important in shaping the development phase.
Answers to these and other questions help organizations to quickly and effectively develop and market innovative ideas. The objective of our paper is to develop a framework to examine several factors essential to achieving high FFE performance.
III. Strategic issues in managing the FFE
II. Framework for FFE performance
A. What must be achieved in the FFE? The outcomes of the FFE determine the direction and serve as the base for the subsequent development phase activities. Therefore, sufficient preparation in the FFE is essential to select the most appropriate project and to save time and effort in the development phase. Fortunately, there are a few studies that shed light on the goals and the activities to be pursued in the FFE. Cooper and Kleinschmidt (1987a) found that a welldefined target market, product specifications, clear product concept, and extensive preliminary market and technical assessment are important FFE activities. Smith and Reinertsen (1992) noted several crucial decisions that are made during the FFE, e.g. identifying the target customer, aligning the project with corporate strategy, and specifying key technologies and resource requirements. The findings of Moenart et al. (1995) noted that successful project teams are characterized by their ability to reduce ambiguity during planning, particularly technological and marketing uncertainty. Smith et al. (1999) suggested that the FFE process is designed to provide an ``information package'' that supports investment decisions at the target selection or product definition gate of the development process. This package includes information about technology feasibility and performance; markets, customers, and timing; a definition of ``manufacturability'' with a favorable cost model and data; proprietary positioning; and risk assessment.
While many factors influence FFE performance, the project (or the FFE idea) and the FFE team (or a champion) are of major significance. With regard to the project, the degree of project complexity, for example, determines the effort required and the length of the development cycle (Smith and Reinertsen, 1992). In addition to the idea, the impact of people working on the FFE is direct and considerable, since individuals and teams play a major role in cultivating FFE ideas. Our framework incorporates these two factors and is depicted in Figure 1. Figure 1 shows that both the idea and the project team are primary determinants of FFE performance and, in turn, influence and shape the development phase. Ideally, ``FFE performance'' will involve the development of an FFE idea into a useful, validated product concept and the concept will then evolve into a commercial product or service. Relations with senior management and functional groups, however, also significantly affect the project team in managing the FFE. Relations with external groups such as customers, partners, suppliers, and channel members, as well as regulators and competitors, can expose the project team to new information and new ways to manage the FFE. Figure 1 illustrates that both internal and external factors can be significant contributors. The concepts and linkages illustrated in Figure 1 are useful in understanding the major issues surrounding the management of the FFE. 28
Strategic issues in managing innovation's fuzzy front-end
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Figure 1 Framework of major factors influencing FFE performance
It is difficult to propose a universal set of activities necessary in the performance of the FFE. This depends upon such factors as how innovative and complex the technology is: how important the opportunity is to a company; how much impact FFE activities are likely to have on subsequent processes; and how easily can changes be made in the development phase. We note, however, that, by the end of the FFE, the responsible individuals or team needs to have produced a well-defined product concept; clear development requirements; and a business plan aligned with the corporate strategy. A clearly defined product concept is mandatory to understanding development time, costs, market potential, and required technical expertise. Clear concepts also help avoid costly, ill-informed project decisions (Murphy and Kumar, 1997). Khurana and Rosenthal's (1997) research reveals, however, that clarifying the product concept at the frontend is surprisingly difficult and most companies fail to generate clear, stable product definitions. It is also essential for the following issues to be addressed by those responsible for FFE activities: . What criteria should be used to decide when to start the development phase?
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How can FFE performance be measured? Can it be evaluated separately from development? What performance dimensions need to be assessed? What activities are to be performed in the FFE? How can these activities be managed? In the FFE, most project teams are likely to approach FFE activities with a broad, conceptual perspective; however, once the development phase has begun, difficulties related to developing the product require an intensive, focused effort. How can FFE learning be effectively transferred to the development teams?
B. What should be considered at the beginning of the FFE? As we have previously discussed, the FFE begins when an opportunity is first considered. Thus, promising ideas are fundamental. If a firm can identify a promising idea and begin the FFE process early, then the development phase can be initiated more quickly. To identify and invest in suitable opportunities, several issues need to be addressed at the beginning of the FFE. First, it is important to identify and sustain the sources of promising ideas, since generation of useful ideas requires in-depth knowledge 29
Strategic issues in managing innovation's fuzzy front-end
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Third, it is necessary to evaluate and document the FFE process. Promising ideas are often abandoned during the FFE and go undocumented, since there is no commitment nor investment in them and since more urgent requirements for existing products take precedence. However, we recommend that reasons for abandoning ideas be documented, since a change in business climate may initiate resurrection of an idea. Moreover, documentation can also serve as a useful tool to calculate loss due to idea abandonment or delay.
and experience in a particular technology and market. Fast and reliable information also helps organizations select the right product ideas, produce promising concepts, and accelerate the FFE. Managers at all levels are responsible for understanding how such knowledge is accessed and channelled (Leonard, 1995). To improve the ideation process and to avoid missing promising opportunities, it is imperative to consider how ``knowledge networks'' are established; how the organization currently captures ideas for NPD; what functional groups ± R&D, manufacturing, or marketing ± initiate new product ideas and how they communicate while each idea is being processed; and what factors hinder the consideration of promising ideas, i.e. organizational climate or the resistance to change. Equally important is how the learning that occurs throughout the FFE is captured and used. Second, the screening of ideas needs to be well managed. Conceptually there are two screening processes in the FFE phase. The first is to determine if an idea is worthy of beginning the FFE phase; the second is to determine whether or not it is time to end the FFE and begin the development phase. Both are important, but here we focus on the first screening process. With sound criteria, organizations are more likely to choose opportunities that align with the firm's goals and capabilities and with market needs. Complexity, feasibility, potential and compatibility are useful attributes when evaluating ideas. However, well-established product screening criteria, such as ROI, can be a barrier to identifying highly innovative ideas, since this financial measure requires considerable information about a product candidate. Lester (1998) indicates that, all too often, the expertise within a company is limited to the company's existing product technologies and market applications. Christensen (1997), in discussing disruptive technologies, notes that there are instances when it is wise to ignore current customers and to invest in developing lower-performance products that produce lower margins. These smaller, emerging markets often lead to substantial new markets. In summary, it is important to encourage imaginative, experimental, and divergent views to help ``shape'' ideas and to establish a system in which efforts among the FFE, development, and existing products are balanced.
C. Proper selection versus speed of selection It is well established that execution has a strong positive relationship with NPD success (Cooper, 1998). For example: . Experience has shown that predevelopment work pays for itself in reduced development time and improved success rates (Cooper, 1993, 1995). . ``Poor definition of product requirements'' was the reason most cited for product development delays. About 71 per cent of the respondents in a study focusing on product development acceleration noted that process delays occur when there is poor understanding of customer requirements and insufficient knowledge of a product's technology and market forces such as competition, suppliers and distributors, all of which should be addressed in the FFE (Gupta and Wilemon, 1990). A clear product definition (proper selection) is essential, since prevention in the FFE is more efficient, less costly, and easier to remedy than in the development phase. Despite the need for a clear product definition, FFE project teams often face considerable pressure to speed their efforts (speed of selection), due to competitive moves, rapid market or technological changes, or internal pressure to begin development. Time is a competitive advantage and a company that suffers delays in the FFE cannot compensate for those delays, even if the development process is completed quickly. In our background research on this topic one manager told us, ``Unless it can be sold, we will not develop.'' Another manager noted, ``We seem to have a fear of failure that makes us justify slow 30
Strategic issues in managing innovation's fuzzy front-end
European Journal of Innovation Management Volume 5 . Number 1 . 2002 . 27±39
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Third, costs associated with speeding the FFE phase need to be considered. Dyer et al. (1999) cite, for example, that the challenge of speed-to-market can include a larger dollar investment in R&D; a high-pressure organizational environment; costly errors; broken promises to customers; and lost time and revenue when the firm selects the wrong product to develop. By analyzing the influences of key measures of performance (e.g. the expense of and time needed to screen an opportunity and the effectiveness of the screening process) on profitability, Reinertsen (1999) examines the economics of some of the major design decisions and suggests that the FFE process structure should vary according to the underlying economics of a situation. Quantitative approaches can be helpful in prioritizing FFE objectives. In addition, we recommend that the following issues be examined by those charged with FFE activities: . What is the relationship between the time required to complete FFE activities and the time needed to develop a product? Do the factors used to accelerate activities in the FFE help achieve cycle-time reduction in the development phase? . When is it most appropriate to complete the FFE and begin the development phase? What is the signal?
development. As a result, our successes are rarely completely successful.'' Project teams frequently encounter tradeoffs between the product candidate selection process and the speed of the selection process (e.g. Bayus, 1997; Crawford, 1992; Meyer and Utterback, 1995). Their challenge is to achieve quicker development without sacrificing quality or eliminating valuable steps. The ability to compete depends on a firm's ability to quickly develop products that customers value and to market them well. Product quality alone is not enough to remain competitive. Choperena (1996) demonstrated a commercial case in which the company achieved not only fast product development, but also high quality and innovative commercialization of an automated immunoassay system. Project teams often need to prioritize several conflicting objectives, aligning the quality of execution with internal and external market situations. These factors are further examined below. First, project characteristics are important in determining the objectives to be pursued. Selection speed is often more highly valued when errors and omissions in the ``up-front'' activities can be easily corrected in the following phases and the unresolved or postponed problems in the FFE can be better managed in subsequent processes. But when a project requires a considerable investment or involves a high degree of cooperation and integration with external groups, errors and omissions in the FFE can be serious. In fact, in some cases such errors can force a project to be restarted. Second, front-end speed can be more important when trying to head off an emerging competitor (Smith and Reinertsen, 1992). Smith and Reinertsen (1998) also recommend that, when markets are predictable and the cost of delay is low, opportunity choice is more important, but in fast moving markets, when the cost of delay is high, speed is critical. Such responsiveness is crucial in finding early markets for radical innovations where innovators, market researchers or users cannot quite visualize a product's potential (Quinn, 1985). Christensen (1997) notes that non-existent markets are best researched through action rather than through passive observation and that it is in disruptive innovations, where we know little about the market, that there are such strong first-mover advantages.
D. What are desirable ways to manage the FFE? A first step toward achieving FFE performance is to assign competent people to it. To assure success of the FFE process, people with expertise must be designated and the project team must be effectively organized. Moreover, the staff (the quantity and quality of people involved in the FFE process); the skills (people's knowledge about performing in the FFE process); and the structure (the organizational framework of FFE management) require careful consideration. To secure staff with relevant skills, we stress two other components, knowledge and passion (motivation). Since many decisions based upon criteria such as consumer acceptance, technical feasibility, and resource requirements must be made, it is important for a knowledgeable individual or team to lead the FFE. If an individual (or team) is deficient in any of these knowledge areas, difficulties will be encountered. Thus, sufficient 31
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feasibility as well as manufacturability, yield and reliability. Aligning FFE activities with corporate strategy and balancing new product/technology development with the system's existing capabilities are vital. The main objective of the team is to balance new research with manufacturing's capabilities. Problems with CFTs, such as heterogeneity, may actually increase the level of conflict within the team (Priem, 1990). Dougherty (1992) notes that successful projects are not distinguished by the absence or presence of barriers and conflicts but rather how they are overcome. Clearly, throwing a group of people together and calling them a ``team'' seldom achieves the desired results. Companies can benefit by learning how to build high-performing NPD teams (Dyer et al., 1999) and, to attain maximum performance in the FFE, organizations need to develop skills in guiding their CFTs. To this end, we recommend that the following issues be examined: . What personal qualities, other than knowledge and passion, are likely to facilitate FFE performance? Which might hinder the FFE process? . What problems result when R&D dominates the FFE phase? For example, Rubenstein et al. (1997) state that a strong research unit may easily ignore other functional units and that differing degrees of importance and dominance of some units over others may distort the flow of technology and hinder success.
knowledge and experience in technology, markets and resource management are imperative. Moreover, some companies select a ``product champion'' to lead this effort, since the process can be strengthened with their knowledge and passion. These champions play an important role in transforming fuzzy ideas into concepts worthy of development and commercialization. They also often create new resource combinations, making innovation possible by bringing both technical and commercial capabilities together in profitable ways. Lee and Na (1994) empirically found that the existence of product champions is critical to technical performance, especially when technical innovation is radical. Project teams in the FFE usually comprises only a few people, since most firms are reluctant to commit significant resources to the FFE, or the FFE may not need the involvement of many people. Thus, a project team may not be as important in the FFE as in the development phase. However, when a team is needed, a cross-functional team (CFT) is generally recommended (e.g. Lester, 1998). CFTs are composed of members from several functional areas such as R&D, Engineering, Manufacturing, and Marketing. Ancona and Caldwell (1990, 1992) found that CFT members communicated more with outsiders who had similar functional backgrounds. When there are different functions represented on a team, team members can access more diverse information and have better opportunities to determine and drive internal and external best practices and information into the FFE process. According to Merrills (1989), since team members share ideas about what is commercially important, technically feasible, or difficult to manufacture while the product is on the drawing-board, the involvement of CFT members is more likely to resolve problems more quickly and at a lower cost. Iansiti (1993) reports that system-focused companies which integrate the entire R&D process, rather than just feed small projects and components down a narrow pipeline, form a core team of managers, scientists and engineers at the earliest stages of the R&D process. This integration team assesses the impacts that various technical choices have on the design of the product and on the manufacturing process. This team also selects the most promising concepts, considering the
E. Project leadership in the FFE Project leaders are pivotal in managing the NPD process. Internally, project leaders (with their teams) manage the project by defining goals, developing plans, prioritizing work, and leading the team. At the same time, project leaders serve as linking pins or bridges (e.g. Lysonski, 1985) among the project team, senior management, and other functional groups. Research also shows that project leaders can influence development speed (e.g. McDonough and Barczak, 1991), innovativeness and other performance outcomes. Many of the same capabilities required to manage the development phase also are needed to manage the FFE. Smith et al. (1999) suggest that leadership in the FFE tends to come from research, technology, and new business development leaders, as many 32
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are also important. Based on these efforts, project teams are more likely to gain senior management and related functional group support and cooperation in both the FFE and the development phases. These efforts also help facilitate approval procedures. Fourth, providing flexibility is important. Adherence to every stage, step, activity and gate in the ``formal process'' depends on the risk level of the project. Cooper (1998) suggests that, instead of being a template or road-map, the ``formal process'' too often becomes a strait-jacket beset with bureaucracy. He notes that ``process flexibility'' is significantly correlated with positive profits. We posit that flexibility also is an important FFE attribute. The following questions deserve consideration by managers responsible for FFE activities: . Which leadership styles are most appropriate in managing FFE activities? . How do leadership styles affect crossfunctional teamwork in the FFE? According to Norrgren and Schaller's (1999) research on the relationships among work climate, leadership style, and work group learning strategies, leadership style (especially the leaders' employee orientation) co-varied significantly with CFT members' perceptions of their work climate and with the possibilities for innovative learning. . Is there a relationship between the type of project leadership and the type of project? There have been studies that examine the role of project leaders in NPD. Kim et al. (1999), for example, noted that, during their jobs, R&D project leaders perform the following five different roles: strategic planner, team builder, gatekeeper, technical expert, and champion. They found that the team-building role of R&D project leaders is particularly important for relatively certain R&D projects. In contrast, for R&D projects characterized by uncertainty, strategic planning appears to be more important.
ideas are tested and failure occurs far more often than success. They further note that the commercial development/concurrent engineering phase needs to be led by business entrepreneurs and program managers in a focused, coordinated team environment. Which leadership styles are appropriate and what roles are valued in the FFE are debatable. They depend on the nature of the idea, the experiences of team members, the organizational structure, and priorities. In the FFE, however, several project leader capabilities have been found to be important. First, project leaders need to clarify objectives and direction to help provide a clear vision of what the new product is expected to provide. McDonough and Spital (1984) found that leaders of successful projects delineated product specifications carefully. They set targets for the particular product's technology and features, which helps to prevent development engineers from losing sight of financial and temporal limits, and emphasize the need to be pragmatic about market needs. The project vision, which communicates the goal to the product team, can help create a psychologically safe environment (Lynn et al., 1999). As expressed by Quinn (1985), it is important to accept the essential chaos of development and to allow entrepreneurial teams to pursue competing alternatives within a clearly conceived framework of goals and limits. Second, as Gemmill and Wilemon (1994) suggest, when only the technical responsibilities of the team leader's role are considered, an incomplete and misinformed view of project team leadership occurs. Effective project leaders understand and are competent in dealing with a wide range of interpersonal issues which, if not managed, can undermine project performance. An FFE team can perform poorly due to lack of vision, lack of urgency, and poor supervision, and an inability or unwillingness to deal with important interpersonal issues. Failure to address any of these factors can lead to apathetic, frustrated team members. It is particularly critical for project leaders to gain the commitment of team members and to encourage openness, creativity and innovative problem solving. Third, project leaders must possess the capability of ``marketing'' ideas within a firm during the FFE. Information sharing with key participants and creating a supportive climate
F. Senior management responsibilities in the FFE Senior management can have a significant impact on the firm's commitment to innovation (Daellenback et al., 1999). They influence NPD by providing strategic vision (e.g. Lester, 1998), allocating resources (e.g. Rosenau, 1988), affecting level of innovation 33
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visibility (e.g. McDonough and Spital, 1984), facilitating coordination within the project team and across departments, managing organizational cooperation (e.g. Rubenstein et al., 1997), creating a productive climate for NPD programs, and providing commitment. In the FFE, however, senior management plays particularly important roles in prioritizing projects and allocating resources. The resource allocation and project prioritization processes are based on the strategic objectives of the company, e.g. which projects ``fit'' and how important each is to the company's goals. Considering that each project team is likely to focus on its own project, to help optimize the entire development effort, senior management must use a broad, comprehensive perspective in managing and guiding FFE activities. As Gupta and Wilemon (1990) emphasize, it is crucial for senior management to balance short-term operating demands with long-term innovation needs. Ultimately, senior management must consider all projects together and handle R&D and marketing investments as a portfolio decision, thus implementing portfolio management in parallel with a stage-gate process (Cooper, 1999). Portfolio planning maps all new product initiatives across the organization to balance risk and potential return, short and long time horizons, and mature and emerging markets (Khurana and Rosenthal, 1997). Khurana and Rosenthal (1998) also suggest that the greatest success comes to those organizations that take a ``holistic approach,'' linking together the business strategy, product strategy, and product-specific decisions in the FFE. A myopic perspective will constrain progress and growth and will also produce conflicts. As Rosenau (1988, p. 152) notes:
consistent decisions on each FFE project such as: Is this idea worthy of managerial attention and resources? Does the project fit the company's mission and market requirements? What level of resources and how many people need to be allocated to FFE activities? When is it desirable to start the actual development process? Such questions should be viewed and weighed iteratively against the company's goals and its environment. G. Motivating the FFE project team The FFE phase is dynamic and demands a great deal of perseverance, creativity and commitment. The project team requires support to take risks and push boundaries and several factors can influence the FFE team motivation. First, the level of senior management support is an important determinant to new product success or failure (Cooper and Kleinschmidt, 1987b; Maidique and Zirger, 1984). In the FFE, senior management may influence the motivation of the project team by the level of support given, financial as well as commitment of managerial time and resources. In some cases, senior management's openness to innovation and experimentation can be the most important type of support. Moreover, relationships between senior management and project members, in the FFE and the ensuing climate, are often sustained during subsequent development phases and may continue into entirely new projects. Second, an organizational culture that values and rewards the performance of FFE activities can influence project teams. The efforts of people working on FFE activities are often overlooked, since it is difficult to measure FFE contributions and assess performance. The team's FFE contributions are embedded in the product and activities in subsequent phases; therefore, to isolate specific, measurable contributions is difficult. Furthermore, in some instances the effort and time invested in upfront activities go unrecognized, since many projects are often abandoned. If the attrition rate of new product projects is considered (e.g. Page, 1991; Stevens and Burley, 1997), one can easily grasp the consequences of this problem. To ensure that people recognize the importance of FFE activities and encourage teams to perform well, it is important to consider the following:
It is better to introduce a few products in a timely manner than to maintain a larger number of development projects, each of which is starved for adequate resources and thus delayed.
Senior management has the responsibility of evaluating individual FFE projects based on a long-term, comprehensive, systematic view, considering the required resources (e.g. resource capacity-versus-demand analysis (Cooper, 1999)), and each project's relationship with existing products and technologies. Based on these perspectives, senior management can make important and 34
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Reward systems can affect behavior in the FFE. To facilitate desirable performance, reward systems should encourage desirable FFE activities. Appraisal of FFE performance in the context of the total development process must be considered. Various reward systems need to be evaluated to determine which are more effective in the FFE and when their use is most appropriate. When selecting rewards and recognition, project member characteristics must be considered. According to Quinn (1985), inventorentrepreneurs often desire to achieve a technical contribution, recognition and independence as much as money. Consequently, they do not panic or quit when others who value monetary rewards might. Chen et al. (1999) compared the beliefs held by members of diverse demographic groups in R&D organizations regarding which types of rewards produce organizational benefits. Their results revealed that members of different ethnic groups and genders held varying beliefs about the utility of different rewards. How can FFE team members be rewarded for their ``upfront'' efforts when others actually develop the product? In many companies it is the ``downstream participants'' who are rewarded, e.g. marketing personnel, while ``upfront'' efforts go unrecognized.
process. Such early involvement helps ensure commitment and contribution. According to Rochford and Rudelius (1992), however, only a small percentage of firms actually had more than one source of information during the early, predevelopment stages of the new product process. This can seriously limit the potential of a new idea. It is important to note that poor intergroup relations contribute significantly to difficulty in defining product requirements. In addition, the development process consists of a set of activities that cut across several functions. Both aligning all participants with the project and cooperating with functional groups in the FFE help lay groundwork for the development phase. Value chain perspectives at the product concept and definition stages become necessary as product designs and market delivery systems become increasingly competitive and complex (Khurana and Rosenthal, 1997). This indicates that, when FFE members are connected with key outsiders, the FFE effort is more likely to be successful. The benefits from cross-functional cooperation in the FFE are numerous: . Problems in the FFE are more likely to be efficiently solved. Early involvement of functional groups can result in early testing of an idea, since each group brings its special knowledge to the process. In addition, ambiguity can be diminished through the understanding early on of various functional capabilities, resources and commitments. . Project teams can secure resources and task-related information, helping to minimize internal resistance in the development phase. . The early resolution of conflicts through mutual accommodation speeds the development process. According to Hayes et al. (1988), recognizing conflicts early can contribute to successful development projects. . By sharing information in the FFE, technology transfer between functional groups and between customers and suppliers is enhanced. To support strong external links, organizations need to build equally strong internal crossfunctional links among their R&D, marketing and manufacturing groups (Dyer et al., 1999).
H. Functional group cooperation and support Functional groups perform several critical roles in the development phase. The underlying premise of the ``communication web'' stream of research (Brown and Eisenhardt, 1995) is that communication among project team members and with ``outsiders'' stimulates the performance of development teams. The greater the extent to which members are connected with key outsiders, the more successful an NPD project is likely to be. However, studies of US and Japanese firms indicate that joint involvement in and of itself does not ensure the success of NPD efforts; the timing of joint efforts also matters (e.g. Song and Parry, 1993). Gupta and Wilemon (1990) note that key groups, such as R&D, marketing, engineering, and manufacturing, need to be involved very early in the development 35
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Some product ideas, for example, may be too difficult, time-consuming, or costly to evaluate internally. Cooperation with external organizations can facilitate reliable information gathering about changes in technologies, markets, and external developments. Over the past decade, mergers, acquisitions and strategic alliances have occurred; their intent, in part, has been to improve technological exchanges and add to the technology base of organizations (Rubenstein et al., 1997). Cooperation in the FFE, particularly, can develop productive relationships based on trust and information sharing, since early cooperation usually accompanies high degrees of involvement and extensive communication. Von Hippel (1986) stresses the importance of communication with key customers about product designs. Herstatt and Von Hippel (1992) report on a successful field application of a ``lead user'' method to develop concepts for needed new products; this method involves joint user-manufacturer development of new product concepts. The lead user method was found to be twice as fast as and to cost half of the concept development methods previously used. Strong ties to suppliers can also be valuable to the FFE and the development process, since these relationships may reduce development costs, promote higher quality with fewer defects, reduce time to market, and help incorporate supplier-originated innovation (Bonaccorsi and Lipparini, 1994). An unusual source of useful new technology can be a firm's competitors. Firms that compete in one market may become vibrant partners in noncompetitive arenas. Competitors can also help diminish ambiguity confronted in the FFE via strategic alliances such as joint ventures, consortia and partnerships. Difficulties associated with early communication and cooperation between NPD and external groups may also exist. Specific issues are difficult to forecast during the early NPD alliance planning stages and in the FFE phase. Moreover, selecting a single source in the concept stage would not allow companies to capture new ideas emerging from other suppliers (Bonaccorsi and Lipparini, 1994). When planning to cooperate with external organizations in the FFE, the firm (or the project team) needs to consider such issues as:
Rochford and Rudelius (1992) empirically found that obtaining information from several functional areas and sharing information across these areas during the FFE had a positive impact on new product performance. However, problems can result from this early cooperation with functional groups and other external groups. For example, if a promising idea is surrounded by high uncertainty, then early involvement of others can consume considerable resources and cause unnecessary conflicts in the FFE. In other cases, a potential idea, which seems troublesome or is not valued by one or more functional groups, may be rejected before it has a chance to prove its worth. Hence, FFE project teams need to find effective ways to obtain crossfunctional cooperation and support. The following questions deserve consideration from FFE teams: . What are the most helpful methods of ``marketing'' FFE ideas to the organization in order to gain support? . When is the best time to seek functional group support? Which is more desirable ± stepwise cooperation (sequential) or concurrent cooperation? . How can conflicts be effectively managed between functional groups in the FFE? How can conflicts be imaginatively resolved to ensure that high creativity and clear communication result? I. Cooperating with external organizations in the FFE The Atuahene-Gima (1995) study noted that market orientation has a strong positive effect on the proficiency of predevelopment activity. By gathering information from external organizations in the FFE, project teams gain a clearer understanding of current customer needs as well as potential needs (e.g. Chandy and Tellis, 1998), probable market size and growth rates, marketing strategy ideas, regulation trends, and the market responsiveness indicators. External groups are sources of valuable information and innovative ideas; they also can help manage the FFE directly. Increased need for involvement of external organizations in the NPD process, e.g. customers, vendors, strategic partners, governments, and virtual community (e.g. Nambisan and Wilemon, 2001), is one characteristic in the NPD environment of many technologically advanced industries. 36
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When is the best time to cooperate with external organizations? Under what conditions is an alliance beneficial? How can a company find and select the right partners? What types of alliances yield both the flexibility and control necessary to facilitate the development of desired new products? What are the important issues that need to be documented and verified when developing new products, markets, or technologies, especially as they relate to the eventual dissolution of alliance arrangements? What are the costs and benefits expected from cooperation? What causes dysfunctional behavior within an alliance? What causes alliances to dissolve?
Effective decisions about these issues are dependent upon FFE ideas, competition among suppliers and buyers, external organization capabilities, and bargaining power. To avoid conflicts and problems with competitors in subsequent phases, the following options need to be considered: . Cooperating only in the pre-competitive stage. For example, cooperating during the FFE but conducting the development phase separately. . Fostering mutual trust among partnering firms, so dysfunctional events can be managed without jeopardizing the success of the alliance (Millson et al. 1996). Decisions to cooperate with external groups should be made based on what sources of fuzziness (uncertainties) are most critical in managing the FFE, e.g. uncertainties about markets, technologies, or regulatory issues.
IV. Implications The major goal of our paper is to identify several key issues that need to be addressed in effectively managing the FFE. Knowledge of the factors influencing the FFE performance can help develop more effective ways to manage the FFE process. Difficulties occur in studying the FFE, as it is dynamic, unstructured and uncertain. It also has traditionally been characterized by low levels of formalization (Murphy and Kumar, 1997). As noted, FFE performance cannot be easily 37
measured, since the contributions of the FFE performance need to be assessed in the context of the total development cycle and overall NPD performance. The following areas need further consideration by companies when they rely on effective FFE performance as part of their overall innovation strategy: . Accumulating FFE knowledge is important. Organizations having more NPD experiences generally have more knowledge about the FFE; however, knowledge of the FFE, to be useful, must be systematically accumulated, transferred and applied. Companies thus need to build a knowledge base of their FFE activities. Documenting and disseminating useful FFE processes can help others within an organization deal with their FFE challenges. . Most activities in the FFE are interrelated. In a situation where an organization needs to pursue rapid results, different project leadership styles, project team structures and reward systems may be required. Thus, discovering ways to manage the FFE in a more holistic manner can help build capabilities for future innovation efforts. . Several studies suggest that contingency approaches are necessary in the FFE (e.g. Khurana and Rosenthal, 1997, 1998; Reinertsen, 1999). Competition, technologies, tools, markets and organizational structures and relationships may require changes in some front-end practices. Reinertsen (1999) notes that front-end process structures should differ depending on the underlying economics of specific situations. Khurana and Rosenthal's (1998) studies suggest that the decision of which front-end approach to use should be compatible with the firm's product, market and organizational contexts. Each project needs to be managed differently depending upon situational factors, such as the opportunity's characteristics (e.g. magnitude of change ± Kessler and Chakrabarti, 1999), internal resources, new product strategy, and external markets. The more standardized approaches seem to work best for incremental innovations. Therefore, preparing useful contingency approaches relies on identifying the situational factors affecting FFE performance.
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Summary
Cooper, R. (1995), ``Developing new products on time, in time'', Research-Technology Management, Vol. 38, pp. 49-57. Cooper, R. (1998), ``Benchmarking new product performance: results of the best practices study'', European Management Journal, Vol. 16, pp. 1-17. Cooper, R. (1999), ``The invisible success factors in product innovation'', Journal of Product Innovation Management, Vol. 16, pp. 115-33. Cooper, R. and Kleinschmidt, E. (1987a), ``New products: what separates winners from losers?'', Journal of Product Innovation Management, Vol. 4, pp. 169-84. Cooper, R. and Kleinschmidt, E. (1987b), ``Success factors in product innovation'', Industrial Marketing Management, Vol. 16, pp. 215-23. Cooper, R. and Kleinschmidt, E. (1988), ``Resource allocation in the new product process'', Industrial Marketing Management, Vol. 17, pp. 249-62. Crawford, C. (1992), ``The hidden costs of accelerated product development'', Journal of Product Innovation Management, Vol. 9, pp. 188-99. Daellenback, U., McCarthy, A. and Schoenecker, T. (1999), ``Commitment to innovation: the impact of top management team characteristics'', R&D Management, Vol. 29, pp. 199-208. Dougherty, D. (1992), ``Interpretative barriers to successful product innovation in large firms'', Organizational Science, Vol. 3, pp. 179-202. Dwyer, L. and Mellor, R. (1991), ``Organizational environment, new product process activities, and project outcomes'', Journal of Product Innovation Management, Vol. 8, pp. 39-48. Dyer, B., Gupta, A. and Wilemon, D. (1999), ``What firstto-market companies do differently'', ResearchTechnology Management, Vol. 42, pp. 15-21. Gemmill, G. and Wilemon, D. (1994), ``The hidden side of leadership in technical team management'', Research-Technology Management, Vol. 37, pp. 25-32. Gupta, A. and Wilemon, D. (1990), ``Accelerating the development of technology-based new products'', California Management Review, Vol. 32, pp. 24-44. Hayes, R., Wheelwright, S. and Clark, K. (1988), Dynamic Manufacturing, Free Press, New York, NY. Herstatt, C. and Von Hippel, E. (1992), ``Developing new product concepts via the lead user method: a case study in a `low-tech' field'', Journal of Product Innovation Management, Vol. 9, pp. 213-21. Iansiti, M. (1993), ``Real-world R&D: jumping the product generation gap'', Harvard Business Review, Vol. 71, pp. 138-47. Kessler, E. and Chakrabarti, A. (1999), ``Speeding up the pace of new product development'', Journal of Product Innovation Management, Vol. 16, pp. 231-47. Khurana, A. and Rosenthal, S. (1997), ``Integrating the fuzzy front-end of new product development'', Sloan Management Review, Vol. 38, pp. 103-20. Khurana, A. and Rosenthal, S. (1998), ``Towards holistic ``front-ends'' in new product development'', Journal of Product Innovation Management, Vol. 15, pp. 57-74. Kim, J. and Wilemon, D. (1999), ``Managing the fuzzy front-end of the new product development process'', Proceedings of Portland International
Our objective is to identify several issues necessary in successfully managing the FFE. Unfortunately, few companies understand the importance of the FFE phase, despite the considerable impact this phase can have on NPD performance. How companies manage the FFE can become an important competitive advantage and a core competency in accomplishing their innovation strategies. Additional studies will help develop further insights and strategies in FFE management.
References Ancona, D. and Caldwell, D. (1990), ``Beyond boundary spanning: managing external dependence in product development teams'', Journal of High Technology Management Research, Vol. 1, pp. 119-35. Ancona, D. and Caldwell, D. (1992), ``Demography and design: predictors of new product team performance'', Organizational Science, Vol. 3, pp. 321-41. Atuahene-Gima, K. (1995), ``An exploratory analysis of the impact of market orientation on new product performance: a contingency approach'', Journal of Product Innovation Management, Vol. 12, pp. 275-93. Bayus, B. (1997), ``Speed-to-market and new product performance trade-offs'', Journal of Product Innovation Management, Vol. 14, pp. 485-97. Bonaccorsi, A. and Lipparini, A. (1994), ``Strategic partnerships in new product development: an Italian case study'', Journal of Product Innovation Management, Vol. 11, pp. 134-45. Brown, S. and Eisenhardt, K. (1995), ``Produce development: past research, present findings, and future directions'', Academy of Management Review, Vol. 20, pp. 343-78. Chandy, R. and Tellis, G. (1998), ``Organizing for radical product innovation: the overlooked role of willingness to cannibalize'', Journal of Marketing Research, Vol. 35, pp. 474-87. Chen, C., Ford, C. and Farris, G. (1999), ``Do rewards benefit the organization? The effects of reward types and the perceptions of diverse R&D professionals'', IEEE Transactions on Engineering Management, Vol. 46, pp. 47-55. Choperena, A. (1996), ``Fast cycle time-driver of innovation and quality'', Research-Technology Management, Vol. 39, pp. 36-40. Christensen, C. (1997), The Innovator's Dilemma: When New Technologies Cause Great Firms to Fail, Harvard Business School Press, Boston, MA. Cooper, R. (1988), ``Predevelopment activities determine new product success'', Industrial Marketing Management, Vol. 17, pp. 237-47. Cooper, R. (1993), Winning at New Products: Accelerating from Idea to Launch, Addison-Wesley, New York, NY.
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Jongbae Kim and David Wilemon
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Conference on Management of Engineering & Technology, Vol. 2. Kim, Y., Min, B. and Cha, J. (1999), ``The roles of R&D team leaders in Korea: a contingent approach'', R&D Management, Vol. 29, pp. 153-65. Lee, M. and Na, D. (1994), ``Determinants of technical success in product development when innovative radicalness is considered'', Journal of Product Innovation Management, Vol. 11, pp. 62-8. Leonard, D. (1995), Wellsprings of Knowledge: Building and Sustaining the Sources of Innovation, Harvard Business School Press, Boston, MA. Lester, D. (1998), ``Critical success factors for new product development'', Research-Technology Management, Vol. 41, pp. 36-43. Lynn, G., Abel, K., Valentine, W. and Wright, R. (1999), ``Key factors in increasing speed to market and improving new product success rates'', Industrial Marketing Management, Vol. 28, pp. 319-26. Lysonski, S. (1985), ``Boundary theory investigation of the product manager's role'', Journal of Marketing, Vol. 49, pp. 26-40. McDonough, E. and Barczak, G. (1991), ``Speeding up new product development: the effects of leadership style and source of technology'', Journal of Product Innovation Management, Vol. 8, pp. 203-11. McDonough, E. and Spital, F. (1984), ``Quick-response new product development'', Harvard Business Review, Vol. 62, pp. 52-62. McGuinness, N. and Conway, A. (1989), ``Managing the search for new product concepts: a strategic approach'', R&D Management, Vol. 19, pp. 297-308. Maidique, M. and Zirger, B. (1984), ``A study of success and failure in product innovation: the case of the US electronics industry'', IEEE Transactions on Engineering Management, Vol. 31, pp. 192-203. Merrills, R. (1989), ``How Northern Telecom competes on time'', Harvard Business Review, Vol. 67, pp. 108-14. Meyer, M. and Utterback, J. (1995), ``Product development cycle time and commercial success'', IEEE Transactions on Engineering Management, Vol. 42, pp. 297-304. Millson, M., Raj, S. and Wilemon, D. (1996), ``Strategic partnering for developing new products'', ResearchTechnology Management, Vol. 39, pp. 41-59. Moenart, R., De Meyer, A., Souder, W. and Deschoolmeester, D. (1995), ``R&D/Marketing communication during the fuzzy front-end'', IEEE Transactions on Engineering Management, Vol. 42, pp. 243-58. Murphy, S. and Kumar, V. (1997), ``The front-end of new product development: a Canadian survey'', R&D Management, Vol. 27, pp. 5-15.
Nambisan, S. and Wilemon, D. (2001), ``Online customer communities: redefining customer participation in NPD'', Proceedings of Portland International Conference on Management of Engineering & Technology, Vol. 2. Norrgren, F. and Schaller, J. (1999), ``Leadership style: its impact on cross-functional product development'', Journal of Product Innovation Management, Vol. 16, pp. 377-84. Page, A. (1991), ``PDMA new product development survey: performance and best practices'', paper presented at PDMA Conference, Chicago, IL. Priem, R. (1990), ``Top management team group factors, consensus, and firm performance'', Strategic Management Journal, Vol. 11, pp. 469-78. Quinn, J. (1985), ``Managing innovation: controlled chaos'', Harvard Business Review, Vol. 63, pp. 73-84. Reinertsen, D. (1999), ``Taking the fuzziness out of the fuzzy front-end'', Research-Technology Management, Vol. 42, pp. 25-31. Rochford, L. and Rudelius, W. (1992), ``How involving more functional areas within a firm affects the new product process'', Journal of Product Innovation Management, Vol. 9, pp. 287-99. Rosenau, M. (1988), ``Faster new product development'', Journal of Product Innovation Management, Vol. 5, pp. 150-3. Rubenstein, A., Geisler, E. and Abeysinghe, R. (1997), ``Industrial practices of research conversion and technology transfer'', Journal of Technology Transfer, Vol. 22, pp. 49-56. Smith, G., Herbein, W. and Morris, R. (1999), ``Front-end innovation at AlliedSignal and Alcoa'', ResearchTechnology Management, Vol. 42, pp. 15-24. Smith, P. and Reinertsen, D. (1992), ``Shortening the product development cycle'', Research-Technology Management, Vol. 35, pp. 44-9. Smith, P. and Reinertsen, D. (1998), Developing Products in Half the Time: New Rules, New Tools, 2nd ed, John Wiley & Sons, New York, NY. Song, X. and Parry, M. (1993), ``How the Japanese manage the R&D-Marketing interface'', ResearchTechnology Management, Vol. 36, pp. 32-8. Stevens, G. and Burley, J. (1997), ``3,000 raw ideas = 1 commercial success!'', Research-Technology Management, Vol. 40, pp. 16-27. Von Hippel, E. (1986), ``Lead users: a source of novel product concepts'', Management Science, Vol. 32, pp. 791-805. Wood, S. and Brown, G. (1998), ``Commercializing nascent technology: the case of laser diodes at SONY'', Journal of Product Innovation Management, Vol. 15, pp. 167-83.
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Introduction
An adopter-centered approach to understanding adoption of innovations
Recent IT adoption literature has focused on acceptance models relating perceptions and beliefs to attitudes, behavioral intention, and usage of the technology. Much of the most recent literature addresses the antecedents of these perceptions. What remain largely unexplored, however, are the processes by which these factors and others work together in adoption-related attitude formation, decision making, short-term and long-term behavior, and mental modeling. Such a process-oriented perspective raises new types of questions. Instead of asking how adoption constructs are related, we begin to ask how and why they become related. Instead of discovering the strengths of relationships, we discover how they are formed, and we begin to ask whether the formation of the relationships can be altered so that the adoption process itself can be manipulated. This paper uses Weick's (1995) description of sensemaking to develop an adoptercentered, process-oriented model of adoption.
Rex Eugene Pereira
The author Rex Eugene Pereira is an Assistant Professor of Management Information Systems at the College of Business Administration, Drake University, Des Moines, Iowa, USA. Keywords Innovation, New technology Abstract
Adoption as sensemaking Sensemaking is defined as the cyclical process of taking action, extracting information from stimuli resulting from that action, and incorporating information and stimuli from that action into the mental frameworks that guide further action. Waterman (1990) referred to sensemaking as the structuring of the unknown. Sensemaking has been described as the placing of stimuli into a mental framework (Dunbar, 1981; Goleman, 1985; Starbuck and Milliken, 1988) that is
Introduces an adopter-centered, process-oriented model with which to explore behavioral processes related to technology adoption. This approach enables us to learn about adoption as a process and to explore the subprocesses that affect perceptions and attitudes. This perspective provides the opportunity for a much richer understanding of how adoption occurs and how it can be influenced. Sensemaking focuses on the adopter herself, i.e. her mental frameworks, and the antecedents and products of those frameworks. The sensemaking model describes the evolution of the adopter's mental framework. Rogers' innovation-decision process model charts a progression of activities during the adoption process, whereas the sensemaking model explains the adopter's mental mechanics at each stage.
Since the publication of this article in the European Journal of Innovation Management, it has come to light that the content has been plagiarised from a paper by Larry Seligman entitled ``Adoption as sensemaking: toward an adopter-centered process model of IT adoption''. This paper was presented to the Twenty-First International Conference on Information Systems (ICIS) in Brisbane, Australia in December 2000 and was subsequently made available online in the library of ICIS proceedings. Emerald sincerely apologises to Larry Seligman for our error in publishing the paper. The research contained in the paper has been significantly updated by Larry Seligman and is available to read in the following article: Seligman L. (2006), ``Sensemaking throughout adoption and the innovation-decision process'', European Journal of Innovation Management, Vol. 9 No. 1, pp. 108-120.
Electronic access The research register for this journal is available at http://www.emeraldinsight.com/researchregisters The current issue and full text archive of this journal is available at http://www.emeraldinsight.com/1460-1060.htm
European Journal of Innovation Management Volume 5 . Number 1 . 2002 . pp. 40±49 # MCB UP Limited . ISSN 1460-1060 DOI 10.1108/14601060210415162
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An approach to understanding adoption of innovations
European Journal of Innovation Management Volume 5 . Number 1 . 2002 . 40±49
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used to direct interpretation (Cantril, 1941). Sensemaking is the recurring process of forming anticipations and assumptions, and the subsequent interpretation of experiences that deviate from these anticipations and assumptions (Louis, 1980). Thomas et al. (1993) call it ``the reciprocal interaction of information seeking, meaning ascription, and action''. If technology adoption is a form of sensemaking, then it should have the following characteristics: . it should be influenced by initial and evolving mental frameworks; . users should have initial perceptions and understandings about the technology; . these perceptions and understandings should be subject to change based upon stimuli (information) that the user receives; . the mental frameworks should be changed because of the incorporation of stimuli.
inevitability, turmoil, Utopianism, etc. As computerization progressed into implementation, the turmoil and Utopianism symbols were no longer used, but the new symbol ``otherness'' (alienness) emerged. Therefore, through training and implementation, the mental frameworks of the nurses changed. Some perceptions were dropped and replaced by other perceptions. Especially important is the fact that mental frameworks were in place from the beginning and continued well after initial adoption as individuals who used the system were attributed increased social status within the organization. Therefore, the adoption process does not begin at introduction to the technology, but rather substantially beforehand with the formation of initial perceptions and symbolic representations of the technology. Similarly, adoption itself does not take place as a single decision, but rather as a series of sensemaking cycles causing perceptions of the technology to change until apparent adoption or rejection actions are performed.
Figure 1 illustrates a general sensemaking cycle. These sensemaking characteristics are exemplified in Prasad's (1993) study of symbolic processes during the implementation of technological change. Prasad found that the symbolism of computerization held by occupational groups within a health-care organization changed as the computerization effort progressed from pre-computerization, through training and implementation, into the ``adoption'' phase of the process. Nurses, for example, initially represented the computerization process with such symbols as professionalism,
Other models of adoption Several adoption models view adoption as a linear, decision-focused progression through stages such as knowledge acquisition, problem framing, decision, implementation, and confirmation (Mintzberg et al., 1976; Simon, 1977; Rogers, 1995). Mohr (1987) suggests that adoption can be modeled in a number of ways related to readaptation and routine change. Dean (1987) and others suggest that adoption is a political process driven by technology champions. These approaches to adoption modeling view the
Figure 1 The sensemaking cycle
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adopter as a black box. They model adoptionrelated activities instead of modeling the adopter (Langley and Truax, 1994). Sensemaking focuses on the adopter herself, i.e. her mental frameworks, and the antecedents and products of those frameworks. Focus on the adopter reveals a variety of new influences on the adoption process and begins to explain curiosities in other adoption models (e.g. Simon's (1977) puzzle of stages within stages being viewable as a series of sensemaking cycles). The technology acceptance model (TAM) (Davis et al., 1989) and the theory of planned behavior (TPB) (Ajzen, 1991) are both linear representations of a portion of the sensemaking process. TAM in its essence suggests that perceptions of usefulness and ease-of-use can be used to predict behavior. TPB uses both social and non-social perceptions as well as identity constructions (within ``perceived behavioral control'') to predict behavior. However, it is through sensible interactions with the technology and/or previous experiences with using other technologies and performing similar tasks that the potential adopter forms these perceptions. Because these perceptions are both outcomes of and contributors to the sensemaking cycle, it is just as accurate to say that action predicts cue extraction and retrospection, and that these predict perceptions of usefulness, ease-of-use, behavioral control, etc. It is also important to note that the sensemaking model suggests that the adopter's mental framework as a whole is an action driver. Habit, impulse, and other components of the mental framework combine with perceptions to drive action, and the framework itself may not be the only action driver.
done), the actions of others (expression of opinions), his observations (of the reactions of others), and his reflection upon these things that contribute to his understanding of himself as a good or bad worker. Similarly, IT adoption directly impacts identity construction. A technology user may consider himself intelligent, cutting edge, aggressive, nerdy, professional, or other things, because he has or has not adopted technologies. Prasad's (1993) study provided examples of this by noting that some employees felt professional, organized, intelligent, respected, etc., when they used the information system. Interestingly, perceived adoption by other individuals, or even by other organizations, may also affect a person's self-identity. For example, a person may consider himself ``cutting edge'' until his co-worker obtains new equipment. IT adoption can impact an individual's social identity, as evidenced by the social status attributed to users of the system. IT adoption can even be a component of the constructed identity (Gremy et al., 1999). Several research questions emerge from identity construction's impact on IT adoption. Whose identities are constructed by potential adopters? What factors are related to these identity constructions, and how can they be manipulated? How does identity construction differ in different social environments? Sensemaking is retrospective Sensemaking is retrospective, because a person can only make sense of what has already happened, not what is happening at the instant it occurs. This implies that behavioral intention, especially when measured before subjects actually use a technology, is a weak indicator of enduring adoption behavior, since there is no real experience yet with the system. This implication is supported by Pfeffer's (1982) ``emergent'' view of action in organizations. Another implication of retrospective sensemaking is that adoption attitudes are formed by past adoption experiences or similar experiences in which the subject learned to use a complex tool. Antecedents of self-efficacy may, therefore, include past successes and failures in using various other complex technologies (a finding supported by Agarwal and Prasad, 1999), experiences in adapting to new ways of working, etc.
Properties of sensemaking Sensemaking is grounded in identity construction Sensemaking is grounded in identity construction, meaning that individuals learn by acting and reflecting upon their actions and the actions of others. When a worker accomplishes a task and receives feedback from others about his work, he learns opinions not only about his work but also about his identity as a good or bad worker. It is, therefore, his action (the work he has 42
An approach to understanding adoption of innovations
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Rex Eugene Pereira
characteristics suggest the importance of identifying the cues that people extract from their experiences with technologies, social contacts, organizational situations, etc., to understand how these cues affect mental frameworks. Cue extraction may be subject to a variety of influences. How does cue extraction differ in different social environments? What features or other characteristics of a technology become cues? How do different types of cues affect the resulting mental framework? An individual enacts the environment from which she will eventually extract cues. For example, consider an individual using an Internet search engine. The search engine prompts her for keywords (cues), and she decides how best to represent her topic of interest using one or more language cues and provides those cues to the search engine. Those cues guide the search engine to the information that it then presents to her. She has, therefore, substantially influenced the information from which she must now extract her cues. Therefore, it is important that anyone who provides cues to an information system must have some skill in knowing what cues to provide; otherwise, the system's usefulness and adoption may be diminished. Additionally, users should understand the importance of context for choosing an information source. Do users know the differences in the types of information they can get from information systems versus other sources? Are users being trained specifically in how to cue information systems?
Even more interesting is the notion that the mental framework that generates perceptions is subject to change during and after experience with the technology. Rice and Contractor (1990) found that technology adoption can change the conceptualization of office work. Such a reconceptualization can lead to remodeling of the relationships pertaining to IT adoption. For example, imagine that a potential IT user has certain norms and beliefs that influence his attitude toward adoption, including low self-efficacy. If his experience with the system improves his perception of that self-efficacy, will his mental framework evolve to exclude some of the norms and beliefs that were once important for considering technology adoption? Norms and beliefs are sometimes only justifications that protect a person from confronting the relationships between selfefficacy, attitude and intention. How are other perceptions changed by experience with computers? What existing influences affect the way that experiences with technology are retrospectively considered? Can future technology adoption be influenced by changing the sense the adopter retrospectively makes of past adoption experiences? Sensemaking is focused on and by extracted cues Extracted cues are simple, familiar structures that are seeds from which people develop a larger sense of what may be occurring. Cue extraction is the process of noticing what is salient and useful for mentally representing stimuli. It occurs both as scanning and as focused search, and contributes to both the maintenance and evolution of mental frameworks. Cues have several important characteristics. First, they are received as perceptions and, therefore, with subjectivity. Second, there is no reason to assume that everyone who experiences a particular event will pick up the same cues, or that two people who perceive the same cue will incorporate it similarly into their mental frameworks. Third, control over cues is a source of influence and power (Smircich and Morgan, 1982). Fourth, since cues are extracted from encountered stimuli, people often fail to consider what cues they may have extracted from stimuli that they did not encounter (Sanbonmatsu et al., 1997). These
Sensemaking is enactive of sensible environments Sensemaking is enactive of sensible environments, meaning that a person participates in the evolution of her environment and then must make sense of environmental events that resulted in part from her participation. One implication of enactment is the garbage-in, garbage-out principle. If the user does not enter data into an information system correctly, the system may fail to live up to her expectations and adoption may suffer. Another implication is that, although compatibility of the system with the user's current behaviors is known to have an influence on attitudes toward the system (Taylor and Todd, 1995), the user herself has influence over those behaviors. 43
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Therefore, the user manages the compatibility of her personal work environment with system usage. This personal work environment may separate the user from social influences or other stimuli that would impact her perceptions of the system. For example, an individual's work habits may prevent her from interacting with adopters who attribute social status to the system's users. In this case, a reengineering of social contacts may change her perceptions of the technology. What environmental conditions constrain or support technology adoption? How are personal, social and organizational habits related to adoption attitudes and behavior? How do a potential adopter's social contacts and the adoption behaviors of those contacts affect her behavior? How do individuals attempt to change their personal environments in response to new technology, and what factors affect the success of these environmental changes?
Social impacts on the IT adoption process include: . a person's adoption behavior being influenced by her perceptions of the adoption behavior of her workgroup, especially if the person is highly attracted to the workgroup (Fulk, 1993); . adoption being resisted if it is perceived to negatively affect the subject's autonomy, status, or relationships with other staff members (Rice and Anderson, 1994); and . the adoption behaviors of a group working closely together being different from the adoption behaviors of the same individuals working in isolation. Social impacts have been studied extensively. Ajzen (1985) and Ajzen and Fishbein (1980) used social norms as an antecedent of behavioral intention. Karahanna and Straub (1999) found social influences to be antecedents of perceived usefulness and perceived ease of use. Studies by Aydin and Rice (1991, 1992) and Rice and Anderson (1994) demonstrated that social worlds affect adoption attitudes. Socializing also allows for the sharing of symbolism, another form of representation and communication through cues (Prasad, 1993; Stryker and Statham, 1985). However, the sensemaking perspective stimulates new questions. What informational cues are communicated during social interactions that affect technology adoption? In what forms (e.g. informative statements, opinions, jokes, etc.) are these cues communicated? How should an adopter's connections be managed so that technology adoption is supported?
Sensemaking is social Sensemaking is social, in that no one makes sense in isolation, but rather each person derives sense in part from the words and actions of others, and produces sensible action and discussion that contribute to the sensemaking of others. For example, each statement in a group discussion contributes to the direction and outcome of the discussion. Each person contributes sensible statements or questions that, in turn, are used by others as the discussion proceeds. The conclusions developed by a participant at the end of the discussion may not reflect the opinions of the entire group but, as long as he listened to the discussion, his mental frameworks incorporated stimuli from the discussion and contributed stimuli by generating and contributing statements. Because social interactions allow for the development of common sensemaking, it follows that group interactions strengthen the group's common sense (Bettis and Prahalad, 1995) and help them to self-organize around it (Aydin and Rice, 1992; Brown and Eisenhardt, 1997). These interactions involve the entire sensemaking cycle as each individual interacts with her social environment and develops her mental models based on the information cues extracted from those interactions.
Sensemaking is ongoing Sensemaking is ongoing because of the cyclical nature of the sensemaking process. A person acts, makes sense of her actions, and then acts again, guided by the sense that she has already made. In the short term, the results and experiences of a user's first attempt to use a technology are part of the basis by which the user will decide whether or not to make a second attempt. Over time, continued use of a system affects the user's level of expertise with the system and the compatibility of the system with the user's other duties. This view is supported by structuration theory, which suggests that a 44
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inaccurate or incomplete information, the sense that is made is not necessarily formed into a belief in what would happen if the sensemaker adopted the technology (a probability belief), but rather an understanding of what could happen (a plausibility belief). This distinction is important because many constructs in existing technology acceptance models incorporate beliefs about what would happen, not what could happen (e.g. Davis's (1989) perceived usefulness and perceived ease of use constructs). This raises several interesting questions. What are the relationships between plausibility beliefs and user perceptions of and attitudes toward a technology? Are plausibility beliefs more emotionally driven than probability beliefs? How do emotional appeal and attractiveness affect adherence to plausibility and probability beliefs? How do these answers change in different contexts (e.g. common sensemaking in groups)?
technology can ``condition'' the practices of its users by facilitating and constraining user actions (Orlikowski and Robey, 1991). Many systems change over time due to software and hardware upgrades, maintenance changes, etc. The contextual conditions under which users work change over time as well. A system perceived as invaluable under certain conditions may seem trivial and wasteful under different conditions. Because of these changes, adoption behaviors at various points in time may differ because of contextual conditions. This perspective leads to behaviors such as postponed adoption (the intention to use the technology exists but circumstances delay usage), re-adoption (using again what was used before and then abandoned), and periodic adoption (occasional usage and relearning). The question arises, then, as to how organizational and contextual factors affect adoption at various stages of computerization. What models of change are useful for understanding how mental frameworks change over time? Do these mental frameworks become more stable over time, or do they demonstrate a form of punctuated equilibrium where users occasionally change their mental frameworks?
Sensemaking and technology adoption This section compares the sensemaking model of adoption with Rogers' (1995) innovation-decision process model (IDPM), the adoption-related part of Rogers' cornerstone contribution to diffusion theory. Rogers describes the innovation-decision process as ``the process through which an individual (or other decision-making unit) passes (1) from first knowledge of an innovation, (2) to forming an attitude toward the innovation, (3) to a decision to adopt or reject, (4) to implementation of the new idea, and (5) to confirmation of this decision''. These five stages describe the types of activities undergone by the individual during the innovation-decision process. The sensemaking model is a lower-level view, describing the evolution of the adopter's mental framework. At each of Rogers' stages, sensemaking compels the individual to sensible action, causing him to progress through the stages. Rogers' innovation-decision process model charts a progression of activities during the adoption process, whereas the sensemaking model explains the adopter's mental mechanics at each stage.
Sensemaking is driven by plausibility rather than by accuracy Sense is not only an understanding of what is directly observable and accurate, but also the achievement of a level of reasonableness for a situation that is suitable for the sensemaker's needs. This ``plausible reasoning,'' as Isenberg (1986) refers to it, exists even if the sensemaker has an incomplete or inaccurate understanding of the facts. Furthermore, plausibility is the result of preferential consideration of, and belief in, information. Fiske (1992) stated that sensemaking ``takes a relative approach to truth, predicting that people will believe what can account for sensory experience but also what is interesting, attractive, emotionally appealing, and goal relevant''. The resulting sense is a type of preferential plausibility that frames stimuli so that the preferences of the sensemaker are addressed. This preferential plausibility affects adoption-related attitudes and perceptions. Because the plausibility can stem from 45
An approach to understanding adoption of innovations
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Rex Eugene Pereira
The knowledge stage In the knowledge stage, an individual is exposed to an innovation's existence and gains some understanding of how it functions. This exposure may have happened by chance, or may have been the result of an effort to seek out the innovation once the individual had identified a need for it. Knowledge of an innovation is gained by extracting cues from stimuli. The stimuli that the individual encounters are partially a result of the individual's enacted environment. The individual may manage his social contacts and other elements of his environment in such a way as to gain knowledge about a particular innovation or about ways to meet a particular need. As Rogers notes:
If the innovation is desirable, the individual may alter his identification of himself, other people, or objects in his environment in order to justify adoption. For example, an individual who desires a new computer may justify purchase by convincing himself that his old computer is slow, failing, or inadequate. He may also try to convince others that he needs the new computer in order to gain support for it. Similarly, if the innovation is undesirable, then support for rejection will be sought. The decision stage In the decision stage, the individual ``engages in activities that lead to a choice to adopt or reject an innovation'' (Rogers, 1995). Adoption can be partial or full, probationary or complete. Rejection can be active or passive. Trial adoption can be done vicariously by observing or asking about a peer's adoption experience. Partial adoption and vicarious trial adoption allow the individual to encounter new stimuli for further adjustment of perceptions of the technology and for understanding how the innovation can be incorporated into the individual's environment. These types of adoption allow for retrospective mental framing before implementation. Trial adoption also allows for the gathering of socially developed information for sensemaking. The sensemaking model suggests that the individual has been engaging in adoptionrelated or rejection-related activities all along, and will continue to do so once the decision is made. The decision to adopt or reject the innovation involves actions to carry out the decision, but it is not the end of sensemaking about it. Unless the innovation is passively rejected, sensemaking will be directed toward implementation or toward the consequences of rejection. Once the decision is made, the justification of the decision will then be developed retrospectively.
Individuals tend to expose themselves to ideas that are in accordance with their interests, needs, and existing attitudes.
The persuasion stage In the persuasion stage, a favorable or unfavorable attitude toward the innovation is developed. At this stage, the individual seeks ``innovation-evaluation information'' (Rogers, 1995) to reduce uncertainty about the innovation's expected consequences. Formation of this attitude is dependent upon the opinions of peers and their experiences with the innovation. Any knowledge of the innovation must be incorporated into existing mental frameworks. This fact contradicts the idea that attitude formation occurs only after experiencing the technology. Because these mental frameworks contain knowledge of other, possibly similar innovations, the individual is able to have an attitude toward types of innovations and toward specific characteristics of innovations. These preexisting attitudes become part of the attitude toward the innovation. Because attitude formation begins before persuasion, information-seeking at the persuasion stage is for justifying, affirming, or modifying the attitude. Therefore, an individual can have an attitude toward an innovation based on very limited information and plausible beliefs. An individual who can only justify his attitude toward an innovation as a ``feeling'' or a ``hunch'' is doing so because the attitude formation is based on limited information about the innovation.
The implementation stage In the implementation stage, the adopter puts the innovation into use. If the adopter is also the implementer, then he will encounter the innovation extensively during implementation, acting to incorporate the innovation into his environment, while modifying his environment for the innovation and reinventing the technology. 46
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Table I summarizes the sensemaking activities within the innovation-decision process model.
Reinvention is simply evolutionary sensemaking (Swanson, 1994). Reinvention is driven by the same influences that drive sensemaking (e.g. exposure to new stimuli through environmental changes or social contacts, retrospection, identity construction, etc.). During implementation, the adopter will extract and incorporate many more cues from his experience with the innovation. His peers may be involved in or may observe the implementation and provide more stimuli for mentally framing the innovation and for constructing his identity. These peers may also be trial adopters of the technology and would, therefore, be extracting informational cues from the implementation during their own decisionstage activities.
Conclusions Having identified many of the factors that influence adoption of information technology, it is now important to learn about adoption as a process and to explore the subprocesses that affect perceptions and attitudes. This paper introduced an adopter-centered model with which to explore behavioral processes related to technology adoption. Exploration of the research questions mentioned in this paper must use a variety of methodologies. Survey research and interviews may be sufficient to explore changes in self-identity, changes to mental frameworks from retrospection, and perceptions of plausible impacts of technology usage. A more process-based approach may be necessary to understand the social interactions that affect, and are affected by, interaction with technology. Group conversations surrounding individual and group adoptions may be analyzed for signs of the effects of social interactions and other sensemaking activities. Understanding enactment and the ongoing nature of sensemaking may require longitudinal data or simulations because of the need to investigate environmental and perceptual changes over time. Cue extraction lends itself to experiments and questionnaires (e.g. asking subjects about the details that they notice as they interact with a system and how those details are interpreted).
The confirmation stage In the confirmation stage, the individual seeks reinforcement of his adoption or rejection decision. The individual may encounter cognitive dissonance and may decide to reverse his decision depending on the information he receives. Having performed a decision-related action and possibly implementation, the individual gathers information to retrospectively assess what he has done and what he should do next, including the possibility of reversing the previous adoption/rejection decision. However, according to the sensemaking model, action and retrospection have been happening at every stage of the IDPM. Confirmation is, therefore, an outcome of sensemaking that is occurring constantly throughout all the IDPM stages.
Table I Sensemaking activities within the innovation-decision process model Innovation-decision process model stage Knowledge Persuasion
Decision
Implementation Confirmation
Sensemaking activities Need-based identity construction Search for stimuli to mentally frame technology and adopters Reconstruction of identity to support or resist adoption Plausibility belief construction to frame possible outcomes of adoption or rejection Seeking of social guidance/reinforcement for the adoption decision Actions that can be identifiable as adoption or rejection, leading to enactment of the environment Partial or vicarious trial adoption enables retrospection Many stimuli from experience with the technology Reinvention through evolutionary sensemaking Action and retrospection lead to confirmation or disconfirmation throughout the IDPM stages
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References
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An approach to understanding adoption of innovations
European Journal of Innovation Management Volume 5 . Number 1 . 2002 . 40±49
Rex Eugene Pereira
Waterman, R. Jr (1990), Adhocracy: The Power to Change, Whittle Direct Books, Memphis, TN. Weick, K. (1995), Sensemaking in Organizations, Sage Publications, Inc., Thousand Oaks, CA.
Stryker, S. and Statham, A. (1985), ``Symbolic interaction and role theory'', in Lindsay, G. and Aronson, E. (Eds), New Handbook of Social Psychology (3rd ed.), Random House, New York, NY, pp. 311-78. Swanson, E.B. (1994), ``Information systems innovation among organizations'', Management Science, Vol. 40 No. 9, pp. 1069-92. Taylor, S. and Todd, P. (1995), ``Understanding information technology usage: a test of competing models'', Information Systems Research, Vol. 6 No. 2, pp. 144-76. Thomas, J., Clark, S. and Gioia, D. (1993), ``Strategic sensemaking and organizational performance: linkages among scanning, interpretation, and outcomes'', Academy of Management Journal, Vol. 36 No. 2, pp. 239-70.
Further reading Porac, J., Thomas, H. and Baden-Fuller, C. (1989), ``Competitive groups as cognitive communities: the case of Scottish knitwear manufacturers'', Journal of Management Studies, Vol. 26 No. 4, pp. 397-416. Vandenbosch, B. and Higgins, D. (1996), ``Information acquisition and mental models: an investigation into the relationship between behavior and learning'', Information Systems Research, Vol. 7 No. 2, pp. 198-214.
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