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his issue of Creativity and Innovation Management represents some of the fundamental underpinnings of the journal, as they are presented in the Editorial philosophy in the inside cover. There are two reasons for this. First, the five articles included in this issue contribute markedly to exploring innovation and creativity from distinct, and enriching, angles and perspectives. Not only the texts describe empirical studies carried out in different countries (Tanzania, England, Sweden and Spain) and industries (pharmaceuticals, ceramic tiles, and small and medium-sized enterprises), but they also show the application of several methodologies (interview, questionnaire), and present practitioner and academic views of the topics. This richness highlights the global importance achieved by innovation and creativity in modern society. Second, the variety in the articles content and form is counterbalanced by a common tenet. In fact, all contributing authors more or less offer challenging thoughts with regards to how should one organize for innovation and creativity, and even to what extent innovation and creativity should be central goals and purposes in the organization. The three empirical articles show that context is a powerful determinant in shaping the way the organization makes the necessary internal arrangements to start the innovation journey. The two conceptual articles go a step further, challenging the need for organizational structures in support of innovation and creativity, or even the need for being innovative and creative. In the first conceptual text, Isaac Getz and Alan Robinson use a considerable number of examples from service and manufacturing companies to illustrate their argument that the mantra (as they put it) ‘innovate or die’ does not quite capture the realities of several organizations. In fact, not innovating – or at least not coming up with radical innovations – may be the best choice! A more productive alternative is to use a system for managing ideas. The first empirical article, by Maria Oltra and Marisa Flor, explores the concept of absorptive capacity and its relationship with technological opportunities and with a firm’s output capacity in the Spanish ceramic-tile industry. Based on questionnaires collected from 91 companies, © Blackwell Publishing Ltd, 2003. 9600 Garsington Road, Oxford OX4 2DQ and 350 Main St, Malden, MA 02148, USA.
the authors found that technological opportunities with a significant effect on firms’ innovation activities are those stemming from co-operation with other firms. Mats Sundgren and Alexander Styhre put forward nine principles to manage creativity as an organizational resource. These principles emerged from a study in the pharmaceuticals industry, where they used a system approach and interviewed 18 researchers in two British and Swedish companies. Their results suggest that creativity is complicated to manage as an organizational resource since it is based on both tight control and clear objectives at the same time. In the article by Christopher Mahemba and Erik Joost de Bruijn, Tanzanian small and medium-sized manufacturing enterprises provide questionnaire data concerning firms’ innovation practices. Amongst the interesting results found, the authors report that innovating practices in the areas of adoption of new products, production methods and organization or market development, were generated by actively obtaining external support, from customers and from other enterprises, but not from government or universities. Finally, Miguel Cunha and Jorge Gomes draw a parallel between organization science and new product development and innovation models in order to propose five innovation models – sequential, compression, flexible, integrative and improvisational. These models illustrate several movements: from universal to contingent models, from invariant to flexible practices, from avoiding risks to taking advantage of opportunities, from planning to learning, from exclusive teams to inclusive networks, and from structure to structured chaos. All in all, the message delivered by these articles and authors is that notwithstanding the centrality achieved by creativity and innovation in recent years, academics, managers, consultants and policy makers alike need to carefully and critically think through these subject matters, prior to embarking in solutions which may not deliver the expected results. Olaf Fisscher Jorge F.S. Gomes, Guest Editor
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Innovate or Die: Is that a Fact?1 Isaac Getz and Alan G. Robinson ‘Innovate or die’. This mantra has been repeated so many times – by the media, governments, business leaders, business professors, consultants and management gurus – that people have come to assume it is actually true. This article explores why have business leaders been so prone to fall for such a naïve message, and shows how it has caused them to overlook the true sources of long-term high performance.
Introduction
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n October 2002, as it does every year, the French daily Le Monde published the rankings of French corporate R&D budgets and held a special event to celebrate the biggest spenders. This year the winner, at €5.1 billion, was EADS, an aerospace consortium, followed by Aventis at €3.5 billion, and €Alcatel at 2.9 billion. The media is not alone in hyping this kind of ranking. Governments do it, too. In 2002, for example, the UK Department of Trade and Industry (DTI) published its twelfth annual R&D Scoreboard. Other governments track the same data in their own countries. Why? The reason is the cherished dream of corporations and governments – a dream of innovation with its promise of success and riches. As the DTI R&D Scoreboard put it: ‘Innovation has been highlighted as the origin of growth in free market economies and R&D is a key investment in innovation since it leads to new products, processes, and services’ (p. 3). Although the report immediately backtracks, and comes close to questioning this latter assertion (‘It is, of course, only part of the investment in innovation since investments in capital equipment and in the development of new markets, systems and skills are also important’ (p. 3)), it then carries on blithely about its business of displaying R&D budget data under the assumption that it holds the key to everything. ‘Innovate or die’. This mantra has been repeated so many times – by the media, governments, business leaders, business professors, consultants and management gurus – that people have come to assume it is actually
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true. Even if a company is well-managed and has the highest profits and customer satisfaction in the industry, without the ability to generate breakthrough innovations, so the mantra goes, it is not long for this earth. But is this really so? There are plenty of examples of companies with outstanding engines of innovation that consistently perform poorly. There are equally many of organizations that have been high performers for decades without innovating much at all. How did Lucent Technologies, which owns Bell Laboratories, perhaps the leading generator of inventions in the world, end up in so much trouble? How did Xerox – which invented the laser printer, the Ethernet, and the point-andclick interface – turn in such an appalling performance over the last decade? How did Alcatel, third in the Le Monde rankings and consistently in the top few over the last fifteen years, get in such trouble in recent years? Was it the bursting of the dotcom or telecom bubbles? Cisco and Microsoft, on the other hand, did just fine. When we asked one executive from Cisco, which recently became the world largest telecommunication infrastructure supplier – and unlike Lucent, Alcatel or Nortel is hugely profitable – how it manages innovation, his reply was: ‘We do not. We just buy it’. And how did Microsoft, a laughing stock in the industry for its lack of innovativeness, become one of the most powerful companies in the world? Until 1991, the company did not even have an R&D function. 1
This paper draws partly on the material published in our book Vos idées changent tout! (in French), Editions d’Organisation, Paris, 2003 (German edition to appear in October 2003, Hanser, Munich).
© Blackwell Publishing Ltd, 2003. 9600 Garsington Road, Oxford OX4 2DQ and 350 Main St, Malden, MA 02148, USA.
INNOVATE OR DIE: IS THAT A FACT?
In this article, we discuss how the ‘innovate or die’ assumption has led companies to make costly mistakes. To begin with, it made many managers think that their companies had to generate inventions themselves. It gave them a ‘jackpot mentality’, a belief that everything would be made right with a handful of ‘homerun’ innovations – innovations that would change the very terms of competition in their industries. Worst of all, it has led a generation of managers to try to build the ability to innovate before taking care of more important things – such as making sure their processes are customer-focused, and that their organizations are listening to the more mundane everyday ideas of their front-line employees. The ‘innovate or die’ mantra has been an easy sell for consultants and management gurus, because it promises great riches, with relatively little effort.
The Bright and the Dark Sides of the Innovation Mantra In the preface to his book Leading the Revolution, Gary Hamel (2000) lays out his imperative: ‘We’ve reached the end of incrementalism, and only those companies that are capable of creating industry revolutions will prosper . . . Radical innovation is the competitive advantage for the new millennium’ (p. xii). In The Circle of Innovation, Tom Peters (1999) makes essentially the same point: ‘Incrementalism is innovation’s worst enemy . . . If you’re spending every . . . hour making “it” a bit better . . . then . . . you are not spending every hour on reinventing it, blowing it up’ (p. 27); ‘The only sustainable competitive advantage comes from out-innovating the competition’ (p. 29). The bottom line is: ‘Innovate or die’ (p. 308). Why have business leaders been so prone to fall for such naïve messages? As Dauphinais and Price (1999) put it in their book Straight from the CEO: ‘Of all the wish-fulfilling dreams a CEO might have, none can be more glittery than the notion of massive transformation by innovation, of getting rich on needs and wants undreamed of by anyone before. This is the innovation jackpot’ (p. 235). It is the mantra’s bright side, the same thing that attracts people to casinos or lotteries – the prospect of a ‘big win’ that will solve all their problems and bring them success in a single moment of glory. There are, however, two problems with managers pinning all their hopes on a glamorous splash. First, it causes them to believe that the wrong things matter, and that the
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right things do not. Second, because of exactly the same psychology behind the highly successful ads for state-owned lotteries, management forgets the probabilities involved and believes it has a real chance of hitting the jackpot. Let us look more closely at each of these assertions. Are Hamel and Peters right? Is the innovation jackpot, in fact, the key to it all, with the alternative being a gory death? The answer is a resounding no. We have already mentioned Cisco and Microsoft, which became their industries’ leaders (and continue to grow) without originating much in the way of innovation themselves. Sony is another example. It is known for having generated dozens of innovations. But beginning in 1980, CEO Akio Morita deliberately decreased Sony’s ability to generate technological inventions, and built instead an ability to create better products through incremental improvements.2 Morita realized that his company’s focus on generating radical inventions actually diverted attention, time and resources away from what was truly important for its success – continuously improving and putting topnotch products on the market before the competition and at a reasonable cost. Many observers still cite Sony as one of the most innovative companies in the world and they are right. After having dramatically reduced its internal capacity to innovate, Sony remains as innovative as ever, and still alive and kicking. Another reason that seeking the innovation jackpot gets companies into trouble is that the probability of hitting it is extremely low. Many companies entertain the belief that hitting an innovation jackpot through in-house, R&Dgenerated inventions is a realistic possibility. Almost a century ago, Freud explored and explained the human tendency to take our dreams for reality. And the innovation jackpot certainly fits his theory. It is an expensive dream with a very low probability of realization. A cross-industry study (Stevens and Burley, 1997) estimated that out of every 3,000 initial ideas, only 300 result in experiments and/or patent filings, from which only 125 advance into full-fledged projects, and from these only 1.7 products are launched, with only one finally succeeding in the market (in
2
See Clayton Christensen’s (1997) The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail, Harvard Business School Press, Boston, USA as well as his interview ‘Sony celebrates the results of fine tuning’, Financial Times, 4 May 2001, p. 9.
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pharmaceutical industry, the proportion is not 3,000, but 5,000 to 1). The same study also found that only 5 to 10 percent of US patents have any market relevance and only 1 percent of them actually bring any profit. With odds like these, companies might well be better off putting their money into the lottery! To understand why these probabilities are so low for most companies, consider the following example of a company that did hit the jackpot. In August 2001, CyThera, a small start-up, stunned the biotechnology research community with the announcement that it had derived nine colonies of stem cells. This put it second only to Göteborg University in Sweden, which had nineteen, and ahead of every other academic and corporate research lab in the world. The company put itself on the National Institutes of Health list of stem cell lines eligible for use by scientists financed by the US federal funds and others who work on growing cells with therapeutic potential to repair damaged heart, brain, liver, or other organs. This cell-growth technology instantly made the company a leading provider of a service – growing stem cells – that was in great demand in the research centres all over the world. So what did it take for a company with $2 million in venture financing and only ten employees to get ahead in a research area in which major academic institutions and, according to one recent estimate, one-tenth of all pharmaceutical corporations worldwide are all actively jockeying for position? It had, of course, a top scientist, Jonathan C.R. Jones, a professor of cell and molecular biology and CyThera’s co-founder, who developed the technology to grow certain cells in the laboratory. But its other two co-founders, CEO Michael J. Ross and COO (Chief Operating Officer) Lutz B. Giebel, were long-time biotechnology industry executives and entrepreneurs. Ross spent 13 years at Genetech, after which he was the first CEO of Arris, and then, in 1996, started MetaXen, which was sold to Exelixis in 1999. Giebel worked at Arris, and then co-founded MetaXen with Ross. These two men are the equivalent of Silicon Valley insiders who know their industry well. They are familiar with the various lines of research and inventions, and know how to connect them to market needs, how to sell new product or service prototypes to outside financing bodies, and how to move from prototypes to final products. What are the chances that an average company, if it was involved in this stem-cell research area, would come out with such an innovative service if it had hired only Professor Jones as the head of research? Witness IBM
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Research Laboratories, one of the benchmark corporate labs in the world and employing a number of Nobel-prize level researchers. IBM owns the world’s largest patent portfolio but, in terms of its patents’ relevance to profits – most often measured by the number of patent citations by other inventors (cf. Harhoff et al., 1999) – it falls far short of the array of start-ups acquired by Cisco or even of a relatively small company like Micron Technology in recent years.3 If IBM – ‘the gold standard for turning research into corporate profit’4 – is beaten by start-ups and smaller companies in generating profit-relevant inventions, the average corporation using the same approach is almost certain to be left behind too. Depending on its industry, a company may need top-flight researchers (like Professor Jones) and research facilities (like corporate labs). But whatever its industry, in order to come up with inventions that will ultimately be profitable, it needs CyThera-like entrepreneurial dynamics and specialized market knowledge – a unique combination of research and business savvy, which can connect an initial research invention with customers’ needs and success factors and then turn it into a market opportunity. The lottery-like statistics for success at dramatic innovation merely reflect how difficult it is for a company to bring all this together. Witness the latest data from the industry in the USA that spends most heavily on R&D – the pharmaceutical industry, to which CyThera belongs. Several studies based on data from the Food and Drug Administration and other sources explored the relationship between this industry’s R&D investment and the number of new drugs put on the market.5 One key finding is that between 1991 and 2001 R&D spending rose from $9.7 billion to $30.3 billion, while the number of new drugs introduced each year dropped from 30 to 24. The Tufts Center for the Study of Drug Development report also notes that ‘blockbusters are rare and largely unpredictable’ (p. 3; ‘blockbuster’ means a drug whose annual sales exceed $800 million, the average cost of developing a new drug). Even the probability of hitting a
3
‘The TR patent scorecard 2001’, Technology Review, May 2001, pp. 48–49. 4 ‘Eureka! Labs with profits’, New York Times, 9 September 2001, ‘Money and Business’ section, p. 1. 5 ‘Cross-functional team focus on marketing is key to project success’, Tufts CSDD Impact Report, Vol. 2, December 2000; ‘New drug approvals in 2001’, PhRMA report, January 2002; see also ‘Drug research yields a decreasing return’, International Herald Tribune, 20–21 April 2002, p. 11.
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profitable drug (much less an actual jackpot) through in-house R&D is very, very low. Furthermore, if a company does happen to hit the jackpot – that is, it actually comes up with the next PC or Xerox machine – it will immediately confront a new difficulty: robbers. Other companies that will try to pilfer its jackpot once it is out in the open. Protecting and patenting it is not always feasible in practice and is something many companies that generate inventions are reluctant to do anyway. In particular, small high-tech companies often avoid doing it. For example, Broadcom, a leading designer of chips for communication devices has only eight patents, compared to Intel’s more than three thousand. As Robert Dobkin, CTO of Linear Technologies, puts it, filing the documents for a public patent is like broadcasting to your competition what you’re working on, it is ‘giving away everything’.6 But even if a company does protect its invention, it still faces another difficulty: extremely able and creative imitators. Think of Microsoft with Windows-type technology invented by Xerox and Apple, of Seiko with the Quartz watch mechanism invented in Switzerland, or of Sony with the video-game-dedicated computer invented by Sega. Chances are high that competitors will figure out a way around what is protected, make the jackpot too expensive to protect, or eat away at it in some other way. For example, in 2001, Intel sued a Silicon-Valley company for infringing five of its patents, but according to analysts the burden of proof was so high that it actually had a very low chance of winning (in the USA, between 1921 and 1973, the courts declared almost two-thirds of the patents they ruled on invalid (Lubar, 1990), and a Yale University survey found that in only five out of 130 industries are patents ‘highly effective’ for protection, while they were deemed ‘moderately effective’ in only twenty more (Levin et al., 1987).) Whatever happens, Intel has to spend time and resources protecting its patents, as do many other potential ‘jackpot’ generators who face negative odds and high costs involved in upholding their patents. So apart from the dreams in CEOs minds, for all intents and purposes there may not actually be such a thing as an innovation jackpot. Many companies use a ‘jackpot’ approach, but few have any success with it. Unfortunately, in addition to delivering poor results, the jackpot approach draws attention and resources away from what a company really needs to do to drive progress. 6
‘Are patents really a virtue?’ Fortune, 16 October 2000, p. 136.
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The irony is that the alternative to the innovation jackpot may not be the death of the organization, but its salvation, bringing not only progress but, ultimately, excellence. Furthermore, while the particular mechanisms that bring this progress are important for the company’s general success and growth, they also improve the quality of its innovation management, and innovation may matter in some situations. We believe it is time to shed our unrealistic dreams and focus on what truly matters.
The alternative: progress, excellence, and . . . real innovation What makes an excellent company – not a flash in the pan, but one that will be enduringly successful? The unvarnished truth is that customer-focused processes and basic continuous improvement play a far more important role than innovation in organizational success. This was a clear finding of one of the most extensive studies of the factors underlying long-term corporate success, Built to Last. Authors Collins and Porras (1997) did not find the ability to innovate to be a success factor, but rather what they called ‘mechanisms of progress’ – systematic approaches, whatever these might be, for continually improving. Take GE, in 2001 the world’s biggest and most enduringly successful corporation. It has one of the oldest corporate research labs in the world, but in his recent book Jack, Jack Welch (2001) makes not a single mention of an innovation originating there, or for that matter, anywhere else in the company. But Welch wrote a lot about something else: the customer-focused processes around which he organized the company and the systems he built for continuous improvement. He states that a key mechanism that made the ‘difference between GE and the rest of the world in the 1990s’ was not innovation but the boundaryless system that allowed everyone in the company to ‘search for and apply the best ideas regardless of their source’ (p. 186) and led GE to ‘Find a Better Way Every Day’ (p. 189). We can find the same emphasis on processes in another extensive study on what it actually takes for a company to grow and prosper. In his book Agenda, Michael Hammer’s (2001) key finding was that the ‘must have’ platform for success is good processes, which very few companies have. Toyota, perhaps the world’s most successful car manufacturer – and one we ourselves have studied on three continents – is a good example. The company is hardly known for its innovative products. Its cars are
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fresh and up-to-date, of course, but its success really derives from the extraordinary reliability and quality it delivers at reasonable prices. Toyota has one of best continuous improvement systems of any company we are familiar with. Innovation is not like water or food. It is not true that if you do not have them, you will not live. Many companies are not innovative but are enduring and prosperous because they take care of what really is water to them – processes – and really is food – improvement mechanisms. However, if most business leaders are familiar with how to get good water, few really know the secret of getting great ‘food’. The single most important improvement mechanism is the ability to listen to and act on the ideas of front-line employees. Most companies rely almost exclusively on top-down improvement approaches such as Reengineering and Six Sigma which, the claims of their proponents aside, do not go very deep. They are, in essence, ‘planned’ approaches that address mostly issues big enough to have been noticed by management. While top-down approaches are necessary and good, they are inherently limited, because they miss the far-larger set of less visible improvement opportunities that regular employees spot in the course of their daily work. Companies that track the source of improvement ideas, such as the Dana Corporation and Pirelli have come up with an interesting rule of thumb – in practice, 80% of improvement ideas come from employees and only 20% come through planned improvement activities. This astonishing fact would seem to indicate that many companies have poured money and resources into initiatives with relatively low return. Several years ago, we set out on a three-year study – ultimately involving some 50 European companies plus a few US ones – to learn about how the best companies tap this largely overlooked potential and what they gain from it. Although every company we studied used a different name for what we are about to describe, we call it here a System for Managing Ideas (SMI). Perhaps the most surprising thing we learned however is that in addition to enabling truly deep process improvement, an SMI can also be a pillar of internal innovation, a statement we will elaborate on in the last section of the article.
The System for Managing Ideas An SMI encourages the expression, processing of, and recognition of ideas from every employee in the company. However it is set
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up, a good SMI incorporates three things: (1) simple and rapid processing of ideas, (2) a means to involve middle managers, and (3) appropriate performance measures and recognition. A good SMI aims to implement the vast majority of employee ideas within a matter of days. This means that the process for authorizing, evaluating and giving the resources to implement an idea has to be very simple. The simplest and fastest approach of all is to enable author-led idea implementation. After all, the biggest champion for an idea is the person who first thought of it. The role of middle managers is to facilitate the process, and demonstrate to employees that the ideas they come up with determine an important part of their value to the company. A company must make sure that middle managers, and particularly front-line supervisors, are actively looking out for employee ideas and responding promptly and supportively when they come in, and make it clear to them that their success at doing this is a key part of how they will be evaluated as managers. Ultimately, managers get involved when they realize that managing ideas in their units well is key to their success. Finally, a good SMI measures the activity it is trying to promote. At a minimum, good SMI track the number of submitted ideas per employee, the implementation rate and the participation rate (the percentage of employees who submit at least one idea in a given period). These measures have two purposes: to monitor and recognize the creative ideas of employees, and to evaluate each manager’s performance in facilitating and encouraging ideas. If a manager is not paying attention to the ideas of her employees, it will soon be reflected in these simple statistics. How well does a good SMI work? A considerable number of organizations around the world have been able to average more than twenty ideas per employee per year, with implementation rates of over 80 percent. In good systems, participation rates run at least 90 percent, and more than €8,000 in net costsavings or new revenue are generated per employee per year. No centralized suggestionbox scheme has ever come close to this level of performance. In 2000, Sweden, with the best suggestion schemes in Europe, got 0.53 ideas per employee per year, with a 50 per cent implementation rate, a 20.7 per cent participation rate, and €224 of savings per employee per year.7 A good SMI is a very different beast, 7
Suggestion Systems in Sweden 2000, Swedish Institute for Suggestion Systems, 2001.
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which uses an entirely different process than a traditional suggestion scheme. A good SMI is key to high corporate productivity, quality and growth, and to creating a work environment that is fulfilling to work in. The CEO of Michelin told us that François Michelin once commented to him that over the years he had asked many Michelin retirees what they remember most fondly about working at his company. Almost invariably, he had noticed they told him of some ideas they had come up with that the company had implemented. In other words, their ideas were the way they left their mark on the organization, and felt they had made a difference. But a good SMI delivers much more than this. Our research found that it also plays a critical role in improving company’s ability to innovate.
The SMI – the Foundation of Good Innovation Management A good SMI promotes a culture in which everybody is encouraged to express and act upon ideas. This culture and all the resulting ideas greatly increase the likelihood of success for innovative projects. For example, a few years ago, Pirelli engineers in charge of launching a multi-million euro and highlyinnovative new manufacturing line were stuck for months on a problem. Funnily enough, a number of technicians had already figured out a solution to it, because the company had a good SMI and they were used to identifying and working on improvement ideas. But they kept these particular ideas to themselves because of the company’s ‘moratorium’ on rewarding employee ideas regarding new projects. The engineers discovered this only when one of them noticed some technicians smiling while he and his colleagues were struggling with a problem, realized why and got the company to lift the moratorium. This natural experiment demonstrated how even a few months’ moratorium on employee ideas may derail an important innovation. The sad thing is that in most companies such moratoriums are permanently in place, because they have no real mechanisms to listen to employee ideas. Even if an employee is not expert enough to solve a given problem, in companies having good SMIs, he or she can help identify it and bring it to the attention of people who can deal with it. An effective SMI puts more control and predictability into the process of innovation. An SMI also helps to involve everybody in an innovation and make them stay more closely in touch with customers, suppliers,
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partners and competitors whose input is often critical to the company’s success. At WeberHaus, the leading timber house company in Germany, the SMI is used to allow its employees to initiate innovation projects with suppliers. For example, one operator suggested a design for some new equipment, contacted the supplier and worked with him for several weeks. The supplier then manufactured the new equipment and delivered it to WeberHaus. The company thus triggered an innovation and benefited from it at a minimal cost. The SMI turns every employee into a set of antennae for the company, discovering and solving problems critical for its success in innovation. An SMI also compels persons directly involved in the innovation project to confront problems and facts they might otherwise prefer to ignore. How many times has a project failed because of something a person tried to tell those responsible for a project but could not get them to listen. The space shuttle Challenger’s dramatic explosion is a much-studied case where an engineer tried many times to get those in charge to listen to his warnings. And regarding the September 11, 2001 terrorist attack, if the FBI had an SMI, the warnings of its field officers in Minnesota and Arizona on this attack planning might have been captured and acted upon instead of being ignored by the headquarters. In these, as in many other cases, there was a lot of pressure to ignore the warnings and proceed. The SMI makes it much more difficult to do this. Every idea submitted to an SMI is documented and there is a process that is followed to check it out, which is documented too. Instead of ignoring informal comments, managers now have to ignore official suggestions that are part of an entire system to encourage such proposals – and one that is equipped with controls and checks, and is fully transparent. A good SMI also increases the quantity and the creativity of successful innovation projects. We have already mentioned the initially counter-intuitive statistic at work regarding the percentage of ideas that come from frontline employees. Because most companies are poor at listening to their front-line employees – particularly those on the boundaries of their organizations – they are really tapping only 20 per cent of the potential creativity available to them. Another way of looking at this is that using an SMI to gather ideas for innovation projects as well, will increase their number by at least a factor of five. But there is more: our studies revealed that the 80 per cent of projects initiated by the front-line employees also tend to be the most creative ones. That means that using the SMI
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as a tool to initiate innovation ideas leads not only to the increase in their number by the factor of five, but also to the significant increase in their novelty and creativity.
Conclusion We believe a company that seriously wants to grow and prosper in the coming decade can not afford to lose the ideas of its front-line employees. Many good companies have fallen prey to ‘Innovate or Die’ mantra, skipped over the foundations of progress – customerfocused processes and managing their employees’ spontaneous ideas – and jumped straight into building the penthouse – the layer of innovation capability. They have paid the price of not taking care of the foundation first. It is always fun in the penthouse, but the fun will not last long if it is built on moving sand.
References Collins, J.C. and Porras, J.I. (1997) Built to Last. HarperBusiness, New York. Dauphinais, G.W. and Price, C. (eds.) (1999) Straight from the CEO. Simon Schuster/Price Waterhouse, New York. DTI (2002) R&D Scoreboard (12th edition). Department of Trade and Industry, U.K. Hamel, G. (2000) Leading the Revolution. Harvard Business School Press, Boston. Hammer, M. (2001) Agenda: What Every Business Must Do to Dominate the Decade. Crown Business, New York. Harhoff, D., Narin, F., Scherer, F.M. and Vopel, K. (1999) Citation frequency and the value of patented inventions. The Review of Economics and Statistics, 81(3), 511–15. Levin, R.C., Klevorick, A., Nelson, R.R. and Winter, S.G. (1987) Appropriating the Returns from
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Industrial Research and Development. Brookings Papers on Economic Activity, (3), 783–820. Lubar, S. (1990) New, useful, and nonobvious. Invention & Technology, Spring/Summer, 9–16. Peters, T. (1999) The Circle of Innovation. Vintage Books, New York. Stevens, G.A. and Burley, J. (1997) 3,000 raw ideas = 1 commercial success! Research-Technology Management, May-June, 16–27. Welch, J. (2001) Jack: Straight from the Gut. Warner Books, New York.
Isaac Getz is Professor of Creativity and Innovation Management at the ESCP-EAP European School of Management, Paris 75011, France,
[email protected]. He was also Visiting Professor at Cornell and Stanford Universities and at the University of Massachusetts. Dr. Getz’s current work focuses on creativity, innovation, and idea management, and has led him to over sixty companies in Europe. He is editor of a recent book, Organizational Creativity, and co-author (with A. Robinson) of another book, Our ideas change everything, appearing in French and German in 2003. Dr Alan Robinson’s last book Corporate Creativity (co-authored with Sam Stern) was translated into twelve foreign languages, was a finalist in the Financial Times/Booz Allen & Hamilton Global Best Business Book Awards, and was named “Book of the Year” by the Academy of Human Resource Management. He has advised more than ninety companies in eleven countries, and has served on the Board of Examiners of the U.S. Malcolm Baldrige National Quality Award. He received his Ph.D. from Johns Hopkins University, and a B.A./M.A. from Cambridge University. Isenberg School of Management, University of Massachusetts, Amherst, MA 01003, USA, agr@som. umass.edu
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The Impact of Technological Opportunities and Innovative Capabilities on Firms’ Output Innovation María J. Oltra and Marisa Flor In this study, we analyse the effect that external sources of knowledge and absorptive capacity exert on a firm’s output innovation. In addition, we examine the moderating influence of absorptive capacity on the effect that technological opportunities have on output innovation. Empirical research was carried out on a sample of 91 Spanish firms from the ceramic tile industry. Absorptive capacity is operationalized by ‘systematic or continuous R&D’ and output innovation by ‘percentage of sales from new products’. Technological opportunities are divided into several industry and non-industry related variables. Our results show the positive effect that both the industry’s technological opportunities and a systematic approach to R&D exert on output innovation. Moreover, firms with a systematic approach to R&D usually achieve higher innovation output than firms which do not follow this approach. The innovation results of this second group decrease as a result of embedded technology acquisition.
Introduction
T
he identification of both internal and external factors that determine a firm’s technological innovation activity is one of the most widely examined issues in innovation literature. Internally, the technological capabilities of the firm constitute an important aspect when explaining its innovative behaviour. Externally, one of the most relevant factors affecting firm’s innovation is technological opportunity. Although the opportunity to incorporate external technology may discourage internal innovation activities, the relation between the two may be seen as complementary, since knowledge developed outside the firm differs from internal knowledge. Thus, the influence of external sources of knowledge on a firm’s innovative activity cannot be isolated from the characteristics of the firm itself, in particular, its internal capabilities concerning the generation of technological innovations. Absorptive capacity, defined as the ability to identify, assimilate and exploit external knowledge, is an important basis of a company’s innovative capability, which depends on the © Blackwell Publishing Ltd, 2003. 9600 Garsington Road, Oxford OX4 2DQ and 350 Main St, Malden, MA 02148, USA.
level of existing related knowledge in the company (Cohen and Levinthal, 1990). In other words, it is not only a matter of internally producing basic resources and outsourcing those which are not critical, since absorptive capacity in a certain technical area constitutes an essential asset, representative of the nexus between internal and external resources and capabilities (Chiesa and Barbeschi, 1994; Christensen, 1996). In addition, the level and quality of absorptive capacity is not homogeneous and varies from one company to another, and, to a certain extent, between industries (Becker and Peters, 2000). There is little evidence of the role of absorptive capacity in relation to its joint effect with technological opportunities on firms’ technological innovation. Thus, in this study, we start from the premise that a firm’s innovation output depends both on internal innovation capabilities and external technological sources, and propose that the extent to which companies can use technological opportunities is closely related to the knowledge possessed prior to the use of external knowledge, i.e. it depends on its absorptive capacity. The study is structured in three sections. First, the
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perspectives on innovation that constitute the theoretical framework of the research are presented and the relevance of technological opportunities and absorptive capacity on innovation activity are briefly outlined. We then examine the influence of technological opportunities and internal technological capabilities, as an expression of a firm’s absorptive capacity, on output innovation. This section also introduces the research methods and describes the sample, measurement and analytical tools used. Finally, our main conclusions are presented.
Literature Review Classical contributions in economics literature on technological innovation stressed that differences in firms’ innovation activities could be explained predominantly by an industry’s structural characteristics, firm size, technological opportunities and demand conditions (Kamien and Schwartz, 1982). In addition, studies carried out over recent decades have demonstrated that, together with those factors, other aspects such as the accumulative nature of technology and the existence of multiple innovation inputs also determine a firm’s innovation activities (Cohen, 1995; Dosi, 1988; Freeman, 1994). In this context, evolutionary approaches, mainly developed from Nelson and Winter (1982), focus on understanding how technological and competitive evolution occurs. They explain that differences among firms are due not only to firms’ size but to their technological capabilities, which also contribute to explaining the differences in their innovative behaviour (Dosi, 1988). Thus, innovative activities are related to accumulative, tacit and firm-specific knowledge incorporated into the firm by means of routines. Closely linked to these approaches, in the strategic management field, the resourcebased view has constituted the basis for numerous contributions that emphasise differences among firms and the importance of resources and capabilities as a source of competitive advantage (e.g. Barney, 1991; Grant, 1991; Mahoney and Pandian, 1992; Wernerfelt, 1984). This perspective highlights the intangible nature of technological resources, which hinders their transfer in the market and duplication by competitors. Hence, competitive advantage sustainability is linked to the firm’s ability to develop and accumulate technological resources, since accumulation of resources over time obstructs the imitation of abilities and knowledge and opens up unique opportunities for innovation. Together with the internal development of technological capabilities,
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the incorporation of external knowledge and its integration with internal resources is relevant. External sources of knowledge are viewed as a way of complementing, rather than substituting, internal innovation efforts (Teece, Pisano and Shuen, 1997). Within this framework, technological opportunities can be seen as an important source of external knowledge for a firm’s innovation process. Nevertheless, their influence on innovation activities will be less effective than it might be if the firm does not possess a certain absorptive capacity to identify and exploit external knowledge.
Technological Opportunities Technological opportunity refers to the opportunity firms have for technical advance. Other than this general concept, there is no consensus on how to make it precise and empirically operational (Cohen and Levin, 1989; Klevorick, Levin, Nelson and Winter, 1995). In the neoclassical theory of production, technological opportunities have been regarded as the set of production possibilities for translating research resources into new production techniques that employ conventional inputs. They have been represented in the production function by one or more parameters relating research resources to increments in the stock of knowledge. Several works associate technological opportunity with industry and classify industries on the basis of their scientific or technological knowledge field. In this sense, Scherer’s (1965) initial proposal classified industry-related fields as chemical, electrical and mechanical. As well as the scientific and technology field classification, the contribution of other sources of technical knowledge, classed as extra-industry sources, such as the knowledge coming from upstream suppliers, downstream users, universities, government agencies and labs and professional societies are included within technical opportunity by other authors (e.g. Levin, Cohen and Mowery, 1985; Cohen, Levin and Mowery, 1987). In this line, a more complete scheme is used by Klevorick et al. (1995), where feedback from an industry’s own technological advances is considered as a third source of technological opportunities. Since technological opportunity was expected to be industry specific, most initial research that included the above-mentioned technological opportunity dimensions attempted to analyse inter-industry differences, although research can also be found by taking the firm as a unit of analysis (Becker and Peters, 2000; Cohen and Levinthal, 1989, 1990). In this sense, in Becker and Peters
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(2000), technological opportunity is more precisely conceived and related to the contribution of external knowledge to the firms’ innovation activities, and can be divided into industrial and non-industrial sources. Technological information from suppliers, customers and competitors constitutes information from industrial sources. Non-industrial sources relate to knowledge from innovation activities outside the private sector. Various empirical studies have stressed the importance of sources of technological opportunities in the innovative process, mainly by testing their effect on R&D indicators, both at firm level (Becker and Peters, 2000; Cohen and Levinthal, 1989, 1990; Sterlacchini, 1994) and at industry level (Klevorick et al., 1995; Sterlacchini, 1994). In general, they agree that the less-targeted knowledge sources such as universities and scientific research have a positive effect on R&D intensity (Becker and Peters, 2000; Cohen and Levinthal, 1989, 1990; Klevorick et al., 1995 Sterlacchini, 1994). Fewer studies have analysed the influence of technological opportunity on firm innovation output and their results cannot be directly compared because of the differences in the classifications of technological opportunities (Becker and Peters, 2000; Klevorick et al., 1995).
Absorptive Capacity Absorptive capacity represents the firm’s ability to link technological opportunity and internal capabilities to develop new and improved products. These abilities help firms to be competitive in the face of external technological developments (Joglekar, Bohl and Hamburg, 1997). However, as Veugelers (1997) indicates, although there is a wide theoretical and empirical body of research on firm and industry characteristics that lead to innovation, when it comes to examining the links between them and the effect of other companies’ and institutions’ activities that may facilitate innovation, existing literature is scarce, and mainly focuses on the substitutive nature of the relationship. Although the availability of external technology may deter, and therefore substitute, investment in internal research, there are also arguments that stress the complementarity between internal and external knowledge. These arguments are based on two related areas of reasoning: learning is cumulative and learning performance is greatest when the object of learning is related to what is already known (Cohen and Levinthal, 1990). In that sense, internal R&D may play an important role when reducing some of the inefficiencies and
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problems associated with external technology acquisition, even when it is only a matter of adapting and improving it (Veugelers, 1997). Technological knowledge is not equally shared between firms and its transference between companies requires learning due to the tacit nature of technology and the difficulty of understanding its underlying principles (Dosi, 1988). Therefore, technological capabilities determine not only the competence or skills with which certain technologies are developed and improved in the firm, but also how internal efforts are used to assimilate technologies acquired or imitated from other companies (Lall, 1992). Incorporation of external technology implies more than simply acquiring equipment or product designs. It involves a continuous, incremental change, where external contributions are shaped to particular conditions in multiple specific situations and are improved to achieve higher performance levels than those initially presented (Bell and Pavitt, 1993). Therefore, technologically dynamic companies seldom act passively, even when their investment in new facilities and production equipment depends on different external agents. In addition, as pointed out by Bell and Pavitt (1993), technological change is generated through complex interactions between companies and institutions. In this sense, universities and research institutes complement firms’ internal knowledge and rarely act as a substitute for their innovating activities by generating complete innovations to be immediately implemented. Rather, they usually create certain knowledge that companies need to manage their own technical change. In general, companies which more frequently resort to these institutions are not looking to compensate their own technological capabilities, but are firms that make a considerable effort in R&D and are searching for certain knowledge inputs to complement their internal innovating activities. In this vein, the process by which firms accumulate technological capabilities may be helped by the creation of different types of institutional structures. Empirical evidence for these arguments is not conclusive. Some research finds no signs of complementary effects between internal technological capabilities and different forms of external knowledge. Kleinknecht and Reijnen (1992) verified that neither a firm’s R&D intensity nor a high rate of product R&D influences the extent to which a firm cooperates. Likewise, Rocha’s results (1999) cannot confirm the hypothesis that a higher intensity in R&D is necessary when firms are willing to absorb external knowledge from alliances. Similarly, although indirectly,
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Sen and Egelhoff’s findings (2000) partially support these results, since they show that firms more frequently attempt to increase their market power through technological alliances with firms possessing similar capabilities rather than using them to complement their innovative capabilities. Nevertheless, some empirical evidence also supports the notion that absorptive capacity is necessary to make best use of the complementary nature between internal and external know how. Kleinknecht and Reijen (1992) verified the positive effect of having a formal R&D department when co-operating with R&D institutes. Veugelers (1997) demonstrated that the effect of co-operation in R&D is not significant in R&D intensity unless companies have an R&D infrastructure. Likewise, external R&D hiring and technology acquisition, essentially in the form of equipment, enhances internal R&D only when there is an absorptive capacity, as represented by the existence of an R&D department. The different empirical models in the research carried out by Becker and Peters (2000) lend support to the fact that the combined effect of technological opportunities stemming from scientific research and internal R&D, expressed both in terms of possession of a formal department and regularity of R&D activities, exerts a positive effect on the firm’s innovative activity, represented either by inputs or outputs of the innovation process.
Research Method Scope of Research This study was set within the Spanish ceramic tile industry. One of the most outstanding features of this industry is the high concentration of firms in the province of Castellón. In 1999, 93 per cent of national production took place in this area, where 77 per cent of Spanish tile companies are located (ASCER, 2000). A combination of various characteristics justifies our selection of this sector. According to Pavitt’s (1984) classification, most ceramic tile companies can be identified as supplier-dominated firms, a category that comprises traditional manufacturing sectors. In this type of industry, technical change usually comes from equipment and other production-process suppliers, which in our case would be the ceramic enamel suppliers. Technical choices reflect relative factor costs and the opportunities for internal technological accumulation are focused mainly on improvements and modifications in production methods and associated inputs, and occasionally on product design (Pavitt,
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1984). Accordingly, although innovation possibilities are essentially external to the firms, companies must still develop a strong commitment to and an active behaviour towards innovation, which will materialize in the constant adoption of new technologies generated by materials and machinery suppliers, and internal innovation efforts. Nevertheless, most studies which examine firm’s technological innovation behaviour have focused either on emergent, science-based industries or on specialised supplier industries. Consequently, less attention has been given to mature sectors with a more traditional technology, even when they present continuous technological development as reflected in the consistent adoption of new technology and introduction of incremental innovations. Data used in our analysis was gathered through a questionnaire addressed to company managers and mailed to all the firms in the industry with complete production cycles. Drawing on available 1998 databases, 205 firms were identified. Information was gathered between May and November 1999. The total number of responses was 93, of which two were eliminated as they were incomplete. The final sample was composed of 91 firms, representing 44 per cent of the population.
Measurement of Variables Bearing in mind the characteristics of the industry, it seemed appropriate to reflect a firm’s technological performance in relation to its products. Accordingly, innovation activity was represented by means of an output indicator, product innovation, as an expression of a firm’s technological performance. Firms were asked to specify, from total sales in 1998, the percentage attributable to sales of technologically new products and to sales of technologically improved products introduced during the 1996–1998 period. The sum of the two figures was used as an indicator of product innovation. As pointed out by Klevorick et al. (1995), in spite of the importance of technological opportunities, their formalisation or measurement is not clear, since they are diverse and multi-faceted. In our case, following the distinction made by Becker and Peters (2000), external sources of knowledge incorporated in the analysis include those directly stemming from linkages with other companies related to the industry (industrial technological opportunities), and those derived from institutes and organizations outside the business sector (non-industrial technological opportunities). Generally, suppliers, customers and competi-
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tors constitute industrial knowledge sources and technological information from these sources is incorporated into the firm either when the firm acquires technology or co-operates with one or other of these groups. Three variables were used to reflect these industrial technological opportunities: embedded technology acquisition, non-embedded technology acquisition and co-operation with firms. Information was obtained by asking the companies to assess, on a 7-point scale, the importance of the above-mentioned forms of co-operation and technology acquisition as a source of innovation. Embedded technology acquisition was represented by the importance as a source of innovation given by the firm to the purchase of machinery and equipment for new products and processes. Non-embedded technology acquisition was reflected by the importance given to patents and/or design acquisition, license of know-how, and so on. Co-operation with firms represents the average of scores on importance given to (1) co-operation with customers, (2) co-operation with equipment suppliers, (3) co-operation with raw materials suppliers (enamels), and (4) co-operation with other firms in the industry. Non-industrial technological opportunities were represented by co-operation with research centres, which reflected the average of scores given by the company to (1) co-operation with universities, (2) co-operation with the Ceramic Technology Institute (ITC) and (3) co-operation with the Association for the Promotion of Ceramic Design (ALICER) as sources of innovation. The last two items refer to institutes devoted to research related to the ceramic tiles industry. As in the other variables, assessment of these items was carried out on 7-point scales that expressed various degrees of importance. As pointed out by Becker and Peters (2000), the empirical measurement of absorptive capacity is difficult. Several proxies have been suggested in different studies: the existence of a formalised R&D department (Becker and Peters, 2000; Veugelers, 1997); regular company activity in internal R&D (Becker and Peters, 2000); percentage of total sales devoted to personnel training (Becker and Peters, 2000); percentage of R&D personnel with a doctorate degree (Veugelers, 1997); relation to the scientific base of research undertaken in a company (Veugelers, 1997); total R&D expenditure (Rocha, 1999); and R&D intensity (Rocha, 1999). We represented the absorptive capacity of a firm with the dummy variable systematic R&D, which reflected the regularity of a firm’s internal R&D activities, as it was asked about in the questionnaire. The selection of this variable reflects the accumulative
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nature of the abilities needed to adapt external knowledge. On the other hand, as highlighted by Becker and Peters (2000), it illustrates the idea that firms which are continuously engaged in R&D have efficiently established internal capabilities for generating their own innovations as well as for the adaptation of external knowledge.
Analysis and Results Analysis Multiple regression analysis was used to examine the effect of technological opportunities and absorptive capacity on output innovation. Following a hierarchical procedure, different models were estimated (Table 1). In all cases, the examination of error terms verified that regression assumptions were met, and there were no severe multi-colinearity problems. First, we analysed the impacts of technological opportunities on the innovation output (Model 1). We then added absorptive capacity (Model 2). Finally, we estimated different models (Models 3–6) in order to examine the influence of absorptive capacity on the relationship between the diverse technological opportunities and innovation output. In doing so, interaction terms representative of the joint effect of systematic R&D and each one of the technological opportunities variables considered were incorporated into the regression equation.
Results The effect of technological opportunities on output innovation, as shown in Model 1, indicates that only industry technological opportunities positively affect the percentage of sales attributable to new and improved products. Specifically, those stemming from cooperation with other firms are statistically significant. Technology acquisition, embedded and non-embedded, does not influence product innovation output. These results are in line with findings reported by Klevorick et al. (1995), where equipment suppliers only showed a positive correlation coefficient with process innovation but not with product innovation, which was positive with material suppliers and users. With regards to non-industry technological opportunities, they were not significant. Although different works have demonstrated the influence of scientific knowledge on R&D intensity, both at firm level (Becker and Peters, 2000; Cohen and Levinthal, 1989, 1990; Sterlacchini, 1994) and at industry level
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Table 1. Regression Analysis Results Variables Unstandardised coefficients
Intercept Embedded technology acquisition Non-embedded technology acquisition Co-operation with firms Co-operation with research centres Systematic R&D Interaction term F R2 Adjusted R2
Model 1
Model 2
Model 3 Embedded Technology
Model 4 NonEmbedded technology
Model 5 Co-operation with firms
Model 6 Co-operation with research centres
4.05 1.87
4.46 1.42
-8.96 3.8
0.733 1.11
-5.842 1.446
4.69 1.47
1.15
0.48
1.02
1.89
0.865
0.48
9.89** -2.33
9.58** -2.39
10.68** -3.8
9.78** -1.906
12.2** -2.86
9.6** -2.63
73.36* -11.73* 6.033** 0.301 0.251
28.603* -5.204 5.205** 0.271 0.219
45.52* -7.67 5.38** 0.278 0.226
11.57 6.193** 0.224 0.188
5.817** 0.255 0.211
9.98 0.52 4.794** 0.255 0.202
* The relationship is significant at a level of 0.05. ** The relationship is significant at a level of 0.01.
(Klevorick et al., 1995; Sterlacchini, 1994), there is no agreement on the direct effect on firm innovation output (Becker and Peters, 2000; Klevorick et al., 1995). The fact that only industry technological opportunities affect innovation output, and that the effect of non-industry technological opportunities is not significant lends new support to the proposals of Becker and Peters (2000), which justify similar results because of the indirect effect caused by scientific research on firm innovation output. Incorporation of the systematic R&D variable in Model 2 confirms that a systematic or continuous approach to R&D is positively related to the percentage of sales of new and improved products. In addition, the fact that co-operation with other firms is still significant suggests the complementary nature of both variables. The moderating effect of absorptive capacity is only significant when we consider the joint effect of systematic R&D and embedded technology acquisition (Model 3). In this case, the significance of the interaction coefficient indicates the existence of pairwise differences between the slopes of the equation regression models for both groups considered, i.e. firms with and without systematic R&D activities. By testing the statistical significance of each group slope (Jaccard, Turrisi and Wan, 1990), that is, its difference from value of zero, we can reject the null hypothesis for firms with absorptive capacities. Thus, replacing the significant coefficients in the general interaction
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equation, the equation for the group with no systematic R&D activities is: FIP = 10.68 CF + e and for the group with absorptive capacity, FIP = 73.36 + 10.68 CF - 11.73 ETA + e where FIP represents firm innovation product, CF co-operation with firms and ETA embedded technology acquisition. It can be observed that the effect of the technological opportunity of co-operation with firms on firm innovation performance is always positive, but the effect of technological embedded acquisition varies depending on the possession of absorptive capacity achieved through systematic R&D. In firms that do not possess absorptive capacity, technological embedded acquisition does not exert any effect on their product innovation performance. When firms have absorptive capacity, the acquisition of embedded technology causes a drop in firm product innovation output. On consideration of the relatively high intercept value in equation (2), our interpretation of the results is that most firms with systematic R&D achieve higher firm innovation performance than firms that do not carry out R&D activities. But this interaction is nonordinal. Both groups of firms reach the same level for innovation business performance when the embedded technology acquisition value is very high (6.254). Thus, only in the
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case of very high values of embedded technology acquisition, firms with absorption capacity achieve lower values of innovation firm performance than firms that do not carry out R&D systematically. The fact that neither co-operation with firms nor co-operation with research centres presented significant interaction terms with our moderating variable, in contrast to the findings of Becker and Peters (2000) and Veugelers (1997), suggests that the specific characteristics of the industry analysed might contribute to explaining our findings.
Conclusions In this research, we have studied the influence of technological opportunity and absorptive capacity on firms’ innovation output. Specifically, our interest focuses not only on the main effects of these variables, but also on the existence of a moderating effect of absorptive capacity in the relation between technology opportunity and innovation results. Bearing in mind that these determinants of innovation are not only industry specific but also firm specific, we have examined the above relationship at the firm level and focus on a single industry, the Spanish ceramic tiles industry, which is mainly made up of supplier-dominated firms. Results obtained highlight that the technological opportunities with a significant effect on firms’ innovation activities are those stemming from co-operation with other firms. Other technological opportunities, such as technology acquisition and non-industry opportunities are not significant. In the latter case, it reinforces Becker and Peter’s (2000) suggestion about the indirect effect of scientific knowledge as a technological opportunity. Nevertheless, the scant work on the effect of scientific knowledge on firm innovation output must be pointed out, and suggests a need for further consideration of this relation in future research. Additionally, as expected, the possession of absorptive capacity, expressed by a systematic approach to R&D, shows a positive influence on innovation output. Findings requiring reflection are those derived from interaction analysis between both categories of variables, as they do not lend support to our initial approach. The fact that neither co-operation with firms nor cooperation with research centres presents significant interaction terms with our moderating variable, in contrast to findings by Becker and Peters (2000) and Nelson and Wolff (1997), might be explained by the specific characteristics of knowledge transfer in the industry analysed, such as the complexity. But a deeper analysis would require more information
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which would also provide clues for future research. The interaction term embedded technology acquisition shows a significant effect, the analysis of which has revealed that this opportunity only has an influence on innovation output when a firm has absorptive capacities, and it reduces firm innovation output. This result could be explained by the existence of different types of absorption capacity for different types of external knowledge, which has been suggested in previous works. For example, Meeus, Oerlemans and Hage (2001) found quality differences in the internal resource base that explained interactive learning. Also, Nelson and Wolff (1997) pointed out that science-based technological opportunity requires a higher level of absorptive capacity than that generated by other knowledge sources such as customers, due to its higher complexity. Different types of absorption capacities might also be needed for product or for process innovation. In this sense, Veugelers (1997) justifies her results on the moderator influence of absorptive capacities in the relation of technology purchase on firm innovation activities, because of the need to adapt the technology acquired. Evidence is also obtained about the fact that, for similar levels of co-operation with firms, most firms carrying out systematic R&D achieve higher levels of innovation performance. Firms that do not carry out systematic R&D only reach higher product innovation output when they have a very high dependence on embedded technology acquisition. Differences in firm innovation output between firms that carry out R&D systematically and those that do not are lower for higher values of co-operation with firms. In all likelihood, these constitute the main guidelines obtained for managers interested in product innovation output. They should consider the two roles developed by R&D activities, not only its direct effect on firm innovation output, but also the indirect effect, through the accumulation of absorptive capacity. It has been proved that in supplier-dominated firms, systematically developed R&D, together with firm co-operation, enhances product innovation output but also allows for a lower dependence on external technology acquisition.
References ASCER (2000) El sector español de fabricantes de baldosas cerámicas 1999. Castellón: ASCER, Área de Estudios Económicos. Barney, J. (1991) Firm resources and sustained competitive advantage. Journal of Management, 13, 363–80.
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Becker, W. and Peters, J. (2000) Technological opportunities, absorptive capacities and innovation. Paper presented at The Eighth International Joseph A. Schumpeter Society Conference, Manchester, July 2000. Bell, M. and Pavitt, K. (1993) Technological accumulation and industrial growth: Contrasts between developed and developing countries. Industrial and Corporate Change, 2, 157–209. Chiesa, V. and Barbeschi, M. (1994) Technology strategy in competence-based competition. In Hamel, G. and Heene, A. (eds.), Competence Based Competition, Wiley, Chichester, pp. 293–314. Christensen, J.F. (1996) Innovative assets and interasset linkages – A resource-based approach to innovation. Economics of Innovation & New Technology, 4, 193–209. Cohen, W. (1995) Empirical studies of innovative activity. In Stoneman, P. (ed.), Handbook of the Economics of Innovation and Technological Change, Blackwell, Oxford, pp. 182–264. Cohen, W.M., Levin, R.C. and Mowery, D.C. (1987) Firm size and R&D intensity: A re-examination. Journal of Industrial Economics, 35, 543–63. Cohen, W.M. and Levin, R.C. (1989) Empirical studies of innovation and market structure. In Schmalensee, R. and Willig, R.D. (eds.), Handbook of industrial organization, Elsevier Science, Amsterdam, pp. 1059–107. Cohen, W.M. and Levinthal, D.A. (1989) Innovation and Learning: the two faces of R&D. The Economic Journal, 99, 569–596. Cohen, W. and Levinthal, D. (1990) Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35, 128–52. Dosi, G. (1988) Sources, procedures, and microeconomic effects of innovation. Journal of Economic Literature, XXVI, 1120–71. Freeman, C. (1994) The economics of technical change: A critical survey. Cambridge Journal of Economics, 18, 463–514. Grant, R.M. (1991) The resource-based theory of competitive advantage: Implications for strategy formulation. California Management Review, Spring, 114–35. Jaccard, J., Turrisi, R. and Wan, Ch.K. (1990) Interaction effects in multiple regression. Sage Publications, Newbury Park, California. Joglekar, P., Bohl, A.H. and Hamburg, M. (1997) Comments on Fortune Favors the Prepared Firm. Management Science, 43(10), 1455–62. Kamien, M.I. and Schwartz, N.L. (1982) Market Structure and Innovation. Cambridge University Press, Cambridge, MA. Kleinknecht, A. and Reijnen, J.O.N. (1992) Why do firms cooperate on R&D? An empirical study. Research Policy, 21, 347–60. Klevorick, A.K., Levin, R.C., Nelson, R.R. and Winter, S.G. (1995) On the sources and significance of inter-industry differences in technological opportunities. Research Policy, 24, 185–205. Lall, S. (1992) Technological capabilities and industrialization. World Development, 20, 165–86. Levin, R.C., Cohen, W.M. and Mowery, D.C. (1985) R&D appropriability, opportunity and market structure: New evidence on some Schumpeterian
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hypotheses. American Economic Review Proceedings, 75, 20–4. Mahoney, J.T. and Pandian, J.R. (1992) The resourcebased view between the conversation of strategic management. Strategic Management Journal, 13, 363–80. Meeus, M.T.H., Oerlemans, L.A.G. and Hage, J. (2001) Sectoral patterns of interactive learning: an empirical exploration of a case in a Dutch region. Technology Analysis and Strategic Management, 13(3), 407–31. Nelson, R.R. and Winter, S.G. (1982) An evolutionary theory of economic change. Belknap Press: Cambridge, MA. Nelson, R.R. and Wolff, E.N. (1997) Factors behind cross-industry differences in technical progress. Structural Change and Economic Dynamics, 8, 205–20. Pavitt, K. (1984) Sectorial patterns of technical change. Towards a taxonomy and a theory. Research Policy, 13, 343–73. Rocha, F. (1999) Inter-firm technological cooperation: Effects of absorptive capacity, firm size and specialization. Economics of Innovation & New Technology, 8, 253–72. Scherer, F.M. (1965) Firms size, market structure, opportunity and the output of patented inventions. American Economic Review, 55, 1097–125. Sen, F.K. and Egelhoff, W.G. (2000) Innovative capabilities of a firm and the use of technical alliances. IEEE Transactions on Engineering Management, 47, 174–83. Sterlacchini, A. (1994) Technological opportunities, intraindustry spillovers and firm R&D intensity. Economic Innovation and New Technology, 3, 123–37. Teece, D.J., Pisano, G. and Shuen, A. (1997) Dynamic capabilities and strategic management. Strategic Management Journal, 18, 509–33. Veugelers, R. (1997) Internal R&D expenditures and external technology sourcing. Research Policy, 26, 303–315. Wernerfelt, B. (1984) A resource-based view of the firm. Strategic Management Journal, 5, 171–80.
María J. Oltra is Professor of Operations Management at Universitat Jaume I, Department of Business Administration and Marketing, 12071 Castellón, Spain, e-mail:
[email protected], teaching and conducting research in the fields of Operations Management and Innovation Management. She graduated in Agronomic Engineering in Polytechnic University of Valencia (Spain). Her main research interests include operations strategy and its influence on firm’s performance and determinants of firm innovation performance. Marisa Flor is assistant professor of Innovation Management at Universitat Jaume I, Department of Business Administration and Marketing, 12071 Castellón, Spain e-mail
[email protected]. Her research focuses on technology strategy and its influence on export performance of firms and factors influencing firm’s innovation behaviour.
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Creativity – A Volatile Key of Success? Creativity in New Drug Development Mats Sundgren and Alexander Styhre This paper presents a study of successful and creative projects in the pharmaceutical industry. Creativity is here defined as the ability to bring forth a new product within a specific domain of knowledge, namely in gastrointestinal, cardiovascular and oncological medicine. The paper, being based on interviews with 18 of the most leading pre-clinical, clinical and pharmaceutical researchers at former AB Hässle and ICI Pharmaceutical Division, suggests that if creativity is to be managed as an organizational resource, there are at least nine facets that need to be considered. These nine facets range from the most practical aspects to issues of project culture and human faculties such as curiosity and joy. The paper concludes that there is such a thing as creativity management but also claims that creativity is complicated to manage as an organizational resource, since it is based on both tight control and clear objectives at the same time, as there must be space for experimentation, discussions and what could be called non-linear thinking.
Introduction
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rganizations and companies need to renew themselves continuously and be innovative in order to remain competitive (D’Aveni, 1994; Leonard-Barton, 1995; Nonaka and Takeushi, 1995). This is particularly true for the pharmaceutical industry, an industry renowned for its strong dependence on applied research in various disciplines of the natural sciences such as medicine, organic chemistry, biochemistry, and pharmacology and drug delivery technology (Koretz and Lee, 1998). Heavy investment in applied research and long new-product development cycles, in conjunction with legal protection through patents is the basis for competitive advantage in the pharmaceutical industry (Cardinal, 2001; Jones, 2000; Roberts, 1999; Yeoh and Roth, 1999). The bedrock for all innovation is the ability to contrive new services and products (Dougherty, 1999; Hargadon and Sutton, 2000). Products and services are in turn constituted by a multiplicity of components, for instance, a machine is composed of various entities, a service is constituted by a number of processes. These components (entities, processes, technologies, etc.) are themselves dependent on the employees’ ability to come © Blackwell Publishing Ltd, 2003. 9600 Garsington Road, Oxford OX4 2DQ and 350 Main St, Malden, MA 02148, USA.
up with new ideas. In brief, the employees’ ability to be creative is of great importance for all organizations (Oldham and Cummings, 1996). One of the trends in the pharmaceutical industry is expansion and consolidation. For the last five years, mergers, acquisitions or alliances have consolidated many pharmaceutical companies. Novartis, Pharmacia Corp., GlaxoSmithKline, AstraZeneca and Pfizer are some examples. The R&D budgets for theses large companies are substantial. Pfizer for example, has an R&D budget of more than US$5 billion and is an R&D organization of more than 12,000 researchers (The Economist, 2000). To gain optimal revenue, many large pharmaceutical companies are becoming more focused on products in the research pipeline that are expected to become blockbusters or megabrands (revenue of more than US$1 billion per year). One reason for this is the substantial cost involved in new drug product development, which is underlined by the example reflected in the increased demands of documentation and extensive clinical trials. The tendency in industry is, therefore, to maintain high focus, to decrease time to market and to reduce bottlenecks in order to optimize the patent term of the product
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(Tranter, 2000). Another aspect of making the research process more effective is the increased influence of technology in R&D programmes, such as computer-aided drug design (CADD), combinatorial chemistry linked to high throughput screening (CC/ HTS), and genomics (Horrobin, 2000). The pharmaceutical industry has always been a knowledge-based industry and its profitability is based on its past ability to create and utilize new scientific knowledge. The last decade has resulted in an unprecedented rate of generation of information in almost every domain of science. This presents many opportunities, but the snag is to utilize it wisely in a cost-effective and timely manner. One of the pronounced concerns or outcomes of these factors, in combination with large complex organization structures and increasing demands for efficiency and decreased risktaking in early research, is how to create a balance between creativity and economies of scale (The Economist, 1999). R&D-intensive organizations often claim that creativity is one of their most critical success factors and important assets. Creativity is needed to come to new insights that may lead to innovation and competitive products (Rickards, 1999). However, from an organizational, and a practical perspective, there are gaps between theory and practice when attempting to understand creative action organizations. From a theoretical perspective, much of the previous research on creativity has in some sense been influenced by the ‘myths’ and ‘romance with creativity’ which may oversimplify explanations for events and attribute the great achievements merely to individuals. More recent research has questioned the validity of the personalized approach to creativity and rather stressed the importance of the productive interplay between individuals and the ‘ecosystems’ of individuals (i.e. organizational design, reward systems) (Ford and Gioia, 2000). This fascination with individual-centred creativity itself is not well suited to understand and deliberately promote creativity in organizations. Furthermore, to understand creativity in an organizational context, it is valuable to take a more holistic approach and use the concept of organizational creativity. Much of the existing theory of creativity either has a person-centred perspective, or has not fully taken into account the organizational setting. In addition, most creativity research has been done outside the boundaries of organizations (Ford, 1995). This leads forward to focus on the higher potential source of creativity and to increase the understanding of creativity in organizations. The practical and theoretical
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research problems in this paper can thus be formulated as: • In the background of seven successful pharmaceutical projects, developed from 1975 to 1985, what organizational aspects are important for improving the understanding of organizational creativity in pharmaceutical R&D? • What theoretical framework can increase the understanding of creative action in an organizational context of the two pharmaceutical companies studied? This paper presents a retrospective study of two separate pharmaceutical companies: ICI Pharmaceutical Division (UK) and AB Hässle (Sweden), operating within the fields of oncology, gastrointestinal and cardiovascular medicine. The companies have been very successful in new product development and a number of blockbuster drugs have been developed. The study is based on recent interviews with 18 of the most influential researchers, including project leaders and line managers in office during the period 1975–1985, when several new important drugs were developed. The study thus aims at investigating the new product development activities during the period and is focused on seven projects within the two companies. The selected projects later became successful products that today represent a total sale of more than US$9 billion. The paper suggests that creativity is never located as specific entities (machines, databases, etc.) or persons, but is always a fundamentally distributed capacity, which takes place within networks or through individuals in a specific setting. Furthermore, if creativity is to be managed as an organizational resource, there are at least nine facets that need to be considered, ranging from the most practical aspects to issues of project culture and human faculties such as curiosity and joy. The paper concludes that there is such a thing as creativity management, but also claims that creativity is complicated to manage as an organizational resource since it is based on both tight control and clear objectives at the same time, as there must be space for experimentation, discussions and what could be called non-linear thinking.
The Notion of Creativity Webster’s dictionary defines creativity as the ‘ability to create’ and put forth; ‘uncreativeness’ is its antithesis. Creativity is, in turn, defined as ‘having the ability or power to create’ and as being ‘characterised by originality and expressiveness’, e.g. ‘creative writing’. Next, creation is defined as ‘the act of creating’, or ‘the fact or state of being created’. These
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definitions indicate that creativity is grounded in itself, as being either an act (‘to create’) or a quality (‘creative solutions’, ‘creative thinking’) rather than being based on two or more external processes or as signifying some underlying activities. Whitehead (1978) points out that the English notion of creativity is etymologically derived from the Latin creare, ‘to bring forth, beget, produce’. Thus, creativity is about producing new things, ideas, or entities. Therefore, to Whitehead (1978, p. 21), ‘creativity is the principle of novelty’. Creativity and creation are used in various discourses; it is simultaneously a theological, metaphysical, and a sociological or psychological concept. Most religious systems include an idea of the creation of the world as we experience it. In addition, creativity is a metaphysical concept in terms of being the movement from actuality to possibility. For instance, in Bergson and Whitehead’s process philosophy, creativity is the continuous force that is underlying Being and that perpetually turns Being into Becoming (Bergson, 1998). In social theory, creativity has been used in sociology, economics, psychology and management studies. Schumpeter (1942, p. 83), a well-known theorist of entrepreneurship, talked about ‘creative destruction’ as being the imminent force in capitalism that is ‘incessantly destroying old [economic structures], incessantly creating new ones’. To Schumpeter, creative destruction is ‘the essential fact about capitalism’. In Schumpeter’s view, creativity is two-fold: on the one hand, it creates and produces novelty, while on the other hand, it destroys preceding entities and ideas. Creativity both builds up and destroys. An additional perspective on creativity is organizational creativity. A useful definition of organizational creativity is offered by Woodman, Sawyer and Griffin (1993): ‘the creation of a valuable, useful new product, service, idea, procedure, or process by individuals working together in a complex social system’. Organizational creativity can also refer to the extent to which the organization has instituted formal approaches and tools, and provided resources to encourage meaningfully novel behaviours within the organization (Bharadwaj and Menon, 2000). Therefore, organizational creativity can be seen as a phenomenon that is structurally embedded in the organization rather than some innate quality of a few extraordinary individuals. Moreover, the concept of organizational creativity is more suited to understand creative action in organizations. Studies on creativity, including the vast research literature on creativity, are often either person-centred or focused primarily on
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four distinct aspects of creativity. First there is the creative person, which includes personal properties, traits and behaviour in terms of the ability to generate new ideas. Second, the creative process, which includes cognitive variables such as thinking styles, skills and problem-solving techniques. A third research domain has focused on the creative product, which deals for example with aspects of the evaluation of what defines creative output (e.g. originality, relevance, usefulness, complexity and how pleasing the output is). The fourth aspect concerns the creative place and investigates different aspects of cultural, environmental or working climate factors in the organizational context (cf. Amabile, 1999; Boden, 1996; Eysenck, 1996). These factors are often referred to as the creative climate of an organization (Ekvall, 1987, 1997). They include for example the leadership styles, visions, objectives, strategies, resources, personnel policies, values, structures and systems of an organization. All these factors are crucial for how people view the climate in which they work. As an example, there is an important link between the creative climate and innovation (Ekvall and Ryhammar, 1999). Much research has in some way been influenced by the ‘romance of creativity’ and may oversimplify explanations of events and attribute great creative achievements to single individuals (cf. Isaksen, 1987). Another aspect of much previous research is that the different distinct foci of creativity do not give a useful understanding of how creativity works in an organizational context. According to Ford (1995), creativity is not an inherent quality of a person, process, product or place, but is rather a domain-specific social construction that is legitimised by judges serving as gatekeepers to a particular domain. Furthermore, most of the research on creativity pays no attention to organizational or professional concerns (Ford, 1995). Thus, an important step in understanding creativity in an organizational context is to take a more holistic approach and use the concept of organizational creativity. In this paper, we use a systems theory perspective on creativity (e.g. Gruber, 1988; Rathunde, 1999) in which creativity can be seen as an emergent property within a sociocultural context shaped by multiple forces, including, but limited to the contributions of the individual. Within this perspective we make use of the system model or DIFI model (Domain Individual Field Interaction) as a creativity model. This framework is useful for understanding organizational creativity. The basic argument underlying this view is that creativity should be defined as a socially
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constructed label used to describe actions embedded within particular contexts (Ford and Gioia, 2000).
The DIFI Model and System Approach on Creativity An alternative theoretical framework, defining creativity as being dependent upon persons, processes, products or places, is the DIFI model of creativity developed by Csikszentmihalyi (1990, 1999, Figure 1). This framework is now widely accepted as a theoretical framework and is useful for understanding organizational creativity. The basic argument in this view is that creativity should be defined as a socially constructed label used to describe actions embedded in particular contexts (Ford and Gioia, 2000). According to Csikszentmihalyi’s model, creativity must be defined with respect to a system that includes individual, social and cultural factors that influence the creative process and help to bring about a creative outcome. This systems approach describes three interrelated subsystems, the domain, the field and the individual. One important implication of the model is that the level of creativity in a given place at a given time does not depend only on the amount of individual creativity. It depends just as much on how well-suited respective domains and fields are to the recognition and diffusion of novel ideas. The first subsystem – domain – can be seen as a symbolic system of rules and procedures
that defines a system of its own set of symbolic elements, knowledge, rules and notations. One important general characteristic of the domain is that every domain has its own internal logic, its pattern of development, and those who operate within it must respond to this logic. For instance, the scientific discipline of biochemistry can be seen as a specific domain constituted by various axioms, practices, rules and so forth. Applying this concept, almost any human activity can be seen and framed into different domains and subdomains of knowledge and activity – from football teams to scientific disciplines and corporations. From this definition, a domain can be exemplified in different levels in an organization, including different functions and skills in which represent a specific body of knowledge, language and customary practices. The domains in organizations are presented as ‘given knowledge’, the basic factors of the profession, which in most cases in practice turn out to involve creativity in the sense that creativity is necessary to identify areas that can be intelligently and cost effectively improved (Csikszentmihalyi and Sawyer, 1995). The second subsystem – field – can be seen as the gatekeepers, managers, experts, or stakeholders who personify and affect the structure of a domain and are entitled to select a novel idea, service or product for consideration. A field includes ‘all individuals who act as gatekeepers or managers to the domain’. Gatekeepers have the function to decide whether a new idea of product should be a
Figure 1. Csikszentmihalyi’s DIFI (Domain Individual Field Interaction) Model
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legitimate part of the domain. Gatekeepers in the domain of mathematics are for instance distinguished professors and journal editors that decide whether a new contribution to the domain is to be published or not. Thus, the field is made up of experts and authorities whose responsibility it is to passing judgements on performance in the domain. This responsibility creates a competition between individual and group in order to convince the field that the person or group has a valuable innovation. In many organizations the different management teams play this role. The last subsystem – the individual – is the individual or the group that produces the novelty. All these three subsystems jointly bring about the occurrence of a ‘creative’ act. The primary role of the person is to introduce variations in a field. The gatekeepers or managers who comprise and represent the domain select from among these variations (novel acts). Thus, creativity, according to the systems approach, always takes place within specific configurations of knowledge, and there can never be any creativity as such; creativity is always creativity with others. Some interesting implications of the model can be noted. First, the model emphasizes a crucial step in the creative process; innovation can only be secured when the actual idea or novelty is selected and accepted by the appropriate field or management and implemented into a relevant domain. Second, the model overcomes the dichotomy of over-socialization and under-socialization through aligning the systems view (the domain) with the actorperspective of the gatekeepers and the creative individuals. Another important aspect of the theory is the fact that creativity cannot be separated from its recognition. Csikszentmihalyi illustrates this aspect from an example of the domain of music. The conventional explanation is that J. S. Bach was a creative composer. However, his music was actually dismissed as old-fashioned for several generations and was actually rediscovered by F. Mendelssohn as a representative of the field during the midnineteenth century, which resulted in his full recognition as a creative composer. This example implies that we are constantly reassessing the past and creativity. Third, this theoretical approach gives opportunities for a better understanding of new-product development activities, such as those in the pharmaceutical research process, including the discovery process, and views the different development stages of pharmaceutical research as creative processes. The model does not restrict creativity to artistic expression but claims that all domains enable creative extensions of what can be done.
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Furthermore, the model also emphasizes the importance of the role of management in the creative process. This notion that creativity in an organizational context, as an interaction between individuals within a domain and gatekeepers (managers, peers or experts) who reject or retain creative action for future or further implementation, should not be restricted to only one domain (e.g. a department, a function or a scientific discipline). The result is that creative actions in organizations often face overlapping, multiple domains rather than single domains (Ford and Gioia, 2000; Ford, 1995). Thus, this view of creativity in organizations includes the importance of the interaction of many domains in the organization in which different informal social networks play an important role (Bras, 1995).
The Pharmaceutical R&D Organizations/Companies This paper describes a retrospective study of two pharmaceutical R&D organizations: AB Hässle and ICI Pharmaceutical Division. AB Hässle was located in Sweden and a subsidiary of Astra AB, a medium sized Swedish Pharmaceutical Corporation. AB Hässle’s main field of research was within the cardiovascular and gastrointestinal therapeutic areas. During the time period from 1975 to 1985, the R&D organization was comprised of approximately 250 to 500 employees. An important breakthrough in the late 1960s was the launch of a product for high blood pressure that was a starting point for further expansion (Östholm, 1995). ICI Pharmaceutical Division was a division within ICI, a large British chemical corporation. ICI Pharmaceuticals had gained previous success in a relatively wide range of products representing antiseptics, antibiotics and cardiovascular therapeutic areas. During the late 1960s, cardiovascular and later on, cancer, became ICI Pharmaceutical’s most significant domains of research (Pettigrew, 1985). Important breakthroughs were made in the cardiovascular area during the beginning of the 1960s, which also resulted in a significant expansion of the R&D organization. From 1975 to 1985 the R&D organization comprised approximately 500 to 800 employees. In 1993, ICI de-merged three of its business divisions (Pharmaceuticals, Agrochemicals and Specialties) to form a separate company, Zeneca. By the end of 1998, Astra and Zeneca merged into AstraZeneca. The new pharmaceutical company is now one of the largest pharmaceutical companies in the world with more than 50,000 employees world-wide and
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an R&D budget of more US$2.5 billion and a R&D organization of 10,000 employees.
Methodology The study presented in this paper is based on a qualitative methodology (Glaser and Strauss, 1967; Denzin and Lincoln, 2000; Silverman, 1993; Strauss and Corbin, 1990). It is based on interviews (Fontana and Frey, 1994; Kvale, 1996) with the 18 most leading researchers, several of them as project leaders or managing directors of the activities in the two pharmaceutical R&D organizations, AB Hässle located in Mölndal, Sweden, and ICI located in Alderley, UK. Qualitative methodology is useful when rather complex issues are investigated. Rather than selecting a few variables of the new product development process, we have aimed at integrating a number of interrelated questions and issues that are of importance in the discovery and development stages of the new product development processes. Therefore, a semistructured interview guide has been used in all the interviews. The study aims at investigating the research activities and initiatives that took place between 1975–1985, a period that produced research results that would later become blockbuster drugs for both companies. Thus, we have used what could be called a historical approach inasmuch as the interviews have been focused on past experience rather than present activities. This approach raises a number of issues. First, there are other studies in organization and management science that are based on a historical research in the field of strategic management (Chandler, 1962), operations management (Cusumano, 1985), and human resource management (Jacques, 1996). Thus, the historical approach can be claimed to be a legitimate methodology that could contribute to organization science (Prasad and Eylon, 2001). Second, the historical approach implies, by definition, that there is a time lag between when the activities actually took place and when the interviews were conducted. Bourdieu (1977) warns us that there may be a difference between the modus operandi, the actual practices and activities of the project, and the opus operatum, the succeeding idealized accounts of the actual events and activities. The opus operatum could thus succumb to moral storytelling, i.e. the interviewee giving modified account of the actual activities in order to give legitimacy to the interviewee’s performance. The interviewee’s proclivity towards giving idealized accounts on past
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activities can never be fully anticipated by the researcher. Nevertheless, this problem is not only inherent to the historical approach but in all interview situations as an interview can never be seen as offering fully objective knowledge (Kvale, 1996). Following Boje (2001), we believe that the interviewees’ accounts of their experiences are never final but are continuously modified as the interviewee’s interpretative horizon (cf. Gadamer, 1975; Ricoeur, 1974) is extended through, for instance, further work experience. Thus, we can use Luhmann’s (1982, p. 278) notion of temporal horizons, emphasizing that the present always comprises the past and the future. The interviewee’s accounts are always situated within idiosyncratic temporal horizons, therefore their accounts of the research project activities never come to a closure, a final, truthful version, but are always subject to modifications. Thus, we are reporting the interviewees’ stories of the research projects rather than the actual activities. As researchers, it is important to evaluate whether the individual interviewee appears to be giving a sincere and straightforward account of the experience. In the 18 interviews that serve as the basis for this study, we believe that the interviewees were trying to give as adequate and ‘credible’ answers as possible. In addition, few accounts of research project experiences deviated from the others. Finally, the pharmaceutical industry is widely renowned for having costly and long-term new product development processes. Since the research and new product development processes are substantial, i.e. each project researcher worked with a fairly limited number of research projects, and the activities were well documented, the interviewees were rather clear about what had happened during the period and could provide rather straightforward descriptions of their experiences. The main objective was to interview people who significantly contributed to the research process of a specific successful project or projects. The selection was based on four general criteria for the time period: (1) The interviewee significantly influenced and contributed to the research process of the project; (2) The interviewee took a major part in the decision process of the project; (3) The interviewee served as an inventor or patentee related to the project, or; (4) The interviewee worked as a successful project manager within the project. The DIFI model also guided the selection of respondents in combining actual creative persons and important persons representing the ‘field’ (i.e. managers) in the domain of the pharmaceutical R&D process. Most of the
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respondents fulfilled more than one of these criteria. The interviews were oriented towards seven different successful research projects within the two R&D organizations. Questions were directed to different categories, such as organizational structure and design, daily work aspects, the decision-making process, problem solving, research process oriented communication aspects and leadership. To avoid offset in earlier responses the final category of questions that was asked in the interviews were specifically related to creativity. The majority of the interviews, nine from each R&D organisation, were done at AstraZeneca R&D, Mölndal (former Hässle) and AstraZeneca R&D, Alderley, UK (former ICI Pharmaceutical Division) respectively. Data were collected during a six months period in 2001 (see Table 1). An additional objective was to interview at least two persons from different parts of the R&D organization (i.e. Discovery or Development) for each project. This outline was chosen to improve the understanding of the research process and important factors that influenced each project. The actual selection of respondents represents a group of very renowned scientists. Many of them have produced a prominent number of scientific publications and achieved distinguished scientific awards
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and gained international recognition within their domains of science. Many of the respondents are also inventors of a number of patents including important substance and formulation patents.
Understanding Organizational Creativity in Projects Using Systems Approach In the evaluation and interpretation process of data, we specifically aimed to relate creativity using a system approach for the two organizations. The system approach aims to describe relationships within a system important to creative action rather than describing a single cause of the origin of creativity. In this process we have used the DIFI model to describe important aspects of organizational creativity that took place in the seven projects. In the interpretation process data, a pattern of different characteristics emerged that were considered to be important or that heavy influenced the projects or the research process. These characteristics were categorized into nine aspects that we believe relate to creativity and subsequently to innovation. We define innovation, in line with West and Rickards
Table 1. Overview of the Respondents for the Two R&D Organizations during 1975–1985 Respondents
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
Company
Part of the R&D organisation
Domain of science
Project (Code)
AB Hässle AB Hässle ICI Pharm. ICI Pharm. AB Hässle ICI Pharm. AB Hässle ICI Pharm. AB Hässle ICI Pharm. ICI Pharm. AB Hässle AB Hässle AB Hässle & ICI Pharm. ICI Pharm. ICI Pharm. AB Hässle AB Hässle
Discovery Discovery Discovery Discovery Discovery Discovery Discovery Development Development Development Development Development Development Development
Chemistry Chemistry Chemistry Endocrinology Biochemistry Biochemistry Pharmacology Drug delivery Drug delivery Oncology Oncology Cardiology Regulatory Marketing
Beta Gamma Epsilon Delta & Eta Beta Delta Alpha & Gamma Epsilon Alpha & Beta Zeta Eta Alpha Gamma Alpha & Epsilon
Development Development Discovery Discovery
Drug delivery Endocrinology Pharmacology Biochemistry
Epsilon & Eta Delta & Eta Alpha Alpha & Gamma
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Figure 2. Relationships of Organizational Creativity in the Seven Projects
(1999), as the implementation of ideas in practice within a project, team or domain of science (e.g. pharmacology, biochemistry) that was designed to benefit the objectives of the project. The actual categorization of data into aspects is also based on the fact that the majority of the respondents expressed similar or shared meanings relating to the aspect. The empirical data reflecting three important aspects from each of the three dimensions in the context in the DIFI model is shown in Figure 2.
The Domain-Related Aspects (Company Level) The DIFI model points out that creative actions in organizations often face simultaneously overlapping, multitude domains rather than single domain. Domains in the context of the two pharmaceutical organizations, were defined primarily at company level. However, this high domain level took into account the different sub-domains in each organization. Thus, each company was viewed as a domain with a large number of sub-domains. This was done not only for the Discovery and Development units, but also for different specialized knowledge domains. Functional departments
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could, therefore, be seen as domains of specialized science, for example pharmacology, biology, organic chemistry, medicine and regulatory. The domain concept was also applied to describe other parts in the two R&D organizations, including the project organization, and also saw the management as a domain in the companies. In the study we found three important domain characteristics on a company level.
Endurance The lexicon definition of endurance is the ability to sustain a prolonged stressful effort or activity. Or simply, not giving up. We define endurance as organizational factors that not only can withstand difficulties but also keep the belief in vision. The study displays several interesting examples of projects in different stages of the research processes that have persisted through several obstacles, adversities or managed to reach deadlines despite very tight time-frames or scarce resource availability. The following is an example from an interview of a project team that had strong belief and ability to endure adversities and scientific drawbacks:
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For example the history of a project, that was part of a research area more or less continued for about 20 years with product after product was terminated for different reasons. But even so, people got back in the saddle and continued thinking – What did that depend on – Let’s test that mechanism – It failed again – Could it be another mechanism and so on. They simply didn’t give up. Finally the right mechanism was discovered that resulted in the successful project. The explanation that the company was first to launch this class of drug was because they showed it was possible. Other companies simply gave up. (Development, Person 9) Another example reflects the importance of staying with problems and overcoming obstacles in projects: I think it may have happened almost despite of, rather than because of management; it was the perseverance by lot of people. (Development, Person 3) Endurance may also be important in taking personal initiatives. An example of this is taken from a project in a late clinical phase. The product had been initially launched in some countries: The commercial success in the US goes back to one individual Clinical Research Investigator. The marketing company in the US had no interest in the product at all, but she took it round the opinion leaders and got trials set up and just carried on. She made the drug successful in the US, almost singlehanded. I think in this sort of situation it is a small number of individuals who very often swim against the tide, against the river. (Development, Person 11) Endurance as a factor to overcome barriers is reflected in this episode. The background was that the project had several problems during its development and was actually stopped twice. During clinical studies, the project faced problems with the delivery of the drug. The project teams tried once more to improve the formulation. After a completely new formulation, the project ran into problems with the initial toxicology studies that resulted in a decision to terminate the project for the second time. The medical director of the project refused to accept it, and for a period after the decision was taken, the project team continued to investigate the formulation and eventually discovered important characteristics that led to a re-evaluation. In combination with new knowledge and a strong determination from the project team, the medical director
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managed to convince the company to reestablish the project. Or as the respondent commented about the episode: And some time later the team came back and said, we have discovered that it was actually intralipid, it was a perfectly good vehicle. And there was great debate whether it was acceptable because, you know all the resources needed and concern about them to control it. And eventually he persuaded the company to try and then it was successful; that it is, the bottom line was it was killed to my knowledge nearly twice. (Development, Person 16) This study demonstrates in several examples that endurance was actually one important success factor for several of the projects. One other explanation for this endurance, indicating a creative capability of finding solutions to overcome problems or using an unknown quote – perseverance will prevail when others fail.
Flexibility According to Webster’s Dictionary, flexibility can be characterized as a ready capability to adapt to new, different, or changing requirements. We define flexibility as factors that facilitate the project by means of creating manoeuvrability in achieving goals. The facet also covers how actual project plans influenced development of their work. Flexibility is believed to be an important aspect of creating necessary ‘degrees of freedom’ and inducing creativity. This aspect is important because it reflects the ability of doing things within the overall defined objectives of the project such as testing new ideas or sidetracks. This study shows that project plans were not very detailed and not very much time was spent on updating them. Progress reports were pragmatically handled: The project plans were very brief and were not regularly updated. Meeting protocols actually played an important role on how things proceeded. (Discovery, Person 5) Another aspect of having some sort of flexibility and manoeuvrability is taken from another respondent: We had the opportunity to have exploratory research within pharmaceutical development, which actually prepared us for future problem, where we had a much shorter start up time. (Development, Person 9) Both organizations were small which made communication easy:
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Short and direct communication to management. (Development, Person 9) Another example of communication in the organization is described as: I mean the system was that you were able to know and go and talk to everybody, whereas that system doesn’t exist anymore. Whether it is a good thing or a bad thing is debatable. (Discovery, Person 3) One reason to allocate resources within several projects was because very often the project leader and line manager were the same person. Several examples show that the flexibility of project plans allowed relatively high manoeuvrability for testing ideas simply because the plans were not very detailed. Resource allocation was made easier in some cases because line management often played the project management role. In addition, projects were handled with a certain degree of organizational slack so that the resources that were not already appropriated or claimed for organizational could therefore be claimed in order to support invention. Absence of slack is believed to inhibit innovation (West and Rickards, 1999).
Core Competence The creativity literature displays several examples, either explicit or implicit, of theoretical perspectives on the role of knowledge (Scott, 1999). Amabile (1983) exemplifies the role and importance of ‘special domain talents’ in creative production. The pharmaceutical industry is a knowledge-based industry with multi-scientific skill involvement and its success is very much based on its ability to utilize new scientific knowledge or techniques. The capability to discover relevant chemical substances, which not only are relevant to the intended treatment of disease but furthermore superior to previous drugs, is complicated and difficult per se. We define core competence as how special company skills, knowledge-based approach or techniques may have interacted in the research process to bring about the success of the project. Several respondents from both organizations have enunciated the importance of having successful and appropriate biological models or techniques to use in the drug discovery phase. An interesting simile for describing one of these approaches is taken from one of the respondents: When flying a jet plane, the pilot actually sees nothing. The shortest distance a trained pilot will be able to locate a Boeing by eye-
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sight, without a proper navigation instrument, is approximately 7 km. It is the same as sitting in a dark closet. You need a system to navigate. I call it the blind man’s problem. It is no problem to put a blind man in a car with an automatic gearbox if he knows how to accelerate and has an assistant telling him to steer and so on. But if you search for a drug with the wrong instrument, even if it fulfils some of the specifications, the target could be completely irrelevant for what you are looking for. Take the pilot again for example, who mixes up the altitude instrument with the accelerator – things will go wrong. That’s why the interaction between biochemistry and drug discovery and the use of pro-per biological models is so important. (Discovery, Person 1) Another example illustrates the importance of the combination of techniques and knowledge: Good biological test models that we believed in and deep knowledge in the domain of science. (Discovery, Person 5) But some examples also demonstrated innovative combination with core skills and techniques. The background for this example was that a biological model was using spontaneously hypertensive rats for testing a drug for hypertension: One of the breakthroughs in our biological model testing was when one of our pharmacology researchers developed further the Okamoto rat model and overcame the need for sophisticated computed aided technology. The development of the model also resulted in being able to use the rats reused over and over again. It was really effective and exciting. (Discovery, Person 1) An additional factor for solving pivotal problems that sometimes actually led to a breakthrough for several of the projects was when new knowledge or a certain technique was applied or modified: I think the reason why it had a chance to succeed, was that we were actually able to access the kind of skills that you needed and they were not traditional skills in the pharmaceutical company. (Development, Person 3) Another example is taken from one project describing the way of using mixed competencies to increase the potentials and seeing things from other perspectives: It was a deliberate attempt to try to get people together with different backgrounds in order to get as high competence as
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possible, so there were no specific things the company looked for. It was more of a general idea of having physicians, veterinarians, physiologists and chemists come together. (Discovery, Person 7)
Field-Related Aspects The field according to the DIFI model can be defined as the sum of individuals who practise a given domain and have power to change it. Changes or new ideas in an organization will not be adopted unless they are sanctioned by some group entitled to make decisions as to what should or should not included in the domain. The field receptiveness is important in order to recognize not only valuable ideas but also accurate ways of implementing them. We have defined the field in the context of the two pharmaceutical organizations to represent primarily the line and project organizations. The role of the field in this context did play different roles within the management structures in influencing the different projects. The empirical data reflect three particular important field aspects that influenced the projects.
Swift Decisions The research process involves in many cases complex decision-making that may influence the project in many ways. This aspect deals with different aspects of how decisions were made in relation to the projects. The decision process is important for many reasons and may reflect the ability to combine creative skills such as intuition and risk in order to achieve success of the project (Keeney, 1992). By intuition we mean that tacit form of knowledge that orients decision-making in a promising direction. In the context of problem solving, a promising direction is one that leads potentially to effective outcome (Policastro, 1999). In some projects important decisions can be taken by few individuals, so the process is simple: There were defined decision targets or milestones, and it was very clear who decided so it was no problem to make decisions. (Discovery, Person 5) For several of the projects studied, decisions were very much based on mutual consent: The decision making process was much more of a consensus. (Development, Person 8) One example that made the decision process easy, was the support from senior management:
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You got your assignment, and then you did it, maybe it sounds very idealistic, but it was like that. The members in the team had authority to take the necessary decisions. We had full support from our CEO. The ones who had to be persuaded were at the corporate headquarter. (Development, Person 12) It was said that the strong scientific influence facilitated the decision making process: The decision making process was scientifically led more than anything else. (Development, Person 8) In some examples, decisions were taken very quickly and were often the result of a critical problem that confronted the project. In those cases, a very pragmatic approach was taken by gathering the most appropriate skills without reference to project or organizational belongings: It was very much ad hoc meeting-based. For better or for worse I think, it resulted in swift and well-thought decisions, but it was not the structured leadership that is aimed at today. (Development, Person 12) Also, how the structure of accessing and managing information facilitated decisions is illustrated in this example: Because the routes of accessing information were short, you were able to take decisions and go on, without going through groups of hierarchies; it was possible to work on fast forward. It was very informal of course, and many decisions were made in the corridors, which probably is disturbing for some people. Yet, I think it was an effective way to work at least for that organisation. (Discovery, Person 7) In summary: many projects display a very pragmatic and fast decision-making procedure. In addition, several projects reveal that intuition played an important role in the decision making process, which may have included a relatively high ability to take risks.
Idle Time Webster’s dictionary defines ‘idle’ as inactive or not occupied or employed. We define idle time as an important aspect of available time for exploration, testing hypotheses and for discussions. Previous research shows time as an important factor related to creative work in a numerous ways (e.g. Runco, 1999). The study precludes some interesting viewpoints on carrying out exploratory research and experimentation. Several examples show that
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explorative studies can be conducted with or without project plans. An interesting comment from one of the respondents regarding time for thinking was: It’s a strange thing, I think you have to be interested in what you are doing. I know it sounds strange, but these things don’t go out of your mind. I have a different view from many colleagues. There are a lot of scientist that go around saying I don’t have enough time to be creative. I need thinking time. If you’re interested in the problem you can’t stop thinking about it. You’re unconsciously doing it. You’re having a bath and you sit back and things start going around in your mind and out pop ideas. Where you need time isn’t in the thinking, because thinking happens anyway. But where you need time is to test your hypotheses, test your ideas, either with what’s known in the literature or with colleagues. (Discovery, Person 4) The study also indicates a relative high flexibility of managing time, at least in some stages of projects, which is exemplified by this description of the organization: It was much more relaxed, I mean it was a very unstructured, very pleasant, nonpressurised place to work. (Development, Person 3)
Climate We define the climate in the organization as a pattern of shared meanings (concepts, beliefs, expectations, values etc.) that evoke normative thought and behaviour from organizational actors (Ford, 1999). The organizational climate is believed to have influence on factors that either stimulate or block creativity and innovation in companies (Ekvall and Ryhammar, 1999). The study reflects several important aspects of the organizational climate. One example that reflects openness towards ideas is: In that environment, you had an idea incubator. You walked around and talked to other people about different ideas and in that way one was able to catch new aspects different from what you had before. (Development, Person 9) An organizational climate indicating integrity and pride is exemplified below: The people in discovery had a strong belief in that they were right. They had courage in spite of threats to their careers. It was the slim line between arrogance, belief and courage. (Discovery, Person 4)
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One other example is characterized by open communication and discussions: It was a climate in which you could to a high degree question things. In the research management team, we tried to question each other’s ideas, without anybody actually getting angry or embarrassed. (Development, Person 9) The open attitude and tolerance between researchers and managers is figuratively illustrated in this example: I could argue vigorously and scream until I was blue in the face at the R&D director, it is rather amazing, and he actually tolerated that. Then he gave it a thought; did this person say something sensible? (Development, Person 17) One part of the culture also considered the importance of networks. One organization used an internal scientific network based around the different core business products, which provided a high degree of scientific knowledge within the corporation: I’ve worked with people who were very senior scientists in the true sense of the word, who were leaders in their own field, and this was our own what we called the scientific ladder. We used to have cross company meetings, cross company organisations around specific areas of work, a material science and things like that. (Development, Person 8) The other organization solved it differently, and used external academic networks and an external advisory board consisting of renowned scientists: We had an external advisory board, where we anchored important issues and research ideas. (Development, Person 12) This example describes the most important characteristics of the organizational climate: The ability to take risks, endurance and swift decisions. (Development, Person 13) Another aspect about strong determination and independence is exemplified below: The importance of management to me is that it was tolerant and had the confidence in me to leave me alone to get on with the thing, and my contract was that I would deliver something they wanted at the end of it. (Discovery, Person 4)
The Individual-Related Aspects In order for individuals to introduce creative variation, they must have access to the domain
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and must learn to perform according to its rules. This applies to several important aspects like motivation, domain skills, good communication and access to the field, broad networks of contacts in the domain, and access of information. The study demonstrates three important aspects reflecting the individual perspective in the studied projects.
Scientific Champions The definition of a ‘product champion’ is an individual who enthusiastically supports an innovation project and who is personally committed to it. This person often plays the role of internal entrepreneur and is particularly effective maintaining impetus or stimulus and being supportive when the project encounters major difficulties (Rothwell, 1992). In the study we discovered individuals that fitted this definition, but the concept needed to be broaden in order to reflect additional important aspects. We define the ‘scientific champion’ as an individual who significantly influences the project, providing a scientific contribution, an authority to take important decisions with an extraordinary personality of creating new ideas and commitment. These persons not only played an important role for a specific project; they also influenced the R&D organizations, which is exemplified from one of the respondents: The company has in spite of itself not because of itself, succeeded largely because a relatively small number of individuals have battled to make it happen and have not taken no for an answer from the management. (Development, Person 11) A good example from one respondent displays the importance of personality and ability to commit co-workers to sharing common visions: He is the sort of person who could carry you into a swamp because of his personality. He could persuade you that this is worth going across to get to the golden land of the other side. You may not be able to see the land, but I think you’d probably step into the swamp. I do believe that leadership and all of these things are true, but it’s about people having confidence in you and believing in your sincerity and believing that you’re somebody worth following. And that it’s worth them taking a risk in committing themselves to you. (Discovery, Person 4) The study also displayed several examples of scientific champions also acting as productive idea generators:
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He was this kind of person who came to my office every morning and basically had a new project idea. My own approach was to have the same ideas two days in a row. (Discovery, Person 1) The study reveals that scientific champions played a very important role not only for a specific project but also for other projects. With their combination of personality and knowledge base in their domains of science, they also played important roles as enablers for creativity and innovation.
Pathfinders We define the pathfinder as a personal ability to encounter alternative ways and sometimes find new paths for doing things. This facet includes also the capability of finding other ways to solve problems or to achieve project goals. The routes of doing things may not have been according to previous experience or exactly in conformity with standard operating procedures. One aspect of the pathfinder is the ability to take the opportunity when it comes. Or as one of the respondents called it ‘the ability to exploit the unexpected’. Irving Langmuir, 1932 Nobel Prize winner in chemistry, defined the word serendipity as ‘the art to profit from unexpected occurrences’. We believe that the pathfinder is ready when serendipity occurs. Another aspect is openness towards alternative solutions and in very flexible ways using the resources available. The study shows several aspects of this facet. One example is taken from an episode of how a small clinical team worked under considerable time pressure and with limited resources to achieve a certain goal. The respondent, who was also the team leader at the time, describes: High performing teams are a kind of fly, you know, when they are flying, they do everything. People are multitasking and are doing this and that. You experience that everything can happen very quickly. If you put the controlling systems on them, everything just slows down. (Development, Person 11) One example of serendipity is taken from a project in the development phase. The background was that the drug itself was highly biodegradable and existed as an infusion solution. A depot or a formulation that was able to release the drug over a long period would significantly improve treatment and compliance of the product. A fruitful collaboration between Discovery and Development in combination with special circumstances,
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lead to the right track of developing the final product: The second serendipity was going on holiday and finding the solution of the problem. We thought we could only get depots that worked for seven days and that was because we had to terminate the experiment at the end of it. And the depots stopped working after seven days, so we thought. But when I went on holiday and came back and read the results from the analytical test, they had stopped after seven days and started again on day 14, and went on to about day 40 or 50. That was serendipity. If I hadn’t gone on holiday, we probably wouldn’t have done those experiments. (Discovery, Person 4) The ability to perform a task that was believed feasible but did not have full support from the company is illustrated for another project in development phase: The head of development was able to go away and work on the formulation and produced it anyway, as I understand it. I think it was quite typical of that period. Often in the labs away in the corner an experiment was going on which was the scientist’s private experiment. The managers probably knew that bubbling away in the corner was something that a pet thing. It was a sort of accepted thing that some of the people did their own scientific work. (Development, Person 11)
Intrinsic Motivation Several studies suggest that motivation is an important component of organizational creativity. This notion derived from the intrinsic motivation principle of creativity, which suggests that people will be most creative when they are primarily intrinsically motivated, by the interest, enjoyment, satisfaction and challenged of the work itself (Amabile, 1996; Amabile et al., 1996). Intrinsic motivation is relevant to the interest and curiosity in science. The component includes factors such as motivation, joy and curiosity attitudes that influenced the research or characterized the project work or correlated as success factors for different projects. Another ambition of the theme was to understand daily work-life aspects. There is an established notion about the important roles motivation (Conti and Amabile, 1999) and humour (Quinn and Davies, 1999) play as drivers in the creative process. In this study, all respondents describe a very pronounced and common characteristic of feeling a true joy in their work and a high
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motivation towards their project and domains of science. The study demonstrates a very concise trend of high commitment in the projects. One characteristic example is: I have always enjoyed doing research. I wouldn’t be doing it if I didn’t enjoy it. I am doing research in an area that I found fascinating and wanted to work in. (Discovery, Person 4) In the research process, there is a lot of routine work that is monotonous and not very motivating. One example is taken to demonstrate the need to motivate the organization in a situation which is critical for the project, but, at the same time a very monotonous task. The background for this example is that during the pre-clinical toxicological studies an adverse event was discovered in dogs. The dogs developed gingival hyperplasia or swollen gums. In order to investigate the effect, an extensive study was carried out. Each dog was sedated, and half of the jaw manually brushed and the other part of the jaw was left alone. This procedure was repeated every day over a period of one year. More than 20 dogs participated in the study. The result of the study demonstrated that this particular side effect of the drug would not occur if normal mouth hygiene were maintained. The respondent who was also the pre-Development team leader for the project commented this episode: Yes it was not easy to go out to the people in the animal department and say – now you should brush the teeth in the dogs for a year including Saturdays and Sundays. This is an example of the importance of motivating people to do not very exciting work. You have to have them with you. The reason why it worked was because they really understand why we had to do it in this particular way, and the importance of doing it. (Discovery, Person 5) Another example from the respondents emphasizes the source of motivation of being able to follow and contribute to a project during different stages: So in a sense, you saw the compound going from the design stage to the market, which not many people will see nowadays. (Discovery, Person 3) Factors for motivation in the projects were also the ability of knowing people from different disciplines, and furthermore, playing an active part in different discussions: I was part of all the discussions with the biologists; I was part of the whole develop-
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ment process where toxicology and those things were done, so I knew all the people who actually did the toxicology. (Discovery, Person 3)
Discussion The study of creativity in new drug development projects suggests that creativity is a fundamentally distributed organizational capacity that is produced within dynamic interactions between what has been referred to as the domain, the field and the individual. Person-centred views of creativity, assuming that creativity is an innate resource or capability among certain talented individuals, tend to underrate the social nature of creativity. In new product development practices, the person-centred view of creativity needs to be complemented by more dynamic models such as Csikszentmihalyi’s DIFI model, because the person-centred perspectives of creativity do not fully recognize the distributed nature of new product development practices. In this study of successful new drug development projects, the domain, field and individual constituted a highly creative and effective organizational climate in the two companies that enabled the seven successful new drugs to be developed. The study also suggests that the new drug development process is determined by traditional managerial practices such as effective decision-making and company product strategies as well as more personal interests and qualities. As a consequence, new drug development is not solely an effect of technical-instrumental rationality but is also fundamentally embedded in the individual researcher’s interests and dispositions. Creativity is therefore not to be conceived as a tangible, ‘thing-like’ organizational resource but is rather the outcome of a number of interrelated managerial practices and individual behaviours. Rather than seeing organizational creativity as a static organizational competence, it should be examined as a social accomplishment, constituted by actors engaging in new product development activities. This study also shows that the DIFI model may be applicable when examining organizational creativity. The DIFI model offers a dynamic framework wherein structural as well as social, emotional and behavioural aspects can be integrated. While many models of creativity are either reductionist, i.e. locate creative work and practices in specific conditions or relations, the DIFI model examines creativity at an aggregated level, effectively integrating a number of different components. The DIFI model can also be used when exam-
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ining what has been referred to as organizational creativity, that is, an organizational resource in terms of producing new artefacts and solutions to practical problems. The pharmaceutical industry serves as an interesting area of research in terms of organizational creativity. Being based on the application of sciences such as medicine, biochemistry, micro-biology and pharmacology and employing extensive research budgets and thousands of researchers, the pharmaceutical industry represents one of the most knowledge-intensive industries. In addition, the regulation of the industry produces limitations and opportunities for organizational creativity. The present study is based on an analysis of the creative work preceding the registration of seven successful drugs and shows that the new drug development work is by no means a linear process based on technical-instrumental rationality but also embodies human faculties such as joy, curiosity and interest. Therefore, pharmaceutical research is, as is all creative work, a blend of strict rulefollowing and playful transgressions of such rules. Creativity is therefore always in some respect somewhat subversive as it enables novel thinking and new ideas. Concerning the generalizibility of this study, we argue that former Astra and Zeneca, and its merger into AstraZeneca, are good examples to reflect characteristics of the modern pharmaceutical industry in general. As such the study is relevant for AstraZeneca. Furthermore, the pharmaceutical industry is now a heavily regulated business and, in the pursuit of greater efficiency and to be able to deal with complex risk taking during the long development times, new business processes are created that are not completely harmonious with aspects of organizational creativity. Therefore in this environment the notion of creativity as a capability in the organization may be taken for granted, or, worse, may not be accepted in practice because of different mindsets and assumptions. However, it is also important to point out that regulations should not only be perceived as being impediments to creativity, but that regulations may at times even enable for creative thinking in terms of imposing standard operations and shared worldviews. Still, creativity in pharmaceutical industry, or in the life science industry, is creativity under the influence of two major aspects: regulations and scientific breakthroughs. In this perspective, this study may not be relevant for industries such as media or advertisement industries, in which what is regarded as being creative contributions, are closely entangled with social constructions such as what mechanisms attract attentions
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and interest. In comparison to these industries, pharmaceutical industry is based on scientific work at least partially separated from social constructions such as public opinion and common beliefs.
Conclusion This exploratory study of seven projects in new product development in AB Hässle and ICI Pharmaceutical Division during 1975–1985 is also a study of creative processes. It suggests that creative projects are always based on distributed resources; the combination of tightly and loosely coupled systems ensuring that they are never linear. Thus, creativity management constitutes a source of sustainable competitive advantage since such processes are complex and complicated to manage and need continuous understanding and awareness. Therefore, creativity may be regarded as an impermanent or volatile factor to consider. The historical perspective of the study includes several factors that at the time, were quite different compared to those prevailing in pharmaceutical industry of today. Some examples are: smaller organizations, a more flexible regulatory process, less-demanding clinical studies and so on, which subsequently allowed the R&D organizations to operate with fewer routines and other formal constraints, which facilitated many processes. However, despite this historical setting, we propose that findings from this study are relevant and important for managing organizational creativity in a modern pharmaceutical R&D organization.
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Rathunde, K. (1999) Systems Approach. In Runco, M.A. and Pritzker, S.R. (eds.), Encyclopaedia of Creativity. Academic Press, London, pp. 605–10. Rickards, T. (1999) Creativity and the Management of Change. Blackwell, Oxford. Ricoeur, P. (1974) The Conflict of Interpretation. Northwestern University Press, Evanston. Roberts, P.W. (1999) Product innovation, Productmarket competition and persistent profitability in the U.S. pharmaceutical industry. Strategic Management Journal, 20, 655–70. Rothwell, R. (1992) Successful industrial innovation: Critical factors for the 1990s. R&D Management, 22(3), 225–27. Runco, M.A. (1999) Time. In Runco, M.A. and Pritzker, S.R. (eds.), Encyclopaedia of Creativity, Academic Press, London, pp. 659–64. Schumpeter, J.A. (1942) Capitalism, Socialism, and Democracy. Harper & Row, New York. Silverman, D. (1993) Interpreting Qualitative Data. Sage, London. Strauss, A.L. and Corbin, J. (1990) Basics of Qualitative Research. Sage, London. The Economist (1999) Drowning in Numbers, June 24 issue, pp. 71. The Economist (2000) The New Alchemy, January 20 issue, pp. 65. Tranter, D. (2000) Evolving to reflect the modern industrial life-science environment. Pharmaceutical Science and Technology Today, 3(12), 399–400. West, M.A. and Rickards, T. (1999) Innovation. In Runco, M.A. and Pritzker, S.R. (eds.), Encyclopaedia of Creativity. Academic Press, London, pp. 45–56. Whitehead, A.N. (1978) Process and Reality. Free Press, New York. Woodman, R.W., Sawyer, J.E. and Griffin, R.W. (1993) Towards a theory of organizational creativity. Academy of Management Review, 18(2), 293–321. Yeoh, P.-L. and Roth, K. (1999) An empirical analysis of sustained advantage in the U.S. pharmaceutical industry: Impact of firm resources and capabilities. Strategic Management Journal, 20(7), 637–53.
Mats Sundgren is executive doctoral student at Fenix Research Program, Chalmers University of Technology, and Scientific Advisor at Clinical Science, AstraZeneca R&D; Fenix Research Program, Chalmers University of Technology, Sweden and Aschebergsgatan 46, Vasaområdet Hus 3, S-412 96, Göteborg, Sweden. E-mail:
[email protected] Alexander Styhre is Associate Professor at Fenix Research Program, and the department of Project Management, Chalmers University of Technology; Fenix Research Program, Chalmers University of Technology, Sweden and Aschebergsgatan 46, Vasaområdet Hus 3, S-412 96, Göteborg, Sweden. E-mail:
[email protected]
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Innovation Activities by Small and Medium-sized Manufacturing Enterprises in Tanzania Christopher M. Mahemba and Erik J. De Bruijn The primary aim of this research is to explore innovation activities and ascertain the relationships between these activities and growth performance of SMEs in the Tanzanian manufacturing sector. The applied model has been derived from international studies of innovation. A survey of SMEs combined with in-depth case studies was made to study innovation practices of SMEs in the Tanzanian manufacturing sector. The results of this survey are used to compare the situation with findings of previous research. An increased level of applied change is associated with innovating SMEs, and a positive relationship between innovativeness in the SMEs with growth performance could be established. Based on the comparison of the results, recommendations are made for stimulating innovation.
Introduction
I
nnovative small and medium-sized Enterprises (SMEs) make a significant contribution in the global economy, with respect to enterprise development and new job creation. There also is an increasingly important role for SMEs to contribute to economic growth and technological development specifically in those developing countries where liberalization and globalization of the economy is currently taking place. It is estimated that SMEs make up more than 90% of all business establishments worldwide (Lin, 1998). In Tanzania, it is estimated that approximately 50% of the industrial output originates from SMEs (United Republic of Tanzania, 2001). Successful innovation is associated with good performance and related to subsequent growth. Empirical studies support the existence of this relationship between innovative behaviour of SMEs and their performance (Gunasekaran, Forker and Kobu, 2000; Olomi, 1999). In the industrialized countries a common conviction exists that economic growth stems from innovation, particularly in industry (Rothwell and Zegveld, 1982) and that the SMEs provided an important contribution to this growth. For this reason, it is considered relevant to investigate what the innovative capabilities of SMEs are in developing countries.
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This research had the objective to explore the issues of innovation in small and mediumscale manufacturing enterprises in the context of a developing economy. Since management in this type of industry is the initiating and driving force, this study investigates the relationship between innovation management practices and (growth) performance of these enterprises. The results in Tanzania are compared with previous findings in the innovation literature.
Innovation Activities of SMEs Empirical studies have demonstrated that in order to manage the innovation process successfully, enterprises must develop particular practices (Pitt and Clarke, 1999; Tidd, Bessant and Pavitt, 1997). That is, to develop specific ways of performing tasks and organizational behaviour that Tidd, Bessant and Pavitt (1997, p. 32) refer to as ‘the way we do things around here as a result of repetition and reinforcement’. Organizational practices differentiate one organization from another, and also determine the success or failure of that organization in the long run. They call innovation management a process of searching for effective practices. Innovation management practices of SMEs are defined as the activities that SMEs undertake
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in order to provide in new solutions for their products, production, marketing and administration to cope with dynamics of the markets. Well-established organizational practices are difficulty to copy and acquire. Since they have been developed through trial and error methods, values, behaviour and experiences are involved for quite a long period of time. The practices are also considered to be firm specific. Pitt and Clarke (1999) emphasize that innovation requires practices that can cut across structural boundaries of an organization. With respect to the interaction between SMEs and a market, SMEs are characteristically advantaged because in principle they are able to react quickly and efficiently to market changes. Studies of small firms confirm that SMEs’ entrepreneurial characteristics and structural flexibility do not have a long chain decision-making process. SMEs can serve a narrow market by establishing close contact with customers (Rothwell and Zegveld, 1982). In addition, SMEs can achieve high growth by focusing on particular product groups, avoiding spreading their marketing activities too widely, avoiding operating in markets dominated by large firms by choosing carefully the markets in which they operate (Adams and Hall, 1993). Innovative behaviour is described as having an appropriate outlook on obstacles, and treating these obstacles as learning opportunities rather than as negative events. There are a variety of definitions for SMEs. Using the number of employees to define SMEs has been a common practice in literature (Adams and Hall, 1993; Freel, 1999; Rothwell and Zegveld, 1982). Other methods include using capital invested and turnover (Wijewardena and Cooray, 1995). It is not useful to stick to a single common definition of an SME because of the variation of the notion from country to country and from sector to sector (Gunasekaran, Forker and Kobu, 2000). In Tanzania both number of employees, capital
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invested and turnover have been used to defining SME sector as shown in Table 1. This research adopted an SME definition based on the number of employees as follows: micro (1–4), small (5–20), medium (21–100), and large (more than 100 employees). This (draft) definition is adopted, since no official definition has been established by the Ministry of Industry and Trade in Tanzania.
Innovation and Its Adoption Process Boer and During (2001) defined innovation by three elements: key activities of innovation (the process), the results of innovation (combination of product-market-technologyorganization), and the extent to which innovation is new (incremental to quantum-leap and to whom it is new). As a result of the specific situation of SMEs in a developing country context, this research takes the more limited view that technological change is the most appropriate in the measurement for innovation of this type of industries, i.e. the measurement of activities that have employed for improvement in product/service(s), process(es), method(s) in the organization. Innovations can either be generated or adopted by an organization. A firm can generate and/or adopt innovations depending on its internal capabilities, and its strategic orientation. The innovation generation process as specified in the literature requires a number of factors such as a high level of technological capabilities, strong R&D and a pool of multidisciplinary skills whereas the innovation adoption process does not. Because of high demand for such resources in innovation generation, the innovation generation is not feasible for SMEs in developing countries such as Tanzania. A more appropriate choice in those countries is to adopt innovations that are already generated (Adeboye, 1997). Buratti
Table 1. Categories of SMEs Category of enterprise
Number of employees
Capital invested (Tshs) in million
Turnover (Tshs) in million
1–4 5–50 51–100 101 and above
Up to 5.0 5.1–200.0 201–800.0 Above 800.0
12.0 150.0 300.0 300.0
Micro Small Medium Large
1 Tshs = US$ 1.050 (2003). Source: URT, 2001, p. 6.
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and Penco (2001) proposed assisted technology transfer as a solution. De Bruijn and De Boer (1989) argue that well-organized technology transfer centres can contribute in this way to narrow the technological gap between developing and developed countries. Gopalakrishnan and Damanpour (1994) suggest that innovation adoption entails the borrowing, or adaptation, of innovations already in use within the industry, aiming at a future generation of simple innovations. The innovation adoption process entails activities that must be carried out in order to accomplish the process. They take place in a series of stages, from initiation to implementation, in the following order: awareness, interest, evaluation, and trial-adoption. Rogers and Shoemaker (1971) hold the opinion that innovation cannot be an instantaneous action; rather it is a process that occurs over a period of time and consists of a series of overlapping actions.
Influence of the External Environment on Innovation and Sources Innovation can be regarded as a process of interaction between an SME and its external environment. The effectiveness in the innovation adoption process depends on what is taking place in the external environment (Nadler and Tushman, 1997). It makes demands on the organizations in terms of customer requirements; it provides opportunities; and it places constraints on organizations. In order for the innovation adoption process to take place, the availability of, as well as the access to, technological information and knowledge is a prerequisite. Technology, the market and other external environmental factors must be integrated with the internal activities of SMEs. Three sources of innovation can be identified: imitative, acquisitive and incubative. Effective use of each source needs different levels of requirements from an organisation. The imitative source requires an organization to have the abilities to imitate an innovation quickly when others develop it. The acquisitive source requires an organization to have the abilities to obtain an innovation through licensing, acquisition or merger. An organization will develop its own innovations internally, or through joint ventures, if it opts for the incubative source of innovation. In the Tanzanian manufacturing sector the SMEs’ characteristics and capabilities, knowledge and skills of the employees and of owners/managers, are recognized as significant elements for realizing innovation adoption. Empirical findings support various
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relationships between the innovation capabilities of a firm and its characteristics (Hadjimanolis, 2000).
A Model of Innovation Activities of SMEs Combining the concepts provided in previous studies, a diffusion model, emphasizing acquisition, adoption and adaptation of already existing innovations has been developed for the SMEs industrial sector. The focus of the research model is on utilizing the entrepreneurial characteristics and capabilities of SMEs in the Tanzanian manufacturing sector to access and exploit already existing technology. Information and knowledge about sources of technology are important components of the model. For a successful innovation diffusion process in a competitive market, integration of SME activities both vertically and horizontally is essential. The model contains concepts (constructs) whose existence and possible relationships have been addressed and gauged in order to determine how they influence innovativeness. The constructs are categorized as: (a) technological information and knowledge; (b) knowledge and skills; (c) nature of the market and external relationships; (d) characteristics and capabilities of SMEs The relationships between these constructs are depicted in Figure 1.
Research Base and Operationalisation Research Base This research can be classified as a descriptive survey. A pilot study was undertaken to pre-test a developed questionnaire. Revisions were made to various questions to remove ambiguities, in order to increase the validity of the questionnaire before embarking on the full-scale survey (Zikmund, 2000). A comprehensive structured questionnaire has been used to collect data and information from owners/managers of SMEs by means of personal interviews. These were applied because it also allows probing for explanations, elucidations and broadening out responses. The interactions facilitated an in-depth understanding of the relevant concepts. SMEs in the manufacturing sector have been selected because such sector has a high proportion of SMEs compared to other sectors in Tanzania, and for its relevance for the economy (Mbelle, 2000; Tanzania Chamber of
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Level 3: GENERAL ENVIRONMENT (International issues) innovations and technology, competitiveness pressures and interactions
Level 2: MACRO ENVIRONMENT (Tanzanian context) Policies and regulatory framework, institutional support sources of technology information and knowledge
Level 1: TASK ENVIRONMENT (SMEs) Te
Sources of information on innovations & other inputs
Characteristics and capabilities In Organizational change INNOVATION Incremental innovations in products ADOPTION and/or services ACTIVITIES Diffusion of innovations growth performance Knowledge and skills
Nature of the market and external relationships competitiveness and conducive markets
Figure 1. Model of Innovation Activities of SMEs Commerce, Industry and Agriculture, 1995). A total of 150 manufacturing SMEs were selected through a stratified random sampling technique in five regions of Tanzania namely: Dar es Salaam, Tanga, Kilimanjaro, Morogoro and Arusha, where major manufacturing establishments are concentrated (Mbelle, 2001). The database of the Bureau of Statistics in Dar es Salaam was used as a sampling frame to obtain the names of all SMEs in these regions. From total sample of 460 SMEs a random sample for each region was made of the total sample of 150 (33 per cent), 135 (90 per cent) usable questionnaires were returned. The survey is a cross-section study, in which data are collected at a specific point in time. A top-down approach was selected as the most appropriate method for executing the survey because the nature of the information required for the research could be best provided by owners/managers.
of three years was used. This time-frame was selected because of the nature of the measurements used required owners/managers of SMEs to provide accurate estimates of their innovativeness. Technological change that was selected as the innovativeness indicator of technology adopted, was measured as it was experienced by owners/managers of SMEs. Innovation measurement is based on technological adoption, modifications and incremental changes that took place in the SMEs in the Tanzanian manufacturing sector. This approach is in line with a study by Landa (1993), in which he was able to separate innovating from non-innovating firms.
Measurements of Innovativeness
(b) Knowledge and skills
To measure innovativeness of SMEs in the Tanzanian manufacturing sector, a time-frame
This concept is divided into two concepts: level of knowledge and skills, and owner/
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Measurements of Innovation Indicators (a) Technological information and knowledge This concept is divided into technology information access and technology knowledge awareness; the operationalized variables are shown in Table 2.
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Table 2. Technological information and technological knowledge (based on Hadjimalonis, 1999, and Adeboye, 1997) Technology information access
Technology knowledge awareness
(a) Usage of sources of technical support (b) Rate of use of computers and ICT (c) Usefulness of sources of technology information
(a) Importance of strategies for technological collaboration (b) Extent of utilization of methods of acquiring new/unused technology (c) Importance criterion for acquiring new/unused technology (d) Technology adoption
Table 3. Knowledge and skills (based on Lin, 1998, and Olomi, 1999) Level of knowledge and skills
Owner/manager characteristics
(a) Percentage of various skills and background in total work force (b) Importance of accessing external expertise (c) Importance of increasing in skilled personnel (d) Importance of improving in-house skills (e) Employing foreign experts
(a) (b) (c) (d) (e)
Position and gender Age Business experience Formal education background Training after employment
Table 4. Nature of the market and external relationships variables (based on Hankinson et al., 1997, and Johne, 1999) Nature of the Market
External Relationships
(a) Market interactions • Number of markets • Number of customers • Number of products (b) Nature of competition
(a) (b) (c) (d)
Usefulness of technological institutions Nature of business relationships Membership of business associations Extent and level of external service/assistance receive from various sources and programmes
manager characteristics. Each is operationalized using the items in Table 3. (c) Nature of the relationships
market
and
external
This expression is divided into nature of the market and external relationships, subdivided into various items (see Table 4). (d) Characteristics and capabilities This concept is divided into SMEs’ general characteristics and their operational capabilities, each with the group of items as indicated in Table 5.
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(e) Growth performance Measurements for growth performance of SMEs that have been identified in the literature are: 1. Employment growth 2. Conventional measurements (volume, efficiency and cost) 3. Sales in monetary value in a given time period 4. Relative (global) measurement of growth performance. For measuring the growth performance of SMEs in the Tanzanian manufacturing sector,
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Table 5. Characteristics and capabilities of SMEs variables (based on Olomi, 1999, and Hankinson et al., 1997) General characteristics (a) (b) (c) (d) (e)
Business location Type of industry Business experience Size of business Type of ownership
Operational capabilities (a) Delegation of authority (b) Use of formal business plan and plan horizon (c) Internal behaviour: • Rate of internal communication • Rate of recognition for good performance • Rate of staff morale • Rate of successful in teamwork spirit • Rate of use of idea-generation techniques
a combination of these criteria was used: profitability, size, market share and growth rate. The measurement combines four selfevaluations on a three-point scale: profitability, size, market share and growth rate. This scale was adopted from Deshpandé, Farley and Webster (1993) and was originally grounded in a Profit Impact of Market Strategy (PIMS) study (Coulter, Baschung and Bititci, 2000). This approach has been used in several studies to measure growth performance and is able to differentiate between good and poor performers (Deshpandé, Farley and Webster, 1993; Hadjimanolis, 1999).
Results of the Survey Innovation Activities by SMEs Change in the technology level was used as a measure to differentiate between innovating and non-innovating SMEs. The chi-square independency test shows that there are differences in the way SMEs have changed their levels of technology in the Tanzanian manufacturing sector. The observed differences are statistically significant at the 5 per cent level (c2(df=4) = 70.776). The level of technology change was used to measure innovativeness of SMEs in the Tanzanian manufacturing sector, and the empirical results have confirmed that SMEs in the Tanzanian manufacturing sector adopted diverse levels of technology. An increased level of technological change is associated with innovating SMEs. Innovation literature broadly supports the view that innovating SMEs are likely to perform innovative activities of a new and/or incremental nature (Kabecha, 1999). This can be in the form of introducing and/or improving products,
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processes, organization methods or market development. This research has established that innovating SMEs in Tanzania are more likely than their non-innovating counterparts to launch new products, at the 10 per cent significance level (c2(df=1) = 3.510). New products here are defined as copies from other firms and/or imports. They are not new for the market but are new for the SMEs concerned. Customers’ demands were found to be an impetus for this kind of adoption process, especially in innovating SMEs. For other types of innovation activities: improvements in products and product designs, and introducing new product designs, the research findings could not ascertain a significant difference between innovating and non-innovating SMEs (see Table 6). The findings imply that SMEs in Tanzania carry out incremental innovations with products produced outside their firms due to pressures to meet customers’ demands. SMEs’ own staff and customers have been established as useful sources of these innovative ideas to innovating and non-innovating SMEs respectively. Innovation theory positively links innovativeness and expenditure on R&D (Tidd, Bessant and Pavitt, 1997). The findings could not empirically support this theory although some R&D expenditure was done by the SMEs. SMEs in the Tanzanian manufacturing sector do not have adequate in-house facilities to carry out R&D. In many cases these do not exist at all. SMEs’ R&D activities cannot be linked to their innovativeness as a number of authors advocate (Adeboye, 1997). This is supported by Rubenstein (1980), who argued that because of low technological level in those countries, the objectives of R&D in SMEs in developing countries should be focused on alteration and adoption of discoveries made
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Table 6. Chi-square results: innovating activities in non-innovating (NI) and in innovating (I) SMEs Activity
N
Launch new product
133
Introduce new product design
133
Product improvement
134
Design improvement
134
No Yes No Yes No Yes No Yes
elsewhere. For details of the research construct and data collected see Mahemba (2003).
Technological Information and Knowledge This research has established that innovating SMEs in Tanzania are likely to seek external technical support; the differences are significant at the 1% level (c2(df=2) = 12.224). SMEs proactively interact with the external environment in solving their technical problems. The findings support the theory that innovation performance depends on the opportunities an SME can seize from its external environment (Keizer, Johannes and Halman, 2002). The findings have further ascertained that innovating SMEs are likely to use computers/ICT in business operations. The observed differences in the use of computers/ICT are significant at the 2.5% level (c2(df=4) = 13.074). Use of computers/ICT in administration is considered to be innovative behaviour by small businesses (Chatterji, 1990; Cumming, 1998). Access to sources of both technology and innovation is one aspect enabling innovation initiatives to diffuse in an organization. In Tanzania, it is shown that both innovating and non-innovating SMEs utilize their own staff and customers as their main sources of information on technology. No evidence has been found on interactions between these SMEs and other sources of technological information. The findings imply that existing types of interactions between SMEs and sources of information on technology are normal routine activities in business operations. Shared costs, dealing with science and technology complexity, and the learning process, were viewed by non-innovating SMEs as important strategies when collaborating in technological development compared to their innovating counterparts. Non-innovating SMEs are significantly more likely, than inno-
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NI (%)
I (%)
Total (%)
c2
55.4 44.6 47.3 52.7 25.0 75.0 30.4 69.6
39.0 61.0 34.6 65.4 16.7 83.3 32.1 67.9
45.9 54.1 39.8 60.2 20.1 79.9 31.3 68.7
3.510 2.156 1.407 0.043
vating ones, to consider these strategies as important at the 5 per cent, 1 per cent and 10 per cent significance levels respectively. However a short-term production requirement strategy tends to be the most important criterion for non-innovating SMEs to acquire a technology at the 10 per cent significance level. SMEs use these strategies to identify technologies they need from both internal as well as external sources. Information about sources of innovation as well as access to these sources is an important means for SMEs to achieve innovation goals. Technology is one of the enablers of innovation. In Tanzanian SMEs, it was found that there is no local adaptation of hard technologies, such as new tools and the purchase of new equipment; other empirical studies support this finding (Mambula, 2002). SMEs in Tanzania tend to adopt soft technologies. These are operating methods, improvements in production processes, methods, organization and the market.
Knowledge and Skills Know-how, know-why, as well as know-where are all necessary for enabling innovation activities to diffuse in SMEs. The chi-square test results show that innovating SMEs are more likely than their non-innovating counterparts to employ graduates (46.1 per cent versus 17.9 per cent); significant at the 5 per cent level (c2(df=1) = 11.408). Innovating SMEs are more likely inclined than their non-innovating counterparts to employ scientists and engineers (61.8 per cent against 41.1 per cent) at the 5 per cent significant level (c2(df=1) = 5.585). This implies that adequate knowledge and skills in SMEs are prerequisites in facilitating the innovation adoption process. With regards to increasing, access, and improvement of skills, both innovating and non-innovating SMEs do not consider these
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methods to be important. Empirical findings from this research indicate that these approaches are statistically independent to each other. This indicates a low level of knowwhy among owners/managers of SMEs concerning the importance of human resources in their organizations. Innovating SMEs are significantly more likely to employ foreign experts in technical positions at the 5 per cent level (c2(df=1) = 4.317). This finding suggests that employing foreign experts is a measure to cover skill shortages in SMEs; it does not indicate any innovative practice, because the findings do not indicate the employment of foreign experts with technical skills. The majority of Tanzanian SMEs are owned or managed by males (95.5 per cent). Individuals who are not the actual owners of the business manage almost half of SMEs. The sample findings do not reveal a relationship between personal characteristics (age, position, business experience and formal education) of the owner/manger and the innovativeness of SMEs. The findings therefore do not support the innovation theory, which advocates a linkage between innovativeness of small firms and the characteristics of the owner of the business; see for example, Lin (1998) and Pitt and Clarke (1999).
Nature of the Market and External Relationships A large percentage of SMEs occupy single business locations, produce multiple products and serve only one type of customer. Diversification in terms of business location is considered to facilitate innovative behaviour, through being exposed to a number of innovation opportunities that are available in various locations. This is not the case from the research findings in SMEs in the Tanzanian manufacturing sector. Another important issue that is related to the nature of market is the degree of competition in the market. The research findings indicate that both innovating and non-innovating SMEs equally experience strong competition. No correlation was found between the innovativeness of SMEs in the Tanzanian manufacturing sector and market competition: Spearman’s rho correlation coefficient was -0.053. Innovation literature links positively the degree of innovativeness with the nature of competition in the market (Rothwell, 1996). This also does not appear to be the case, with SMEs in the Tanzanian manufacturing sector. No statistically significant difference was found between innovating and noninnovating SMEs in their perception of market competitiveness (c2(df=4) = 0.208).
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Based on these results, it is plausible to conclude that the nature of the market competition prevailing in Tanzania does not challenge SMEs to innovate; rather, it acts as a barrier. SMEs in Tanzania are not aware of the opportunities that are available in the external environment, such as collaborations with other organizations such as research institutions, universities, technology centres and the government. The majority of SMEs in Tanzania do not have formal relationships with technology institutions. The percentages of innovating and non-innovating SMEs are the same. The innovativeness of Tanzanian SMEs cannot be related with external linkages with such institutions as indicated in other studies (Havnes and Senneseth, 2001; Keizer, Johannes and Halman, 2002). There are only a few interactions between technology institutions and the majority of SMEs, and those are on an informal basis. The SMEs do not acknowledge the importance of having such interactions. Johnson and Tilley (1999) also found a low level of awareness by SMEs of the kinds of services offered by HEIs. More than half of the sample SMEs belong to one of the business associations, but this factor also does not reflect any difference in innovative efforts. The outcome of this research supports innovation theories that advocate a tendency for SMEs to establish business relationships along the value chain (Diez, 2000). A significantly higher percentage of innovating SMEs, compared with non-innovating SMEs tend to have established relationships with local suppliers (79.7 per cent versus 56.9 per cent; significance at 1 per cent level). This finding reinforces the innovation theory that innovative behaviour by SMEs depends on the interactions that occur along the value chain. In Tanzania, interactions with suppliers are considered to be useful, especially for small businesses, because of the need to get supplies on credit. This is supported by the literature that indicates that small firms normally rely on suppliers because they are not self-sufficient in-house (Woolgar et al., 1998). Literature associates small firms’ innovative capabilities with the level of assistance sought and obtained from various sources (Kaufmann and Tödtling, 2002). The findings show that SMEs in Tanzania get little assistance and/or business services from the government, NGOs or foreign programmes. Either there is a limited amount of assistance available from these institutions, or SMEs are not aware of where to seek such assistance. With their flexibility nature, one would expect SMEs to act proactively and search for assistance from government departments, NGOs or foreign donors.
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This does not appear to be the situation with the SMEs in Tanzania.
Characteristics and Capabilities of SMEs to Innovate According to Hadjimanolis (2000), capabilities are defined as features of the firm and managerial skills forming routines, which lead to competitive advantage. The heterogeneous nature of SMEs on one hand, and their behavioural advantages such as less bureaucracy, good internal communication, efficiency, flexibility and adaptability and closeness to market on the other, enable them to be innovative. Many researchers have consistently advocated these kinds of relationships (Rothwell and Zegveld, 1982; Vossen, 1998). For SMEs in Tanzania, the research findings show that location and legal form are different for innovative and non-innovative SMEs. Location is a factor that is associated with the ability of SMEs to innovate. The findings support the literature, which suggests that a difference in external environment factors such as location ultimately influence the innovation activities of small firms (North and Smallbone, 2000). Innovating SMEs are likely to be incorporated companies where as those with proprietors are not; the observed differences were significant at the 5 per cent level (c2(df=4) = 12.622). The findings support innovation theory in that there are no significant differences in innovativeness across industries in the same sector (c2(df=8) = 10.345). This means that differences in innovating efforts can be significant between sectors but only minor variations within a sector were observed. On the issue of age (or business experience) and size of SMEs and innovativeness, the research findings do not demonstrate any significant differences between innovating and non-innovating SMEs. Innovation theories positively link the innovativeness of SMEs to the level of delegation of authority to others (Hankinson, Bartleth and Ducheneaut, 1997). However, the delegation of responsibilities especially in small firms can only be very limited. This is a result of not only the limited staff, but also of the entrepreneurial characteristics of an owner avoiding loss of power to control the business as a result of delegation (Freel, 1999). The research findings support these theories on delegation. Few SMEs in the sample had more than three levels of management, and hence limited delegation. This implies that the owners/managers of these SMEs make most of the decisions on all aspects of their businesses. The majority of SMEs in the Tanzanian
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manufacturing sector carry out formal business planning (71.1 per cent), not significantly differentiated between innovating and noninnovating SMEs (73 per cent versus 68.5 per cent). The planning activities tend to be of a short-term nature, generally covering a period of one year. These findings imply that the kinds of planning used in these SMEs do not have a strategic nature. The internal behaviour of SMEs in the Tanzanian manufacturing sector is defined by the managerial behavioural factors that are important in their work environment; communication, co-operation, recognition, staff morale, the idea generation process and teamwork. These results show that innovating SMEs are significantly more likely to have adequate internal communication and co-operation at the 5 per cent level than their non-innovating counterparts. There are no significance differences in the other behaviour categories. It is plausible that this is due to the observation that these measurements in general are more relevant for the larger enterprises. The theory of innovation links the innovativeness of SMEs to a high degree of communication and cooperation (Freel, 2000). In this regards the findings are consistent with the theory.
Innovation and Growth Performance Innovativeness of SMEs in the Tanzanian manufacturing was measured by changes in the level of technology applied in the enterprise. Growth performance is gauged by a combination of four measurements of profitability, size, market share and growth rate. The results of Spearman rank test indicate a positive relationship between innovativeness of SMEs and growth performance of SMEs in the Tanzanian manufacturing sector (r = 0.209), at the 5 per cent significant level. North and Smallbone (2000) caution that there is no simple cause and effect relationship between innovation and growth, but that rather an interdependent and mutually reinforcing relationship is expected to exist. Findings of this study have established this kind of phenomena between innovativeness and growth performance in the Tanzanian manufacturing sector SMEs, with a weak correlation.
Conclusions and Recommendations This study on innovating practices in the Tanzanian small and medium-scale manufacturing industry only partially confirmed what has been found in literature. Innovating
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SMEs are defined as those who have adopted new practices over a period of three years, as making improvements in operating methods, internal organization and specific changes in market development. In the Tanzanian SMEs, there were no adoptions found of tools and equipment. Those innovating practices that were found in the areas of adoption of new products, production methods, organization or market development were generated by actively obtaining external support, from customers and from other enterprises, but not from government or universities. The linkage between innovativeness and characteristics of the business (Lin, 1998) and Pitt and Clarke (1999) could not be established for the SMEs in Tanzania. International studies on the relation between SMEs and research institutes and technology centres show that their existence leads to innovative practices (Havnes and Senneseth, 2001; Keizer, Hohannes and Halman, 2002). This relation was not found in this study, although these institutes and centres are available in significant numbers in Tanzania. No relation was found that membership of business organizations had influence of innovative behaviour. Specific active relations with suppliers confirmed that interaction along the value chain influences innovativeness. The execution of formal planning activities, in this type of enterprises albeit of short term nature (up to one year) was found not to be a discriminating factor. Only a weak relation between innovative behaviour and growth performance was established. This may be due to the finding that innovation practices in SMEs in Tanzania found adoption of organizational, product and process changes, but not adaptation of tools and equipment.
Recommendations for Owners/Managers of SMEs The links with suitable elements of the macro environment observed are instrumental for developing innovative initiatives in the enterprises. This can be realized by intensifying the existing contacts with external sources such as suppliers and customers. Collaboration with business support institutions and other organizations can serve to acquire the expertise and services that currently are lacking in the industry. A requirement is of course that these institutions are fit for their task. In Tanzania this cannot always be taken for granted. The form of a co-operation between enterprises could be a way to achieve more innovation. The research shows that the business
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associations in the Tanzanian setting are not fulfilling this function.
Recommendations for Policymakers The formulation, as well as the implementation, of a clear development policy on SMEs is of paramount importance given the contributions of SMEs to economic and industrial development. A steering organization could co-ordinate SME activities and make followup to appraise their development efforts. The government can take this role through the Ministry of Industry and Trade. The research exposes the use of obsolete technology in Tanzanian SMEs and a lack of awareness of sources of new technology. This is the result of heavy dependence on foreign technology and lack of know-where to find appropriate technology, and no internal capacity to achieve technical innovation. Concerning the external environment, the research has established that the low level of knowledge on the external environment is a major drawback for SMEs in Tanzania. In order to augment interactions between SMEs and external organizations, the design of sensitization programmes is proposed. This can be achieved through organizing workshops and seminars conducted in these institutions, and supervised by the Ministry of Industry and Trade through its SMEs section. Most of the technology institutions in Tanzania are weak in terms of facilities, finance, and manpower, and there are no linkages between them to enforce them to cooperate. Innovation diffusion depends, among other things, on the economy and government of a nation (Silveira, 2001). This suggests the importance of having a national innovation policy that links together all the economic factors of a nation. This is considered particularly important for developing countries because of market failure, international competitiveness, and institutional inadequacies in such countries (Hadjimanolis and Dickson, 2001).
Research Extension Research is required to identify specific barriers and success factors for innovating practices in various cross-cultural settings in Tanzania. The area of innovation and networking activities in SMEs is a promising opportunity because of its association with their innovation efforts. Resource-based research on innovation in SMEs needs specific attention, especially in developing countries like Tanzania where a lack of resources for innovation effort tends to
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be a major constraint. Critical resources that affect SMEs’ sustainable competitive advantage based on innovation, production and market management capabilities are recommended (Rangone, 1999). Innovation and technology adoption policies, innovation support for SMEs, public-sector support for innovation are relevant subjects for research in the Tanzanian context to obtain insight in the functioning mechanisms and to be able to design mechanisms for stimulating more and better innovation processes.
References Adams, G. and Hall, G. (1993) Influences on Growth of SMEs: An International Comparison. Entrepreneurship and Regional Development, 5, 73–84. Adeboye, T. (1997) Models of Innovation and SubSaharan Africa’s Development Tragedy, Technology Analysis & Strategic Management, 9(2), 213–35. Boer, H. and During, W.E. (2001) Innovation, What Innovation? A Comparison between product, process and organizational innovation. International Journal of Technology Management, 22(1/2/3), 83–107. Buratti, N. and Penco, L. (2001) Assisted Technology Transfer to SMEs: Lessons from an Exemplary Case, Technovation, 21, 35–43. Chatterji, M. (1990) Innovation, Management and Diffusion of Technology: A Survey of Literature. In Chatterji, M. (ed.), Technology Transfer in the Developing Countries. MacMillan, Hong Kong, 3–18. Coulter, J., Baschung, N.S. and Bititci, U.S. (2000) Bench-marking for Small- to Medium- Sized Enterprises. Production Planning & Control, 11(4), 400–8. Cumming, B.S. (1998) Innovation Overview and Future Challenges, European Journal of Innovation Management, 1(1), 21–9. De Bruijn, E.J. and De Boer, S.J. (1989) A Review of Rural Technology Development Through Small-Scale Industry Service Centres. International Journal for Development Technology, 4, 21–35. Deshpandé, R., Farley, J.U. and Webster Jr., F.E. (1993) Corporate Culture, Customer Orientation, and Innovativeness in Japanese Firms: A Quadrad Analysis. Journal of Marketing, 57, 23–7. Diez, J.R. (2000) Innovation Networks in Manufacturing: Some Empirical Evidence from the Metropolitan area of Barcelona. Technovation, 20, 139–50. Freel, M.S. (1999) Where are the Skills Gaps in Innovative Small Firms? International Journal of Entrepreneurial Behaviour and Research, 5(3), 144–54. Freel, M.S. (2000) Strategy and Structure in Innovative Manufacturing SMEs: The Case of an English Region. Small Business Economics, 15, 27–45. Gopalakrishnan, S. and Damanpour, F. (1994) Patterns of Generation and Adoption of Innovation in Organizations: Contingency Models of Inno-
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vation Attributes. Journal of Engineering and Technology Management, 11, 95–116. Gunasekaran, A., Forker, L. and Kobu, B. (2000) Improving Operations Performance in a Small Company: a Case Study, International Journal of Operations & Production Management, 20(3), 1–14. Hadjimanolis, A. (1999) Barriers to Innovation for SMEs in a Small Less Developed Country (Cyprus). Technovation, 19, 561–70. Hadjimanolis, A. (2000) A Resource-based View of Innovativeness in Small Firms. Technology Analysis & Strategic Management, 12(2), 26381. Hadjimanolis, A. and Dickson, K. (2001) Development of National Innovation Policy in Small Developing Countries: the Case of Cyprus. Research Policy, 30, 805–17. Hankinson, A., Bartleth, D. and Ducheneaut, B. (1997) The Key Factors in the Small Profiles of Small-Medium Enterprise Owner-managers that Influence Business Performance. The UK (Rennes) SME Survey 1995–1997, An International Research Project, UK Survey. International Journal of Entrepreneurial Behaviour and Research, 3(4), 168–75. Havnes, P-A. and Senneseth, K. (2001) A Panel Study of Firm Growth among SMEs in Networks, Small Business Economics, 16, 293–302. Johne, A. (1999) Using Market Vision to Steer Innovations. Technovation, 19, 203–7. Johnson, D. and Tilley, F. (1999) HEI and SME Linkages: Recommendations for the Future. International Small Business Journal, 17(4), 66–81. Kabecha, W.W. (1999) Technological Capability of the Micro-enterprises in Kenya’s Informal Sector. Technovation, 19, 117–26. Kaufmann, A. and Tödtling, F. (2002) How Effective is Innovation Support for SMEs? An Analysis of the Region of Upper Austria. Technovation, 22, 147–59. Keizer, J.A., Johannes, L.D. and Halman, I.M. (2002) Explaining Innovative Efforts of SMEs. An Exploratory Survey among SMEs in the Mechanical and Electrical Engineering Sector in the Netherlands. Technovation, 22, 1–13. Lambert, R. and Barber, J. (1998) Technology Sources for SMEs. In Oakey, R. and During, W. (eds.), New Technology-Based Firms in the 1990s. Paul Chapman, London, Vol. V, pp. 122– 37. Landa, O. (1993) Innovating organizations and managerial cultures in Czech and Slovak organizations. In Cozijnsen, A. and Vrakking, W. (eds.), Handbook of Innovation Management. Blackwell, Oxford, 71–89. Lin, C.Y. (1998) Success Factors of Small-andMedium-Sized Enterprises in Taiwan: An Analysis of Cases. Journal of Small Business Management, 36(4), 43–65. Mahemba, C.M. (2003) Innovation Management Practices of Small and Medium Scale Enterprises in Tanzania, dissertation, University of Twente. Mambula, C. (2002) Perceptions of SMEs Growth Constraints in Nigeria, Journal of Small Business Management, 40(1), 58–65. Mbelle, A.V.Y. (2000) The Manufacturing Sector in Tanzania, A study by the Confederation of
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Tanzania Industries (CTI) and the Confederation of Danish Industries (DI), University of Dar es Salaam. Mbelle, A.V.Y. (2001) The Imminent Challenges of Globalizing: Small and Medium Manufacturing Enterprises in Tanzania. Tanzanian Economic Trends: A Bi-annual Review of the Economy, 14(1), 11–32. Nadler, D.A. and Tushman, M.L. (1997) A Congruence Model for Organization Problem Solving. In Tushman, M.L. and Anderson, P. (eds.), Managing Strategic Innovation and Change: A Collection of Readings. Oxford University Press, New York, pp. 159–71. North, D. and Smallbone, D. (2000) The Innovativeness and Growth of Rural SMEs During the 1990s, Regional Studies, 34(2), 145–57. Olomi, D.R. (1999) Entrepreneurial Characteristics and Small Firm Performance. In Rutashobya, L.K. and Olomi, D.R. (eds.), African Entrepreneurship and Small Business Development. DUP LTD: Dar es Salaam, pp. 161–80. Pitt, M. and Clarke, K. (1999) Competing on Competence: A Knowledge Perspective on the Management of Strategic Innovation. Technology Analysis and Strategic Management, II(3), 301– 16. Rangone, A. (1999) A Resource-Based Approach to Strategy Analysis in Small-Medium Sized Enterprises. Small Business Economics, 12, 233–48. Rogers, E.M. and Shoemaker, F.F. (1971) Communication of Innovations: A cross-cultural Approach (2nd edn). The Free Press, New York. Rothwell, R. (1996) Industrial Innovation: Success, Strategy, Trends. In Dodgson, M. and Rothwell R. (eds.), The Handbook of Industrial Innovation. Edward-Elgar, Cheltenham, pp. 33–53. Rothwell, R. and Zegveld, W. (1982) Innovation and the Small and Medium Sized Firms: Their Role in Employment and Economic Change. Frances Pinter, London. Rubenstein, A.H. (1980). Research and Development Issues in Developing Countries. In Dean, B.V. and Goldhar, J.L. (eds.), Management of Research and Innovation. North-Holland, Amsterdam, pp. 253–83. Silveira, G. (2001). Innovation Diffusion: Research Agenda for Developing Economies, Technovation, 21, 767–73. Tanzania Chamber of Commerce, Industry and Agriculture (TCCIA) (1995). Tanzania Business Contacts 1995/1996. TCCIA, Dar es Salaam. Tidd, J., Bessant, J. and Pavitt, K. (1997) Managing Innovation: Integrating Technology, Marketing and Organizational Change. John Wiley & Sons, Chichester. United Republic of Tanzania (URT) (1991) Informal Sector Survey (NISS). Planning Commission and
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Ministry of Labour and Youth Development, Government Printer, Dar es Salaam. United Republic of Tanzania (URT) (2001) Draft: Small and Medium Enterprise Development Policy 2002–2012. Ministry of Industry and Trade, Dar es Salaam. Vossen, R.W. (1998) Research Note: Relative Strengths and Weaknesses of Small Firms in Innovation. International Small Business Journal, 16(3), 88–94. Wijewardena, H. and Cooray, S. (1995) Determinant of Growth in Small Manufacturing Firms: Japanese Experience, Journal of Small Business Management, 33(3), 87–92. Woolgar, S., Vaux, J., Gomes, P., Ezingeard, J-N, and Grieve, R. (1998) Abilities and Competencies Required Particularly by Small Firms to Identify and Acquire New Technology. Technovation, 18(8/9), 575–84. Zikmund, W.G. (2000) Business Research Methods (6th edn). The Dryden Press, Fort Worth.
Christopher M. Mahemba (PhD, University of Twente) is lecturer in Operations management, innovation management and operations research at the Faculty of Commerce and Management University of Dar es Salaam. He is researcher at the Dar es Salaam University Entrepreneurship Centre. His research interest concerns the management and innovation practices in small and medium scale enterprises in the woodworking, food and metal working sectors. Faculty of Commerce and Management, University of Dar es Salaam, P.O. Box, 35046 Dar es Salaam, Tanzania. E-mail:
[email protected] Erik J. de Bruijn (PhD, University of Twente) is professor of Business management in non-western countries and Chairman of the Technology and Development Group at the University of Twente. He worked as research coordinator in various international development projects, and as consultant for the industry, World Bank, and The Dutch Directorate for International Development cooperation. He published books and articles on transfer of technology, joint ventures and business management in developing economies. Universiteit Twente, School of Business, Public Administration and Technology, P.O. Box 217, 7500 AE Enschede, The Netherlands. E-mail:
[email protected]
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Order and Disorder in Product Innovation Models1 Miguel Pina e Cunha and Jorge F.S. Gomes This article argues that the conceptual development of product innovation models goes hand in hand with paradigmatic changes in the field of organization science. Remarkable similarities in the change of organizational perspectives and product innovation models are noticeable. To illustrate how changes in the organizational paradigm are being translated into changes in new product development (NPD) practices, five NPD models are presented: the sequential, compression, flexible, integrative and improvisational models. The evolution of product innovation management shows a move from planned and mechanistic, towards emergent and organic models. Such a process of re-orientation poses several challenges that are presented in the form of six propositions: from universal to contingent models, from invariant to flexible practices, from avoiding risks to taking advantage of opportunities, from planning to learning, from exclusive teams to inclusive networks, from structure to structured chaos.
Introduction In the rapidly-changing environments characterizing most industries today, proficiency in the management of product innovation is a necessary although not sufficient condition for organizational survival (Shervani and Zerillo, 1997). Considering that environmental change requires organizational adaptation, then new product innovation models can be expected to be appearing in response to new competitive landscapes (Bettis and Hitt, 1995). In this article, the evolution of product innovation models is traced. It is argued that organizations are developing new approaches to the product innovation process as they realize that traditional approaches may no longer be appropriate, given the characteristics of today’s competitive game. New competitive conditions may require thorough diagnosis and fast decision-making simultaneously, which implies the management of two opposite pressures (Dickson and Gigleriano, 1986): the needs of taking fast action (to avoid the closure of market windows by faster-acting competitors) and of reducing the risks involved in product innovation (through careful but time-consuming analysis). Such conflicting demands are changing the product innovation practice and research, and forcing new product innovation models to emerge.
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These new models and the way they accompany the general development of organization science will be discussed here. Aiming to parallel the developments of organization theory and NPD theory, this paper does not review the product innovation field in its entirety (for that purpose see e.g. Brown and Eisenhardt, 1995, or Wind et al., 1997); rather it reviews product innovation models, which have been central to new product and organizational success (Ernst, 2001). The paper starts with the presentation of two alternatives on the ethos of organizing: organizing as order versus organizing as disorder. From the organizing as order to the organizing as disorder continuum, five product innovation models can be devised: the sequential, compression, flexible, integrative and improvisational models. These two sections will be followed by a final section in which six trends in NPD, derived from the previous discussion, will be presented.
1
We gratefully acknowledge the comments of and discussions with several colleagues that helped in developing the ideas presented in this article. Ken Kamoche, José Manuel Fonseca and João Vieira da Cunha deserve special mention.
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Organizational Paradigms: Order/Disorder Organizations are complex social systems that can be approached from a variety of perspectives (Westwood and Clegg, 2003). The intrinsic diversity of organizations allows researchers to develop correspondingly diverse views of the several phenomena taking place inside them. Product innovation is no exception: it can be approached from sharply distinct departure assumptions, and proceed towards diverse descriptions and prescriptions. In this section, this contention is illustrated by showing that two radically distinct perspectives about organization and organizing coexist in the literature: (1) an engineeringbased perspective that views organization as order, and (2) a complexity-based perspective that equates organizing with a partially disordered process. These views are expected to illustrate how the general evolution of organization science is deeply penetrating into theory-building in the field of product innovation models. This conceptual discussion may be pertinent considering that, as claimed by several authors (e.g. Brown and Eisenhardt, 1995), product innovation is often viewed as a technical and an a-theoretical subject. This article’s main assumption is that theorizing about product innovation is necessarily close to the conceptual frameworks available in organization science. Two major and contrasting perspectives on organizing will therefore be considered: organizing as order, and organizing as disorder.
Organization as Order Organizations are often portrayed as open systems, and therefore as being vulnerable to the uncertainty coming from markets and technologies. Despite the inevitable impact of environmental factors, classical organization theory tried to find ways of protecting the core organizational processes from environmental interference (Thompson, 1967). According to rationalist, engineering-based approaches, organizations should simultaneously buffer themselves from external influences while maintaining a controlled degree of porosity to the environment. These contradictory requirements can be achieved by regulating/controlling the external flows of information and resources. Stability was viewed in this approach as the essence of organizing (Shenhav, 1999). Homeostasis was expected to be achieved through the introduction of slight, incremental innovations, developed in order to help
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adaptation of the organization to environmental changes. The top-management team was presumed to act as the driver of innovation and renewal, and to base its strategic decisionmaking processes on the premises of rationality. Organizations were expected to change mainly voluntarily and consciously, in order to maintain a state of fit with the external environment (Lawrence and Lorsch, 1967). The organizational landscape was mainly described as composed of cycles of negative feedback, and perspectives on organizing based upon sounding and comforting concepts, such as stability, regularity and predictability (Stacey, 1995). In this perspective, cause–effect relations could be known, organizations could be able to design their futures, and adaptation could be taken as the outcome of managerial competence. Under a rationalist framework, the organization pursues clear and shared goals, set by managers who are able to transform divergent and often ambiguous information into convergent solutions. The essence of classic approaches to management and organization consisted in the maintenance of order and control as paths to organizational equilibrium and stability. To achieve these goals, companies sought to rationalize work processes and to introduce operating routines. The rationalist perspective follows, in sum, an organizational archetype based on control and rationality, from which chaos has been removed (Nonaka, 1988).
Organization as Disorder Recent theoretical developments, implicitly or explicitly associated with such ideas as complexity (Stacey, 1995), paradox (Clegg, Cunha and Cunha, 2002) or emergent designs (Hatch, 1997) are challenging the traditional representation of organizations as orderly systems. Under these approaches, organizations tend to be portrayed as messy and partly disorganized systems (Abrahamson, 2002). They should then be viewed as systems of interrelated, complex and not fully predictable behaviours. Management, by consequence, calls not only for logic and analysis, but also synthesis, intuition and analogy. In consequence, processes like change and innovation involve not only a sequence of planned activities, but also a parcel of emergence and improvisation, as will be discussed below. Table 1 summarizes the main characteristics of traditional and emergent perspectives on organizing. The central argument of this paper is that the general changes taking place in the field of organization science are penetrating product innovation models: after trying clearly
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Table 1. Rational and emergent perspectives of organizations Perspective
Traditional
Emergent
Organization Order, clarity Information processors Static Decision Planning
Organizing Disorder, ambiguity Information creators Dynamic Interaction Discovery
Features Object Essence of organizing Role of people Nature of the approach Unit of analysis Basis for action
structured, uncertainty-avoiding models, some organizations are now engaging in the use of minimally structured, uncertaintyaccommodating ones. These models make use of concepts such as team-working, real-time decision-making, improvisation and collective discovery. After having accepted the premises of the traditional paradigm, organizations are now trying to implement more nimble and faster processes. New organizational architectures are becoming more dynamic and less mechanical, as captured by such labels as ‘modular’, ‘virtual’ or ‘barrier-free’ organizational forms (Dess et al., 1995). Product innovation models seem to be evolving in the same direction: modular, virtual and barrier-free, are all labels that can be applied to developments in the management of product innovation (Adler and Zirger, 1995). The following section provides a discussion of product innovation models, ranging from engineering/mechanistic models, to emergent/organic ones.
Product Innovation Models NPD is a necessary condition for organizational adaptation and renewal. The dynamics of competition may be viewed as compulsory stimuli for product innovation. Product innovation is a prominent strategy for renewal: by launching new products, firms may stay closer to customers (Schilling and Hill, 1998), counterbalance the organizational tendency towards inertia (Hannan and Freeman, 1984), out-innovate competitors (Moore, 1993) and influence the characteristics of their environments (Utterback, 1993). Product innovation is thus a powerful mechanism for organizational adaptation. Many organizations, however, develop incomplete or inadequate new product innovation processes (Cooper, 1993). These deficient processes may be partly responsible
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for the high levels of new product failures reported in many industries, which are calling for a re-examination of how companies plan and implement their product innovation processes (Wind and Mahajan, 1988). Empirical evidence shows that successful and unsuccessful new products frequently follow different paths of development, with failures being the result of incomplete, inadequate or deficient innovation processes (Edgett, 1994). Despite the existence of empirical data showing that innovative firms tend to perform best (Deshpande, Farley and Webster, 1993), product innovation is still an uncertain and risky activity, which must be rigorously managed for organizations to increase their chances of success. In the remainder of this section, five product innovation models will be presented, ranging from assumptions of order to assumptions of disorder. This presentation will make clear that the first condition for the success of product innovation may not consist in the proper implementation of any universal model, but rather in the choice of an appropriate model for particular environmental or project contingencies. The models fall into a continuum ranging from more planned to more emergent approaches, and can be classified according to the types of learning they rely upon: sequential and compression models try to develop increasingly efficient and reliable routines, while the flexible, integrative and improvisational models look for an increment of resilience and agility. These two forms of learning have been identified in the organizational literature (Sitkin, 1992) and seem to be helpful for capturing and interpreting the assumptions underlying each model.
The Sequential Model The sequential, step-by-step approach to product innovation, constitutes the dominant
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Table 2. Characteristics of the sequential model Model Environment Assumptions underlying the model Process characteristics Process goals Major raw material Key organizational functions Fundamental assumptions about organizing Shortcomings
Sequential Placid clustered Buffering the process from unnecessary change and uncertainty Explicit Efficiency, predictability, incremental change Product innovation principles Introducing discipline and control, evaluating each phase Certainty, equilibrium, stability, predictability, mechanicism Rigid, early lock-in, fitted to long-cycle products, vulnerable to crystallization/centripetal forces, risk of ‘missing the boat’
Figure 1. Sequential model perspective in the management of product innovation (Cooper, 1993; see Table 2 and Figure 1). Step-by-step models are presented as blueprints for safe and efficient new product development projects. These models are mechanical tools intended to guide product managers along the entire product innovation journey. They are expected to reduce the uncertainty inherent to innovation (Dosi, 1988) by suggesting a number of steps to be made in sequence (see Figure 1). Between phases, there are decision gates or points for deciding about whether the process should continue (i.e. ‘go’) or be interrupted (‘killed’, according to the model’s jargon). The number of phases varies amongst authors, from two (e.g. Moenaert et al., 1994), to six (e.g. Cooper, 1988) or even nine (e.g. Hardingham, 1970). Sequential models rely heavily on planning, anticipation and control. Their rationality, however, does not seem to fit the way most organizations actually work: as reported by Cooper (1988), less than 1 per cent of the firms examined in his study used a complete sequential or stage-gate approach. The question then is: why do companies resist the stepby-step approach? To answer this question, it should be considered that step-by-step models are ‘tools to manage, direct, and control . . . product innovation efforts’ (Cooper, 1990, p. 44). Or, to phrase it differently, they are tools
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for rationalizing and controlling product innovation. As such, they are not learning or creativity-oriented tools, but means of control through standardisation (Perrow, 1986). This characteristic may make them more appropriate for managing routine, incremental innovations, than for discovering radical innovations (those that deviate a company from current courses of action). The definition of tight steps to follow while developing new products inhibits the development of innovations that require unexpected movements, i.e. radical or frame-breaking innovations. These, in fact, cannot be expected to be accomplished ‘by a simple application of programmed switching rules’ (March and Simon, 1958, p. 175). One of the dangers inherent to these models is the creation of habits of mind (Louis and Sutton, 1991) or automatic ways of dealing with problems that may instead require learning and flexibility. The physical and social separation of activities implied by sequential models also seems to work against learning because social interaction – facilitated by physical proximity and intense cross-functional communication – is a fundamental means for knowledge creation and diffusion (Brown and Eisenhardt, 1997). Some organizations may also decide not to follow the complete set of instructions provided by step-by-step approaches, because the model may not be adequate to the kind of products they are developing: in the case of
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new service development, for example, the technical development phase may be greatly reduced or even absent, while in the case of manufacturing this is the most timeconsuming and costly phase of the whole new product-development process (Meidan, 1984). Despite the potential pitfalls mentioned above, step-by-step models have many potential advantages. They can be instruments for developing systematic, standardized and comprehensive product innovation practices (Cooper, 1993). As such, they provide a clearcut, easy-to-learn and easy-to-standardise set of guidelines for developing new products. This road map, however, does not seem to be a universal solution. Some goals, namely the exploration of novel opportunities and high speed of response, may require different means for managing product innovation. This latter necessity led to the introduction of the compression model.
The Compression Model The compression model may be thought of as a version of the step-by-step approach adjusted to high-velocity environments (see Table 3). As in the previous model, a sequence of steps forms the basis for developing new products under a compression model (for an illustration, see Figure 2). However, as a result of market pressures, collapsing product life cycles, and the competitive importance of time (Kessler and Chakrabarti, 1996), these steps sometimes need to be accelerated or compressed. There are several ways of achieving compression: improving planning, simplify-
ing the process, eliminating unnecessary steps, involving suppliers, shortening the completion time of each step, overlapping steps and rewarding people for speed of development (Eisenhardt and Tabrizi, 1995). The crucial phase of a compression approach is predevelopment planning: if pre-development planning is accurate, the entire process may be rationalized, delays eliminated and mistakes detected earlier. Careful planning is presented as a determinant of quick development. Deficient planning, on the other hand, can lie at the root of numerous product pathologies, like stop gaps, disruptive re-orientations (Brown and Eisenhardt, 1997), hidden costs, low profit/high triviality, or unexpected inefficiencies (Crawford, 1991). Other practices that facilitate speed of development include knowledgeable leadership, the use of crossfunctional teams, and an organization-wide support for the project (Maber, Muth and Schmenner, 1992). The compression model implements Cooper’s (1994) and Clark and Wheelwright’s (1993) suggestions for parallel processing of the activities involved in product development. With parallel processing, organizations strive to integrate the advantages of sequential
Figure 2. Compression model
Table 3. Characteristics of the compression model Model Environment Assumptions underlying the model Process characteristics Process goals
Major raw material Key organizational Functions Fundamental assumptions about organizing Shortcomings
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Compression Placid clustered, high speed Rationalizing the process as a way of adapting Explicit Increasing speed while keeping low levels of uncertainty, incremental innovations for fast moving markets Product innovation principles, time Rewarding speed, emphasizing planning, using multi-functional teams Certainty, equilibrium, stability, adaptation, mechanicism The traps of acceleration: lack of quality, shortcuts, omission of important steps
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models with the demands for a faster process. Thus, the logic is that some development tasks can start simultaneously, instead of following a rigid sequence of developmental steps. This perspective intends to keep the uncertaintyreduction philosophy of sequential models, while recognizing the need to save time. Therefore, it presents the advantages of investing in planning in order to gain speed. Unnecessary tasks should be removed, time spent on each task reduced to the minimum, interactions and responsibilities within teams regulated, and some tasks delegated, namely to suppliers. The compression model assumes that: (1) development activities can be known in advance, and that (2) product innovation models are expected to reduce uncertainty as much as possible. Recognizing the need to speed up processes, this model’s authors envision ways for shortening development phases as much as possible, compressing some activities, overlapping others and obliterating those that are not strictly necessary. Similarities between the sequential and compression models exist because they both rely on the assumptions of planning and certainty. The compression model can be adequate for developing products that demand the use of familiar technology and are directed towards well understood but fast-changing markets (Eisenhardt and Tabrizi, 1995). Or, in other words, to high-speed routines.
The Flexible Model The mix of high-speed and uncertainty of a growing number of industries led to the appearance of another model for developing new products: the flexible model. The flexible model introduces an organic approach to the
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development of new products (Iansiti, 1995). Flexibility, or the capacity to introduce changes in design in response to a changing environment with little or no penalty (Sobek, Ward and Liker, 1999), becomes an important feature of product innovation models when turbulence increases. When flexibility is low, the economic cost of modifying the product is high. The need to do things right the first time, a major challenge when the environment is permanently changing, is also high. A possibility to bridge the gap between planning and execution is to trade a mechanistic approach for an organic one, where the strict succession of changes is no longer the essence of the game. The flexible model, then, substitutes the machine-like process of previous models, with a focus on adaptation through diversity seeking. Flexibility is influenced by the product development’s expense, unit cost, performance, and development schedule, and can be increased via the adoption of flexible technologies, the modification of management processes (e.g. locking requirements progressively, instead of in advance) or of design architectures (e.g. using modular product structures and reducing the coupling between modules). The speed of change and the high levels of environmental turbulence invite organizations to see innovation not as an organizational disruption to keep under control (as in traditional mechanistic models) but as an engine of renewal. This need for agile product innovation led to the flexible model (see Table 4), a model whose necessity was firstly felt in industries where even ‘the ground is in motion’ (Emery and Trist, 1965, p. 26). In these industries, instead of encapsulating the process, an organic approach was taken, based on keeping
Table 4. Characteristics of the flexible model Model Environment Assumptions underlying the model Process characteristics Process goals Major raw materials Key organizational functions Fundamental assumptions about organizing Shortcomings
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Flexible Disturbed reactive, turbulent Embracing change, absorbing uncertainty Explicit, with tacit elements; variety is acquired through iteration Flexibility, responsiveness Product innovation principles, time, variety Organic structures, unclear timings Uncertainty, surprise, adaptation The ‘might as wells’ syndrome can provoke serious delays, due to unfreezing product concept
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Figure 3. Flexible model the concept development stage open as long as possible, in order to increase development agility through diversity and fast integration (see Figure 3). This also reduced the negative impact of forecasting errors. Rejecting the idea of product innovation as a rigid and mechanistic sequence of phases, the flexible model proposes the agile utilization of ‘rapid and flexible iterations through system specification, detailed component design, and system testing’ (Iansiti, 1995, p. 2). Frequent iteration and testing can work in turbulent environments because these practices favour the creation of more opportunities and probabilities for variety to occur (Eisenhardt and Tabrizi, 1995) and offer frequent feedback, which has two advantages: errors are uncovered earlier and team members can have a perception of progress and improvement, which will be a source of learning and motivation (Eisenhardt and Tabrizi, 1995). In the flexible model, the idea that sequencing (with or without overlapping) is the most appropriate way of handling new product development is abandoned, and a more dynamic perspective is adopted, based on learning-while-doing and on the emergent nature of the innovation journey under turbulent conditions. Considering that less that 5 per cent of the developing products are completely specified before beginning product design (Thomke and Reinertsen, 1998), the flexible model may benefit from the realistic premises it is based upon. This model is best suited to business environments that are unpredictable, rapid and populated by aggressive competitors (e.g. computers and software, multimedia and the fashion industry). Here, companies with a flexible approach may continue to incorporate market information in the new product concept until late, neutralizing competitor moves or taking advantage of surprise (Cunha, 2003).
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A flexible approach to NPD is also an actionbiased one: instead of investing in careful prespecification of design details, the model rests upon the creation of alternative and nondefinitive (i.e. reversible) designs. The use of prototypes, for example, may generate early knowledge of real product attributes and immediate customer feedback. A distinguishing feature of the model is that the generation of diversity should be accompanied by quick integration when a satisfying solution is achieved. The flexible model is not immune to criticism. One major criticism is the ‘might as well’ syndrome, or the propensity to keep on waiting for information to come, which can lead to delays due to late concept freezing.
The Integrative Model Integration is a concept initially proposed in organization theory by Lawrence and Lorsch (1967) and has gained widespread acceptance in the NPD and innovation literature in recent years. Initially referring to the quality of collaboration between team members in an NPD project, integration now refers to the quality of coordination and collaborative work amongst all entities involved in NPD (Jassahalla and Sashittal, 2000). The integrative model acknowledges that NPD is a complex activity that requires the capability to obtain, transform and interpret large amounts of market, technical, financial and other internal and external information, in order to develop product ideas and evaluate their technical soundness, manufacturability and economic feasibility (Ancona and Caldwell, 1990). This usually requires the efforts of various individuals from a number of functional areas, and increasingly from external entities (Mintzberg et al., 1996), hence turning NPD into a highly-complex collective achievement, more than an individual activity (Emmanuelides, 1993) (see Table 5 and Figure 4).
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Table 5. Characteristics of the integrative model Model Environment Assumptions underlying the model Process characteristics Process goals Major raw materials Key organizational functions Fundamental assumptions about organizing Shortcomings
Integrative Disturbed reactive, turbulent, complex Structure defined by teams, decisions are structured Half tacit and half explicit Trade-off between long-term and short-term, responsiveness Knowledge, competencies, information Teams, teamwork, internal and external collaborative networks Uncertainty, surprise, adaptation, emergence Conflict, time-delays if marketers are not included in the team
Figure 4. Integrative model The integrative model reinforces some of the major shifts between previous and recent NPD models, and introduces new paradigmatic changes in the way the NPD process is conceived. First, it reinforces the shift from structure to processes. Processes are collections of tasks and activities that together transform inputs into outputs (Garvin, 1998). Many modern organizations do not operate on a process-basis, rather they are functional and hierarchical, suffer from isolated departments, poor co-ordination and limited lateral communication. All too often, work is fragmented and compartmentalized, and managers find it difficult to get things done. Managing and describing organizations in terms of processes instead of structures helps to go beyond a static view of innovation and NPD, thus permitting to address in a more direct way the issues of fragmentation and lack of cross-functional integration. The Japanese recognize this when they define cross function as:
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a management process designed to encourage and support interdepartmental communication and cooperation throughout a company – as opposed to command and control through narrow departments or divisions. The purpose is to attain such company-wide targets as quality, cost, and delivery of products and services by optimising the sharing of work’ (Japan Union of Scientists and Engineers, in Dimancescu, 1992, p. 14). Second, the shift is also from functions to knowledge. Instead of thinking in terms of distinct departments that come together to take an idea from inception to launch the rational of the integrative model is to think in terms of the pool of knowledge required to deliver a new product. One implication of this shift is to extend NPD solutions beyond structural systems, such as the stage-gate process (Cooper, 1988), into more emergent ways of organizing, such as team empowerment. In
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other words, managing NPD is about managing not only the technical but also the human systems involved in innovation. A second implication is that the concept of integration now extends to integration of product innovation in other organizational systems such as the business system. Finally, NPD is a collective task, which means that teams and teamwork are crucial. NPD teams are groups of individuals reciprocally interdependent and directly involved with a project (Ancona and Caldwell, 1990). These teams are created to work in a particular project and they are dissolved at the end of it. They usually include people from different functional areas or departments in the organization, or multi-functional teams. Multi-functional teams can potentially improve integration in NPD by reducing hierarchical and functional barriers, facilitating lateral communication and promoting co-ordination of efforts. Teams can be given autonomy and responsibility for deciding how an NPD project unfolds, therefore project stages are highly ill-structured as they are defined by teams themselves. Structured points in the process consist of the decision-gates only, when the project team and the board team meet to take strategic decisions. In line with these views, NPD can be conceived as a knowledge-creation process, in which new ideas and concepts are transformed into new or improved products. In the process, knowledge is used and new knowledge is created, which can be used for generating more ideas and concepts (Mendes, Gomes and Bátiz-Lazo, 2003).
The Improvisational Model Improvisation refers to the temporal convergence of planning and execution, which
means that an action is improvised when it constitutes a deliberate, real-time response to a problem or opportunity, and is executed with the available resources (Cunha, Cunha and Kamoche, 1999; Miner, Bassoff and Moorman, 2001). The improvisational approach to NPD (see Table 6) tries to facilitate innovation under relentlessly shifting and fluid conditions. This model may be best suited to disturbed or turbulent environments. It combines elements of the flexible model (e.g. exploratory learning) with elements of traditional approaches including the need to use developmental models as control devices. However, control is executed through the use of minimal structures, which makes a significant difference. Clear roles, no-exceptions milestones, experimentation and gradual convergence are on the basis of the improvisational model, an approach that synthesises order and disorder (see Figure 5). Improvisational NPD teams are allowed to work autonomously inside the limits prescribed by a small set of ‘big rules’ (i.e. within the confines of a minimal structure). If the synthesis of freedom and control constitutes a major challenge for product innovation in today’s firms (Clark and Fujimoto, 1991), the improvisational model suggests a pragmatic way of operating this paradoxical need, via the utilization of minimal structures. Minimal structures basically consist of a simple and well-defined set of rules, where some features are formalized while others are not (Kamoche and Cunha, 2001). In the case of product innovation, minimal structures may consist of clear roles and responsibilities (for product definition and financial performance, project schedules, portfolio priorities and time intervals between projects; Brown and Eisenhardt, 1997), action-based communication and
Table 6. Characteristics of the improvisational model Model Environment Assumptions underlying the model Process characteristics Process goals Major raw material Key organizational functions Fundamental assumptions about organizing Shortcomings
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Improvisational Disturbed-reactive, turbulent Trading structure for minimal structure Mainly tacit, with explicit elements Coping with turbulent environments, adaptiveness Product innovation principles, ideas Minimal structures, learning-while-doing Complexity, emergence Fuzzy, unclear, ambiguous process; vulnerable to disintegration/centrifugal forces, risk of ‘sinking the boat’
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Figure 5. Improvisational model
freedom to act inside existing limits. Minimal structures collapse the traditional notion of structure, substituting a serial, step-following process, by the freedom to act and to build a unique process, contained within a set of technical and social rules that must be known and accepted by those working in an improvisational mode. The case of the Honda City model provides a good illustration of the use of NPD with minimal structuring. Honda’s top-management provided the NPD team with only two instructions: (1) to come up with a product concept fundamentally different from any previous concept developed at Honda; (2) to make an inexpensive but not cheap car (Nonaka, 1991). Minimal social structures should coexist with minimal technical structures. NPD in an improvisational mode may proceed through gradual convergence or the progressive narrowing of an initially larger range of acceptable solutions. Gradual convergence means that each group involved in the development of a new product works autonomously, but has to meet regularly with the other groups to coordinate efforts and eliminate flawed solutions. The search for variation is then limited, from the very beginning of the project, by the structural constraints introduced by the improvisational modus operandi. Because of the improvisational model’s search for flexibility and efficiency (Adler, Goldoftas and Levine, 1999), it seems to be especially suited to organizations competing in industries where high levels of efficiency can be considered critical, and for which the purely organic functioning of the flexible model is not suitable (e.g. the automobile and computing industries).
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The improvisational model, as depicted in Figure 5, synthesizes order and emergence: like the more traditional models, it implies the existence of a strong, although minimal, structure that gives direction and facilitates coordination (Kamoche and Cunha, 2001); emergence is embraced because the new product concept is achieved gradually, while action unfolds. As pointed out by Sobek, Ward and Liker (1999), gradual convergence provides the group with the possibility of collective learning based on real-time information, not forcing the choice of early and potentially misleading convergence points. Innovating in an improvised mode entails some risks, including high levels of stress and ambiguity, and the possibility of strategic drift. These risks are increased if improvisational processes are not clearly embedded in organizational goals. Table 7 summarizes the main features of both organization and NPD models, and establishes a link between theoretical characteristics of the former with views of organizing for NPD.
Conclusion It was argued in this article that organization theories and product innovation models are co-evolving in the planning to emergence direction, a conceptual move that has been triggered by changes in business landscapes: new landscapes require new product innovation models. From the previous discussion, it is possible to derive six propositions (see Table 8 for an overview).
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Table 7. Linking organization theory and product innovation Organizing as order
Organizing as disorder
Role of the environment
Should be under control
Complex relationships with organization
Essence of organizing
Stability, control, rationality, predictability
Disorder, ambiguity, improvisation, random
Main goal
Achieving equilibrium and stability
Achieving dynamical equilibrium
Organizational structures
Mechanistic, hierarchical, functional
Organic, flat, horizontal
Product innovation model
Sequential
Compression
Flexible
Integrative
Improvisational
Assumptions
Certainty, equilibrium, stability, predictability, mechanicism
Certainty, equilibrium, stability, adaptation, mechanicism
Uncertainty, surprise, adaptation
Uncertainty, surprise, adaptation, emergence
Complexity, emergence
Main goal
To standardize innovation
To optimize the sequential model
To adapt to the project needs
To integrate multiple PD components
To manage efficiency and flexibility at the same time
PS structures
Universal: all products; all organizations; all industries
Universal: all products; all organizations; adaptable to industries
Adaptable to product types and industries; universal: all organizations
Adaptable to product types, organizations and industries
Dependent on the particular project
First, the discussion shows that the principle of contingency seems to be valid to NPD. Traditional, sequential models were context-free and presumed to fit every case in any context. The ‘one size fits all’ assumption is no longer tenable. As Gomes et al. (2003) have concluded, different cases require diverse approaches. Future research will need to refine a contingency approach to product innovation. Such an approach will need to find types of products, structures and technologies that recommend the use of a certain product innovation model.
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Second, the evolution of product innovation models is also due to the growing recognition that there is an element of emergence in organizational life that cannot be removed and that encourages the adoption of flexible NPD practices. Innovation researchers have paid attention to the planned side of the process, but treated emergent actions and particularly improvisational actions as less functional if not harmful (Lewin, 1998). Recently, however, a growing body of work is placing a significant focus on the emergent side of product innovation. Thus, it was suggested
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Table 8. Innovations in product innovation models Proposition 1: From universal to contingent models
There is not a one best model The innovation process should be adapted to the type of product The process should be adapted to the type of environment
Proposition 2: From invariant to flexible practices
Introduce freedom if necessary Consider the possibility of making use of more emergent models
Proposition 3: From avoiding risks to taking advantage of opportunities
Product innovation is not only risk avoidance but also building on opportunity Long-range plans should be complemented with short- term, real-time plans
Proposition 4: From planning to learning
The product innovation process is a technical but also a social one The process should include planning, but infuse it with real-time learning (while doing) To prevent errors of forecasting, product flexibility should be high
Proposition 5: From exclusive teams to inclusive networks
NPD teams are networks of inclusion, not cells of exclusion Transfer of knowledge between projects should be systematic Customers and suppliers should be included in the team for contribution
Proposition 6: From structure to structured chaos
Over-engineering may be constraining Process focus (control vs innovativeness; principles vs ideas) should be diagnosed
that if the traditional mechanical approach may aptly describe what happens in some product innovation efforts, it is not adequate for other processes. That is why it was argued that developments in product innovation models are moving from planning to emergence. The third proposition states that new NPD models understand the intrinsic novelty of innovation processes as an opportunity for learning and discovery, and not as an uncertainty to be removed. Students and practitioners of management have been taught that deviations from order are generally bad (Abrahamson, 2002), but recent theorizing is pointing in a different direction: novelty may be part of the fabric of social organizations (Fonseca, 2002) and therefore should not be ‘combated’. This is closely related with the fourth observation: innovation processes are technical endeavours that need to be planned, but are also social processes that will bring diversity to the organization. As forecasts are condemned to failure, learning-while-doing
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should be facilitated. Learning is stimulated in communities of practice (Brown and Duguid, 1991). These communities enrich their repertoires of knowledge, engaging in communication with other communities. This leads to a fifth observation: NPD teams need to be understood as inclusive networks instead of exclusive, self-focused teams. All the above propositions result in a final one: NPD practices are evolving from structure to structured chaos, as Brown and Eisenhardt (1998) have put it. This means that the traditional engineering roots of management processes (Shenhav, 1999), including NPD, should be complemented with a more organic and adaptive view. In summary: order may not be as good as it seemed and the challenge may reside in the identification of the appropriate combination of structure and disorder.
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Miguel Pina e Cunha (PhD, Tilburg University) is an assistant professor at the Universidade Nova de Lisboa, in Lisbon, Portugal. His main research interests are in the interplay between structured and unstructured change, improvisation and knowledge appropriation. His research has been published in journals such as the Academy of Management Review, Organization Studies, Organization, Journal of Management Studies, and Human Relations, among others. Faculdade de Economia, Universidade Nova de Lisboa, R. Marquês de Fronteira, 20, 1099-038 Lisbon, Portugal. E-mail:
[email protected] Jorge F.S. Gomes (PhD, Manchester Business School) is an assistant professor at the Instituto Superior de Psicologia Aplicada, Lisbon, Portugal, and senior researcher in innovation management in the University of Twente, The Netherlands. His research interests include the management of innovation and knowledge, and the structuring of innovation teams in an organisational environment. He has published in the International Journal of Management Review, Technovation, Creativity and Innovation Management and the Journal of Workplace Learning, amongst others. Univ. Twente, School of Business, Public Administration and Technology, P.O. Box 217, 7500 AE Enschede, The Netherlands. Email:
[email protected] and Instituto Sup-erior de Psicologia Aplicada, R. Jardim do Tabaco, 34, 1149-041 Lisbon, Portugal. E-mail:
[email protected]
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