EDITORIAL
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Editorial
‘C
ontinuous and Discontinuous Innovation: overcoming the innovators dilemma’ is the theme of this issues’ special guest-edited section of, in total, six contributions. This includes an editorial introduction on the theme authored by the guest editors Mariano Corso (Politecnico di Milano) and Luisa Pellegrini (University of Pisa). The guest editors brought together five relevant papers working on research and discussion from the 7th CINet Conference held in Lucca (Italy) in 2006. The special aims at contributing to theory and practice on the two complex balancing acts of continuous and discontinuous innovation, that today represent a hot topic in innovation management. Please turn to their article which commences this issue, for a more detailed introduction of the five articles. Creativity and Innovation Management is affiliated with CINet and will continue to publish selected papers from their conferences in the future. The next CINet conference will be held in Valencia, Spain, focusing on radical challenges in innovation management (7–9 September 2008, see http:// www.continuous-innovation.net). This fourth and final issue of 2007 is quite a well filled one, with another (mini)special on Innovation Roles. These three articles are based on original presentations at the 2006 TIM Tagung in Vienna (Gemünden et al.), and the International Product Development Management Conference organized by EIASM, in 2006 in Milan (Sim et al. and Anderson & Berggren). All three articles address innovation roles issues from their own specific viewpoint. To start with Hans Georg Gemünden, Sören Salomo and Katharina Hölzle address role models for radical innovations in times of open innovation, reporting on their study of the influence of innovator roles in highly innovative ventures. Edward Sim, Abbie Griffin, Raymond Price and Bruce Vojak explore differences between inventors, champions, implementers and innovators in developing new products in large, mature firms. The summary conclusion is that different management strategies need to be developed to allow each of these specialist types to function in top form and subsequently be appropriately rewarded. It is unlikely that someone who is adept at managing inventors will be adept at managing champions, or that a good manager of implementers could also © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
manage innovators. And yet, as Sim et al. stress in their contribution, inventors, champions, innovators and implementers need to interact effectively in order for a technology to proceed from capability to successful product in the marketplace. Knowing how to get all these specialist types to work together is important to the firm! Closing the minispecial, Hans Andersen and Christian Berggren focus on individual inventors who, as they say in their introduction, often figure prominently as examples, role models or myths in the histories of technologybased companies. Whether individual inventors are still important in the rationalized R&D operations of modern, internationally competing firms is one of the questions they address in their article. This question is answered affirmatively and, moreover, the authors also shed light on how managers can leverage these inventors, as well as how to maintain and nourish the fragile inventive space in increasingly lean R&D organizations. Last but not least, Diana Grosse’s paper on project leadership in R&D was already announced in the September issue editorial as being complementary to the Leadership special we published in that issue. It has already been available on Online Early since September, and we indeed encourage you to check this feature on our Blackwell webpages regularly for the latest articles in digital form. The issue of Creative Leadership will be a topic for our 2nd Creativity and Innovation Management Community meeting to be held in Buffalo, 28–30 May 2008, combining among others the European perspective of our own founding editors Tudor Rickards and Susan Moger, with Gerard Puccio’s (the host in Buffalo) own views. A preliminary programme for that event will also be published on our website (in December 2007) and we hope to meet many of you there! The issue concludes with two book reviews which we hope will lead you to read the books discussed in full. Antoni Brack reviews Intellectual Property Law and Innovation by W. van Caenegem, and Bram Snitslaar highlights the main issues from Utterback et al.’s Design Inspired Innovation. We hope you enjoy your last CIM issue for this year, which has been a fruitful year for the Journal. We look forward to our 17th volume
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in 2008, which will start in March with a small selection of papers based on presentations from the 2006 R&D Management on Creativity and R&D held in Taiwan, brought together by our guest editors and members of editorial board Ming Huei Chen and Geir Kaufmann. Also, 2008 will bring new PDMA (Boston), CINet and EIASM (Hamburg) conferences, and perhaps already some publication of papers from the tenth European Conference on Creativity and Innovation (ECCI X, held in Copenhagen in October 2008). Also, there is the possibility to submit for a new special on TRIZ: Theory of Inventive Problem SolvingImpact for Creativity and Innovation Management. Please see the call for papers initiated by Carsten Gundlach and Martin Moehrle on our website and remember to submit via Manuscript Central mentioning TRIZ, as well as e-mailing your paper to gundlach@ kassel.ihk.de. The deadline is 15 March! Next year will also be the year of the second Tudor Rickards Best Paper Award, to be handed out if all goes well in Buffalo. Please send your nominations from among the four issues of our 16th volume to the editors at
[email protected].
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Last but not least your editorial team will be strengthened by a third editor-in-chief, our former special issues advisor and colleague at the University of Twente, Klaasjan Visscher. In the March issue he will introduce himself a bit further. We will end this editorial by acknowledging the invaluable help of our ‘behind the scenes’ CIM team at Wiley-Blackwells in Oxford. A special thank you goes to our Journal Content editor David Thresher, accurate and always flexible! Thank you all for another year of stimulating cooperation. In Twente, our own editorial assistant Jeannette Visser-Groeneveld has been invaluable in many ways, and in particular in her skill to manage Manuscript Central. We wish all members of the CIM community a very merry Christmas and a happy New Year, and look forward to being in touch with you again in 2008! October 2007 Petra de Weerd-Nederhof Olaf Fisscher
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Continuous and Discontinuous Innovation: Overcoming the Innovator Dilemma Mariano Corso and Luisa Pellegrini Challenged by competition pressures and unprecedented pace of change, firms can no longer choose whether to concentrate on the needs of today’s customers or on the anticipation of those of tomorrow: they must be excellent in both. This requires managing two related balancing acts: on the one side, being excellent in both exploitation and exploration of their capabilities and, on the other side, being excellent in managing both incremental and radical innovation. These balances are critical since exploitation and exploration, on the one side, and incremental and radical innovation, on the other, require different approaches that have traditionally been considered difficult to combine within the same organization. Working on evidence and discussion from the 7th CINet Conference held in Lucca (Italy) in 2006, this Special Section is aimed at contributing to theory and practice on these two complex balancing acts that today represent a hot issue in innovation management.
1. Introduction
T
oday excellent firms are challenged by very strong and unprecedented pressures. This is essentially due to the performance that their products have to possess to address customer needs, i.e., the needs of today’s and tomorrow’s customers (Boer & Gertsen, 2003; Boer, Kuhn & Gertsen, 2006). Indeed, if we focus our attention on the former, it is evident that today’s customers ask to be satisfied in terms of function, price, time, quantity, service and place of the existing product. This requires firms to be excellent in exploitation capabilities (‘Exploitation includes such things as refinement, choice, production, efficiency, selection, implementation, execution’, March, 1991, p. 71; ‘The essence of exploitation is the refinement and extension of existing competences, technologies, and paradigms. Its returns are positive, proximate, and predictable’, March, 1991, p. 85). Then, if we turn our attention to the latter, taking care of tomorrow’s customers means looking for new configurations of products; to satisfy such requirements firms have to be excellent in exploration capabilities (‘Exploration includes things captured by terms such as search, variation, risk taking, experimentation, play, flexibility, discovery, innovation’, © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
March, 1991, p. 71; ‘The essence of exploration is experimentation with new alternatives. Its returns are uncertain, distant, and often negative’, March, 1991, p. 85) (Boer, Kuhn & Gertsen, 2006). Focusing on exploitation or exploration capabilities, therefore, entails different skills, attitudes, and management styles that have traditionally been considered difficult to combine. From these considerations, we can determine a first type of balancing need that organizations face: • In order to combine excellence in both satisfying today’s customer needs and anticipating the demand of tomorrow’s customers, firms are required to combine excellence in exploitation of old certainties and in exploration of new possibilities. (March, 1991; Boer & Gertsen, 2003; Boer, Kuhn & Gertsen, 2006) In addition, if we extend the argument connected with the requirements of tomorrow’s customer one step further, we can see that tomorrow’s customers ask for products with higher and higher levels of performance, or attribute sets, that are possible because of the technology embedded in the product (Danneels, 2004). This requires firms to
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manage the steady state innovation process, i.e., innovating incrementally, building upon their existing knowledge and capabilities. What has emerged recently is that customers not only ask for new configurations of products with higher performance, but also for new products with different attribute sets from the existing products (Danneels, 2004). It is the case, for example, with new products that address people who previously lacked the money or skill to buy/use a product (new market disruption), or new products based on a disruptive technology, that have, at first, lower performance on dimensions relevant to the mainstream market segment, but are valued by a different market group which leads the disruption (Christensen & Raynor, 2003; Burgelman et al., 2004; Danneels, 2004; Bessant, 2006a; Bessant, de Weerd-Nederhof & Fisscher, 2006), or products based on innovations which come ‘out of left field’, from the periphery. This requires firms to be excellent in incremental innovation, while at the same time innovating radically beyond the organizational normal operating envelope. This poses another challenge, in that incremental and radical innovation requires different processes, and organizations are often in conflict in terms of use of resources and management attention. The above-mentioned customer needs highlight the existence of another balance which does not substitute, but is concurrent with the previous one: • In order to sustain competition, firms are required to be excellent in both incremental and radical innovation. (Boer, 2001; Bessant, de Weerd-Nederhof & Fisscher, 2006) Firm sustainable competitiveness – i.e., the possibility for organizations to improve their performance continuously in order to cope with market demands and turbulence, customer sophistication and changing technology (Porter, 1990; Hamel & Prahalad, 1994; Douma, 1997) – requires the management of these two balancing needs that make innova-
Exploitation
tion in all of its 4Ps (the introduction and/or improvement of (i) products/services and (ii) process, (iii) the (re-)definition of the positioning of the firm or its products, and (iv) the (re-)definition of the dominant paradigm of the firm (Francis & Bessant, 2005)) play a key strategic role. During the last few years, innovation theory has produced a large but fragmented mass of literature that, more or less explicitly, has emphasized the importance of knowledge creation and learning. The objective of our work is to construct a coherent framework of the literature in order to highlight the theoretical and managerial implications in terms of knowledge generation and learning, following a historical-evolutive perspective. The abovementioned balancing acts – exploration/ exploitation and incremental/radical innovation – will serve as the key dimensions for this objective. The rest of this article is divided into three sections. In the next two sections the interpretative framework and the detailed analysis of the literature will be analysed; the final section will present the contributions selected for this Special, while collocating them in the interpretative model.
2. The Interpretative Framework of Innovation: The Role of KM The two balancing acts suggest, respectively, two key dimensions through which it is possible to review the state-of-the-art management literature on innovation: (i) the balancing act connected with exploration/exploitation focuses attention on the dimension connected with the ‘learning focus’, and (ii) the balancing act connected with incremental/radical innovation focuses attention on the dimension connected with the ‘innovation focus’. If we focus on the first dimension – the learning focus – the analysis of the management literature emphasizes an evolution like that shown in Figure 1.
Binary/orthogonal balance Balancing need Synergistic balance
Exploration t
Figure 1. Evolution of the ‘Learning Focus’ in Management Literature
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As shown in Figure 1, the state-of-theart management literature has traditionally considered and analysed exploitation and exploration separately (Andreassen & Gertsen, 2006; Boer, Kuhn & Gertsen, 2006), in the conviction that organizations can be good in one of the two capabilities, but are likely to fail to maintain an effective balance between the two (Burns & Stalker, 1961; Skinner, 1974; Porter, 1980; March, 1991, 1995). In the words of March (1991, p. 72): In studies of organizational learning, the problem of balancing exploitation and exploration is exhibited in distinctions made between refinement of an existing technology and invention of a new one [. . .]. It is clear that exploration of new alternatives reduces the speed with which skills at existing ones are improved. It is also clear that improvements in competence at existing procedures make experimentation with others less attractive [. . .]. Finding an appropriate balance is made particularly difficult by the fact that the same issues occur at levels of a nested system – at the individual level, the organizational level, and the social system level. It has only been in the last ten years that an increasing number of scholars – e.g., Spina et al. (1996) with the multi-focused manufacturing system – have begun to suggest that in the ‘continuously innovative organization’ (Boer, Kuhn & Gertsen, 2006) the ongoing interaction between exploitation and exploration processes is not only possible, but even necessary for sustainable excellence (Schonberger & Knod, Jr., 1997; Hamel, 2006; Soosay & Hyland, 2006). The question is (Boer, Kuhn & Gertsen, 2006): how is it possible? Recent management literature seems to suggest two different possibilities: binary and dual organizations that balance demands for exploitation and exploration in an orthogonal and a synergistic way, respectively. Binary and dual organizations, however, and the latter in particular, need much more investigation.
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The analysis of the first dimension highlights the three values in which the ‘learning focus’ can be articulated: (i) exploration, (ii) exploitation, and (iii) equilibrium between exploration and exploitation, both orthogonal (where a time/space separation takes place), and synergistic. If we focus our attention on the second balancing act, i.e., on the second dimension – the innovation focus –analysis of the management literature regarding innovation emphasizes an evolution like that shown in Figure 2. As shown in Figure 2, the management literature has analysed separately incremental and radical innovation, with radical innovation in conditions of discontinuity being investigated only recently (Bessant, 2006a), because of the ever increasing non-linear shifts in the ‘rules of the game’ of technologies and markets, i.e., highly uncertain and rapidly evolving conditions which result from discontinuities (Bessant et al., 2005). In the last few years some scholars have begun to discuss the interaction between incremental and radical innovation (Gilbert, 2003; Bessant et al., 2005), but this interaction really needs much more investigation as the management literature is still in its infancy. When considering the above-mentioned discontinuities, the management literature seems to be rather contrasting, particularly when incumbents’ serendipity is considered. In fact, many scholars report examples of the inertia/failure of established organizations when discontinuities occur (Tushman & Anderson, 1986; Henderson & Clark, 1990; Leonard-Barton, 1992a; Utterback, 1994; Tripsas & Gavetti, 2000). In particular, Christensen and Raynor (2003) state that when the market becomes disrupted from below, the existing incumbents, notwithstanding their dominant position in the mature phase of an existing technological trajectory, have little room to manoeuvre in the new one, being able at best to imitate or to move upmarket toward more complex, higher margin products (Gilbert, 2003), and at worst withdraw (Bessant, 2006a), because of their psychological
Incremental innovation
Binary/orthogonal balance Equilibrium
Radical innovation
Synergistic balance
t
Figure 2. Evolution of the ‘Innovation Focus’ in Management Literature © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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(not invented here syndrome) and institutional rigidities, sunk costs, commitments to existing technologies/markets, and the cognitive representations of top management that influence such commitments (LeonardBarton, 1992a ; Tripsas & Gavetti, 2000; Bessant et al., 2005). Others (Danneels, 2004) propose investigating more deeply, since different contributions (Tushman & Anderson, 1986; Markides, 1997; Evans & Wurster, 2000; Foster & Kaplan, 2002) show how incumbents have built on the new trajectory and kept their dominant position over the new players, while deploying/leveraging their knowledge. When discontinuities arise, the challenge is to manage innovation beyond the good practices and routines of the ‘steady state’ (i.e., the routines for ‘do better’ innovation), that are helpful in the mature phase, but can act as barriers against the entry and success in the fluid phase of a new technology/market, when both the old and the new technologies co-exist and evolve (Bessant et al., 2005). In other words, when discontinuities arise, the routines for ‘do different’ innovation assume a fundamental role for dealing with the challenges of ‘do different’, within the entire spread of the 4Ps (Francis & Bessant, 2005). This second dimension connected with the innovation focus can assume three values: (i) incremental innovation, which builds upon existing knowledge and capabilities, (ii) radical innovation, which goes beyond the normal operating envelope of the organization, and (iii) equilibrium between incremental and radical innovation. The combination of these two dimensions – ‘learning focus’ and ‘innovation focus’ – allows the construction of a bi-dimensional matrix, where the main streams of the literature can be mapped (Figure 3). Each stream will be analysed, highlighting the implications
in terms of knowledge creation and learning. However, readers should be warned that there exist overlapping and fuzzy borders between different streams. The analysis of the content of the main streams is presented in the next section. In our analysis we consider articles published in major English-language North American and European journals.
3. Knowledge Management in Innovation: Main Streams in the Literature 3.1 Incremental Exploitation Incremental exploitation refers to the ‘exploitation’ capabilities that lead to incremental product and process improvement. It deals with continuous improvement (CI), or kaizen (Imai, 1986), defined as ‘the planned, organised and systematic process of ongoing, incremental and companywide change of existing practices aimed at improving company performance’ (Boer et al., 2000, p. 1). According to Bessant’s CI maturity model (1998), CI is a long-term learning process that involves a suite of behaviours that cluster around several core themes, namely routines (for example behaviours associated with the systematic finding and solving of problems or with the monitoring and measuring processes, etc.), that evolve and are reinforced over time. The development of routines involves two kinds of learning: improving/reinforcing behaviours within a particular routine cluster or adding new routines to the repertoire. Organizations can progress towards higher CI maturity levels by acquiring, practising and repeating CI behaviours until they become ingrained as ‘the way we do things around here’.
Learning focus Exploitation
Innovation focus
Incremental innovation
Incremental exploitation
Equilibrium between radical and incremental innovation
Radical innovation
Equilibrium between exploration and exploitation
Exploration
Binary and dual forms
Incremental exploration
Full dexterous organization
Equilibrium between radical and incremental exploration
Radical exploitation
Radical exploration
Figure 3. The Matrix of Knowledge Creation and Learning
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There are a number of distinctive characteristics that differentiate CI from the more ‘traditional’ breakthrough innovation: 1. The type of change (Bessant, 1998): CI concerns incremental changes, i.e., the pattern of small modifications and improvements which have their impact on performance in a cumulative fashion, while traditional innovation concerns major discontinuous changes (developing new products, introducing new processes and radically transforming organizational structures). 2. The frequency of change (Bessant & Caffyn, 1997): in contrast to breakthrough innovation, CI is not limited to specific projects and situations, but is part of the everyday working life. 3. The type of knowledge (Bessant, 1998; Bessant, Caffyn & Gallagher, 2001): everyone in the organization has the capacity to solve problems in a creative fashion, while major, hi-tech discontinuous innovation remains the province of specialists, in that it implies skills and formal knowledge constraints. 4. The degree of workforce participation and scope of the innovative base in the organization (Bessant & Caffyn, 1997; Imai, 1997; Mitki, Shani & Meiri, 1997; Bessant, 1998; De Jager et al., 2004): while in the traditional perspective a neat split takes place between those employees concerned with exercising judgement – the specialists who often work apart from the mainstream of the organization’s operations (typically R&D and IT functions) – and those who have to repeat standardized tasks, in CI all the employees are reckoned to have the capacity to solve problems creatively, so amplifying the organizational innovative base. Today many streams of the literature, coming from different perspectives, theorize the necessity to involve people in the innovation activities (Bessant & Caffyn, 1997; Bessant, 1998): lean manufacturing (with its emphasis on team working and participation in innovation; Bessant, 2006c), total quality management (whose underlying recipe is based on the contribution of the participants in the process of finding and solving quality problems; Bessant, 2006c), ‘productivity through people’ programmes, Japanese manufacturing techniques, the learning organization, and advanced technology implementation. From a knowledge management (KM) and learning perspective, the importance of such continuous and widespread participation in problem-solving activities lies in three major effects: the mobilization of the organizational core knowledge base (Bessant, 1998) in that a 100-headed brain is unleashed (Boer et al., © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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2000), the systematic capture and conversion of tacit knowledge into explicit knowledge, which can be articulated in standard operating procedures (Bessant & Francis, 1999), and the possibility to activate learning processes (Bessant, 1998).1
3.2 Incremental Exploration Incremental exploration refers to exploration capabilities that lead to incremental innovation – i.e., innovation which builds on existing knowledge – in both processes and products. As far as processes are concerned, it is important to mention business process re-design or re-engineering (BPR) that attempts to contribute to performance improvement, but, in contrast to CI, through non-linear changes and without the widespread involvement of employees (Boer et al., 2000). As far as products are concerned, since 1980 three main streams have emerged in the management literature regarding new product development (NPD): concurrent engineering, multi-project management and organizational learning. From a KM and learning perspective, such streams move the focus from the quick and intense socialization of knowledge in cross-functional, often co-located teams, to knowledge sharing through commonality and reuse of design solutions, up to the overall dynamic of knowledge creation and transfer also in tacit form or embedded into processes and organizational routines (Corso et al., 2001). Since the early 1980s, concurrent engineering has been considered the new paradigm for NPD as it replaces phased programme planning (the stage-gate process) with the joint participation of different functional groups in the PI process (Joice, 1986; Nonaka, 1990). From the KM viewpoint, the focus is on quick and intense socialization of knowledge in crossfunctional, often co-located teams. In order to improve time-to-market of the specific development project, knowledge is socialized in tacit and contextual forms, with limited emphasis on its codification, abstraction and generalization to foster future innovation. Furthermore, concurrent engineering keeps a rigid separation between product concept generation and product development (Dougherty, 1990, 1992; Iansiti, 1995). Also within the development project, milestones and ‘gates’ are defined to set constraints on possible information loops (Cooper, 1992, 1994), thus implicitly limiting the scope for knowledge 1
In particular, the approach of the level 3 of Bessant’s (1998) model provides a framework for establishing a ‘learning organization’ (Bessant & Francis, 1999).
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sharing and learning (Iansiti, 1995; MacCormack & Iansiti 1997; Verganti, MacCormack & Iansiti, 1998). From a knowledge management perspective this means fostering rapid learning loops within the overall product development process. Since the late 1980s, multi-project management has highlighted the risk, implicit in a concurrent engineering approach, of isolating each innovation process from the rest of the organization. In a medium- to long-term perspective, success depends on the ability to foster the sharing of knowledge through commonality and reuse of design solutions (Wheelwright & Sasser, 1989; Wheelwright & Clark, 1992; Sanderson & Uzumeri, 1995). From a KM perspective, this means enlarging the scope of learning and knowledge sharing, shifting attention from single products to product families, and emphasizing the importance of components and product platforms as vehicles embodying knowledge (Henderson & Clark, 1990; Cusumano & Nobeoka, 1992). Multiproject management has become a key issue in product development; conceptual models and tools have been developed to support the management of the interdependencies connected with knowledge transfer between projects over time (Czajkowski & Jones, 1986; Clark & Fujimoto, 1991; De Maio, Verganti & Corso, 1994). Analysing such interdependencies, some authors focus on the actual object of the interaction (Itami, 1987; Nonaka, 1991) distinguishing between interactions related to the exchange of tangible technological solutions (e.g., parts, components), of codified knowledge (patents, processes and formulas) and of non-codified know-how, generally personembodied. Others focus on the scope of the interaction, distinguishing between the component level and the architectural level (Henderson & Clark, 1990). A third and final group of contributions focuses on the approach in the transfer process, that can either be reactive, when solutions and knowledge from past projects are ex post retrieved and reused, or proactive, when solutions are deliberately developed for future use, often for not previously planned projects (De Maio, Verganti & Corso, 1994). Many authors have shown how traditional reactive policies, based on the carry over of parts and subsystems, are intrinsically limited and may also be detrimental to innovation (Clark & Fujimoto, 1991; Witter et al., 1994). Excellent companies prefer to use proactive policies where ex ante efforts are made to predict characteristics and features of new parts and subsystems to suit future applications. Depending on the architectural or component knowledge embodied in the solutions, these proactive policies are named ‘product
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platforms’ or ‘shelf innovation’ (Hayes, Wheelwright & Clark, 1988; Wheelwright & Sasser, 1989; Wheelwright & Clark, 1992; Meyer & Utterback, 1993; Sanderson & Uzumeri, 1995). In 1990, product innovation became a key area of interest for scholars of organizational learning. While multi-project management focused mainly on transfer of knowledge embodied in design solutions, organizational learning analyses the overall dynamic of learning and knowledge creation and transfer also in tacit form or embedded into processes and organizational routines (Nonaka, 1991; Nonaka & Takeuchi, 1995). Also, while multiproject management considers learning and knowledge reapplication as an automatic process, organizational learning emphasizes how learning and knowledge reuse may face barriers at organizational and individual levels, asking for an aware management support (Imai, Nonaka & Takeuchi, 1985; Senge, 1990; Nonaka, 1991; Arora & Gambardella, 1994; Hedlund, 1994; von Hippel & Tyre, 1995; Bartezzaghi, Corso & Verganti, 1997). However, most contributions share the assumption that product innovation is the outcome of NPD projects over time, hence, implicitly considering downstream phases only as sources of information for feeding next generation product development, or even constraints to be anticipated during development (Clark & Fujimoto, 1991). Some contributions, in contrast, highlight the necessity to extend the innovative efforts to the overall product life-cycle (Itami, 1987; Bessant et al., 1994; Caffyn, 1997; Bartezzaghi, Corso & Verganti, 1999; Corso, 2002).
3.3 The Equilibrium between Incremental Exploration and Exploitation: Binary and Dual Forms The equilibrium between incremental exploration and exploitation (Tushman & O’Reilly, 1996) entails two forms: binary and dual organizations, where ‘binary organisations balance demands for exploitation and exploration in an orthogonal way, [while] dual organisations do so synergistically’ (Boer, Kuhn & Gertsen, 2006, p. 4). In binary organizations there is a separation between exploration and exploitation, which can be either space or time. Examples of the first case – space – are: (i) the structural ambidexterity,2 i.e., the structural separation of 2
According to Birkinshaw and Gibson (2004), the concept of ambidexterity – the right balance between adaptability and alignment – ‘has typically been associated only with structural separation of activities’ (p. 48), i.e., with structural ambidexterity. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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activities (Birkinshaw & Gibson, 2004) implied in the functional structures, where co-existing functions of exploration and exploitation operate at the same time, but in different places, with obvious shortcomings in terms of response time to environmental changes, innovativeness and horizontal co-ordination between departments (Boer, Kuhn & Gertsen, 2006), which drives toward the frequent failure of research ideas to be accepted (Birkinshaw & Gibson, 2004); (ii) the nonrevolutionary, or gradual, incremental transformation theory (Romanelli & Tushman, 1994) that interprets the organizational transformation as the lengthy and gradual result of the accumulation of short-run, incremental and disjointed reactions that the singular subunits put in place when one change (a problem or a goal) occurs in the local – internal and external – environment. Examples of the second case – time – are: (i) the punctuated equilibrium model in which the ‘equilibrium periods’ (long periods of small and incremental change in their basic pattern of activity, reinforced by the organizational inertia and institutionalization) are punctuated by revolutionary periods (brief periods of discontinuous, fundamental change) that, while disrupting established activity patterns, install the basis for new equilibrium periods (Tushman & Romanelli, 1985; Romanelli & Tushman, 1994; Tushman & O’Reilly, 1996); (ii) the innovation process model, in which radical systemic changes are followed by long periods of maintenance and incremental improvement (Imai, 1986); (iii) the combination of extensive ‘do what we do better’ improvements with periodic and radical ‘do what we do different’ changes, which create a different framework within which future ‘do better’ improvements can be made (De Jager et al., 2004); (iv) the theories of innovation dynamics, which suggest that when a new product concept or process emerges, there is an initial period of uncertainty during which there is experiment around different configurations, but, when a ‘dominant design’ or ‘technological trajectory’ is established, the emphasis shifts to incremental improvements and refinements: in the case of products, the effort is on the introduction of variations on the basic theme, while, in the case of processes, the effort is on the stretching/ developing of the performance, driving out waste, eliminating bugs, etc. (Bessant, 2006c). Dual forms synergistically balance exploitation and exploration (Boer, Kuhn & Gertsen, 2006). Examples include: (i) the continuously innovative organization, analysed from the perspective of co-ordination theory – co-ordination through strategic alignment, process integration, technological integration, © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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and organizational mechanisms (Paashuis & Boer, 1997; Boer, Kuhn & Gertsen, 2006) or (ii) the contextual ambidextrous firm, in which, in contrast to a top-down approach, the employee acts outside the border of his/her job and encourages action that involves adaptation to new opportunities, while being aligned with the business strategy (Birkinshaw & Gibson, 2004). Birkinshaw & Gibson (2004) also propose a sort of equilibrium between the dual and the binary organization, in that they conceive the contextual ambidexterity as complementary to the structural ambidexterity: structural ambidexterity, essential at times, should be temporary in order to give a new initiative the space/ resources to get started. ‘The eventual goal should be reintegration with the mainstream organization as quickly as possible. Contextual ambidexterity can enhance both the separation and reintegration processes’ (p. 55). Chapman and Corso (2005) draw attention to the necessity to extend the unit of analysis from the context of single companies to an inter-organizational setting, that of extended manufacturing enterprises (Busby & Fan 1993; Harland, Lamming & Cosins, 1999; Stock, Greis & Kasarda, 2000), that can scarcely rely on established organizational and managerial mechanisms to support the equilibrium between exploration and exploitation at company level: new information and communication technologies and particularly Internet applications can play a fundamental role in bridging these gaps. Examples include eprocurement, e-sourcing and e-collaboration applications which allow customers and suppliers to increase co-ordination and collaboration through the Internet in terms of inventory management, demand management, production planning and control and new product development (Porter, 1998; Lee & Whang, 2001; Cagliano et al., 2003). When considering this stream of the literature, knowledge represents a valuable tool for managing dualities: in particular, when considering co-ordination through technological integration, technology has to be interpreted as knowledge embedded in (i) people (the knowledge, skills, experience, people use to perform activities), (ii) methods and techniques, and (iii) plant, equipment, tools and infrastructure (Boer, Kuhn & Gertsen, 2006).
3.4 Radical Exploration Radical exploration refers to exploration capabilities that lead to radical innovation in new and uncharted territories (Bessant, 2006c).
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This stream of the literature deals with discontinuities,3 characterized by high instability (unpredictable and unstable conditions) and high uncertainty (the extent to which knowledge can be acquired to help deal with the environment). Such discontinuities reframe the space and the boundary conditions and open up new opportunities, while challenging incumbents (Bessant et al., 2005). As stated earlier, the literature is not all in agreement when analysing the destiny of the incumbents faced with discontinuous shifts. Those who claim to be attentive to the impact that discontinuities can have on established firms highlight the existence of a sort of trade-off between new (often SMEs) and experienced players. The former – only those who are successful, and hence analysable (Danneels, 2004) – are not encumbered with their past experience and are endowed with agility, flexibility, the ability to learn fast, the lack of preconceptions about the ways in which things might evolve (Bessant et al., 2005; Bessant, 2006b), but lack the knowledge base, assets and competencies. The latter have the competencies, the financial assets and the capacity to mix the technologies they master, but in many cases show a sort of inertia in responding effectively and, as a consequence, can falter. The main reasons for this possible inertia are numerous: (i) their core capabilities – both technological (Nelson & Winter, 1982; Teece, Pisano & 3
Bessant et al. (2005) lists the typical sources of discontinuity, namely: emergence of (i) a new market, (ii) a new technology, (iii) new political rules, (iv) running out of road, (v) sea change in market sentiment or behaviour, (vi) deregulation/ shifts in regulatory regime, (vii) fractures along ‘fault lines’, (viii) unthinkable events, (ix) business model innovation, (x) architectural innovation, and (xi) shifts in ‘techno-economic paradigm’ – systemic changes which impact whole sectors or even whole societies. In particular, in this last case, the ‘convergence of a number of trends’ is considered: according to Bröring and Leker (2007), convergence can either be induced by the fusion of demand structures and the combination of previously distinct product features into a hybrid product – such as personal computers and televisions starting to become substitutes (Prahalad & Ramaswamy, 2003) – or technology-driven since a new technological development is applied across conventional industry boundaries, such as genomics applied to both nutrition and pharmaceuticals (Rao, Angelov & Nov, 2006 highlight that the technological convergence of both incremental innovations and disruptive innovations can be sources of discontinuity). In both case, however, the convergence can be of the 1 + 1 = 1 type (total phasing out of the two formerly separate industries) or of the 1 + 1 = 3 type (emergence of an additional industry segment), where innovation seems to be an imperative or an opportunity, respectively.
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Shuen, 1997) and marketing capabilities (Christensen, 1997) – that in some cases prove to be ‘core rigidities’ (Leonard-Barton, 1992b), (ii) the cognitive representations of their top management, which, by restricting and directing search activities connected with technology development, can constrain the development of new capabilities (Tripsas & Gavetti, 2000), (iii) the impact that disruption can have on their competencies, that can be enhanced or destroyed (Tushman & Anderson, 1986), and (iv) the blinkers of dominant logic (i.e., successful recipes in terms of business models, processes, approaches to competition), that limit the ability of people in the organization to drive innovation or see new opportunities and threats (Prahalad, 2004). The incumbents who survived showed the ability to take on new knowledge, while unlearning knowledge that was no longer needed (Utterback, 1994), which indeed is seen to be redundant (Bessant, 2006b). Hence, the challenge for incumbents seems to be that of creating new routines in order to cope with discontinuous innovation (‘do different’ routines), i.e., managing discontinuity – the ‘ripples in the pond’ (Brown, 2004). This entails new approaches for sensing the periphery (Baden-Fuller, 2004; Day & Schoemaker, 2004; Huston, 2004), discovering weak signals regarding potential discontinuities in areas not usually investigated, understanding the needs of a market that does not yet exist which will shape the eventual dominant design, discovering and finding new users, making strategic choices in the face of high uncertainty, carrying out projects which lie at the fringes of the organizational experience, exploiting network relationships with actors other than ‘strong ties’ partners (Bessant et al., 2005), and learning to unlearn and see differently (Brown, 2004). Between these, the exploitation of network relationships, which root in the stream of inter-organizational design (Corso et al., 2001), seems to be the most investigated area4 with particular attention to the role played by customers as innovation sources. More exactly, while in the past, research-intensive companies believed that research in the organization’s core area of expertise had to stay in-house, with outsiders providing only less 4
Inter-organizational design expands the scope of the product innovation process outside the traditional R&D boundaries, in that external complexity hinders the single firm from the chance of managing the knowledge system supporting the whole NPD process. In particular, a first sub-stream stresses the importance of designing new roles within R&D – such as gatekeepers – to bridge to the external environment (Katz & Tushman, 1981; Ancona & Caldwell, 1990; Allen, 1997). A second © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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important support activities, today – as the pharmaceutical and chemical companies illustrate – businesses are using external sources for all phases of innovation, from discovery and development to commercialization and even product maintenance. This evolution, which gives organizations the possibility to access disruptive new ideas, implies the necessity to deploy a sourcing strategy in order to manage innovation holistically, as opposed to managing innovation transactionally, whose major shortcomings are failure to leverage organizational learning (no method for applying the lessons learned from one external relationship to the others) and, most importantly, unintentionally losing knowledge (Linder, Jarvenpaa & Davenport, 2003). To give shape to the external sources as part of a complete sourcing strategy, several innovation channels are available – buying innovation on the market, investing in innovators, co-sourcing, re-sourcing (Linder, Jarvenpaa & Davenport, 2003), inward technology licensing (Leone, Boccardelli & Magnusson, 2007) – and, with particular attention to channels specifically conceived for interacting with customers: community sourcing (Linder, Jarvenpaa & Davenport, 2003), democratizing innovation (von Hippel, 2005), co-creating value with customers (Prahalad & Ramaswamy, 2003; Prahalad, 2004), opening innovation (Chesbrough, 2003). When customers are considered, however, not all the authors agree on their role: Christensen (1997), for example, thinks that firms, while ‘[held] captive by their customers’, can miss the boat on disruptive technologies. From a learning perspective there are two major aspects to be highlighted: on the one side the fact that ‘the management task [is] not simply one of building and sustaining routines for innovation but also – and most importantly – one of creating the underlying learning routines which enable the organisation to do so’ (Bessant, 2006c, p. 19); on the other side, the
sub-stream focuses on the direct and early involvement of external actors in inter-organizational groups (Katz, 1982; Imai, Nonaka & Takeuchi, 1985; Clark & Fujimoto, 1991). Finally, other authors investigate the specific relationships the firm builds with actors belonging to the supply chain (vertical agreements) (von Hippel, 1976, 1977, 1978, 1988; Imai, Nonaka & Takeuchi, 1985; Takeuchi & Nonaka, 1986; Nonaka, 1990; Clark & Fujimoto, 1991; Cusumano & Takeishi, 1991; Dyer, 1996; Edwards & Samimi, 1997), with competitors (horizontal agreements) (Clark & Fujimoto, 1991) and with complementary firms and institutions (cross agreements) (Teece, 1986; von Hippel, 1988; Lundvall, 1988; Lee, 1996). © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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creation of organizational routines and processes, by which firms acquire, assimilate, transform, and exploit knowledge to produce a dynamic organizational capability (Cohen & Levinthal, 1990; Andersen & Boer, 2007).
3.5 Equilibrium between Radical and Incremental Exploration This type of equilibrium deals with the challenge of coupling steady state innovation with discontinuous innovation, allowing routines for discontinuous innovation to sit alongside those for steady state innovation. A question of great interest is whether this balance can be reached in a synergistic way or in an orthogonal way, by organizational separation such as the creation of a spin-off unit to pursue disruptive technology (Bessant, 2006c; Danneels, 2006). In other words, when a mismatch between firms’ dominant steady state archetype (the ‘interpretative schema’ of the world, their strategy and resulting resource allocation; their routines and consequent structures and procedures) and the very different requirements for discontinuous innovation occurs, the question is: ‘is it possible to operate both archetypes under the same organizational roof and develop the ability to switch between them [. . .]? Or does successful management under different sets of conditions require setting up completely new organisations – for example, spinning off a completely new company to exploit new opportunities under discontinuous conditions?’ (Bessant et al., 2005, p. 9). The answers in the literature do not all point in the same direction (Danneels, 2004). Christensen (1997) proposes – although in wellspecified conditions5 – an orthogonal balance, in which incumbents should set up a separate organization endowed with their own resources for venturing into disruptive technology, in order to prevent problems connected, on the one side, with the missing fit between the disruptive technology and the mainstream organization’s resources, processes and values and, on the other side, with resources transferred from disruptive technology efforts to serve current customers. Also, other authors support this opinion, highlighting the advantages that creating a separate organization may have (Cohan, 2000), and in particular the possibility of avoiding possible misfits between the needs of the discontinuous 5
That is, when a disruptive technology requires a different cost structure for reasons of profitability and competitiveness, or when the size of the opportunity is insignificant relative to the growth needs of the mainstream organization.
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innovation and the business unit’s existing capabilities (Rice, Leifer & Colarelli O’Connor, 2002), and the opportunity, when the disruptive new business starts small, to figure out the requirements of the new customers, adjusting business models and product architectures early before huge resources are poured into the new business (Gilbert, 2003). Other authors highlight the disadvantages connected with the formation of an independent organization, in terms of lost synergies in purchasing, information sharing, branding, cross-promotion, and customer service (Gulati & Garino, 2000). From a knowledge management perspective, this trade off between arguments for and against a spinoff organization consists of the fact that ‘isolation may protect the project from the counterproductive forces within the mainstream, but it also cuts the project off from its most important sources of learning, competences and resources’ (McDermott & Colarelli O’Connor, 2002, pp. 431–32).
3.6 Radical Exploitation Radical exploitation refers to exploitation capabilities that lead to radical innovation in new and uncharted territories. Within this stream of the literature, many contributions highlight that in different industries many incumbents, while leveraging on their existing knowledge, could be credited with many radical innovations. This is the case with the telecommunications and medical device industries (Methe et al., 1997), manufacturers of television sets (Klepper & Simons, 2000), office products and consumer durables (Chandy & Tellis, 1998).
3.7 Fully Dexterous Organizations Full dexterity implies that organizations have the capabilities to innovate both radically and incrementally, while at the same time focusing on operational effectiveness. With respect to the other streams, full dexterity is the least investigated in the management literature. At the moment, authors simply highlight the necessity to further explore these aspects (Boer, 2001). The first tentative results are those of Martini and Pellegrini (2007), who describe a retrospective case study in which a knowledge management and an innovation management system were created not only for co-ordinating R&D and production – so combining excellence in exploitation and in exploration – but also for searching at the periphery, while picking up and amplifying weak signals – so combining excellence in incremental and radical innovation.
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4. The Special Section The analysis of the state-of-the-art literature shows that there remain research gaps to be covered and research questions to be answered in each stream of the literature of the ‘matrix of knowledge creation and learning’ depicted in Figure 3. This special section of Creativity and Innovation Management, which collects together five papers selected at the 7th CINet conference6 held in Lucca (Italy) in 2006, answers the following research questions. In particular: • In the incremental exploitation stream: 䊊 Are the premises of the CI maturity model culturally bound to national borders or rather do they transcend such borders? That is, to what extent do the constituent behaviour patterns of the CI maturity model converge across national borders, or are there country-specific differences? Mandar Dabhilkar, Lars Bengtsson and John Bessant, who draw upon the 2nd CINet survey, find that the premises of the CI maturity model transcend cultural and national borders and, hence, that the CI behaviour patterns converge across nations. 䊊 For implementing CI, human resource management (HRM) assumes a key role: it should secure a workforce capable of implementing CI and participate in the planning of employee training and development. Hence: which are the HRM practices that yield the greatest benefit in terms of CI development and, consequently, performance? The article by Frances Jørgensen, Bjørge Timenes Laugen and Harry Boer takes as its theme the impact of HRM on CI practices. Basing its results on the 2nd CINet Survey, these authors suggest that HRM can play an important role in supporting CI implementation that positively affects business performance. • In the stream connected with the equilibrium between incremental exploration and exploitation: 䊊 Can the concepts/practices of continuous innovation (that are usually applied to individual companies) be applied to manage improvement and innovation actions designed and implemented jointly among companies in a cluster? 6
CINet – the Continuous Innovation Network (http://www.continuousinnovation.net) – is an international group of researchers and practitioners who share common concerns about the effective management of innovation. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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The article by Luiz Cesar Ribeiro Carpinetti, Mateus Cecilio Gerolamo and Edwin Vladimir Cardoza Galdámez presents a conceptual model for managing actions for improving collective efficiency and measuring performance of an SME cluster. The article concludes that despite some difficulties in developing and using performance indicators in SMEs, the concepts presented by the proposed model can help to foster in clusters of SMEs co-operation and maturity in continuous innovation. 䊊 Is there a methodology for implementing information and communication technologies (ICT) in logistics? In the article by Jesús García-Arca and Carlos PradoPrado, the authors offer a methodology for implementing ICTs in the logistics field, with a participatory approach. • In the stream of radical exploration: 䊊 It is evident that faced with discontinuities, incumbents fail to cope with major changes in the environment and, thus, it is important to develop and search for best practices, whose implementation process is critical for success. Hence the question is: how do best performing companies implement new practices? Bjørge Timenes Laugen and Harry Boer investigate this research question through case studies in two highperforming manufacturing firms. The analysis of the implementation showed that a broad and incremental implementation approach initially leads to reduced performance followed by a gradual improvement as larger parts of the programmes are institutionalized. A ‘big bang’ implementation approach does not seem to lead to deterioration in performance.
Acknowledgements This special section of Creativity and Innovation Management is the closing act of the 7th CINet Conference, held in Lucca, Italy, in September 2006. It is the result of the precious work of many people whose contribution is gratefully acknowledged. In particular we would like to thank all the authors of the selected papers and the reviewers who spent some of their valuable time in reviewing them, namely: Prof. Pär Åhlström, Chalmers University of Technology, Sweden Prof. Vito Albino, Politecnico di Bari, Italy Prof. Ross L. Chapman, University of Western Sydney, Australia © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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Dr. Carmen Kobe, ETH Zürich, Switzerland Dr. Frances Jørgensen, Aalborg University, Denmark Prof. Paul Hyland, Central Queensland University, Australia Dr. Anna Nosella, University of Padova, Italy Dr. Anders Richtnér, Stockholm School of Economics, Sweden Dr. Stefano Ronchi, Politecnico di Milano, Italy Dr. Claudine A. Soosay, University of South Australia, Australia Prof. Stefano Tonchia, University of Udine, Italy Our appreciation also goes to the team at Blackwells.
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Linder, J.C., Jarvenpaa, S. and Davenport, T.H. (2003) Toward an Innovation Sourcing Strategy. MIT Sloan Management Review, 44, 43–49. Lundvall, B.A. (1988) Innovation as an Interactive Process: From User-Producer Interaction to the National System of Innovation. In Dosi, G. (ed.), Technical Change and Economic Theory, Pinter, London, pp. 349–69. MacCormack, A. and Iansiti, M. (1997) Product Development Flexibility. 4th International Product Development Management Conference, EIASM, Stockholm, Sweden. McDermott, C.M. and Colarelli-O’Connor, G. (2002) Managing Radical Innovation: An Overview of Emergent Strategy Issues. Journal of Product Innovation Management, 19, 424–38. March, J.G. (1991) Exploration and Exploitation in Organizational Learning. Organization Science, 2, 71–87. March, J.G. (1995) The Future, Disposable Organizations and the Rigidities of Imagination. Organization, 2, 427–40. Markides, C. (1997) Strategic Innovation. Sloan Management Review, Spring, 9–24. Martini, A. and Pellegrini, L. (2007), Continuous and (Dis)Continuous Innovation: Two Balancing Acts. 8th CINet Conference, 7–12 September, Gothenburg, Sweden. Methe, D., Swaminathan, A., Mitchell, W. and Toyama, R. (1997) The Underemphasized Role of Diversifying Entrants and Industry Incumbents as the Sources of Major Innovations. In Thomas, H., O’Neal, D. and Alvarado, R. (eds.), Strategic Discovery: Competing in New Arenas. Wiley, New York, pp. 99–116. Meyer, M.H. and Utterback, J.M. (1993) The Product Family and the Dynamics of Core Capability. Sloan Management Review, Spring, pp. 29–47. Mitki, Y., (Rami) Shani, A.B. and Meiri, Z. (1997) Organizational Learning Mechanisms and Continuous Improvement. A Longitudinal Study. Journal of Organizational Change Management, 10, 426–46. Nelson, R. and Winter, S. (1982) An Evolutionary Theory of the Firm. Harvard University Press, Cambridge, MA. Nonaka, I. (1990) Redundant and Overlapping Organisation: A Japanese Approach to Managing the Innovation Process. California Management Review, 69, 96–104. Nonaka, I. (1991) The Knowledge-Creating Company. Harvard Business Review, 69, 96–104. Nonaka, I. and Takeuchi, H. (1995) The KnowledgeCreating Company. Oxford University Press, New York. Paashuis, V. and Boer, H. (1997) Organizing for Concurrent Engineering: An Integration Mechanism Framework. Integrated Manufacturing Systems, 8, 79–89. Porter, M.E. (1980) Competitive Strategy. Techniques for Analyzing Industries and Competitors. The Free Press, New York. Porter, M.E. (1990) Competitive Advantage of Nations. The Free Press, New York. Porter, R. (1998) Managing the Supply Chain with Internet Based Collaboration. Logistic & Supply Chain Journal, November, 25–32.
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Prahalad, C.K. (2004) The Blinders of Dominant Logic. Long Range Planning, 37, 171–79. Prahalad, C.K. and Ramaswamy, V. (2003) The New Frontier of Experience Innovation. MIT Sloan Manacement Review, Summer, 12–18. Rao, B., Angelov, B., Nov, O. (2006) Fusion of Disruptive Technologies: Lessons from the Skype Case. European Management Journal, 24, pp. 174– 88. Rice, M.P., Leifer, R. and Colarelli O’Connor, G. (2002) Commercializing Discontinuous Innovations: Bridging the Gap from Discontinuous Innovation Project to Operations. IEEE Transactions on Engineering Management, 49, 330– 40. Romanelli, E. and Tushman, M.L. (1994) Organizational Transformation as Punctuated Equilibrium: An Empirical Test. Academy of Management Journal, 37, 1141–66. Sanderson, S. and Uzumeri, M. (1995) Managing Product Families: The Case of the Sony Walkman. Research Policy, 24, 761–82. Schonberger, R.J. and Knod, E.M., Jr. (1997) Operations Management. Customer-Focused Principles. McGraw-Hill, New York. Senge, P.M. (1990) The Fifth Discipline. The Art and Practice of the Learning Organization. Doubleday, New York. Skinner, W. (1974) The Focused Factory. Harvard Business Review, 52, 113–21. Soosay, C.A. and Hyland, P.W. (2006) Knowledge Exploration and Exploitation: The Absorptive Capacity for Continuous Innovation. 7th International CINet Conference ‘CI and Sustainability – Designing the Road Ahead’, Lucca, Italy, 8–12 September, pp. 734–45. Spina, G., Bartezzaghi, E., Bert, A., Cagliano, R., Draaijer, D.J. and Boer, H. (1996) Strategically Flexible Production: The Multi-Focused Manufacturing Paradigm. International Journal of Operations & Production Management, 16, 20– 41. Stock, G.N., Greis, N.P. and Kasarda, J.D. (2000) Enterprise Logistics and Supply Chain Structure: The Role of Fit. Journal of Operation Managent, 18, 531–47. Takeuchi, H. and Nonaka, I. (1986) The New Product Development Game. Harvard Business Review, 86, 137–46. Teece, D.J. (1986) Profiting from Technological Innovations: Implications for Integrations. Research Policy, 15, 285–305. Teece, D.J., Pisano, G. and Shuen, A. (1997) Dynamic Capabilities and Strategic Management. Strategic Management Journal, 18, 509–53. Tripsas, M. and Gavetti, G. (2000) Capabilities, Cognition and Inertia: Evidence from Digital Imaging. Strategic Management Journal, 21, 1147– 61. Tushman, M. and Anderson, P. (1986) Technological Discontinuities and Organizational Environments. Administrative Science Quarterly, 31, 439– 65. Tushman, M. and O’Reilly, C.A. (1996) Ambidextrous Organizations: Managing Evolutionary and Revolutionary Change. California Management Review, 38, pp. 8–30. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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Tushman, M.L. and Romanelli, E. (1985) Organizational Evolution: A Metamorphosis Model of Convergence and Reorentation. In Cummings, L.L. and Staw, B.M. (eds.), Research in Organizational Behavior, Vol. 7. LAI Press, Greenwich, CT, pp. 171–222. Utterback, J. (1994) Mastering the Dynamics of Innovation. Harvard Business School Press, Boston, MA. Verganti, R., MacCormack, A. and Iansiti, M. (1998) Rapid Learning and Adaptation in Product Development: An Empirical Study on the Internet Software Industry. EIASM 5th International Product Development Management Conference, Como, Italy, 25–26 May. Wheelwright, S.C. and Clark, K.B. (1992) Creating Project Plans to Focus Product Development. Harvard Business Review, 70, 71–82. Wheelwright, S.C. and Sasser, W.E. (1989) The New Product Development Map. Harvard Business Review, 67, 112–25. Witter, J., Clausing, D., Laufenberg, L. and Soares de Andrade, R. (1994) Reusability – The Key to Corporate Agility. 2nd International Product Development Management Conference on New Approaches to Development and Engineering, EIASM, Göteborg, 30–31 May.
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Mariano Corso (
[email protected]) is Full Professor of Organization and Human Resources at Politecnico di Milano where he chairs the course in Management Engineering at the Cremona site. At the MIP, the Business School of Politecnico di Milano, he is director of the Masters in Management and Organization Development and of the Observatories on Enterprise2.0, ICT Strategic Sourcing and ICT Strategy and Governance. He has promoted and co-ordinated national and international research on Knowledge Management. He is author of more than 100 publications at the international level. Luisa Pellegrini (luisa.pellegrini@dsea. unipi.it) is Associate Professor of Management Engineering at the faculty of Engineering, University of Pisa where she teaches Innovation Management and Business Economics and Organisation. She is actively involved in national and international research projects on Knowledge Management and Continuous Innovation. She is member of the Continuous Innovation Network (CINet) and author of more than 40 international publications.
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Convergence or National Specificity? Testing the CI Maturity Model across Multiple Countries Mandar Dabhilkar, Lars Bengtsson and John Bessant This study empirically tests the Continuous Improvement (CI) maturity model across multiple countries. The analysis is based on data from the 2nd International CINet Survey, limited to the situation in Australia, Italy, the Netherlands, Spain, Sweden and the United Kingdom. Despite some differences in Continuous Improvement maturity level between countries, findings lend support to the convergence argument. Regardless of national specificity, Continuous Improvement behaviour patterns emerge in a similar fashion, and furthermore, correspond to improved operational performance if adopted. In addition, findings show that other contextual variables such as company size and type of production system are of limited importance. This implies that Continuous Improvement is something that can be implemented and developed successfully if managed properly, irrespective of contextual influences such as those stemming from cultural and industrial factors.
Introduction
C
ontinuous Improvement (CI), a core principle of the Total Quality Management (TQM) approach, is today commonly recognized and practised in industrial firms all over the world (Sila & Ebrahimpour, 2002). However, both the popular press and academic journals have published numerous accounts describing examples of CI implementation, subsumed under the heading of TQM, which have experienced varying degrees of success (e.g., Keating et al., 1999; Beer, 2003; Yeung, Cheng & Lai, 2006). A major reason why TQM implementations often run out of steam is the heavy focus on CI tools and techniques, neglecting how CI behaviour patterns emerge in the workplace. In order to overcome shortcomings of the tools- and techniquecentred TQM approaches, Bessant and Caffyn (1997) have proposed the CI maturity model. The model illustrates how organizations can progress towards higher CI maturity levels by acquiring, practising and repeating CI behaviours until they become ingrained as ‘the way we do things around here’ and form an integral part of the culture of the organization (Bessant & Caffyn, 1997). The advantage of this emphasis is that it brings insight
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into how CI maturity can be developed in an organization. The general idea is to provide a framework for assessing the maturity level but also, and more importantly, to specify the kind of behaviours that need to be further developed. Until now, few studies have empirically tested the premises of the CI maturity model. In an implementation case study, De Jager et al. (2004) found the model valid, and the study reported significant performance benefits for the case company. The 1st International CI Survey was launched in the mid 1990s. It identified broad differences between groups of companies classified by their CI maturity. However, a far less developed version of the CI maturity model was used at this time and this is one of the reasons for the second round of the survey. The 2nd International CI survey was more directly based on the constructs of Bessant and Caffyn’s (1997) CI maturity model. Several studies have used the dataset to analyse CI activities in the participating countries (e.g., Albors & Hervás, 2007; Corso et al., 2007; Dabhilkar & Bengtsson, 2007; Hyland, Mellor & Sloan, 2007; Middel, op de Weegh & Gieskes, 2007; Readman & Bessant, 2007). An overview of selected results is given in the work by Sloan and Boer (2007). © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
CONVERGENCE OR NATIONAL SPECIFICITY?
However, so far only two studies have taken the opportunity to test the CI maturity model quantitatively. Using Swedish data, Dabhilkar and Bengtsson (2007) showed by multiple regression analysis that enhancement of CI maturity level significantly explained improvements in operational performance, working conditions and customer satisfaction. Recently, Jørgensen, Boer and Timenes Laugen (2006) have also used the aggregated survey data from the 2nd CI survey and confirmed that each prescribed group of CI behaviours was positively related to operational performance. However, this study did not analyse in detail the different CI maturity levels described by the model. Furthermore, as the study used aggregated data, it may cover important differences in CI practices reported earlier in the nation-specific studies. While there is still need for additional tests of the CI maturity model, a remaining question on the reliability and validity of the model also concerns the robustness of national differences. That is, to what extent do the constituent behaviour patterns of the CI maturity model converge across national borders, or are there country-specific differences? The overall purpose of this study is twofold. First, the study sets out to empirically test the CI maturity model by means of a large scale survey, i.e., the 2nd International CI Survey. The second purpose is to analyse whether the premises of the CI maturity model are culturally bound or transcend national borders. The analysis is restricted to countries represented in the 2nd International CI Survey by more than 50 observations, i.e., Australia, Italy, the Netherlands, Spain, Sweden and the United Kingdom. While the first purpose is interesting from a model development point of view, the second purpose relates to the debate on convergence versus national specificity in management practice. In particular, it concerns whether TQM is a universal approach applicable across nations and cultures, or if national specificity considerably affects its effectiveness (Rungtusanatham et al., 2005). As an example, Dahlgaard et al. (1998) found clear differences in TQM implementation between organizations in Western and Eastern countries. The Western companies lagged their counterparts in the East in issues like formulation of a quality policy, communicating its content to all employees in the organization, resources used for quality training per employee, participation of top managers in quality audits, quality motivation and quality suggestions, and the use and variety of quality tools and methods. In contrast to many other studies, Rungtusanatham et al. (2005), however, found preliminary evi© 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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dence that TQM practices possibly can follow indistinguishable patterns, i.e., support for the universality of TQM. In their study they compared Deming-based TQM constructs across German, Italian, Japanese and US plants. Our study is limited to six countries: five European countries and Australia. This limitation to a comparison between rather few countries is common to most TQM-related survey studies (Sila & Ebrahimpour, 2002). We would, of course, expect larger differences in CI practices if we had been able to include firms from Asia or the United States. This is open for further research. However, according to results from project GLOBE (House et al., 2002) on culture and leadership in 61 countries, even the countries represented in our dataset display important differences. According to Dickson, Den Hartog & Mitchelson (2003), the six countries in our study belong to four different kinds of culture and leadership clusters: Nordic Europe (Sweden), Germanic Europe (the Netherlands), Latin Europe (Italy, Spain) and Anglo (the UK and Australia). It is therefore highly relevant to analyse whether the behaviours of the CI maturity model show similar and convergent patterns across the countries in our sample, or if we can detect important national specifics.
The CI Maturity Model The CI maturity model was developed at the University of Brighton during a ten-year, industry-based research programme. Over 100 organizations participated in experiencesharing research aimed at improving the understanding and practice of CI. A detailed description of the model, as well as how it was developed, can be found in Bessant & Caffyn (1997) and Caffyn (1998). The term ‘continuous improvement’ means a continuous stream of high-involvement, incremental changes in products and processes for enhanced business performance. However, in order to fully exploit the potential of the maturity model, it is important to switch from regarding CI as a binary state to considering how CI emerges in the workplace. In particular, CI must be regarded as a bundle of routines which can help the organization improve what it currently does. Thus, CI can be practised with various levels of impact on business performance. The CI maturity model asserts five different capability levels (Bessant & Caffyn, 1997). 1. Pre-CI. There is no formal CI structure, problem solving is random, and the dominant mode of problem solving is by specialists.
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2. Structured CI. There are formal attempts to create and sustain CI, and a formal problem-solving process is used, supported by basic CI tools. CI is often parallel to operations. 3. Goal-oriented CI. All of stage 2, plus formal deployment of strategic goals and monitoring and measurement of CI against these goals. 4. Proactive/empowered CI. All of stage 3, plus the responsibility for CI is devolved to the problem-solving units. 5. Full CI (The Learning Organization). CI has become a dominant way of life, involving everyone in the organization. Learning is automatically captured and shared. Another important term to define is ‘ability’. The maturity model is made up of six CI abilities (Bessant & Caffyn, 1997). Companies enhance their CI capability by developing these abilities. Each ability is made up of a specific cluster of behaviours which reinforce each other. Developing an ability implies changes in its constituent behaviours. The model is made up of 32 behaviours. Details on each ability and its behaviours are given later in Table 5. In summary, enhanced CI capability results from developed abilities, which are all about changing organizational behaviours.
Convergence or National Specificity? An important source of inspiration in testing the CI maturity model across multiple countries comes from the seminal work of Rungtusanatham et al. (2005). In their effort to test the universality of TQM, they also developed the notion of convergence versus national specificity arguments in operations management, which is briefly summarized here. According to Rungtusanatham et al. (2005) the convergence argument posits that the complexity of modern technology leaves little managerial discretion in terms of structuring work and practices. Consequently, as technology evolves and spreads, organizations would need to structure their operations in similar ways if they are to be efficient and effective. The national specificity argument, in contrast, views technology and its implementation as embedded in the social context of the nation. As such, any organizational practice must, therefore, be adapted to the social context to maximize its effectiveness resulting, in turn, in the observed divergence of practices across nations. Therefore, whereas the convergence argument could explain
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how and why organizations adopting TQM should converge across different cultures, the national specificity argument explains how and why cross-national differences would impede the applicability of TQM within organizations. In contrast to Hofstede (1980), who asserts that management theory and practice are culturally bound, Rungtusanatham et al. (2005) argue that this statement is too strong and too general, particularly in the case of TQM. Their empirical investigation demonstrates that TQM is a comprehensive management paradigm with many definitional elements and relationships that appear to transcend cultural and national boundaries. Results of the 1st International CI Survey also favour the convergence argument. This article has so far only discussed results from the second round of the survey, but important contributions with regard to convergence versus national specificity were also made in the first round. While a less developed and different classification of CI maturity was used in the first round, i.e., Laggards, Late adopters, Early adopters and CI innovators, it was concluded that national specificity had only limited influence on CI practices and performance, whilst CI maturity had a much stronger impact (Gieskes et al., 2000). However, when comparing clusters of countries with similar cultural characteristics, some differences emerged in the way CI was organized. For example, starting with the assumption that the Nordic countries have low power distance between managers and employees led to the finding that these countries actually embarked on a more empowering and participatory style of CI (Martinsuo & Smeds, 2000). On the whole, though, little evidence was found supporting the theory that national culture or infrastructure has a dominant effect on the implementation of CI within industrial firms. The broad differences identified between groups of firms classified by their CI maturity were, however, of great significance (Boer et al., 2000).
Hypotheses With this article we try to add to current research on convergence versus national specificity issues in operations management by testing the validity of the CI maturity model across multiple countries. In line with the study on TQM by Rungtusanatham et al. (2005), as well as the findings of the 1st International CI survey (Boer et al., 2000), we expect that the premises, i.e., definitional elements and theoretical relationships, of the CI © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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maturity model transcend cultural and national boundaries. For example, the CI maturity model consists of six reliable and uni-dimensional CI abilities, as in Table 5 or Bessant and Caffyn (1997, pp. 19–20). CI is practised on five different capability levels, and increases in CI maturity correspond to improved operating performance (Bessant & Caffyn, 1997). We test these assumptions according to the following three sets of hypotheses: H1a The CI maturity model consists of six reliable and valid CI abilities. H1b CI abilities form a similar pattern regardless of national specificity. H2a CI is practised on five different maturity levels. H2b The classification into different CI maturity levels is not dependent on national specificity. H3a Increases in CI maturity, in terms of adoption of CI behaviours, will correspond to improvements in operating performance. H3b Increases in CI maturity will correspond to improvements in operating performance regardless of national specificity.
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Table 1. Participating Countries Country Australia (AU) Italy (IT) Netherlands (NTH) Spain (SP) Sweden (SWE) United Kingdom (UK) Total
N 89 60 51 105 77 70 452
Operationalizing Improved Operating Performance In line with Slack et al. (2006), five different aspects of operating performance were measured: flexibility, quality, dependability, speed and cost. The question in the survey instrument was posed as follows: To what extent has continuous improvement contributed to the following areas of business performance over the last three years? An index/composite measure was created, as shown in Table 2, where details on scale reliability are also given.
Data Collection In order to test the hypotheses we used data from the 2nd International CINet Survey. Data collection was conducted in 2004 and included data from 2003 relating to a whole range of CI-related issues. The survey was developed by an international research consortium, and comprises data from 543 manufacturing companies in 10 countries in Asia, Australia and Europe. However, Norway (N = 14), Ireland (N = 21), Hong Kong (N = 29) and Switzerland (N = 27) provided insufficient sample sizes and have therefore been removed from the analysis. Only countries with more than 50 observations were selected (Table 1).
Operationalizing the CI Maturity Model To measure the level and use of CI behaviours, the respondents were asked to indicate to what extent they agreed or disagreed with 32 formulated statements related to CI activities. The statements are based on the constituent behaviours of Bessant and Caffyn (1997, pp. 19–20) and can be found in Table 5 in this article. All statements were measured on a five-point Likert scale to indicate the degree to which the described behaviours were present in the organization. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
Control Variables Jørgensen, Boer and Timenes Laugen (2006), who previously analysed the same dataset as we do in this study, showed the importance of including contextual control variables: CI importance, company size and production process type. Following their example we assessed: • CI importance according to the responses to the CINet Survey item ‘How would you rate the overall importance of continuous improvement in your business unit? 1 = Not important, 2 = Of minor importance, 3 = Of operational importance, 4 = Of strategic importance, 5 = Vital’. • Company size according to the responses to the item ‘How many employees are there in the company?’ • Production process type according to the item ‘How would you describe the production system for your business unit’s most important product line? 1 = Project, 2 = Job shop, 3 = Batch, 4 = Line, 5 = Continuous’. Since our analysis focused on comparisons across multiple countries, we also had to add a set of control variables that assessed differences between countries. We used dummy
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Table 2. Dependent Variable – Improved Operational Performance Variable Flexibility – improved production volumes Quality – improved quality conformance Dependability – improved delivery reliability Speed – reduced lead times Cost – reduced cost X Eigenvalue = 2.7 (55) (Variance explained) Cronbach’s a = 0.79
Mean
Standard deviation
Factor loading
3.26 3.91 3.47 3.17 3.40 3.44
1.12 0.93 1.08 1.07 1.01 0.77
0.67 0.67 0.79 0.79 0.76
Table 3. Scale Reliability – Cronbach’s a Cronbach’s a
N
A – Getting the CI habit B – Focusing CI C – Spreading the word D – CI on the CI system E – Leading the way F – Building the learning organization
6 5 6 3 5 7
variables following the example in Field (2005, p. 208). Dummy coding is a way of representing groups of observations using only zeros and ones. To do this, we had to create several variables. The number of variables needed is one less than the number of groups we are recoding. In our case we had six countries and therefore five dummy variables were created.
Empirical Results Factor Analysis Results – Testing H1 Exploratory factor analysis with Varimax rotation was used to test Hypothesis 1. Results are given in Tables 3, 4 and 5. Behaviours that constituted a prior ability according to the work of Bessant and Caffyn (1997) were subjected to analysis, first by analysing the whole dataset, and then by analysing each country individually. Overall, this analytical procedure found six reliable and valid CI abilities as hypothesized.
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Total
AU
IT
NTH
SP
SWE
UK
0.83 0.85 0.85 0.78 0.85 0.87
0.79 0.83 0.82 0.77 0.79 0.83
0.83 0.86 0.86 0.80 0.88 0.91
0.83 0.82 0.86 0.71 0.86 0.87
0.89 0.86 0.89 0.85 0.89 0.87
0.77 0.85 0.84 0.75 0.77 0.80
0.80 0.83 0.81 0.72 0.85 0.87
However, this procedure also revealed two interesting findings from a model development point of view. A close comparison between Bessant and Caffyn (1997, pp. 19–20) and Table 5 reveal two major differences and some minor differences. First, all items that concerned the role of managers in CI ability A (Bessant & Caffyn, 1997, p. 19) loaded together on a separate factor when the factor analysis was broken down on a country level. A new CI ability (Leading the way) was therefore created (CI ability E in Table 5) following the example in Bessant, Caffyn and Gallagher (2001). Second, when Cronbach’s a was computed for CI ability E (Walking the talk) in Bessant and Caffyn (1997, p. 20) on a country level, this construct was not found reliable. Two countries scored at the 0.4 level and the remaining four countries around the 0.6 level. As a consequence the original CI ability Walking the talk (Bessant & Caffyn, 1997, p. 20) was replaced with the new CI ability Leading the way as shown in Table 5. The minor differences concerned six items that were phrased differently to Bessant and Caffyn (1997) or not © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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Table 4. Scale Validity – First Eigenvalues and Percent of Variance Explained First eigenvalue (% variance)
A – Getting the CI habit B – Focusing CI C – Spreading the word D – CI on the CI system E – Leading the way F – Building the learning organization
Total
AU
IT
NTH
SP
SWE
UK
3.3 (55) 3.1 (62) 3.5 (58) 2.1 (70) 3.2 (65) 3.9 (56)
3.1 (51) 3.0 (59) 3.2 (53) 2.1 (69) 2.9 (57) 3.5 (49)
3.3 (55) 3.2 (64) 3.5 (59) 2.2 (72) 3.6 (72) 4.5 (64)
3.2 (53) 2.9 (59) 3.6 (59) 1.9 (64) 3.2 (65) 3.9 (56)
3.8 (64) 3.2 (63) 3.9 (64) 2.3 (77) 3.5 (70) 4.0 (57)
3.0 (50)* 3.1 (61) 3.3 (56) 2.0 (67) 2.8 (57) 3.4 (49)
3.2 (53) 3.0 (60) 3.0 (51) 2.0 (67) 3.3 (66) 4.0 (57)
Note: * Second eigenvalue = 1.16 (19).
present in the survey instrument and as a consequence omitted from data analysis.1 1
The term ‘organization’ was used rather than ‘managers’ as in Bessant & Caffyn (1997, p. 19) for the item The organization recognizes in formal but not necessarily financial ways the contribution of employees to continuous improvement in CI ability E (Leading the way) in Table 5. Four items from CI ability D in Bessant & Caffyn (1997, p. 20) were omitted: 1. The CI system is continually monitored and developed. A designated individual or group monitors the CI system and measures the incidence (i.e., frequency and location) of CI activity and the results of CI activity. 2. There is a cyclical planning process whereby the CI system is regularly reviewed and, if necessary, amended (single-loop learning). 3. The individual/group responsible for designing the CI system designs it to fit within the current structure and infrastructure. 4. Individuals with responsibility for particular company processes/systems hold regular reviews to assess whether these processes/systems and the CI system remain compatible. The item The ‘management style’ reflects commitment to CI values in CI ability E in Bessant and Caffyn (1997, p. 20) was phrased Managers at all levels display leadership and active commitment to ongoing improvement in the instrument and can now be found as the last behaviour of CI ability E (Leading the way) in Table 5. The item When something goes wrong the natural reaction of people at all levels is to look for reasons why rather than to blame the individual(s) involved in CI ability E in Bessant and Caffyn (1997, p. 20) has been redirected as the last item of CI ability A (Getting the CI habit) in Table 5. The item People at all levels demonstrate a shared belief in the value of small steps and that everyone can contribute, by themselves being actively involved in making and recognizing incremental improvements from CI ability E in Bessant and Caffyn (1997, p. 20) was omitted.
© 2007 The Authors Journal compilation © 2007 Blackwell Publishing
Reliability assessment was performed by computing Cronbach’s a for each CI ability, for the total dataset as well as by each country. Cronbach’s a is a reliability estimate for measurement scales, with 0.60 being the suggested lower bound value (Nunnally, 1967). A multiple-item measurement scale, whose Cronbach’s a is less than 0.60, would therefore not be regarded as reliable. Table 3 shows the result of the performed analysis. The six CI abilities appear to be reliable (0.71 ⱕ Cronbach’s a ⱕ 0.91). Validity assessment was performed by examining the dimensionality of each CI ability, for the total dataset as well as by each country. According to Rungtusanatham et al. (2005), demonstrating that a multiple-item measurement scale is uni-dimensional is one type of evidence indicative of construct validity. In the context of factor analysis, a measurement scale is uni-dimensional when the second eigenvalue is less than 1.00 and when factor loadings for constituent measurement items are greater than 0.30. Table 4 shows first eigenvalues as well as the percent of variance explained by the derived factors. The six CI abilities appear to be valid (only one factor was derived when constituent behaviours were subjected to analysis). There is one exception regarding CI ability A (Getting the CI habit) for the Swedish dataset. The item Ideas and suggestions for improvement are responded to in a clearly defined and timely fashion – either implemented or otherwise dealt with loaded on a second factor. A mistake seems to be the reason for this deviation. When the instrument was translated into Swedish, the word ‘suggestion system’ was mistakenly used. A retrospective back translation would read Ideas and suggestions are responded to by a well structured and time effective suggestion system. Using the term ‘suggestion
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Focusing CI
B
Generating and sustaining the ability to link CI activities to the strategic goals of the company
Getting the CI habit Developing the ability to generate sustained involvement in CI
A
Organizational ability
Individuals and groups use the organization’s strategy and objectives to focus and prioritize their improvement activities Everyone understands what the company’s or their department’s strategy, goals and objectives are Before embarking on initial investigation and before implementing a solution, individuals and groups assess the improvements they proposed against strategic objectives to ensure consistency Individuals and groups monitor/measure the results of their improvement activity and their impact on strategic or departmental objectives Improvement is an integral part of the individuals’ or groups’ work, not a parallel activity
People make use of some formal problem finding and solving cycle People use appropriate tools and techniques to support their improvement activities People use measurement to shape the improvement process People (individuals/groups) initiate, and carry through to completion, improvement activities – they participate in the process Ideas and suggestions for improvement are responded to in a clearly defined and timely fashion – either implemented or otherwise dealt with When something goes wrong the natural reaction of people at all levels is to look for reasons why rather than to blame the individual(s) involved
Constituent behaviours
Table 5. Factor Scores for CI Abilities and Constituent Behaviours (Based on Bessant & Caffyn, 1997)
0.772 0.728
0.440
0.673
0.762 0.784
0.650
0.644
0.776 0.770
0.808
0.724
0.750 0.773
0.835
0.756
0.764
0.852
0.846
0.804
0.743
AU
0.761
Total
0.772
0.853
0.824
0.693
0.854
0.563
0.747
0.610 0.869
0.874
0.750
IT
0.680
0.862
0.806
0.744
0.723
0.652
0.721
0.734 0.702
0.780
0.783
NTH
SWE
UK
0.796 0.747 0.771
0.834 0.788 0.840
0.714 0.761 0.789
0.782 0.782 0.685
0.845 0.833 0.780
0.761 0.713 0.440
0.805 0.110* 0.719
0.780 0.805 0.791 0.825 0.755 0.774
0.842 0.769 0.919
0.784 0.828 0.653
SP
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© 2007 The Authors Journal compilation © 2007 Blackwell Publishing
E
D
C
Generating the ability to lead, direct and support the creation of and sustaining of CI behaviours
Leading the way
Generating the ability to manage strategically the development of CI
CI on the CI system
Generating the ability to move CI activity across organizational boundaries
Spreading the word
Individuals and groups are effectively working across internal (vertical and lateral) and external divisions at all levels People understand and feel ownership of the company’s processes People are oriented towards internal and external customers in their improvement activity Specific improvement projects are taking place with customers and/or suppliers Relevant improvement activities involve representatives from different operational levels The organization uses supplier and customer feedback as a means to improve company performance Ongoing assessment ensures that the organization’s processes, structure and systems consistently support and reinforce improvement activities Senior management make available sufficient resources (time, money, personnel) to support the continuing development of the company’s improvement system When a major organizational change is planned, its potential impact on the organization’s improvement system is assessed and adjustments are made as necessary Managers support improvement processes by allocating sufficient time, money, space and other resources The organization recognizes in formal but not necessarily financial ways the contribution of employees to continuous improvement Managers lead by example, becoming actively involved in the design and implementation of systematic ongoing improvement Managers support experimentation by not punishing mistakes, but by encouraging learning from them Managers at all levels display leadership and active commitment to ongoing improvement 0.761
0.809
0.844
0.877
0.881
0.882
0.485
0.752 0.596
0.822
0.828
0.834
0.748
0.747
0.807
0.752
0.797
0.820
0.775
0.753
0.864
0.779
0.809
0.854
0.714
0.599
0.744
0.714
0.928
0.821
0.921
0.655
0.882
0.850
0.879
0.809
0.764
0.811
0.794
0.766
0.787
0.677
0.856
0.733
0.857
0.805
0.766
0.767
0.776
0.847
0.761
0.877
0.689
0.827
0.798
0.651
0.924 0.837 0.874
0.826 0.835 0.863
0.877 0.870 0.897
0.668 0.334 0.477
0.858 0.760 0.868
0.905 0.841 0.736
0.855 0.755 0.832
0.864 0.855 0.877
0.781 0.704 0.688
0.829 0.727 0.737
0.770 0.759 0.672
0.834 0.839 0.739
0.782 0.690 0.696
0.809 0.743 0.733
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Generating the ability to learn through CI activity
Building the learning organization
Everyone learns from their experiences, both good and bad Individuals seek out opportunities for learning/personal development (e.g., active experimentation, setting own learning objectives) Individuals and groups at all levels share (make available) their learning from all work and improvement experiences The organization articulates and consolidates (captures and shares) the learning of individuals and groups Managers accept and, where necessary, act on all the learning that takes place People and teams ensure that their learning is incorporated into the organization by making use of the mechanisms provided for that Appropriate organizational mechanisms are used to deploy what has been learned across the organization
Constituent behaviours
Note: * Loading on this item on the second factor 0.940.
F
Organizational ability
Table 5. continued
0.756
0.704
0.744
0.777
0.738
0.746
0.788
0.819
0.621
0.669 0.629
AU
0.775
0.659 0.697
Total
0.812
0.896
0.851
0.804
0.837
0.572 0.778
IT
0.789
0.789
0.696
0.786
0.824
0.669 0.651
NTH
SWE
UK
0.620 0.562 0.716
0.833 0.826 0.806
0.813 0.692 0.807
0.800 0.773 0.813
0.783 0.739 0.782
0.665 0.691 0.625 0.749 0.560 0.693
SP
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divide the sample of the 1st International CI Survey into four different groups of CI maturity: Laggards, Late adopters, Early adopters and CI innovators. Furthermore, the groups in Gieskes et al. (2000) are similar to the clusters of CI maturity identified in our analysis, in the sense that they also show evidence of a linear progression in maturity across the six CI abilities. In summary, we find partial support for Hypothesis 1a. There are a certain number of distinct maturity levels. The exact number, though, is still an open question. In order to test whether CI maturity is dependent on national specificity, clusters and countries were cross-tabulated as shown in Table 7. Results are in favour of the convergence hypothesis, even though some minor differences between countries exist. All countries are represented across all clusters in a relatively similar fashion, except for Cluster 4. While Spain is overrepresented, Australia, the Netherlands and Sweden have fewer observations in this cluster than expected. Rather than suggesting that Spanish business culture facilitates higher CI maturity levels, we speculate that the identified differences for Cluster 4 are caused by differences in sampling techniques. The Spanish sample was drawn from various public and private databases, which collected a population of firms already interested in the practice of quality procedures (Albors & Hervás, 2007, p. 335), while the Swedish survey, for example, targeted a representative sample of the Swedish manufacturing sector (Dabhilkar & Bengtsson, 2007, p. 278).
system’ may have led Swedish respondents to think about the old-fashioned suggestion box. We speculate that if this item was properly translated in the first place, all constituent behaviours of this CI ability for the Swedish dataset would load on the same factor. Table 5 shows factor loadings for the behaviours constituting each CI ability. The six CI abilities also appear to be valid from a factorloading point of view (factor loadings > 0.30). As outlined above, Sweden naturally deviates regarding CI ability A (Getting the CI habit). Based on the same line of reasoning, this is not considered problematic.
Cluster Analysis Results – Testing H2 The TwoStep cluster analysis function of SPSS was used to test Hypothesis 2. It is an exploratory tool designed to reveal natural groupings (or clusters) within a dataset. By comparing the values of a model-choice criterion across different clustering solutions, the procedure automatically determines the optimal number of clusters. Overall, results partly support Hypothesis 2 and are shown in Table 6. While five clusters was the number hypothesized, in line with Bessant and Caffyn (1997, p. 18), Table 6 shows that there are four unique clusters of observations with respect to CI maturity in the dataset. Mean values are shown in Table 6. Post hoc analyses (ANOVA, Tamahane’s T2) also show that the differences in mean values across all four clusters are significantly different for every CI ability A–F (p < 0.001). It is interesting to note that, working manually rather than using statistical software, Gieskes et al. (2000) also found it useful to
Regression Results – Testing H3 Hypothesis 3 was tested using hierarchical regression analysis, with blocks of variables
Table 6. Results of Cluster Analysis Mean value (standard deviation)
A – Getting the CI habit** B – Focusing CI** C – Spreading the word** D – CI on the CI system** E – Leading the way** F – Building the learning organization** N
Cluster 1
Cluster 2
Cluster 3
Cluster 4
2.1 (0.5) 2.2 (0.5) 2.4 (0.5) 1.8 (0.6) 2.1 (0.5) 2.2 (0.5)
2.9 (0.3) 3.1 (0.5) 3.3 (0.4) 2.9 (0.5) 3.0 (0.5) 3.0 (0.3)
3.7 (0.3) 3.8 (0.4) 3.9 (0.4) 3.6 (0.4) 3.7 (0.4) 3.6 (0.3)
4.3 (0.4) 4.4 (0.4) 4.5 (0.3) 4.3 (0.4) 4.4 (0.4) 4.3 (0.4)
55
113
91
123
Total 3.4 (0.8) 3.5 (0.8) 3.7 (0.8) 3.3 (0.9) 3.4 (0.9) 3.4 (0.7) 382
Note: ** Differences in mean values across all four clusters are significantly different (p < 0.001). © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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Table 7. Cross-Tabulations for Clusters of CI Maturity by Country
Cluster 1 Cluster 2 Cluster 3 Cluster 4 Total
Count Expected Count Expected Count Expected Count Expected Count Expected
count count count count count
AU
IT
NTH
SP
SWE
UK
Total
7 12 25 24 34 26 15 19 81 81
10 8 14 16 15 17 14 13 53 53
8 6 17 13 14 14 4 10 43 43
13 15 20 31 32 34 40 25 105 105
14 9 27 19 16 21 7 15 64 64
3 5 10 11 12 12 11 9 36 36
55 55 113 113 123 123 91 91 382 382
entered sequentially. This approach facilitates the opportunity to control for the influence of contextual variables. As mentioned earlier, previous research has shown it important to control for CI importance, company size and production process type (Jørgensen, Boer & Timenes Laugen, 2006), and due to the nature of this study, we also have to control for the possible influence of national differences. Furthermore, outliers were detected. Five percent of the sample, that is 27 of 452 observations, had standardized residuals greater than 2 and were consequently removed from the analysis as suggested in Hair et al. (1998). Influential observations were also searched for but not found. According to Field (2005), Cook’s distance values > 1 and Mahalanobis distances > 25 are causes for concern. Finally, we checked for multicollinearity as suggested in Hair et al. (1998). This led us to create the CI maturity index used in the regression analysis shown in Table 8. The original plan was to enter the six CI abilities shown in Tables 3, 4 and 5 in a set. However, the six CI ability variables were found to be highly correlated. Therefore, a CI maturity index variable was created instead, where all 32 CI behaviours that constitute the six CI abilities were averaged. Overall, results of the regression analysis support Hypothesis 3 and are shown in Table 8. That is, organizations can expect improved operating performance in response to adoption of CI behaviours, regardless of national specificity. Standardized b-coefficients are reported along with summary statistics. Two-tailed t-tests were applied to the b-coefficients of the predictor variables. Models 1, 2 and 3 present the hierarchical addition of sets of items addressing contextual variables and CI maturity. Model 1 indicates
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that the first set of contextual variables explains 12% of the observed variance in improved operating performance. The model is statistically significant (p < 0.001). Analysing the standardized b-coefficients shows that, while ‘CI importance’ and ‘Production process type’ have a statistically significant impact, ‘Company size’ does not. This means that the contribution of CI to improved operational importance is dependent on how the overall importance of CI is rated in the organization. It also suggests that CI undertaken in production systems towards the ‘continuous’ type of the continuum, contrary to the ‘project’ type, contributes to a higher extent to improved operating performance. ‘Company size’ does not matter for the contribution of CI to improved operating performance. The addition of dummy variables, representing differences between countries, in Model 2 does not bring the amount of explained variance towards higher levels (Adj R2 = 12%; p-value of F statistic = 0.70). Addition of the CI maturity index in Model 3 brings the explained variance up to 33%. The increase in explained variance is highly significant (p < 0.001), as is the overall regression model (p < 0.001). While the first set of contextual variables follows the same pattern as in Model 1 and Model 2, the second set of contextual variables comes to life in Model 3. With regard to differences between countries, a similar pattern emerges in Model 3 as in Table 7, where clusters of CI maturity are cross-tabulated by country. The regression results indicate significant differences in operating performance, when Spain is compared to Australia, the Netherlands and Sweden, and as CI maturity is taken into consideration. This was expected since Spain has a greater number of observations with high CI maturity (Table 7). More important, however, is to © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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Table 8. Results of Multiple Regression Analysis Standardized b-coefficients
Step 1 CI importance Company size Production process type Step 2 SP vs AU SP vs IT SP vs NTH SP vs SWE SP vs UK Step 3 CI maturity index (CI behaviours/abilities A-F) R2 Adjusted R2 p-value of F statistic p-value of overall model
Model 1
Model 2
Model 3
0.33** 0.03 0.10*
0.33** 0.02 0.10*
0.16** -0.01 0.10*
0.13 0.12 <0.001 <0.001
0.04 -0.03 0.01 -0.04 -0.04
0.11* -0.02 0.10* 0.11* 0.01
0.14 0.12 0.70 <0.001
0.51** 0.35 0.33 <0.001 <0.001
Notes: Improvements in operating performance used as dependent variable. ** p < 0.001, * p < 0.05 (two-tailed).
compare the size of the standardized b-coefficients. The b-coefficients that indicate country differences are only at the 0.1 level and significant at the 5% level, whereas the b-coefficient for the CI maturity index, is at the 0.5 level and highly significant at the 0.1% level. Overall, this indicates that the CI maturity model is not culturally bound. The b-coefficient for the CI maturity index is at a far higher level when compared to country differences. Thus organizations can expect improved operating performance in response to adoption of CI behaviours regardless of national specificity.
Discussion There are two major findings of this study. First, the premises of the CI maturity model (Bessant & Caffyn, 1997) are found valid when tested with statistical data analysis based on a large-scale survey. So far, model development has been based mainly on qualitative research and it is interesting to see how these two research approaches come to the same conclusion. Second, the premises of the CI maturity model transcend cultural and national borders. In relation to the work of Rungtusan© 2007 The Authors Journal compilation © 2007 Blackwell Publishing
atham et al. (2005), which has shown that the Deming-based definition and theory of TQM converges across nations, this study comes to the same conclusion with regard to CI behaviour patterns. Empirical evidence for the two major findings of this study comes from testing three hypotheses, all of which were fully, or at least partially, supported. Full support was found for the first hypothesis, which concerned the reliability and validity of the CI abilities of the maturity model. Six reliable and valid CI abilities were found in line with the work of Bessant and Caffyn (1997, pp. 19–20), which furthermore are shown to transcend cultural and national borders. On a detailed level, the factor analysis also revealed that items on the role of management in CI constitute an ability on its own – Leading the way – in line with how the CI maturity model has developed (see, e.g., Bessant, Caffyn & Gallagher, 2001). This result comes from factor-analysing constituent behaviours of CI abilities by country. The aggregate data file covers differences like these because of the large sample size (N = 452). Partial support was found for the second hypothesis that concerned the exact number of CI maturity levels. While five levels were hypothesized, only four were identified in the
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dataset. From a strict statistical point of view, the hypothesis is partially supported and the exact number of CI maturity levels therefore remains an open question. As discussed in earlier sections of this article, the work of Gieskes et al. (2000) has also shown it to be useful to divide companies into four groups based on their CI maturity. Their work should therefore also be taken into consideration when this issue is clarified in further research. From a model testing standpoint, however, it is in our opinion more important to focus on a related premise of the CI maturity model, namely that of linear progression. While there is a difference in number of levels, our results show that maturity level grows in a linear fashion across all six CI abilities. The linearity issue is under debate in contemporary CI research. Case studies (e.g., Savolainen, 1999; Rijnders, 2002; Jørgensen, 2003) show that companies change CI behaviours in a much less linear fashion than proposed in the CI maturity model. Also, results of the surveybased study by Jørgensen, Boer and Timenes Laugen (2006) support a non-linear understanding of how CI maturity evolves by showing that changes in individual CI abilities can lead to improved performance as well. All these very important empirical studies, which support a non-linear understanding, have to be taken into consideration, and we suggest the following possible explanation that might explain our differences in results. In order to test for differences in CI ability across CI maturity clusters, analysis of variance was performed (ANOVA). The high level of significance (p < 0.001) indicates large differences between all clusters on all six CI abilities. However, this does not mean that the standard deviation is zero. The high level of significance suggests that the variation between the four clusters is greater than the variation within each cluster. This opens up the possibility of individual observations that follow alternative trajectories, although the main pattern of the sample is in the direction of a linear understanding. Moreover, there is another aspect of this issue from the viewpoint of managerial implications. Suppose now that an operations manager, who wishes to enhance her business unit’s CI maturity level, consults a researcher affiliated to the CINet. What would have happened if this researcher proposed something like: ‘Well, to start with, your business unit has to change on these 32 constituting continuous improvement behaviours, and in order to succeed, you will have to accomplish all of this at the same point in time starting right now!’. The researcher would most probably not be consulted again. It is important to acknowledge that organizations
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are unique, and therefore there must be room for alternative trajectories, although the main development path follows a similar pattern. At a certain point in time, some organizations may have logical reasons for consciously prioritizing the development of one or more CI abilities over others or this development may occur naturally due to certain conditions in a given organization. However, as it is shown that the six CI abilities are highly intercorrelated, focusing on one area while neglecting others may sacrifice overall development in the long run. The issue of CI progression, i.e., CI process theory, is thus an important future research area. With respect to the convergence versus national specificity issue, we find partial support for Hypothesis 2 as well. There are some minor differences. Spain is overrepresented in the highest CI maturity cluster. We speculate that the reason for this is sample bias, rather than suggesting that Spanish business culture facilitates higher CI maturity. The Spanish sample was drawn from various public and private databases, which collected a population of firms already interested in the practice of quality procedures (Albors & Hervás, 2007, p. 335), while the Swedish survey, for example, targeted a representative sample of the Swedish manufacturing sector (Dabhilkar & Bengtsson, 2007, p. 278). Thus, Hypothesis 2 is partially supported. Results support the convergence argument even though minor differences in actual level between countries exist. The premise that companies may be separated into different maturity levels is, however, valid. Finally, full support is found for Hypothesis 3. The regression analysis shows that organizations can expect improved operating performance in response to adoption of CI behaviours, regardless of national specificity. It is generally accepted that increases in CI maturity correspond to improvements in operational performance, although there are few studies that lend empirical support for this relationship (Jørgensen, Boer & Timenes Laugen, 2006; Dabhilkar & Bengtsson, 2007). Since the present study also controls for the influence of cultural and industrial factors, results show that successful implementation of CI is well within the reach of operations management.
Conclusions Using survey data, our empirical tests lend support to the premises of the CI maturity model. A development of the constituent CI behaviours is directly related to improved © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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operating performance. Firms that have obtained a higher CI maturity level show better operating performance than firms with less developed CI capabilities. While our study has shown that all groups of CI behaviours are important for performance, but also strongly inter-related, one interesting question for further research concerns the process of CI implementation. We furthermore conclude that despite some differences in CI maturity level between countries, our findings lend support to the convergence argument. Regardless of national specificity, CI behaviour patterns emerge in a similar fashion and, furthermore, correspond to improved operational performance if adopted. In addition, findings show that other contextual variables such as company size and type of production system are also of limited importance. This implies that CI is something that can be implemented and developed successfully if managed properly, irrespective of contextual influences such as those stemming from cultural and industrial factors. In view of this, the practical implications, managed properly, stand for changed organizational behaviour. The CI maturity model as proposed by Bessant and Caffyn (1997) is shown to be a valid and reliable tool for self assessment. Practitioners who wish to enhance their CI capability may well use the CI maturity model to identify strengths and weaknesses in order to accomplish changed organizational behaviour that leads to improved operational performance.
Acknowledgements The assistance of Henrik Borg at the University of Gävle in the early stages of this research project is greatly acknowledged. Furthermore the project has been financed by the Swedish Agency for Innovation Systems (VINNOVA).
References Albors, J. and Hervás, J.L. (2007) CI Practice in Spain: Its Role as a Strategic Tool for the Firm. Empirical Evidence from the CINet Survey Analysis. International Journal of Technology Management, 37, 332–47. Beer, M. (2003) Why Total Quality Management Programs Do Not Persist: The Role of Management Quality and Implications for Leading a TQM Transformation. Decision Sciences, 34, 623–42. Bessant, J. and Caffyn, S. (1997) High-Involvement Innovation through Continuous Improvement. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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International Journal of Technology Management, 14, 7–28. Bessant, J., Caffyn, S. and Gallagher, M. (2001) An Evolutionary Model of Continuous Improvement Behaviour. Technovation, 21, 67–77. Boer, H., Berger, A., Chapman, R. and Gertsen, F. (eds.) (2000) CI Changes: From Suggestion Box to Organisational Learning. Aldershot: Ashgate. Caffyn, S. (1998) Continuous Improvement in the New Product Development Process. Doctoral dissertation, University of Brighton, Brighton. Corso, M., Giacobbe, A., Martini, A. and Pellegrini, L. (2007) Tools and Abilities for Continuous Improvement: What Are the Drivers of Performance? International Journal of Technology Management, 37, 348–65. Dabhilkar, M. and Bengtsson, L. (2007) Continuous Improvement Capability in the Swedish Engineering Industry. International Journal of Technology Management, 37, 272–89. Dahlgaard, J.J., Kristensen, K., Kanji, G.K., Juhl, H.J. and Sohal, A.S. (1998) Quality Management Practices: A Comparative Study between East and West. International Journal of Quality & Reliability Management, 15, 812–26. De Jager, B., Minnie, C., De Jager, J., Welgemoed, M., Bessant, J. and Francis, D. (2004) Enabling Continuous Improvement: A Case Study of Implementation. Journal of Manufacturing Technology Management, 15, 315–24. Dickson, M.W., Den Hartog, D.N. and Mitchelson, J.K. (2003) Research on Leadership in a Crosscultural Context: Making Progress, and Raising New Questions. Leadership Quarterly, 14, 729–68. Field, A. (2005) Discovering Statistics using SPSS. Sage, London. Gieskes, J., Boer, H., Baudet, F.C.M. and Silano, M. (2000) Continuous Improvement in Europe and Australia: Do Location and CI Maturity Make a Difference? In Boer, H., Berger, A., Chapman, R. and Gertsen, F. (eds.), CI Changes: From Suggestion Box to Organisational Learning. Ashgate, Aldershot. Hair, J., Anderson, R.E., Tatham, R.L. and Black, W.C. (1998) Multivariate Data Analysis. PrenticeHall, Upper Saddle River, NJ. Hofstede, G. (1980) Motivation, Leadership, and Organisation – Do American Theories Apply Abroad. Organisational Dynamics, 9, 42–63. House, R., Javidan, M., Hanges, P. and Dorfman, P. (2002) Understanding Cultures and Implicit Leadership Theories across the Globe: An Introduction to Project GLOBE. Journal of World Business, 37, 3–10. Hyland, P.W., Mellor, R. and Sloan, T. (2007) Performance Measurement and Continuous Improvement: Are They Linked to Manufacturing Strategy? International Journal of Technology Management, 37, 237–46. Jørgensen, F. (2003) A Journey Through SelfAssessment, Learning, and Continuous Improvement. Doctoral dissertation, Aalborg University, Aalborg. Jørgensen, F., Boer, H. and Timenes Laugen, B. (2006) CI Implementation: An Empirical Test of the CI Maturity Model. Creativity and Innovation Management, 15, 328–37.
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Keating, E., Oliva, R., Repenning, N., Rockart, S. and Sterman, J. (1999) Overcoming the Improvement Paradox. European Management Journal, 17, 120–34. Martinsuo, M. and Smeds, R. (2000) Managing Continuous Improvement in Different Cultures. In Boer, H., Berger, A., Chapman, R. & Gertsen, F. (eds.), CI Changes: From Suggestion Box to Organisational Learning. Ashgate, Aldershot. Middel, R., op de Weegh, S. and Gieskes, J. (2007) Continuous Improvement in the Netherlands: A Survey-Based Study into Current Practices. International Journal of Technology Management, 37, 259–71. Nunnally, J.C. (1967) Psychometric Theory. McGrawHill, New York. Readman, J. and Bessant, J. (2007) What Challenges Lie Ahead for Improvement Programmes in the UK? Lessons from the CINet Continuous Improvement Survey 2003. International Journal of Technology Management, 37, 290–305. Rijnders, S. (2002) Four Routes to Continuous Improvement: An Empirical Typology of CI Implementation Processes. Doctoral dissertation, Twente University, Twente. Rungtusanatham, A., Forza, C., Koka, B.R., Salvador, F. and Nie, W. (2005) TQM across Multiple Countries: Convergence Hypothesis versus National Specificity Arguments. Journal of Operations Management, 23, 43–63. Savolainen, T. (1999) Cycles of Continuous Improvement: Realizing Competitive Advantages through Quality. International Journal of Operations & Production Management, 19, 1203–22. Sila, I. and Ebrahimpour, M. (2002) An Investigation of the Total Quality Management Survey Based Research Published between 1989 and 2000: A Literature Review. International Journal of Quality & Reliability Management, 19, 902–70. Slack, N., Chambers, S., Johnston, R. and Betts, A. (2006) Operations and Process Management: Principles and Practice for Strategic Impact. PrenticeHall, Harlow, England. Sloan, T. and Boer, H. (2007) Special Issue: Continuous Improvement – Status and Challenges – Introduction. International Journal of Technology Management, 37, 215–20. Yeung, A.C.L., Cheng, T.C.E. and Lai, K.H. (2006) An Operational and Institutional Perspective on Total Quality Management. Production and Operations Management, 15, 156–70.
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Mandar Dabhilkar (mandar.dabhilkar@ indek.kth.se) received his PhD from the Royal Institute of Technology in Stockholm (KTH) in December 2006, where he is currently Senior University Lecturer in Supply Chain Management. He received a BSc in Industrial Engineering and Management from the University of Gävle in Sweden in 2000, where he continued to work after graduation in several research projects financed by VINNOVA. His previous research has focused on several aspects of operations and supply chain management, such as control in team-organized manufacturing, balanced scorecard implementation, continuous improvement behaviour, work organization in lean production, and outsourcing manufacturing. Lars Bengtsson is Professor in Innovation Management in the Department of Industrial Engineering and Management at the University of Gävle in Sweden. He is also professor within a PhD school together with KTH in Stockholm. He holds an MSc in engineering physics and a PhD in industrial management and work science. He has (co-)authored several articles and books on the subjects of work organization, continuous improvements, manufacturing strategies and outsourcing. He currently leads a research group focusing on the significance of manufacturing competence, logistics management and outsourcing for innovation capability in industrial firms. Professor John Bessant, BSc, PhD, currently holds the Chair in Innovation and Technology Management at Tanaka Business School, Imperial College, where he is also Research Director. He previously worked at Cranfield, Brighton and Sussex Universities. In 2003 he was awarded a Senior Fellowship with the Advanced Institute for Management Research and was also elected a Fellow of the British Academy of Management. Author of 15 books and many articles, he has acted as advisor to various national governments and to international bodies including the United Nations, The World Bank and the OECD.
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Human Resource Management for Continuous Improvement Frances Jørgensen, Bjørge Timenes Laugen and Harry Boer This paper investigates the relationship between HRM practices and Continuous Improvement (CI) activities in order to gain an understanding of how the HRM function may be utilized to improve CI implementation success, and consequently, company performance. The paper begins with a brief review of the HRM and CI literature and then presents statistical analyses of data collected from the Continuous Improvement Network Survey (2003), which demonstrate that HRM has a significant effect on CI behaviour and company performance, with the strongest relationship between HRM, CI and performance occurring when companies align their CI activities with their strategic objectives and use systems, procedures and processes to measure the results of their CI activities.
Introduction
I
t is widely agreed that successful implementation of Continuous Improvement (CI) depends a great deal on involving members of the organization at all levels. However, there is surprisingly little literature on the human aspects of CI. As Human Resource Management (HRM) is generally associated with recruiting and hiring people with the appropriate knowledge and skills to accomplish the work tasks, it seems logical that HRM would also be involved with CI, at least in terms of securing a workforce capable of implementing CI. Moreover, since HRM often participates in the planning of employee training and development, companies should be able to capitalize on this function to continuously enhance individual and organizational CI capability. At present, there is little evidence that companies are aware of the importance of the HRM function for their CI efforts and/or how to realize the potential contribution of HRM to CI efforts in practice (Jørgensen & Hyland, 2007). One difficulty companies may face when attempting to support CI through HRM practices is in knowing which practices yield the greatest benefit in terms of CI development and, consequently, performance (Jørgensen & Hyland, 2007). A recent study conducted by Hyland et al. (forthcoming) indicates that companies involving the HRM department in © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
CI tend to have higher levels of CI maturity, but this and other studies stop short of identifying the capacity in which HRM is involved. Consequently, little is known regarding the types of employee behaviours that are influenced by HRM involvement or whether specific HRM practices have a greater or lesser influence on CI implementation, practices and performance. Thus, there is still much to learn about the role particular HRM mechanisms might play in CI development efforts aimed at achieving improved organizational performance. The aim of this paper, then, is to identify whether HRM-related practices are associated with successful CI implementation and if so, to what degree. In the next section, the literature on CI is reviewed to develop a better understanding of the types of knowledge, skills and behaviours considered necessary for successful CI implementation. Next, a brief introduction to HRM provides a general foundation for exploring the areas in which HRM could potentially be exploited to support CI. Thereafter, the results of statistical analyses of data derived from the 2nd Continuous Improvement Network (CINet) Survey (2003) are presented and discussed for the purpose of identifying relationships between HRMrelated practices, CI activities and performance effects. The paper concludes with specific recommendations for integrating
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HRM practices with CI activities that have demonstrated positive influences on company performance as well as directions for further research aimed at providing more insight into the role of HRM in supporting CI.
Continuous Improvement and Performance The term Continuous Improvement (CI) is used to refer to an organization-wide change initiative consisting of incremental improvements planned and implemented with existing resources (Boer et al., 2000). Ultimately, the reason companies implement CI is to improve their performance. Although it has long been assumed that successful CI implementation would affect various measures of company performance, there has been little empirical evidence to support a causal link between the two. Recently, however, statistical analyses of data from the 2nd CINet Survey revealed significant relationships between CI behaviours and the organization’s overall performance (Jørgensen, Boer & Laugen, 2006). Generally, it was shown that increased CI activity increases overall company performance and, specifically, these three measures of performance:
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strategic objectives through CI. However, a number of researchers have described how failure to fully understand CI may serve as a barrier to successful CI implementation (e.g., Schroeder & Robinson, 1991; Boer et al., 2000; Jørgensen, 2003), indicating that organizations may not orientate their employees well in this regard. Thus organizations may fail to realize performance improvement with CI. Another barrier to successful CI implementation mentioned in the literature involves the necessary skills and abilities employees must possess. Jørgensen, Nielsen and Kofoed (2005) suggest that sets of competencies can be described for both shopfloor employees and middle managers, including the use of CI tools (e.g., fishbone analysis, PDCA cycle); CI knowledge (as described above); project management (e.g., running effective meetings, planning and goal setting); team skills (e.g., conflict resolution, communication); and, leadership (primarily for managers). Furthermore, several personal attributes such as motivation, high energy levels and inspiration (i.e., ability to see opportunities) have been identified as being conducive to successful CI implementation. Bessant and Caffyn (1997) describe a number of individual, group and organizational CI capabilities that are consistent with the competencies listed here, with the addition of behavioural routines associated with learning, crossfunctional cooperation and organizational culture. Providing the organization with these competencies, in addition to supporting mechanisms to ensure their application, may easily be construed as partially or wholly within the realm of the HRM function, which is described in the following section.
• Speed/cost performance, including productivity, volume, lead time and reliability. • Relationship performance, including interdepartmental, customer and supplier relations and performance. • Organizational performance, including employee commitment and attitudes towards change, absenteeism, safety and well-being, organization, cooperation and communication, competency and skill development, and administrative routines.
Human Resource Management
Of these performance measures, organizational performance was shown to be most strongly affected by increased adoption of CI behaviours. In addition, the results of these analyses suggest that behaviours that seek to align the company’s strategic objectives with CI goals and the continued development of CI within the organization (i.e., strategic management of CI development) appear to have the strongest impact on speed/cost and organizational performance. These findings highlight a number of important issues regarding successful CI implementation. Most importantly, that CI implementation does in fact positively influence company performance. Specifically, these results emphasize the need for employees to have a thorough working knowledge of CI and their own role in supporting the company’s
The role of HRM can be viewed as encompassing little more than the most basic functions of personnel management such as recruitment, selection, training and perhaps labour negotiator to a critical strategic ally (Storey, 1992; Guest, 1997). One issue that complicates defining HRM and the functions for which HRM is responsible concerns the increasing decentralization or devolution of practices related to obtaining, training, developing, maintaining and sustaining a competent workforce (Hoogendoorn & Brewster, 1992; Brewster & Soderstrom, 1994). For the purposes of this paper, it is not especially relevant to consider who fulfils these functions, but rather how particular practices could support CI. Therefore, a somewhat broad definition of HRM is considered preferable, such as that offered by Beer et al. (1984, p. 1) as ‘all management decisions
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and activities that affect the nature of the relationship between the organization and its employees – the human resources’. Such a definition of HRM would ostensibly include the design and organization of tasks (e.g., job rotation, enrichment, multitasking, group work, quality); staffing (e.g., recruitment, assessment, selection, introduction, career development, education and training, termination, outplacement, retirement); performance measurement and compensation (appraisal, job evaluation, bonuses, employee ownership); and the channels for communication (e.g., performance feedback) and participation in work and decision making (participation, leadership, information and communication). Further, Beer et al. (1984) contend that HRM can and must strive to positively influence the development of the organizational context as a whole, which is consistent with the understanding of CI as a philosophy for change, rather than simply an isolated change initiative. Indeed, a number of studies have supported the notion that HRM can support organizational development, for example through encouraging learning and the establishment of learning environments conducive to change and development (e.g., Pearn, Roderick & Mulrooney, 1995; Walton, 1999; Langbert & Friedman, 2002; Maxwell, Quail & Watson, 2002; Laursen & Foss, 2003). However, although the economic and organizational benefits of utilizing the HRM function to enhance performance and support organizational change and development have been consistently demonstrated for several decades (e.g., Arthur, 1994; Becker & Gerhart, 1996; Wright, Gardner & Moynihan, 2003), the mechanisms and processes by which this occurs are not fully understood (Purcell et al., 2000). According to the resource-based approach to HRM (e.g., Barney, 1995), performance is enhanced through alignment of resources – both human and non-human – with business objectives. Guest (1997) developed a model that illustrates the link between HRM and business performance through strategic alignment (e.g., differentiation/ innovation, low cost). The general premise underlying these models is that, when linked to the organizational strategy, certain HRM practices, such as selection, training, appraisal, compensation, job design and employee involvement, lead to effects (e.g., motivation, commitment, cooperation, involvement, flexibility, organizational citizenship, reduced turnover and absenteeism) that in turn result in positive business outcomes in the form of increased productivity, quality, profit and customer satisfaction (e.g., Arthur, 1994; Becker & Gerhart, 1996; Wright, Gardner & Moynihan, © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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2003). Thus it appears that HRM has the potential to exert a positive influence on performance at individual and group level through a variety of mechanisms (e.g., recruitment, support of learning and development, compensation and rewards, job design). In addition, de Leede and Looise (2005) and Jørgensen, Hyland and Kofoed (forthcoming) suggest that HRM may potentially influence the organization as a whole, via systems, procedures and processes that support organizational development. These types of mechanisms would include, for example, resource allocation, top management support, organization-wide deployment of learning, strategically-aligned performance systems, and structures that integrate the organizational strategy with operational practices.
The Role of HRM in CI From this line of reasoning, business performance should improve through alignment of the organization’s HRM function with its CI strategy. There are indications that increased CI activity is associated with HRM involvement in the implementation of CI (Hyland et al., forthcoming), but the precise nature of this relationship is unknown. Specifically, it is not known which HRM practices are most beneficial in increasing CI activity nor how HRM practices aimed at supporting CI may influence performance. The question investigated in this article therefore is: ‘How and to what extent do HRM-related practices affect business performance through CI?’. The items and responses to the 2003 Continuous Innovation Network Survey (see next section for details) were used to further refine the research question and to formulate two working hypotheses to direct the analyses. The first hypothesis assumes HRM-related practices will indeed positively affect CI activity, as suggested by Hyland et al. (forthcoming) and Jørgensen, Boer and Laugen (2006), and in doing so, have a positive effect on business performance (e.g., Boer et al., 2000), which in this paper is defined according to three variables, namely: speed/cost performance, relationship performance and organizational performance, as described previously and in Jørgensen, Boer and Laugen (2006). H1: HRM-related practices have a positive effect on CI behaviours and, through that, business performance. Previous research on CI (e.g., Boer et al., 2000) has identified a number of potential barriers to successful CI implementation. On this basis, the second hypothesis is formulated as follows:
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H2: CI implementation problems will moderate the relationships between HRM practices, CI behaviours and business performance by either reducing or eliminating positive relationships or increasing negative relationships between these three variables. In the next section, the methodology used to research these hypotheses is presented.
the 1st survey (Middel et al., 2004). The survey tool was conducted as a postal questionnaire addressing the following: company characteristics; the structuring and organization of CI; the mechanisms, procedures, systems and practices used to support CI; and the performance effects of CI. The database comprises data from 543 manufacturing companies in the 11 countries involved.
Methodology
Variables and Data Analysis
Data Collection
We feel it is important to clarify the distinction between HRM mechanisms and CI behaviours to avoid any confusion in the remainder of this article. HRM mechanisms concern ‘all management decisions and activities that affect the nature of the relationship between the organization and its employees – the human resources’ (Beer et al., 1984). Some of these mechanisms may be focused on CI, but have a wider impact on, for example, organizational learning (e.g., introducing a formal CI system – see Table 1). Others may be more generic, but in effect create a suitable context that triggers and/or supports CI behaviours (e.g., managers support experimentation by not punishing mistakes, but by encouraging learning from
Data for the study were collected from responses to the 2nd CINet Survey, which was developed in 2003 by an international research consortium involving researchers from Australia, Denmark, Ireland, Italy, the Netherlands, Norway, Hong Kong, Spain, Sweden, Switzerland and the United Kingdom, and was administered by the Continuous Innovation Network (CINet). The objective of the survey was to explore the purposes and practices of organizations implementing CI-related activities. Further, the 2nd survey was intended to gain insight into the evolution of CI practices during the five year interim since
Table 1. People-Oriented HRM Mechanisms HRM mechanisms People-oriented
Variable description Job design
Middle management involvement Leadership
Middle management participation
Support of experimentation
Support of learning
Reward system
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Items from the questionnaire Improvement is an integral part of the individuals’ or groups’ work, not a parallel activity Managers accept and, where necessary, act on all the learning that takes place Managers at all levels display leadership and active commitment to ongoing improvement Managers lead by example, becoming actively involved in the design and implementation of systematic ongoing improvement Managers support experimentation by not punishing mistakes, but by encouraging learning from them The organization articulates and consolidates (captures and shares) the learning of individuals and groups The organization recognizes in formal but not necessarily financial ways the contribution of employees to Continuous Improvement
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Table 2. Organization-Oriented HRM Mechanisms Mechanisms Organization-oriented
Variable description
Items from the questionnaire
Formal improvement system
Deployment of learning
Monitoring and measurement system Resource allocation
Improvement system maintenance
Top management support
them – see Table 1). CI behaviours concern all activities performed as part of an organization’s attempts to continuously improve its operations and, through that, its performance. In our analysis, first a total of 13 HRM mechanisms were identified in the questionnaire (see Tables 1 and 2), using Beer’s (1984) definition and previous work by Jørgensen and Hyland (2007). Then, 20 CI behaviours were identified from the survey items on the basis of descriptions offered by Bessant & Caffyn (1997) (see Table 4). Based on a theoretical assessment of the target of the HRM mechanisms, the 13 HRM mechanisms were grouped into two factors, people-oriented mechanisms and organization-oriented mechanisms. In essence, this categorization differentiates between HRM-related decisions and actions that were intended to impact the individuals and groups within the organization (see Table 1) and more system-wide intended HRM mechanisms (see Table 2). Because the distinction was made before the construction of the questionnaire and hence was not embedded in the items of the questionnaire, it © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
A Continuous Improvement (CI) or equivalent formal improvement system (e.g. Total Productive Maintenance) has been introduced to involve all employees in ongoing improvement Appropriate organizational mechanisms are used to deploy what has been learned across the organization Improvement activities and results are continually monitored and measured Managers support improvement processes by allocating sufficient time, money, space and other resources Ongoing assessment ensures that the organization’s processes, structure and systems consistently support and reinforce improvement activities Senior management make available sufficient resources (time, money, personnel) to support the continuing development of the company’s improvement system
was delineated between the mechanisms on the basis of theoretical assessment, i.e. the authors’ judgements of the degree to which the mechanisms targeted individuals and groups or were more system-wide. Using SPSS13, a regression analysis was then performed to investigate the relationship between these two groups of HRM mechanisms (independent variables) and the 20 CI behaviours. A second regression analysis was performed to investigate the relationship between the 20 CI behaviours (independent variable) and 16 indicators of performance improvement (dependent variables) also identified from items on the questionnaire. As previously described, the performance indicators were grouped into three factors based on a factor analysis with a Varimax rotation (see Jørgensen, Boer & Laugen, 2006). To exclude relationships with a poor level of significance, the regression was performed stepwise. To study the second hypothesis, 11 implementation problems identified in the literature (e.g., Bessant & Caffyn, 1997; Boer et al., 2000) and included in the questionnaire were
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Table 3. Results of Factor Analysis of CI Implementation Problems Factor
Lack of leadership
Lack of knowledge
Lack of resources
Variable (CI implementation problems)
Variable average*
Factor loading
Factor average*
Culture not supportive of improvement Insufficient worker commitment Insufficient management commitment Lack of clarity or ambiguity in goals Insufficient performance measures Insufficient support/facilitation Insufficient training facilities Insufficient information Insufficient knowledge/capabilities/ experience Insufficient time Insufficient budget
2.94 3.03 3.28 3.13 3.03 3.10 3.05 3.09 3.01
0.802 0.739 0.667 0.565 0.531 0.505 0.800 0.763 0.752
3.086
2.02 2.74
0.797 0.710
3.047
2.384
* Scale: 1 = very frequently, 5 = very rarely.
divided into three groups (see Table 3) through a factor analysis with a Varimax rotation. Next, the moderating effects of these implementation problems on the relationships between the HRM mechanisms and the CI behaviours (Table 4) and the relationships between CI behaviours and performance improvement (Table 5) were measured.
Results Table 41 shows the effects of HRM mechanisms on CI behaviours and the impact of the three groups of implementation problems on these relationships.
Organization-Oriented Mechanisms and CI Behaviours Of the organization-oriented HRM mechanisms, the strongest relationship was found with CI behaviours that involve employees measuring the success of their CI activities (b = 1.12, p < 0.01, R2 = 0.559). The strength of this relationship is significantly reduced by lack of leadership, one of the expected barriers in the implementation process (b = -1.08), while lack of knowledge or resources, two other potential barriers, does not have significant moderating effects. 1
Three CI behaviours that are not significantly influenced by HRM practices have been excluded from the table.
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The organization-oriented HRM mechanisms also have a strong impact on the behaviours linking improvements to organizational strategy (b = 0.88, p < 0.01, R2 = 0.469) and responding to ideas (b = 0.88, p < 0.01, R2 = 0.494). Lack of leadership (b = -0.97) significantly reduces these relationships; however, lack of knowledge appears to increase the strength of these relationships. Further, organizational HRM mechanisms have a positive relationship with CI behaviours involving learning from experience, understanding goals, sharing learning, measuring the CI process, broad involvement, and implementing improvements with customers. Lack of resources reduces the positive effect of organizational mechanisms on doing CI collaboratively with customers.
People-Oriented Mechanisms and CI Behaviours The people-oriented HRM functions have the strongest influence on the following CI behaviours: employees seeking opportunities for learning and development (b = 0.96, p < 0.01, R2 = 0.416), explaining failures by looking for causes rather than blaming individuals (b = 0.78, p < 0.01, R2 = 0.373) and process ownership (b = 0.77, p < 0.01, R2 = 0.410). None of these relationships is significantly moderated by implementation problems. People-oriented HRM mechanisms also have a significant positive effect on CI behaviours related to worker participation, incorporation of learning, customer orientation, use of © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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0.05 0.25 -0.21 0.26 0.72*** -0.23 0.13 -0.24 0.534 40.697 0.000
Customer oriented
0.88*** -0.46 0.22 -0.23 -0.16 0.42 -0.18 0.22 0.469 31.573 0.000
Align CI to strategy
Significance levels: *** p < 0.01, ** p < 0.05, * p < 0.1.
(Constant) Mechanisms – Organizational Leadership Knowledge Resource Mechanisms – People Leadership Knowledge Resource R2 F Sig
CI mechanisms/ Moderating variables (implementation problems)
(Constant) Mechanisms – Organizational Leadership Knowledge Resources Mechanisms – People Leadership Knowledge Resources R2 F Sig
CI mechanisms/ Moderating variables (implementation problems)
*** 0.23 0.26 0.15 -0.20 0.48** -0.24 -0.20 0.24 0.486 33.234 0.000
Formal problem solving
* 0.51* -0.58* 0.39 -0.02 0.11 0.55* -0.44 0.13 0.378 21.700 0.000
*** -0.09 0.29 -0.04 0.08 0.77*** -0.31 0.08 -0.12 0.410 24.749 0.000
*** 0.82*** -0.33 -0.17 0.06 -0.09 0.39 0.11 -0.04 0.512 37.498 0.000
Share learning
1.12*** -1.08*** 0.42 0.09 -0.36*** 1.06* -0.41 -0.09 0.559 45.236 0.000
Measure results
*** 0.28 0.21 0.06 -0.06 0.45** -0.13 -0.11 0.11 0.586 50.320 0.000
0.44* -0.19 0.14 0.18 0.14 0.26 -0.04 -0.18 0.466 30.964 0.000
Use measurement process
0.45* -0.31 0.35 -0.05 0.26 0.38 -0.42 0.05 0.492 34.280 0.000
Broad involvement
Continuous Improvement behaviours
** 0.88*** -0.97*** 0.58** 0.13 -0.14 0.92*** -0.58** -0.14 0.494 35.028 0.000
Respond to ideas
Use improvement tools
*** 0.68** -0.77** 0.70** -0.20 0.04 0.79*** -0.82*** 0.22 0.429 26.769 0.000
Understand goals
Felt process ownership
Learn from experience
Continuous Improvement behaviours
0.82*** -0.06 -0.22 -0.49** -0.07 0.09 0.18 0.36 0.436 27.524 0.000
*** 0.00 0.32 -0.37 0.37* 0.76*** -0.31 0.32 -0.33 0.563 45.654 0.000
Incorporate learning
0.12 -0.38 0.39 0.30 0.58** 0.32 -0.37 -0.29 0.463 30.157 0.000
*** -0.04 -0.37 0.48 0.09 0.78*** 0.21 -0.50 -0.17 0.373 21.119 0.000
Make Explain system failures adjustments
* 0.27 -0.28 0.40 0.10 0.48** 0.35 -0.46 -0.09 0.559 45.090 0.000
Participate in CI
Improvement with customers
*** -0.39 0.52 -0.06 0.17 0.96*** -0.36 -0.02 -0.15 0.416 25.483 0.000
Seek opportunities
Table 4. Results of the Regression Analysis of the Relationships between HRM Mechanisms (Independent Variables) and CI Behaviours (Dependent Variables), and the Influence of Implementation Problems
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Constant *** Strategic 0.731** alignment Respond to ideas Work across divisions Share learning Measure 0.672* results Seek opportunities Worker participation Customer -0.644** oriented Process ownership System adjustments Customer -0.177 feedback Explain failures R2 F Sig 0.869***
-0.405
Significance levels: *** p < 0.01, ** p < 0.05, * p < 0.1.
CI behaviours
-0.524*
0.114
-0.256
-0.225
-0.527*
0.517**
0.169 2.800 0.000
-0.257
-0.169
0.601**
0.162 2.862 0.000
-0.422
-0.189
-0.205
-0.890***
0.871***
0.418*
-0.408** 0.238
-0.230
-0.729**
0.817***
-0.851***
-0.307
0.233
0.232
-0.271
0.607**
-0.679***
0.212 2.668 0.000
0.152
-0.783**
0.395
0.505
-0.763**
-0.926***
0.600
-0.772***
0.160
0.449
-0.439
0.260
-0.520*
-0.330
-0.115
0.307
-0.459
0.212
0.516*
-0.269
0.275
Leadership Knowledge Resources
-0.738***
0.822***
0.403
-0.407
-0.280
0.486
0.469
0.708***
*** 0.221
Leadership Knowledge Resources Organization
0.460*
0.522**
***
Speed/ Leadership Knowledge Resources Relationship Cost
Performance/Moderating variables (implementation problems)
Table 5. Results of the Regression Analysis of the Relationships between CI Behaviours (Independent Variables) and Performance Dimensions (Dependent Variables), and the Influence of Implementation Problems
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formal problem solving and improvement tools and making adjustments to the CI system. Again, none of these relationships is significantly moderated by implementation problems. A quite strong negative relationship is found between people-oriented HRM mechanisms and the CI behaviours associated with measuring the results of the CI activities (b = -0.36, p < 0.01, R2 = 0.559). Lack of leadership appears to aggravate that effect.
CI Behaviours and Performance The next step in the analysis concerned the effects of CI behaviours on performance. The results, summarized in Table 5,2 show that focusing the CI activities on company strategy has a significant and positive impact on speed/cost performance (b = 0.731, p < 0.05). Further, there is an indication (p < 0.1) that measuring results of CI activities has a positive influence on speed/cost performance (b = 0.672) as well. This relationship is significantly reduced by lack of resources during implementation (b = -0.524, p < 0.1). Customer orientation has a negative relationship with improving speed/cost performance (b = -0.644, p < 0.05). The strength of this relationship is increased by lack of leadership (b = 0.869, p < 0.01) and reduced by lack of knowledge (b = -0.527, p < 0.1). Sharing of learning (b = 0.817, p < 0.01), feeling process ownership (b = 0.601, p < 0.05) and responding to ideas (b = 0.522, p < 0.05) are all positively and significantly related to increasing relationship performance (i.e. relationships with customers, suppliers and other departments, customer satisfaction and quality conformance). In addition, the findings indicate that there is a positive relationship between working across divisions and relationship performance. Work participation (b = -0.890, p < 0.01) and seeking opportunities for learning and development (b = 0.408, p < 0.05) are negatively related to relationship performance. Adjusting the improvement system (b = 0.822, p < 0.01) and responding to ideas (b = 0.708, p < 0.01) are strongly related to organizational performance, while explanation of failures (b = -0.679, p < 0.01) is negatively related to this performance measure.
2
Only CI behaviours that have a significant impact on company performance are included in the table.
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Discussion HRM Mechanisms and CI Behaviour In general, the first part of the analysis of hypothesis H1 produced several positive relationships between the use of HRM mechanisms and CI behaviours. The organizationoriented HRM mechanisms appear to increase the following CI activities: • Understanding of strategic goals • Alignment of CI activities with strategic goals • Responding to improvement ideas • Learning from experience with CI activities • Sharing of learning from CI activities • Measuring CI processes • Measuring CI results • Broad employee involvement • Customer-involvement in CI activities. The people-oriented HRM mechanisms increase the following CI behaviours: • Seeking opportunities for training and development • Explaining failures without blaming individuals • Feeling ownership for the CI process • Customer-oriented behaviours • The incorporation of learning into work processes • Worker participation • Using formal problem solving tools and techniques • Using improvement tools • Making adjustments to the improvement system. Only one negative relationship was found, namely between people-oriented HRM mechanisms and measurement of CI results. This is somewhat surprising, as the CI literature emphasizes the need for systems and processes to measure CI results. Further, two of the 20 CI behaviours investigated, namely working across divisions and customer feedback, are not affected by any of the HRM mechanisms. Both of these behaviours do, however, affect performance, as the next subsection will show. These findings suggest that HRM mechanisms (exercised by the HRM function and/or (other) managers in the organization) make a difference and have a generally positive influence on the development of CI in organizations. More interesting, perhaps, is the finding that organization-oriented and peopleoriented HRM mechanisms affect different CI behaviours. In fact, only one CI behaviour is influenced by both types of mechanism.
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CI Behaviours and Performance Effects This part of the analysis of hypothesis H1 produced some expected but also some rather disturbing results. The survey data show that organizations that align their CI activities with their strategy and objectives and measure the results of CI activities realize improvements in speed/cost performance. This should be expected as both behaviours support the pursuit of goal-directed performance. However, speed/cost is affected negatively by customer orientation. Apparently, many companies still experience the relationship between customer orientation and speed/cost performance as a trade-off. Not surprisingly, lack of leadership aggravates that situation. Responding to ideas, sharing of learning, working across divisions and process ownership are all positively related to relational performance, while that performance area is affected negatively by behaviours related to worker participation and seeking opportunities for training and development, respectively. An explanation for the negative impact of participation, which is strongly aggravated by lack of knowledge, could be that this does increase the workers’ local understanding of, commitment to and involvement in CI, but decreases the time and energy they have available for coping with more global issues, including relationships with (internal and external) customers and suppliers. The fact that lack of resources increases the negative impact of seeking training and development opportunities could explain why employees may be more interested in their own goal fulfilment than in contributing to successful relationships with others. Finally, organizational performance is affected positively by behaviours associated with responding to ideas and making system adjustments, respectively, while customer feedback and explaining the causes of failures have a negative influence. The latter relationship is aggravated by lack of leadership. This finding is not only unexpected, but also quite disturbing, as this is most certainly not the desired effect of this behaviour. Thus, this finding begs further exploration. An overall explanation for the unexpected findings reported above relates to what has been referred to as discretionary effort, or the seemingly personal choices employees appear to make with respect to how they will use their time and effort at work (Delbridge, 1998). Implementation problems related to lack of leadership, knowledge or resources were shown to aggravate four of the five negative relationships. Perhaps, however, these problems play a more direct role than expected,
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and actually create a situation in which employees involved in CI are forced to decide themselves (lack of leadership) on how to prioritize their time and efforts (lack of resources) and elect to participate in some activities while choosing not to participate in others, especially those outside their immediate scope (lack of knowledge).
Implementation Problems Hypothesis H2 concerns the impact of implementation problems, some of which have already been touched upon in the previous subsection. The findings reported here confirm that if a relationship between HRM mechanisms and CI behaviour is affected by implementation problems, these problems generally reduce the strength of the positive relationships and aggravate the strength of most of the negative relationships. In fact, there were only three exceptions to this: lack of knowledge has a positive effect on the relationships between: • organizational HRM mechanisms and employees’ understanding of goals • organizational HRM mechanisms and responding to improvement ideas • customer orientation and speed/cost performance. These findings are surprising and warrant further investigation. Also, the finding that implementation problems are significantly related to only a very few of the relationships between the HRM mechanisms and the CI behaviours is worth further study. A somewhat optimistic explanation may be that the HRM mechanisms alleviate the consequences that the problems would otherwise cause for the implementation; however, this explanation is based solely on conjecture. Finally, the possibility indicated previously – that implementation problems play a more direct role and thus create problems for employees attempting to achieve multiple performance objectives – needs further research.
Managerial Implications Figure 1 summarizes the cumulative findings and shows: • All but two of the 20 HRM mechanisms studied affect CI behaviour. • One of the remaining 18 mechanisms has a negative effect; 17 a positive influence. Thus it seems clear that HRM makes a difference when it comes to implementing CI in © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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Measuring CI results
Seeking opportunities for training and development
Aligning CI activities with strategic goals Speed/cost performance Responding to ideas
Process ownership
Sharing of learning Organization-oriented HRM mechanisms
Customer-involvement in CI activities
Relational performance Customer orientation The incorporation of learning into the work processes
Understanding of goals Learning from experience
Explaining failures without blaming individuals
People-oriented HRM mechanisms
Organizational performance
Measurement of CI processes Broad employee involvement
Worker participation Formal problem solving The use of improvement tools. Making system adjustments
Work across divisions positive
Customer feedback
negative
Figure 1. Relationships between HRM Mechanisms, CI Behaviours and Performance Effects
organizations. Making the concept actually work is a different matter. In fact, the effects of CI activities on performance are somewhat puzzling. All the CI behaviours that are affected positively by organization-oriented HRM mechanisms have a positive influence on business performance. This finding entails a clear message for managers as well: organization is a good starting point on the road towards performance improvement. In contrast, most of the CI activities that are positively affected by people-oriented HRM mechanisms have a negative performance effect. This finding, as indicated above, warrants further research. If, however, there is some truth to the explanation offered previously that these findings reflect the impact of lack of leadership, resources and knowledge, the message is clear as well: CI success depends just as much on learning (knowledge, skills, attitude) as it does on the availability of resources (time) for workers not only to perform CI activities, but also to go beyond their immediate scope and make the right choices in doing so, and on leadership to support and facilitate workers in their learning process and in making appropriate choices. Only then ‘either-or’ choices are prevented and ‘both-and’ choices made.
paper shows that HRM has an important role in supporting CI and performance improvement through CI. In general, the analyses indicate numerous strong relationships between mechanisms that are commonly associated with the HRM function and CI behaviours, as well as between these CI behaviours and performance improvement. This suggests that HRM can play an important role in supporting CI implementation. A natural direction for future research would be to examine these relationships more closely in order to identify which HRM mechanisms within each group (i.e., organizational or people-oriented) account for the largest increases in CI activity and performance. A number of unexpected results were also discovered during the course of the analyses, each of which represents directions for further research. Specifically, it would be quite interesting to look more closely at the potentially negative effects of people-oriented HRM mechanisms and performance effects. A related question concerns the possible impact of lack of resources, leadership and knowledge on the actual improvement choices made within an organization: do these barriers in fact lead to ‘either-or’ choices? If so, that finding will hold a major lesson for the management of Continuous Improvement.
Conclusion Schuler (2000) states emphatically that organizations that prioritize their human resources find ways to integrate HRM into all aspects of their business. Based on statistical analyses of the responses to the CINet Survey (2003), this © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
References Arthur, J.B. (1994) Effects of Human Resource Systems on Manufacturing Performance and Turnover. Academy of Management Journal, 37, 670–87.
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Barney, J. (1995) Looking Inside for Competitive Advantage. Academy of Management Executive, 9, 49–61. Becker, B. and Gerhart, B. (1996) The Impact of Human Resource Management on Organizational Performance: Progress and Prospects. Academy of Management Journal, 39, 779–801. Beer, M., Lawrence, P.R., Mills, D.Q. and Walton, R.E. (1984) Managing Human Assets. The Free Press, New York. Bessant, J. and Caffyn, S. (1997) High Involvement Innovation. International Journal of Technology Management, 14, 7–28. Boer, H., Berger, A., Chapman, R. and Gertsen, F. (eds.) (2000) CI Changes: From Suggestion Box to Organisational Learning, CI in Europe and Australia. Ashgate, Aldershot. Brewster, C. and Soderstrom, M. (1994) Human Resources and Line Management. In Brewster, C. and Hegewisch, A. (eds.), Policy and Practice in European Human Resource Management: The Price Waterhouse Survey. Routledge, London. Delbridge, R. (1998) Life on the Line in Contemporary Manufacturing. Oxford University Press, Oxford. Guest, D. (1997) Human Resource Management and Performance: A Review and Research Agenda. The International Journal of Human Resource Management, 8, 263–76. Hoogendoorn, J. and Brewster, C. (1992) Human Resource Aspects of Decentralisation and Devolution. Personnel Review, 21, 4–11. Hyland, P., Decker, K., Sloan, T. and Jørgensen, F. (forthcoming) CI in the Workplace: Does Involving the HRM Function make any Difference? International Journal of Technology Management. Jørgensen, F. (2003) A Journey through SelfAssessment, Group Learning, and Continuous Improvement. PhD thesis, Center for Industrial Production, Aalborg University, Denmark. Jørgensen, F. and Hyland, P. (2007) Human Resource Development’s Contribution to Continuous Improvement’. Proceedings of the 2007 International Research Conference for the Academy of Human Resource Development, 28 February–4 March, Indianapolis, IN, USA. Jørgensen, F., Nielsen, J. and Kofoed, L. (2005) (Human) Resourcing for Continuous Improvement. Proceedings from the 4th International Conference of Technological Change, Chania, Greece. Jørgensen, F., Boer, H. and Laugen, B. (2006) CI Implementation: An Empirical Test of the CI Maturity Model. Creativity and Innovation Management, 15, 328–37.
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Jørgensen, F., Hyland, P. and Kofoed, L. (forthcoming) Examining the Role of Human Resource Management in Continuous Improvement. International Journal of Technology Management. Langbert, M. and Friedman, H. (2002) Continuous Improvement in the History of Human Resource Management. Journal of Management Decision, 40, 782–87. Laursen, K. and Foss, N.J. (2003) New Human Resource Management Practices, Complementarities, and the Impact on Innovation Performance. Cambridge Journal of Economics, 27, 243–63. de Leede, J. and Looise, J.K. (2005) Innovation and HRM: Towards an Integrated Framework. Creativity and Innovation Management, 14, 108–17. Maxwell, G., Quail, S. and Watson, S. (2002) Quality Service: A Trigger for Strategic Human Resource Development in the International Hotel Sector. Third Conference on Human Resource Development Research and Practice across Europe: Creativity and Innovation in Learning, Edinburgh 25–26 January 2002. Middel, R., de Weegh S., Gieskes, J. and Schuring, R.W. (2004) Continuous Improvement in the Netherlands: A Survey-Based Study into the Current Practices of Continuous Improvement. Proceedings from the 5th International CINet Conference on Continuous Innovation: Strategic Priorities for the Global Knowledge Economy, Sydney, Australia, 22–25 September. Pearn, M., Roderick, C. and Mulrooney, C. (1995) Learning Organizations in Practice. McGraw-Hill, London. Purcell, J., Kinnie, N., Hutchinson, S. and Rayton, B. (2000) Inside the Box. People Management, 6, 30–8. Schroeder, D. and Robinson, A. (1991) America’s Most Successful Export to Japan: Continuous Improvement Programs. Sloan Management Review, 32, 67–81. Schuler, R.S. (2000) Human Resource Management Activities in International Joint Ventures. In Storey, J. (ed.), Human Resource Management: A Critical Text. International Thomson, London. Storey, J. (1992) Developments in the Management of Human Resources . Blackwell Publishing, Oxford. Walton, J. (1999) Strategic Human Resource Development. Prentice-Hall, Harlow. Wright, M.P., Gardner, M.T. and Moynihan, M.L. (2003) The Impact of HR Practices on the Performance of Business Units. Human Resource Management Journal, 13, 21–36.
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Frances Jørgensen (
[email protected]) is Associate Professor at the Department of Management, Aarhus School of Business, Aarhus University, Denmark. She received her MA in Industrial and Organizational Psychology at Middle Tennessee State University, USA, and her PhD in Change Management at Aalborg University, Denmark. Dr. Jørgensen’s primary research interests are in the fields of Human Resource Development, Organizational Behaviour, and Change Management, especially from an employee perspective. Bjørge Timenes Laugen is an Associate Professor in the Department of Business Administration at the University of Stavanger, Stavanger, Norway. He received his MSc in engineering in 2000, and his PhD in innovation management in 2006, both from Aalborg University, Denmark. His main research interest is the link between new product development, production, strategy, organizational development and continuous innovation. Dr. Laugen is a board member of CINet (Continuous Innovation Network), a global network set up to bring together researchers and industrialists working in the area of continuous innovation. Harry Boer is Professor of Organizational Design and Change at the Center for Industrial Production at Aalborg University. He holds a BSc in Applied Mathematics and a MSc and PhD both in Management Engineering. He has (co-)authored numerous articles and several books on subjects such as organization theory, flexible automation, manufacturing strategy, and continuous improvement/innovation. His current research interest is in continuous innovation, the effective interaction between dayto-day operations, incremental change and radical innovation.
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Continuous Innovation and Performance Management of SME Clusters Luiz Cesar Ribeiro Carpinetti, Mateus Cecilio Gerolamo and Edwin Vladimir Cardoza Galdámez Continuous innovation and performance measurement methods and tools have been applied in companies as a means to develop improvement actions related to strategic objectives and to monitor results so as to give feedback for further action. However, continuous innovation and performance measurement methods and tools can also be applied to manage performance of a cluster of firms. After a brief review of continuous innovation and the concept of collective efficiency of a cluster, this paper presents a conceptual model for managing actions for improving collective efficiency and measuring performance of an SME cluster. A research case is reported, for which the conceptual model has been applied and results discussed. The paper concludes that despite some difficulties in developing and using performance indicators in SMEs, the concepts presented by the proposed model can help to foster cooperation and maturity in continuous innovation in clusters of SMEs.
Introduction
I
n the past decades, several models have gained widespread acceptance as approaches to improve customer satisfaction and production and operations performance (Currie, 1999). Among these models are Total Quality Management (TQM) (Goetsch & Davis, 1995) and, more recently, Six Sigma Programs (Lientz, 2000) and Lean Production (Rother & Shook, 1999). The adoption of these models by companies in different industries has generally generated a very positive outcome. All of these models are based on the concepts, methods and techniques of improvement and change. In general, the literature on improvement and change management emphasizes the importance of developing organizational values, capabilities and methods for systematic development and review of progress, based on strategic orientation of improvement and change actions. According to Bessant and Francis (1999) companies have to evolve through a process of acquisition of continuous improvement capability, what they call a learning factory. More recently, the concepts of improvement and
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change have evolved to the broader concept of innovation (Bessant, 2006; Hyland & Boer, 2006). Parallel to the evolving theory and practice on improvement and performance management, clustering has also been receiving growing attention as a means to boost growth and competitiveness of small and medium sized enterprises (SMEs) (Krugman, 1991; Schmitz, 1995; Humphrey & Schmitz, 1998; Porter, 2000). Clusters are geographic concentrations of interconnected companies, specialized suppliers, service providers, firms in related industries and associated institutions (e.g., universities, standard agencies, trade associations) in a particular field that compete but also cooperate (Porter, 1998). Schmitz and Nadvi (1999) argued that the agglomeration of enterprises engaged in similar or related activities brings advantages such as a pool of specialized workers, easy access to suppliers of specialized inputs and services and the quick dissemination of new knowledge. Such advantages, called localized external economies, can contribute to the reduction of costs for clustered enterprises. The authors also maintained that external economies alone are © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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not sufficient to explain cluster development and that in addition to incidental external economies, there is often a deliberate joint action. They then proposed the concept of collective efficiency defined as the competitive advantage derived from external economies and joint actions. In this context, the concepts and techniques of continuous improvement and innovation can be of great value in managing collective efficiency and performance improvement of the companies within the cluster. Therefore, the main objective of this paper is to present and discuss a conceptual model for developing and managing actions aimed at improving the collective efficiency of an SME cluster. The following sections first present a brief review of the continuous improvement theory and practice, as well as clustering of SMEs. Next, the proposed conceptual model is presented and discussed. A research case is presented, for which the model is applied to develop actions to an SME cluster in the textile sector. In the final section, the paper discusses partial results and additional expected outcomes.
Improvement and Change Methods Several authors (e.g., Goetsch & Davis, 1995; Rother & Shook, 1999; Lientz, 2000) have proposed methods for implementing and reviewing improvement and change actions, generally based on either the TQM or business process re-engineering philosophies of management. This is the case for the Japanese management by policies approach (Collins & Huge, 1993), which is largely based on the TQM philosophy of management. It applies the Plan-Do-Check-Act (PDCA) cycle, in this case over a longer cycle, to establish strategic business policies, develop and implement them through organizational levels, and to periodically review progress. Also based on the continuous improvement principle is the five steps method proposed by Harrington (1991), which consists of: organizing for improvement; understanding the process; streamlining; measurement and control; and continuous improvement. This method is applied by a team over a 90-day period and is considered as a method for guiding consultants in developing projects. This is unlikely to create continuous improvement capabilities, which is defined by Caffyn (1999) as the ability of an organization to gain a strategic advantage by extending involvement in innovation to a significant proportion of its members. Based on the BPR approach for improvement and change, the method proposed by Kotter (1995) suggests eight phases for trans© 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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formation projects: establishing a sense of urgency; forming a powerful guiding coalition; creating a vision; communicating the vision; empowering others to act on the vision; planning for and creating short-term wins; consolidating improvements and producing still more change; and institutionalizing new approaches. Rentes, Van Aken and Butler (1999) also present a method for transformation process management consisting of seven phases: understanding the need for change; creating infrastructure for change; analysing the current situation; setting the direction for change; defining improvement initiatives; developing and implementing initiatives; reviewing progress and results. Other major contributions to the theory of improvement and change in the 1990s are the conceptual models and methods for developing performance measurement systems. The most widely recognized performance measurement framework is the Balanced Scorecard (Kaplan & Norton, 1996), which proposes four interconnected perspectives of performance measurement in which measurements of internal business process performance and learning and growth are derived from shareholder and customer perspectives of performance. It is based fundamentally on recommendations such as deriving measures from strategic positioning and planning, and balancing financial and non-financial measures derived from different perspectives of measurement and aimed at managing the process of performance improvement. Neely and Adams (2000) argue that organizations should have a clear picture of who their stakeholders (customers, employees, suppliers, investors, etc.) are, what their needs and expectations are and how they can contribute to the organizational objectives. From there, the authors propose a method to derive a performance measurement system, named the performance prism, based on five interconnected perspectives of measurement (which they illustrate by the facets of a prism): identify stakeholders’ needs and expectations; develop strategies to pursue objectives related to stakeholders’ needs and expectations; identify key performance areas and business processes critical to implementing the designed strategies; identify which are the organizational capabilities needed to improve these processes; and identify contributions required from stakeholders in order to maintain or develop these capabilities to improve processes. Fundamental recommendations implicit in the performance prism framework are: deriving measures from stakeholders’ expectations and strategic directions; focusing on critical business processes and capabilities;
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and identifying stakeholders’ contribution required to generate satisfaction and business excellence. Generally, the methods presented briefly above emphasize important principles of management as well as the need to systematically undertake improvement and change initiatives. However, implementation of any of these methods would be very difficult without an underlying organizational capability to manage improvement and change. Bessant and Caffyn (1996) present a model describing what they call the behaviours that need to be acquired and embedded in the organization in order to enable an evolution of continuous improvement (CI) capabilities. The model defines five levels of evolution, from level 0, characterized as no-CI activities, up to level 5, categorized as the learning organization in which there is ability to develop competence, with everyone in the company actively involved in incremental and radical innovation and sharing of learning. The intermediate level 3, strategic CI, is characterized by the formal development of broader strategic goals to operational level activities; improvement driven by monitoring and measurement; training in basic CI tools; use of formal problem-solving processes; and participation and recognition.
Continuous Innovation More recently, the concept of continuous improvement has been evolving into continuous innovation. There are two basic innovation strategies, product and process innovation, apart from hybrid combinations of these two. A broader definition of process innovation states that it involves not only the manufacturing processes of products, but also the planning, steering and supporting processes in the organization. Process innovation also includes improving functions such as strategic planning and implementation, marketing, production, logistics, quality management and human resource management (Riederer, Baier & Graefe, 2005). Riederer, Baier and Graefe (2005) extend the definition of innovation as the economic implementation and exploitation of new ideas and discoveries, including the implementation of an innovation culture in an organization. In addition to the improvement and development of new products and processes, innovation is also concerned with the structure of an organization, the internal processes and the management techniques used. Therefore, the management of innovation should be treated
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as a part of business strategy since it requires a strategic direction (Turrel & Lindow, 2003). There are also two major categories of innovation: incremental or continuous and radical or disruptive. According to Hyland and Boer (2006, p. 390), continuous innovation is ‘the ongoing interaction between operations, incremental improvement, learning and radical innovation aimed at effectively combining operational effectiveness and strategic flexibility, exploitation and exploration’. Accordingly, Fager et al. (2004, p. 315), citing Tushman and O’Reilly (1996) and Day and Schoemaker (2000), state that ‘continuous innovation is needed across a broad front’, combining extensive ‘do what we do better’ improvements with periodic and radical ‘do what we do differently’. There are some conceptual models for continuous innovation presented in the literature. For instance, Hyland and Boer (2006) present a framework for continuous improvement that stresses the need for alignment, coordination and integration among operational, innovative and strategic capacities, which, according to the authors, are needed to achieve excellence and, through that, sustained business performance. These concepts and practices of continuous innovation that are usually applied to individual companies can also be applied to manage improvement and innovation actions designed and implemented jointly, by means of cooperation, among companies in a cluster, so as to strengthen competitive position of the cluster as a whole. The main concepts of industrial clustering are briefly reviewed in the next section in order to present a theoretical background and to support the proposition advanced in this paper.
Industrial Clustering Although the term cluster is indiscriminately used for quite a wide range of business arrangements, in its broad sense it refers to a geographical concentration of certain economic activities. However, what makes clusters potentially beneficial to the competitiveness of small firms are the opportunities for collective efficiency, derived from external economies and joint actions (Schmitz & Nadvi, 1999). The concept of external economies, used by Krugman (1991) to explain why agglomeration can bring the benefit of efficiency and competitiveness, was first developed more than 200 years ago by Marshall (Schmitz, 1999), in his book Principles of Economics. He noted that the agglomeration of © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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firms working in similar or related activities generates advantages such as a pool of suppliers of raw materials, equipment and specialized services, a pool of specialized workers and the dissemination of new knowledge. Adding to the theory of industrial clustering, Schmitz and Nadvi (1999) argue that the results of external economies are not a sufficient explanation for the growth of companies in a cluster. While it is true that the concept of external economies remains valid to explain the growth of clustering today, Schmitz (1999) and Schmitz and Nadvi (1999) propose that deliberate cooperation in joint actions is an essential second component to explain the benefits of clustering. They then define the concept of collective efficiency as the competitive advantage derived from the combination of local external economies and cooperative joint actions (Schmitz & Nadvi, 1999). They also differentiate the concept between passive and active collective efficiency, to express the fact that some benefits require joint action to occur while others come from external economies. Such active collective efficiency can be derived from horizontal cooperation (between competitors) or vertical cooperation (for instance, between producer and supplier) either bilaterally or multilaterally (for instance, groups of firms joining forces in business associations or producer consortia). Examples of active collective efficiency include organization of trade fairs; development of suppliers, human resources or other resources required for production; and the development of actions aimed at mitigating social or environmental problems. In view of this theoretical framework, a more appropriate definition of cluster should take into account external effects and interaction. Porter (1998) presents a definition of cluster as a geographic concentration of interconnected companies, specialized suppliers, service providers, firms in related industries and associated institutions (e.g., universities, standards agencies, trade associations) in a particular field that compete but also cooperate. Altenburg and Meyer-Stamer (1999) list some characteristics that, besides external economies and joint actions, are said to be present in most definitions of cluster, which basically comprise the following points: • forward and backward linkages between firms inside the cluster; • information exchange between firms and institutions; • rhe existence of diversified institutional infrastructure supporting the activities of the cluster; • a social cultural identity made up of common values. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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Adoption of the concepts and practices of continuous innovation to carry out joint actions among companies of a cluster can aid to consolidate cooperation, linkages and information exchange among companies as well as develop a culture of continuous innovation, thus contributing to the development of the collective efficiency of the cluster. Therefore, this gives rise to the need to manage the collective efficiency of a cluster, focusing on the concepts and practice of continuous innovation and performance management, as discussed in the next section.
Continuous Innovation and Performance Management of a Cluster Managing performance and continuous innovation of a cluster, in theory, is similar to managing continuous innovation of an enterprise, in which improvement actions are developed to accomplish performance objectives related to some key performance areas and stakeholders’ needs. Monitoring the results of improvement action implementation gives feedback on which managers are able to act, closing a positive control loop (Souza et al., 2005), as illustrated in Figure 1. However, in this case, capability to manage improvement depends not just on a culture of continuous innovation, training in CI tools, participation and recognition. In view of the theory of performance management (Neely & Adams, 2000), it can be seen that there are key stakeholders, such as the firms and institutional bodies, who have a very important role to play in supporting the activities of the cluster so as to improve cooperation and external economies. These should positively affect a firm’s performance which, in turn, should bring about positive economic and social results. But the existence of an institutional infrastructure to support cooperation depends on the existence of social capital, which can be defined as ‘the stock of active connections among people’ (Cohen & Prusak, 2001, p. 4), i.e., the existence of trust, mutual understanding and shared values and behaviours that bind the members of human networks and communities and make cooperative action among the stakeholders possible. In this continuous innovation management process, performance measurement plays a very important role, since the impact of improvement and change actions can be monitored so as to evaluate progress in the effort to achieve continuous innovation and in terms of economic and social results. In the case of a cluster, apart from the usual stakeholders (customers, shareholders, suppliers and employ-
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Stakeholders´ needs
Strategic Orientation
Objectives of Performance
Metrics Development
Stakeholders´ contribution
Measurement
Social Capital
Improvement Actions
Continuous Improvement Capabilities
Infrastructure for Cooperation
Figure 1. Managing the Continuous Innovation of a Cluster
Economic/ social results
Social Capital
Cluster Performance
Company’s Performance
Collective Efficiency
Figure 2. Conceptual Model of a Performance Measurement System of a Cluster
ees) a very important category of stakeholder is the institution (or institutions) governing the cluster. For this stakeholder, expectations are related to growth and competitiveness of the cluster as a whole, and it has a very important role to play in that: to promote cooperation among the other stakeholders, especially among the entrepreneurs whether competitors or not, within the cluster. Therefore, it can be envisaged that a conceptual performance measurement system model for a cluster based on the concept of balanced perspectives of performance proposed by Kaplan and Norton (1996) should take into account measures of performance related to the concept of collective efficiency and its drivers. In view of that, the conceptual framework proposed here is based on four perspectives of performance (see Figure 2): • Economic and social results: measures related to local gross product, workforce occupa-
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tion and any result that brings economic and social benefits. • Firms’ performance: measures related to the results in terms of growth and competitiveness of the firms and measured by financial and non-financial performance of the firms in the cluster. • Collective efficiency: measures related to external economies and actions of cooperation among companies in the cluster. • Social capital: related to cultural values such as trust and cooperation. The adoption of this model can help the institutions governing the cluster to develop leading indicators focused on the factors of firm performance, social capital and collective efficiency that can bring about economic and social growth, measured by lagging indicators related to the perspective of economic and social results. An analysis of the applicability of these concepts in an industrial cluster of SMEs is presented next.
Research Case In Brazil, there has been a growing interest in studying and supporting industrial clustering, especially of small firms, mainly motivated by several successful cases reported in the specialized literature as well as in the press (e.g., Altenburg & Meyer-Stamer 1999; Schmitz, 1999). Using a methodology based on location quotient (relative significance of employment in a particular industrial sector in a region compared to its significance in Brazil, greater © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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Project Stakeholders SINDICOBI
FIESP / SEBRAE General Manager
Chairman Project Coordinator Local coordinator ad hoc consultants
Local staff
Firms (participants in the project) Government(local and State government) SENAI (National Service for Industry Trainning ) Hired consultants University Researchers Other stakeholders
Figure 3. Stakeholders and Organization for Project Coordination of the Project of the Cluster of Ibitinga than 5) and the location Gini coefficient (equal to or greater than 0.5), Puga (2003) could identify 193 agglomerations in Brazil, made up of nearly 77,000 companies responsible for over 680,000 jobs and exports of over US$3700 million. Of these, 42 clusters are in the State of São Paulo, mainly in the sectors of footwear, bed linen, furniture and ceramics. Realizing the importance of industrial clusters to economic and social development, the Federation of Industries of the State of São Paulo (FIESP) and the ‘SEBRAE’ (a government agency for supporting small enterprises) have launched a project to promote cooperation among companies in five industrial clusters in São Paulo State. The cluster under study includes 586 SMEs whose activities are classified, according to the Brazilian National Classification of Economic Activities, as production of textiles, specifically bed linen (code 17.61-2). It is located in Ibitinga, a city in the State of São Paulo with a population of around 50,000 people. Most of the companies were established in the 1980s and 1990s but agglomeration started in the early 1960s. Over the years, agglomeration has led to the development of some advantages (external economies) such as specialized labour force; suppliers of materials and specialized services; as well as a local infrastructure for retailing. In Ibitinga, perceiving that the benefits of agglomeration could be increased by means of © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
cooperation, the local association of entrepreneurs decided to participate in the project supported by FIESP/SEBRAE. The project started in March 2004, with the following main stakeholders (see Figure 3): • The companies of the cluster participating in the project (19 companies when the project started, which increased to 35 companies at the time this study was carried out). • The ‘SINDICOBI’, the local association of entrepreneurs, which represents 88 companies, provides the local infrastructure for developing the activities of the project and manages the cluster jointly with the local representatives of FIESP and SEBRAE. • The ‘FIESP’ and the ‘SEBRAE’, which coordinate the development of the project and provide financial resources to support the initiative. • The ‘SENAI’ – National Service for Training Industry Labour Force, which provides technical courses to prepare the local labour force. • The local government, which provides infrastructure. • The university researchers, who study the development of the project as well as provide some guidance regarding the methodology adopted. • Local consultants, such as accountants and IT professionals, who benefit from service demands.
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Table 1. Metrics and Associated Objectives and Perspectives of Performance Perspective Company’s performance
Social/economic results Collective efficiency Social capital
Objective Market increase Improve productivity Reduce costs Increase profit Improve employment opportunities Improve availability of specialized labour force Reduce costs, improve cooperation Increase number of participants
Figure 3 shows the stakeholders and the organizational structure involved in coordinating the project of the cluster in Ibitinga. The 35 companies participating in the project are classified as small enterprises. At the time of the project they had 1,354 employees (which gives an average of 38.7 employees per company). As one of the main stakeholders of the project, the companies had a very important role, which was to help to define the objectives and actions and to commit themselves to contribute to the project, not only by implementing or helping to implement the actions defined by the project team but also by promoting the culture of cooperation among them. The main objectives defined for the project were to increase productivity and market share and to reduce costs. Another important objective was to change the reputation for ‘poor quality’ related to the products of the cluster. Interaction between the research team and the institutions governing the cluster started in January 2005. Following the definition of objectives, some improvement actions were defined, planned and implemented. The main actions carried out so far by the governing institutions aiming at improving cooperation are: • hiring consultancy services on finance, operations management, marketing and design; • registering a trade mark for the cluster; • establishing a cooperation programme with a public technical school to offer technical courses focused on the needs of the cluster; • equipping the association with a workshop for training of the labour force; • collective purchasing of raw material; • organizing trade shows. There was a consensus among the governing institutions of the cluster that performance
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Metric definition Average unit sale price Value added per employee Total cost Profit Total labour force Total number of trained people Total amount of collective acquisition of raw material Percentage of companies involved with cooperation
measurement was an essential step in order to evaluate the benefits of the actions, so the research team proposed providing some guidance in the process of implementing a performance measurement system. The programme started in December 2005 with the organization of a workshop to present some characteristics that performance measurement should have and to gain commitment from participants. During the workshops, which involved 23 companies, some metrics were defined based on the objectives of the project. Considering that performance measurement was something of an unknown for the companies in the cluster, it was decided that only a few metrics would be adopted. Also, the metrics chosen were influenced by the degree of difficulty in collecting data. That is, the metrics chosen are the ones whose data have already been collected and thus are easily calculated. For this pilot application, one of the researchers, hired by FIESP, helped the project team and the companies’ employees to collect and display the metrics. Table 1 presents the metrics and associated objectives and perspectives. Also, for each metric, the following points were defined (as presented in Table 2): • formula of calculus, units of measure and form of display; • frequency of measurement; • target for the metric; • responsibility for collecting data and calculating metrics. For this pilot application, data collection started in January 2006. However, data had been retrieved since March 2004, the date the project started. The information presented by the metrics was then used by the companies and governing institutions to evaluate the © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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* Per company and average.
Total cost Profit Total labor force Total number of trained people Total amount of collective acquisition of raw material Percentage of companies involved with cooperation
Value added per employee
Average unit sale price
Metric definition
Number of SMEs engaged in cooperation over total SMEs participating in the project
Growth income over number of sold units Growth income minus total costs, administrative expenses, taxes and investments over production employees Total cost over Growth income Net profit over growth income Number of people hired Number of trained persons Acquisitions of raw material
Formula*
Table 2. Details of the Metrics of the Measurement of the Ibitinga Cluster
%
% % person person Ton
$/employee
$/unit
Unity
Year
Semester Semester Semester Year Quarterly
Semester
Semester
Frequency
50% increase
3% reduction 8% increase 7% increase 300 people trained 30 Ton
15% increase
10% increase
Target
Companies and local coordinator
Responsible stakeholder
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course of actions, closing the loop illustrated in Figure 1. Following this pilot application, the participating companies and the governing institutions became convinced of the usefulness of having metrics to analyse results of actions and support decisions for further actions. For instance, by using metrics they were able to compare performance among the companies in a very objective way, which led to a further action: the development and pilot application of a benchmarking database as described in another paper (Carpinetti & Oiko, 2007).
Conclusion Despite the fact that the research case is still in an early stage of development, it has revealed that the model depicted in Figure 1 adequately captures the process of planning and implementing actions for continuous innovation in a cluster. First of all, the conceptual model explicitly considers the main stakeholders for development, and the monitoring and review of actions. Indeed, the case has shown the importance of having all the stakeholders involved with improvement initiatives. Such an organizational culture of involvement of different stakeholders, a fundamental element for continuous innovation and improvement, reinforces the social capital of the cluster, which in turn is a fundamental element for cooperating, innovating and promoting actions to improve the collective efficiency of the cluster. The conceptual model in Figure 2, considering different perspectives of performance management of a cluster and emphasizing the importance of measuring leading and lagging dimensions of performance, such as collective efficiency and economic/social results, forces the stakeholders not only to look for results but also to pay attention to the drivers of performance in a cluster. Still, additional perspectives of performance can be considered depending on the application, for instance, a perspective related to environmental sustainability. Regarding the implementation of the measurement system, limitations similar to those described by Hudson et al. (2001) could be seen: difficulty in developing metrics from key performance factors; tendency to measure cost and financial results; absence of a culture of decision-making based on analysis of information; and, finally, a lack of resources. Despite that, the pilot implementation of the metrics has also proven the adequacy of closing the innovation management loop by reviewing performance by means of measurement. The
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entrepreneurs have started to realize the importance of developing actions by analysing objectives and different perspectives of performance and using metrics in order to assess performance and review improvement actions. Therefore, even allowing for the fact that there is still a lack of maturity for continuous innovation to be overcome, participation in this project, both as observers and also by implementing the metrics and having the opportunity to exchange experiences with the entrepreneurs, could reinforce the initial supposition that the concepts portrayed in Figures 1 and 2 form a basic framework upon which innovation management of a cluster can be built, thus promoting the collective efficiency of a cluster.
Acknowledgement The authors would like to thank FAPESP, The São Paulo State Research Foundation, for supporting this research project.
References Altenburg, T. and Meyer-Stamer, J. (1999) How to Promote Clusters: Policy Experiences from Latin America. World Development, 27, 1693–713. Bessant, J. (2006) Dealing with Discontinuous Innovation: The European Experience. Proceedings of the VII CINet Conference, Lucca, Italy, 2006, pp. 115–26. Bessant, J. and Caffyn, S. (1996) Learn to Manage Innovation. Technology Analysis and Strategic Management, 8, 59–70. Bessant, J. and Francis, D. (1999) Developing Strategic Continuous Improvement Capability. International Journal of Operations and Production Management, 19, 1106–19. Caffyn, S. (1999) Development of a Continuous Improvement Self-Assessment Tool. International Journal of Operations and Production Management, 19, 1138–53. Carpinetti, L.C.R. and Oiko, O.T. (2007) Benchmarking in Clusters of SMEs: Development and Application of a Data Base. 19th International Conference on Production Research, Valparaiso, Chile (submitted for presentation). Cohen, D. and Prusak, L. (2001) In Good Company: How Social Capital Makes Organizations Work. Harvard Business School Press, Cambridge, MA. Collins, B. and Huge, E. (1993) Management by Policy: How Companies Focus Their Total Quality Efforts to Achieve Competitive Advantage. ASQC Quality Press, Milwaukee, WI. Currie, W. (1999) Revisiting Management Innovation and Change Programmes: Strategic Vision or Tunnel Vision? Omega, 27, 647–60. Day, G. and Schoemaker, P. (2000) Wharton on Managing Emerging Technologies. Wiley, New York. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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Fager, B., Minnie, C., Fager, J., Welgemoed, M., Bessant, J. and Francis, D. (2004) Enabling Continuous Improvement: A Case Study of Implementation. Journal of Manufacturing Technology Management, 15, 315–24. Goetsch, D.L. and Davis, S. (1995) Implementing Total Quality. Prentice Hall Inc., Englewood Cliffs, NJ. Harrington, H.J. (1991) Business Process Improvement: The Breakthrough Strategy for Total Quality, Productivity, and Competitiveness. McGraw-Hill, New York. Hudson, M., Smart, A. and Bourne, M. (2001) Theory and Practice in SME Performance Measurement System. International Journal of Operations and Production Management, 21, 1096–115. Humphrey, J. and Schmitz, H. (1998) Trust and Inter-Firm Relations in Developing and Transaction Economies. Journal of Development Studies, 34, 32–61. Hyland, P. and Boer, H. (2006) A Continuous Innovation Framework: Some Thoughts for Consideration. Proceedings of the VII CINet Conference, Lucca, Italy, 2006, pp. 389–400. Kaplan, R. and Norton, D.P. (1996) Using the Balanced Scorecard as a Strategic Management System. Harvard Business Review, 74, 75–85. Kotter, J.P. (1995) Leading Change, Why Transformation Efforts Fail. Harvard Business Review, March–April, pp. 59–67. Krugman, P. (1991) Geography and Trade. MIT Press, Cambridge, MA. Lientz, B.P. (2000) Achieve Lasting Process Improvement: Reach Six Sigma Goals Without the Pain. Academic Press, New York. Neely, A. and Adams, C. (2000) Perspectives on Performance: The Performance Prism. In Bourne, M. (ed.) Handbook of Performance Measurement. Gee Publishing, London. Porter, M. (1998) Clusters and the New Economics of Competition. Harvard Business Review, 76, 77–90. Porter, M. (2000) Clusters and the New Economics of Competition. Harvard Business Review, 76, 77–90. Puga, F. (2003) Alternativas de apoio a MPMES localizadas em arranjos produtivos locais [WWW document]. URL: http://redeincubar.anprotec. org.br:8280/portal/baixaFcdAnexo.do?id=6 [accessed on 12 November 2004]. Rentes, A.F., Van Aken, E.M. and Butler, M.R. (1999) An Organizational Assessment Method For Transformation Efforts. Portland International Conference on Management of Engineering Technology Annals – PICMET’99. Riederer, J., Baier, M. and Graefe, G. (2005) Innovation Management – An Overview and Some Best Practices. C-Lab report – Cooperative Computing and Communication Lab, 4 [WWW document]. URL: http://www.c-lab.de.
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Rother, M. and Shook, J. (1999) Learning to See: Value Stream Mapping to Add Value and Eliminate Waste. Lean Enterprise Institute, Brookline, MA. Schmitz, H. (1995) Collective Efficiency: Growth Path for Small-Scale Industry. Journal of Development Studies, 31, 529. Schmitz, H. and Nadvi, K. (1999) Clustering and Industrialization: Introduction. World Development, 27, 1503–14. Souza, G., Carpinetti, L., Van Aken, E. and Groesbeck, R. (2005) Conceptual Design of Performance Measurement and Management System Using a Structured Engineering Approach. International Journal of Productivity and Performance Management, 54, 385–99. Turrel, M. and Lindow, Y. (2003) The Innovation Pipeline. Imaginatik Research White Paper, March. Tushman, M. and O’Reilly, C. (1996) Winning Through Innovation. Harvard Business School Press, Boston, MA.
Luiz C.R. Carpinetti (
[email protected]) is an Associate Professor at the School of Engineering of São Carlos, University of São Paulo, Brazil. He holds a PhD in Engineering from the University of Warwick (UK) and an MSc in Metrology and Quality Assurance from the Cranfield Institute of Technology (UK). His current teaching and research interests are on the subjects of quality management and improvement, including performance and measurement, management of industrial clusters, innovation management and related tools and methodologies. Mateus C. Gerolamo (gerolamo@sc. usp.br) is a Visiting Researcher at the Technical University of Berlin, Germany. He holds a PhD and an MSc in Production Engineering from the School of Engineering of São Carlos, University of São Paulo, Brazil. His current research interests are on the subjects of quality management and improvement, including performance measurement and performance management of industrial clusters. Edwin W.C. Galdámez (Edwin@sc. usp.br) is a PhD student at the Graduate Course on Production Engineering at the School of Engineering of São Carlos, University of São Paulo, Brazil. His current research interests are on the subjects of quality management and improvement, including performance measurement and performance management of industrial clusters.
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The Implementation of New Technologies Through a Participative Approach Jesús García-Arca and J. Carlos Prado-Prado Implementation projects of information systems, particularly in the logistics field, are usually long, complex processes requiring a good deal of resources. As an alternative to an exclusively technical viewpoint, the contribution by the users themselves to the design and implementation of these information systems may facilitate better final results. With this participative approach in mind, this paper proposes a methodology for implementing information and communication technologies (ICTs) that includes the recommendations put forward in the literature, which also involves the authors of the paper themselves as agents for change in companies, in line with the ‘action research’ approach. In order to illustrate the potential of this methodology, which may be of interest to the academic and professional world, analysis is made of the successful cases of two Spanish companies in the food sector that have recently applied this methodology in ICT implementation.
Background
I
ncreasing competitive pressure in increasingly globalized markets has reinforced the importance of an appropriate management of the supply chain (Dornier et al., 1998; Gunasekaran & Ngai, 2004; Wisner, Leong & Tan, 2005). In this context, the logistics function in the supply chain has been underlined as a key factor in achieving competitive advantage through improving the standards of quality, service and cost offered to the market (Bowersox et al., 1989; Christopher, 1992; Bolwijn & Kumpe, 1998). The CSCMP (http://www.cscmp.org/Website / AboutCSCMP / Definitions/Definitions. asp) defines logistics as ‘the part of supply chain management that plans, implements, and controls the efficient, effective forward and reverse flow and storage of goods, services and related information between the point of origin and the point of consumption in order to meet customers’ requirements’. This definition understands information to be a key resource in logistics management, being the basis for decision making in order to improve effectiveness, efficiency and flexibility in companies (Langley, 1986; Introna, 1991). From a technological point of view,
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it should be noted that the development and implementation of information and communication technologies (ICTs) in the logistics field have been significant in the improvement of competitiveness (Bowersox et al., 1989). Although there is no doubt that ICTs offer companies considerable possibilities (Closs, Goldsby & Clinton, 1997; Piplani, Pokharel & Tan, 2004), this does not mean that they can be applied indiscriminately, but rather that they should be evaluated to ensure that they respond to the particular needs of each case. Nonetheless, companies may run the risk of implementing ICTs in a disorganized, uncontrolled manner, which may well mean that the levels of satisfaction with the results of the project expected by the organization are not attained. For this reason, Kanji and Asher (1993) explain that in order to achieve a suitable management of the change (such as by incorporating ICTs), it is essential to take control of the change itself, and other authors such as Douglas, Lycke and Dobbie (2000) concur. Going beyond that, if this change is deeplying and innovative, it may fit within the term ‘innovation’ and the current competitive levels involved in this change process on a continuous basis. Thus, the concept of ‘continuous © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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innovation’ may be defined as ‘the ongoing interaction between operations, incremental improvement, learning and radical innovation aimed at effectively combining operational effectiveness and strategic flexibility, exploitation and exploration’ (Boer, 2001). Kotter (1996) and Hanson (2001) summarize strategies for innovation adoption. Thus, organizations that have successfully implemented innovation or changes show two important patterns: first, they have followed a multistage process, which creates empowerment and motivation; second, this process only works efficiently if driven by qualified management. So, a key aspect for the success of this type of project is the application of an adequate implementation methodology to deal with adapting to the problems involved in each company, beyond its technical aspects, so that it is necessary to involve the entire organization in a continuous learning process, at all levels (management team, intermediary positions and operators) (Lycke, 2000). The current literature (Appelbaum et al., 2000; Boer et al., 2000; Aldakhilallah & Parente, 2002; Boselie, 2002) makes the point that adequate management of the human factor will produce positive effects, both in workers’ aptitudes (greater satisfaction, morale and commitment to their job) and in the organization’s performance (increased productivity, benefits and customer guidance). Thus, the companies that set out to be leaders in logistics management require new skills in their organizations and in their workers in order to make them more efficient and flexible (Nah, Lau & Kuang, 2001; Skok & Legge, 2002; Fiksel et al., 2004; McAdam & Galloway, 2005). In a similar vein is a study by Sloan, Becker and Hyland (2005), which underlines the need for the personnel themselves in the logistics area to take part in the ICT process in order to ensure its success. Continuing in the field of implementing innovations and the detail of adopting ICTs in the field, various authors have noted certain factors involved in success, as shown in Table 1. This table reinforces the importance of both setting up an adequate implementation methodology (e.g., by establishing an organizational structure integrating the required know-how and skills, at all levels of the organization, with a carefully designed plan that includes operational and strategic aspects) such as those of participation and commitment of the entire organization. Based on these success factors, the authors develop the research described in the following section. Looking more closely into the role of the personnel in this type of project, it is noted that in the recent literature, there is little research © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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with an in-depth approach to the relationship between an adequate management of human resources and success in implementing ICTs (Spell, 2001; Thierrien & Léonard, 2003), particularly in the area of logistics. In fact, works such as that by Sila and Ebrahimpour (2002) highlight the lack of studies researching the importance of logistics management in companies and other management activities such as human resources management. This lack in the recent literature also extends to the analysis of innovations (including the ICTs) in the logistics field, with the exception, for instance, of the works by Flint et al. (2005), Göpfert and Hillbrand (2005) and Darkow et al. (2006). Although there are few studies dealing with the relationship between human resources management and logistics management in distribution companies (Broersma & Segers, 2001; Soosay & Hyland, 2004; McAdam & Galloway, 2005), studies on manufacturing companies are even less common (Sloan & Sloan, 2006), which also motivates the authors when selecting the case studies in this paper.
Research Description Based on the deficiencies in the academic field and the description of the key aspects in the implementation process, the chief aim of this paper is to present, in a reasoned, detailed manner, a methodology for implementing ICTs in the logistics field, with a participatory approach in order to illustrate its application in two case study companies. Thus, as far as the methodology is concerned (see Table 2), the authors’ proposal is based on three main cornerstones: • Adopt an adequate organizational structure (based on two teams – implementation team and improvement team – with the coordination of a change agent; see Figure 1) involved in the implementation process for all company personnel, both in operations and in management. Under this organizational structure, the coordinating function of the change agent (research directly involved in project) is vital, both for the two internal teams and for the ICT suppliers. • Careful planning of activities to be carried out under the project: from the first stage of designing the project (including the definition of the objectives), covering the development and follow-up of meetings, to the closing stage. • A follow-up dynamics incorporating the best proposals from the users themselves.
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Table 1. Key Factors in ICT Implementation (Authors’ Compilation) N.
Key factor
1
Emphasis on the design process prior to implementation
2
Board commitment
3
Participation in the design and implementation processes by the personnel affected by change
4
Appropriate organization structure to support implementation Multi-skilled work team with clear functions
5 6
Selecting a suitable work methodology with quantifiable objectives
7
Suitable project management and follow-up
8
Understanding corporate culture in terms of making preparations and adapting to change Continuous communication to all levels in the company
9
10
11
Assigning resources for training personnel and for a swift response to their problems, queries or proposals for improvement Knowledge and availability of the technologies
This dynamic is synthesized both in the hard work of implementation and improvement teams (according to the previous planning) and by continuous communication to the entire organization on how the project is progressing.
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References Bancroft, Sep & Sprengel (1998); Nah, Lau & Kuang (2001); Skok & Legge (2002); McAdam & Galloway (2005) Bancroft, Sep & Sprengel (1998); Sauer (1999); Nah, Lau & Kuang (2001); Skok & Legge (2002); McAdam & Galloway (2005) Schroeder & Robinson (1991); Kanji & Asher (1993); Kotter (1996); Cheng (1997); Bancroft, Sep & Sprengel (1998); Michie & Sheehan (1999); Sauer (1999); Boer et al. (2000); Douglas, Lycke & Dobbie (2000); Lycke (2000); Boer (2001); Hanson (2001); Nah, Lau & Kuang (2001); Othman (2001); Skok & Legge (2002); Jørgensen (2003); Laursen & Foss (2003); Looise & Van Riemsdijk (2004); Soosay & Hyland (2004); Bondarouk & Looise (2005); McAdam & Galloway (2005); Jørgensen, Laugen & Boer (2006) Clark (1993); Boer (2001); Soosay & Hyland (2004) Bancroft, Sep & Sprengel (1998); Nah, Lau & Kuang (2001); Skok & Legge (2002); McAdam & Galloway (2005) Bancroft, Sep & Sprengel (1998); Nah, Lau & Kuang (2001); Skok & Legge (2002); McAdam & Galloway (2005) Clark (1993); Bancroft, Sep & Sprengel (1998); Sauer (1999); Boer et al. (2000); Boer (2001); Nah, Lau & Kuang (2001); Skok & Legge (2002); Looise & Van Riemsdijk (2004); Soosay & Hyland (2004); McAdam & Galloway (2005) Bancroft, Sep & Sprengel (1998); Nah, Lau & Kuang (2001); Skok & Legge (2002); McAdam & Galloway (2005) Bancroft, Sep & Sprengel (1998); Nah, Lau & Kuang (2001); Skok & Legge (2002); Looise & Van Riemsdijk (2004); McAdam & Galloway (2005) Clark (1993); Bancroft, Sep & Sprengel (1998); Nah, Lau & Kuang (2001); Skok & Legge (2002); McAdam & Galloway (2005) Sauer (1999); Appelbaum et al. (2000); Boer (2001); Spell (2001); Grugulis (2003); Soosay & Hyland (2004)
Table 2 shows the methodology proposed, in greater detail, including the links with the key success factors in implementing the ICTs described in Table 1. Along these lines, the cases study will illustrate specific aspects of implementation. In this regard, it is noted that © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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Table 2. Implementation Planning Proposed in Methodology Steps in implementation 1
2
3
4
5
The logistics information systems implementation project starts at a step where, on the one hand, the objectives are defined and, on the other, a preliminary diagnosis is made of the management of logistics activities, a task carried out by the Implementation Team. These initial steps include selecting the members of the Improvement Team, the symbolic reward in savings or achievements made by the Improvement Team (more recommended than economic compensation, in the view of the authors), the frequency, duration (one hour recommended maximum) and timetable for the meetings (key factors 1, 6 and 8). Once the objectives and preliminary diagnosis are established, the Implementation Team presents the project to the entire company. These presentations are made not only as a matter of courtesy and respect for people, but also, more especially, to gain the commitment of all to the project (key factors 2, 8 and 9). Subsequently, the This logistics diagnosis forms the basis used at the first meeting of the Implementation Improvement Team to orientate the work in the meetings: this diagnosis is Project and complemented, detailed and enlarged by the contributions from each of the follow-up of members of the Improvement Team by brainstorming. Based on this enlarged its results diagnosis, at each of the meetings, tasks are assigned to each of the members of the start up Improvement Team, such as analysis of processes, search for information, until the proposals for work methods or documentation of logistics activities aimed at proposed objectives solving the problems identified as well as structuring the needs, in detail, of the are achieved new information system supported by the ICTs (key factors 3 and 10). (key factors The members of the Improvement Team will take part directly in installing the new 3 and 7). information system (assisted by the suppliers selected by the Implementation Team) and in the tests needed to adjust the same, facilitating and speeding up the implementation of the ICTs while backing other colleagues in this learning stage (key factors 3, 10 and 11). The Implementation Team designs the information system in its more global and technical aspects, taking charge of the search and selection of the most appropriate suppliers (hardware, software and communications), in accordance with reliability, quality, cost and service criteria (key factors 10 and 11). Before the meeting of the Improvement Team, a meeting is held between the Implementation Team and the Improvement Team coordinator. This earlier meeting prepares the meeting of the Improvement Team, reviews the progress of the project to date (so that, in the team meeting itself, specific correctional measures can be taken, where applicable) and forthcoming actions to be applied are prepared. These prior meetings are extremely important as they make it possible to fix a heading to be followed by the project in order to achieve the objectives set within the estimated period (key factors 6 and 7). Furthermore, to make the meetings worthwhile, the information accompanying the work developed is presented prior to the meeting. The person or people responsible for the action present this information to the coordinator, who in turn ensures that all the members of the team have it at least one day prior to the meeting (key factors 3, 6 and 7). A further unquestionable aspect of interest is to make the agreements reached at the meetings known not only to the personnel in the section that does not belong to the Team, but also to the rest of the staff. For this reason, all measures to be taken and the evolution of the project are made known to all workers, by means of a poster or noticeboard explaining the project (key factor 9). Once the objectives have been achieved, the Improvement Team presents the results; this presentation is held at a meeting attended by all the company personnel, headed by the company management. Furthermore, a panel or noticeboard displays the results achieved to make them known to the rest of the company personnel. Making the results known plays a relevant role as a means of increasing awareness, of showing that the Improvement Team has been successful as well as to encourage the other members of the company to participate in the project and in future experiences in the context of continuous improvement (key factors 2, 3 and 9). Finally, the results achieved can be lost if, once the project is drawn to a close, there is no follow-up mechanism in force, a mechanism which is, furthermore, vital to continued improvement (e.g. frequent auditing without prior warning, frequent meetings of the Implementation Team personnel with the Improvement Team coordinator or frequent meetings with the personnel involved in searching for new improvements and solutions to existing problems related to the field of logistics (key factors 9 and 10).
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The Implementation Team is the central core around which the strategic system implementation plan rotates in both companies. This is responsible both for establishing the objectives and the strategic plan related to the project and to carrying out follow-up of its evolution. This involves a small number of people (ideally, including the management and/or those in charge of the production/logistics area and the “agents of change”)
The Improvement Team is set up in order to develop, at the most operational level, the strategic plan defined by the Implementation Team. The Improvement Team is multihierarchical (intermediary positions and operators) and is multifunctional, i.e., representing all the important logistics processes developed by the companies.
IMPLEMENTATION TEAM
ICTs suppliers are responsible for making available the technologies (key factor 11)
AGENTS OF CHANGE
IMPROVEMENT TEAM
ICTsSUPPLIERS
The “Agents of Change”are researchers responsible for coordinating all teams and suppliers involved in project. furthermore, researches attended as observers of the methodology
Figure 1. Organizational Structure for Implementing ICTs (Key Factors 4 and 5)
the case study approach study is appropriate when studying managerial processes, since boundaries of the phenomenon and its context are not clearly evident (Yin, 1994). So, implementing new information systems based on ICTs is a good example of this situation because of the complexity of the process and the multiple exogenous and endogenous variables to be considered in each company. The description and comments of these methodological aspects can facilitate the implementation of ICT in other companies and sectors, increasing knowledge of this issue. Given that one of the objectives is focused on analysing proposed methodology in companies, it is congruent with Yin’s argument (1994) that such research, when requiring no control over behavioural events, should be carried out with case studies. The qualitative approach and exploratory nature of the research question influenced the data-collection method. Research applying the qualitative approach is characterized by its commitment to collecting data from the context in which social phenomena naturally occur and to generating an understanding that is grounded in the perspectives of research participants (Miles & Huberman, 1984; Bryan, 1988; Marshall & Rossman, 1995). Going one step beyond this, the authors have adopted the ‘action research’ approach, directly participating in the implementation process in the companies selected. Thanks to this involvement, the researchers have the opportunity to witness the process, not only as mere observers, but also as real ‘agents of change’ in intervention and know-how compiling processes. The process of intervention (strengthening collaboration between the business and the academic world) is directly
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intended to solve a certain problem or deal with a certain problematic situation, whereas the know-how generating processes are appropriate techniques and methods to deal with interesting situations or problems due to their importance or the frequency with which they arise. Based on the volume of observations provided by the processes of intervention, a generalization can be made in one of two aspects: either the generalization of descriptive models based on frequently observed phenomena or, alternatively, the generalization of explanatory theories for such phenomena. In the study of the logistics systems, however, real-world observations are especially important in view of the existence of a number of difficulties that prevent their use in this field. The main difficulty is that it is impossible to conduct experiments in controlled environments and, later, to repeat the results. Several authors have supported the action research approach in the field of production/logistics. Therefore, works by Susman and Evered (1978), Warmington (1983), Meredith (1993), Platts (1993), Maull et al. (1995) and Prado-Prado (2000) are to be noted. Thus, the intention is not only to observe a given situation, but also to act on it in order to change it, logically with the consent of the companies, this being a pro-active investigation that unleashes processes of change in the organization, because they are considered to be beneficial, not only for the company but also for the worker, particularly if it involves a participative approach, as proposed in this paper. The knowledge compiled by researchers after the ‘intervention project’ can be discussed and shared with other companies and researchers. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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In this regard, the technique used for compiling the data in the two cases analysed was the participation by the authors in all Implementation and Improvement Team meetings (42 meetings, combining two kinds of teams as will be commented on later). This source of information was complemented with discussions between the authors and both companies’ directors at the beginning and at the end of the projects.
Case Studies The two companies analysed are Spanish manufacturers in the food sector (Pescanova Chapela and Grupo Iberconsa), and the reason for selecting these two companies was the fact that they had previously undergone traumatic implementations of new ICTs in areas other than in logistics (specifically, in the implementation of enterprise resource planning (ERP) ICTs in the commercial and financial area), which had left the organizations disillusioned and, in the opinion of their respective managements, had meant a negative predisposition among the workers towards the implementation of new ICTs. Both companies, however, although aware of improvements in logistics management by incorporating new ICTs, expressed their fears regarding new projects, which had delayed their implementation by a matter of years. Once the methodology had been presented and discussed with the company managements, both decided to take on the project. The projects covered a six-month period for Pescanova Chapela and a nine-month period for Iberconsa Group. Increasing pressure from competitors in the frozen foods market has forced both companies to improve their standards of quality, service and cost. This has particularly affected the flexibility of the production and logistics flows in Pescanova Chapela and the efficiency of the technical and human resources in Iberconsa Group (providing logistics services: supplies orders, storage, picking orders and delivery to clients). In order to achieve flexibility and efficiency, both companies applied two basic measures: to improve reliability of the information and to anticipate the availability of this information. Thus, the main objective of the ICT implementation projects was to improve the standards of quality, service and cost, by removing all the logistics documentation in paper format (‘zero papers’) by implementing a new information system based on barcodes and radiofrequency. Table 3 summarizes the reasons for implementing a new logistics system, a brief © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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description of the system implemented and the main results achieved.
Discussion and Conclusions Within the entrepreneurial field, implementing new information systems, especially in the logistics area, leads to real headaches and, as a general rule, the end result does not usually respond immediately to the expectations raised. Part of this dissatisfaction is caused both by the difficulty in equipping the information system with sufficient flexibility as required by the market (March, 1995; Boer & Gersten, 2003; Boer, Kuhn & Gersten, 2006) and by the slowness with which the organization learns how to use the new system (Aiman-Smith & Green, 2002). In order to reach or surpass a company’s expectations in a project involving implementing a new information system and to solve the problems outlined above, adopting an appropriate, reasoned methodology with a participatory approach, such as that used in the two cases studied, is one of the key factors. The methodology proposed (based on an appropriate organizational structure, a carefully designed work plan and a suitable follow-up dynamics) responds to the lack of detailed ICT implementation methods found in the literature. Nevertheless, this proposal is based on different recommendations contributed by various authors in the recent literature (see Table 1) regarding the implementation of ICTs, improvement of logistics management and, in general, implementing innovation in companies. This methodology, therefore, may be of interest both in the academic and professional world, particularly when it can be useful not only in projects involving the implementation of ICTs in the logistics field, but also it may cover other areas of entrepreneurial management. The fact that this methodology has been tested, with positive results, in two companies, illustrates this entrepreneurial interest, although it presents limitations linked with the low number of implementations. For these reasons, the authors propose that future research should deal with the development and analysis of this methodology for implementing ICTs in the field of logistics to make it possible to qualify or validate it more widely. Also, from an academic viewpoint, the function of the ‘change agent’ within the ‘action research’ approach is extremely interesting, since it makes it possible to consider real ‘laboratories’ when validating and improving exclusively theoretical methods.
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Table 3. Details of ICT Implementation Project in Both Companies
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Pescanova Chapela
The Iberconsa Group
General description
Pescanova Chapela, located in Vigo (northwest Spain), is one of the factories of the Pescanova Group. (It ranks among the top six fishing groups worldwide.) It has 280 employees and an approximate turnover of 39 million euros.
The Iberconsa Group, headquartered in Vigo (northwest Spain), is one of the most important freezer companies in the sector in Spain (the Group’s approximate turnover is 295 million euros and the total number of employees is 650). In order to deliver products to the market, the company has a logistics department in Vigo, with 23 people, with the support of a distribution platform. It is at this logistics platform that the company has implemented a new information system with ICT support.
Need for ICTs in logistics management
All the information flow between the company warehouses and the production lines were supported by handwritten papers (over 300 daily documents). All this information on paper was introduced (with many errors) into the initial information system (AS-400) on the following day. This information was available in the system too late for efficient logistics management. The complexity of logistics flow can be summarized in the number of finished products manufactured (over 800 references) and raw materials (over 1180 references), distributed among eight different internal stores, with no precise control over batches and where they are located (this depended on the knowledge of certain people). The warehouse personnel initially spent only 65% of their time on goods handling tasks (many movements without efficient planning), devoting 35% of the remaining time to searching for goods or to introducing the data into the information system.
Initially, all stock management, goods locating, picking orders and consolidating cargo between warehouses was carried out with little backing from the electronic information system (almost exclusively designed for commercial and financial management; a standard programme with support on UNIX and a ‘cache’ base). All these activities were therefore highly dependent on certain people (not even the best method for carrying out the work had been established), noting a high level of errors in locating goods and in the amounts or references served to customers, as well as frequent breakages of stock. The complexity of logistics flow can be characterized by the storage of an important quantity of products in external warehouses (the information among company and external warehouses was exchanged by telephone or fax) and the wide range of products that company markets, amounting to over 600 references.
Specific methodological aspects
An Implementation Team of seven people (the factory director, the head of logistics, the head of production, the head of administration, the head of management control and the two authors). An Improvement Team of 12 people (including the heads of the manufacturing lines, store and coldstore personnel and the authors). The Improvement Team coordinator was the Head of Manufacturing. The meetings, of which there were nine, were held in the afternoons, on a fortnightly/monthly basis for the six months of the project.
An Implementation Team of five people (the manager, the head of logistics, the head of administration and the two authors). An Improvement Team of eight people (the head of logistics, the two plant managers, two forklift truck operators, two commercial administration people and a truck driver and the two authors). The Improvement Team coordinator was the head of logistics. Meetings were held in the afternoons, totalling 12, with a weekly/ fortnightly/monthly frequency, over the nine months of the project.
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Table 3. continued Pescanova Chapela
The Iberconsa Group
Technical solution
The new system comprised a store management system (tailor-made software developed externally), a manufacturing lines control system (standard software), a production planning system and stocks management system (the latter two with tailor-made software developed internally). All these modules were linked with the AS-400 system, a computer program used for managing non-production/ logistics processes (general ERP). The new system used radiofrequency terminals to manage the stores, industrial computers to capture data in production lines, both devices with barcode readers and labelling printers with EAN 128 barcodes.
Since the current system supplier (a standard program with support on UNIX and a ‘cache’ base) already knew how the company functioned, said supplier made the decision to develop the new logistics system (in this case, a tailor-made measure). The new logistics system included functions of warehouse management (with location map of unit loads in the warehouse and the control algorithm to manage these locations), improvements in stock management and in transport management (including the exchange of goods among warehouses). The new system used radiofrequency terminals with barcode readers for managing warehouses and labelling printers with EAN 128 barcodes.
Some qualitative results
The work carried out by the Improvement Team in both companies made it possible to incorporate improvements in the functioning of the new information system from the user’s viewpoint, improvements in the field of planning the work and handling the goods between factories and stores, run tests with the new system and new equipment in order to detect malfunction problems, analyse them and convey them to the suppliers of software, hardware and communications to solve them. Also, work instructions and user manuals were developed on the new system, certain members of the Improvement Team being selected as ‘teachers’ for their colleagues in the use of the new information system.
The work carried out by the Improvement Team made it possible to incorporate improvements in the functioning of the new information system from the user’s viewpoint, improvements in the field of planning supplies, transport and exchange of products among warehouses, establishing optimum work methods (in terms of times, routes and the resources used) for the processes of unloading, coldstorage, preparing orders and dispatch. Also, work instructions and user manuals were developed on the new system, certain members of the Improvement Team being selected as ‘teachers’ for their colleagues in the use of the new information system.
Some quantitative results
All the ideas/problems (50) commented on by Improvement Team members in the first meeting were solved throughout the project. Implementing the new information system has entailed some savings (basically due to eliminating control based on paper management and by reducing errors in the flows of materials and information), which makes it possible to reimburse the considerable investment involved within a period of less than three years.
Out of the 126 ideas initially proposed by Improvement Team members in the first meeting, 75% were analysed and 62% were solved with effective measures that led to a more efficient functioning of the logistics area in the company. Implementing the new information system has increased productivity in the picking process by 46% (boxes per minute), decreasing the number of errors in this process which has made it possible to reassign the more efficient tasks and a more rational use of the technical and human resources.
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Furthermore, this participative approach can contribute not only to implementation, but also to the design process (Senge, 1990; PradoPrado, 2000). The participative approach applied by companies in designing the new logistics information system (which can be perfectly extrapolated to other companies) has been one of the primordial keys to its success, in terms of the efficiency of the new system and in the ease with which it was implemented. It is important to note that, although the functional design of the system was the decision of the Implementation Team, the Improvement Team took part in its operational design, from the initial stages of its development. In the case of the two companies studied here, the above statement is validated by the previous negative experiences in implementing other ICTs in both companies, where not all of the organizations were included in the project, neither in the design nor in the implementation process. Curiously, in both companies, the main difficulties in developing the project have been of a technical rather than human nature, which once again brings to light the advantages of this participatory approach. In fact, the advantages of the approach put forward go beyond the important improvement in the functioning of the logistics system, since the workers’ commitment and involvement make it possible to bring the organization into line with the ‘continuous improvement’ and ‘continuous innovation’ approach demanded by the market (Boer, Kuhn & Gersten, 2006), through an orderly questioning of the work methods and processes as well as assigning tasks and responsibilities. In this regard, despite the fact that the implementation of the ICT led to some fears in the organization (as they entailed reassigning functions as well as creating new positions and dismantling others), such changes were easier because both companies were growing and were able to channel redundant personnel into other company activities. Evidently, the use of a participatory approach such as the one proposed in the methodology described, may be counterproductive in a less favourable labour environment. Furthermore, the innovative behaviour of the workers in aspects of ICTs not only depends on an appropriate management of the human resources available, but also on the possibilities that these ICTs provide the workers in terms of being innovative (Steijn & Tijdens, 2005). Technological innovation by implementing ICTs in an organization works all the better, the greater is the receptiveness of the workers to incorporating new technologies
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(Boreham & Lammont, 2001; Steijn & Tijdens, 2005).
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Christopher, M. (1992) Logistics and Supply Chain Management. London, Pitman Publishing. Clark, J. (1993) Managing People in a Time of Technical Change: Conclusions and Implications. In Clark, J. (ed.), Human Resource Management and Technical Change, Sage, London, pp. 212–23. Closs, D.J., Goldsby, T.J. and Clinton, S.R. (1997) Information Technology Influences on World Class Logistics Capability. International Journal of Physical Distribution & Logistics Management, 27, 4–17. Darkow, I.-L., da Mota Pedrosa, A. and von der Gracht, H. (2006) Scenario-Driven Innovation Management for Logistics Service Providers. CINet 2006, 302–13. Dornier, P.-P., Ernst, R., Fender, M. and Kouvelis, P. (1998) Global Operations and Logistics: Text and Cases. Wiley, Hooken, NJ. Douglas, A., Lycke, L. and Dobbie, J. (2000) Implementing the Japanese 5S practice. Proceedings of the Ninth International Conference on Productivity and Quality Research, ICPQR 2000, Jerusalem, Israel, pp. 279–84. Fiksel, J., Lambert, D.M., Artman, L.B., Harris, J.A. and Share, H.M. (2004) The New Supply Chain Edge. Supply Chain Management Review, 8, 50– 7. Flint, D., Larsson, E., Gammelgaard, B. and Mentzer, J. (2005) Logistics Innovation: A Customer Value-Oriented Social Process. Journal of Business Logistics, 26(1), 113–47. Göpfert, I. and Hillbrand, T. (2005) Innovationsmanagement für Logistik-Unternehmen, Jahrbuch der Logistik 2005, Düsseldorf, Verlagsgruppe Handelsblatt Fachverlag, pp. 48–53. Grugulis, I. (2003) Putting Skills to Work: Learning and Employment at the Start of the Century. Human Resource Management Journal, 13, 3–12. Gunasekaran, A. and Ngai, E.W.T. (2004) Virtual Supply-Chain Management. Production Planning and Control, 15, 584–95. Hanson, J. (2001) Implementation of TQM in Small Organizations, Experiences from Award Winners in Sweden. Licentiate Thesis 2001: 13, Luleå University of Technology, Luleå. Introna, L.D. (1991) The Impact of Information Technology on Logistics. International Journal of Physical Distribution & Logistics Management, 21, 32–7. Jørgensen, F. (2003) A Journey through SelfAssessment, Group Learning, and Continuous Improvement. PhD thesis, Center for Industrial Production, Aalborg University, Denmark. Jørgensen, F., Laugen, B. and Boer, H. (2006) Human Resource Management for Continuous Improvement. CINet 2006, 443–54. Kanji, G.K. and Asher, M. (1993) Understanding the Change Process. Total Quality Management, 4, 19–20. Kotter, J.P. (1996) Leading Change: Why Transformation Efforts Fail. Harvard Business Review, 73, 59–67. Langley, C.J. Jr. (1986) Information-Based Decision Making in Logistics Management. International Journal of Physical Distribution & Materials Management, 15, 41–55. Laursen, K. and Foss, N.J. (2003) New Human Resource Management Practices, Complementa© 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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rities, and the Impact on Innovation Performance. Cambridge Journal of Economics, 27, 243–63. Looise, J.C. and van Riemsdijk, M. (2004) Innovating Organisations and HRM: A Conceptual Framework. Management Revue, 15, 277–88. Lycke, L. (2000) Implementing Total Productive Maintenance, Driving Forces and Obstacles. Licentiate Thesis 2000: 15, Luleå University of Technology, Luleå. McAdam, R. and Galloway, A. (2005) Enterprise Resource Planning and Organisational Innovation: A Management Perspective. Industrial Management & Data Systems, 105, 280–90. March, J.G. (1995) The Future, Disposable Organizations and the Rigidities of Imagination. Organization, 2, 427–40. Marshall, C. and Rossman, G.B. (1995) Designing Qualitative Research, 2nd edn. Sage, Thousand Oaks, CA. Maull, R.S., Weaver, A.M., Childe, S.J., Smart, P.A. and Bennett, J. (1995) Current Issues in Business Process Re-engineering. International Journal of Operations and Production Management, 15, 37– 52. Meredith, J.R. (1993) Theory Building Through Conceptual Methods. International Journal of Operations and Production Management, 13, 3–11. Michie, J. and Sheehan, M. (1999) HRM Practices, R&D Expenditure and Innovative Investment: Evidence from the UK’s 1990 Workplace Industrial Relations Survey. Industrial and Corporate Change, 8, 211–34. Miles, M.B. and Huberman, A.M. (1984) Qualitative Data Analysis. A Sourcebook of New Methods. Sage, Thousand Oaks, CA. Nah, F., Lau, J. and Kuang, J. (2001) Critical Factors for Successful Implementation of Enterprise Systems. Business Process Management Journal, 7, 285–97. Othman, R. (2001) Antecedents and Outcome of IT Use: How does HRM fit in? Asia Pacific Management Review, 6, 91–103. Piplani, R., Pokharel, S. and Tan, A. (2004) Perspectives on the Use of Information Technology at Third Party Logistics Service Providers in Singapore. Asia Pacific Journal of Marketing and Logistics, 16, 27–41. Platts, K.W. (1993) A Process Approach to Researching Manufacturing Strategy. International Journal of Operations and Production Management, 13, 8. Prado-Prado, J.C. (2000) El proceso de mejora continua en la empresa. Ed. Pirámide, Madrid. Sauer, C. (1999) Deciding the Future for IS Failures not the Choice you Might Think. In Currie, W. and Galliers, R. (eds.), Rethinking Management Information Systems, Oxford University Press, Oxford, pp. 279–309. Schroeder, D. and Robinson, A. (1991) America’s Most Successful Export to Japan: Continuous Improvement Programs. Sloan Management Review, 32, 67–81. Senge, P.M. (1990) The Fifth Discipline. The Art and Practice of the Learning Organization. Doubleday, New York. Sila, I. and Ebrahimpour, M. (2002) An Investigation of the Total Quality Management Survey Based Research Published between 1989 and
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2000. A Literature Review. International Journal of Quality & Reliability Management, 9, 902–70. Skok, W. and Legge, M. (2002) Evaluating Enterprise Resource Planning (ERP) Systems using an Interpretive Approach. Knowledge and Process Management, 9, 72–80. Sloan, K. and Sloan, T. (2006) Logistics and Continuous Improvement – Their Influence on Developing Organizational Competencies and Competitive Advantage. CINet 2006, 708–19. Sloan, T., Becker, K. and Hyland, P. (2005) CI in the Workplace: Does Involving the HR Function Make any Difference. 6th International CINet Conference Continuous Innovation – (Ways of) Making Things Happen. Brighton, England. Soosay, C.A. and Hyland, P.W. (2004) Driving Innovation in Logistics: Case Studies in Distribution Centres. Creativity and Innovation Management, 13, 41–51. Spell, C.S. (2001) Organizational Technologies and Human Resource Management. Human Relations, 54, 193–213. Steijn, B. and Tijdens, K. (2005) Workers and their Willingness to Learn: Will ICT-Implementation Strategies and HRM Practices Contribute to Innovation? Creativity and Innovation Management, 14, 151–9. Susman, G.I. and Evered, R.D. (1978) An Assessment of the Scientific Merits of Action Research. Administrative Science Quarterly, 23, 582–603. Thierrien, P. and Léonard, A. (2003) The Evolving Workplace Series Empowering Employees: A Route to Innovation. [WWW document]. URL http://www.hrdc-drhc.gc.ca/sp-ps/arbdgra/publications/research/2002docs/eeari/e/ eeari_E_0.shtml.
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Warmington, A. (1983) The Nature of Action Research. In The efficiency of manufacturing systems, NATO ARI Series. Plenum, New York, pp. 51–60. Wisner, J.D., Leong, G.K. and Tan, K.-C. (2005) Principles of Supply Chain Management: A Balanced Approach. Thomson, Mason, OH. Yin, R.K. (1994) Case Study Research. Design and Methods. Sage, Thousands Oaks, CA.
Jesús García-Arca (
[email protected]), PhD, an industrial engineer, is currently a lecturer in business administration at the School of Industrial Engineers at the University of Vigo, Spain. He has 11 years’ experience as a consultant in JIT, TQM and continuous improvement projects for several Spanish firms. He is a member of EurOMA, POMS and CINet. J. Carlos Prado-Prado (jcprado@ uvigo.es), PhD, an industrial engineer, is currently a Professor of production management and marketing at the School of Industrial Engineers at the University of Vigo, Spain. He has conducted seminars and conferences in JIT, TQM and continuous improvement and has 19 years’ experience as a consultant in this subject for many Spanish firms. He is member of AQP, ASQ, APICS, IIE, POMS, EurOMA, CINet and AMA.
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The Implementation of Best Practices: Process and Performance Effects Bjørge Timenes Laugen and Harry Boer Much has been written about best practices and world class manufacturing in recent years. Various practices and improvement programmes have been suggested as best practices, assuming that their adoption would to lead to higher performance. The implementation process of these practices is, however, often neglected in the literature and, hence, relatively poorly understood. The purpose of this article is to provide insight into that process and how different implementation approaches influence performance. An analysis of the implementation of a range of manufacturing action programmes in two companies showed that a broad and incremental implementation approach initially leads to reduced performance followed by a gradual improvement as larger parts of the programmes are institutionalized. A ‘big bang’ implementation approach does not seem to lead to deterioration in performance.
Introduction and Research Questions
T
oday’s firms operate in increasingly complex and rapidly changing environments, and the ability to change and innovate is becoming more and more important. New players start competing in established markets, new technologies emerge, and new business models strive for dominance even in mature markets. There is considerable evidence that established companies struggle to adapt to major changes in the environment. Studies by, for example, Christensen (1997), Francis and Bessant (2005), Tripsas and Gavetti (2000) and Lant and Mezias (1990) all suggest that established players often fail to respond to changes in the environment when new technologies, actors or markets emerge. Thus, it is important for managers and academia to develop useful, usable and robust knowledge, methods, tools and techniques allowing established companies to cope better with major changes in the environment. Both industry and academia have been concerned with developing and searching for best practices for decades. Best practices have been argued to underpin high or even world-class performance (e.g., Schonberger, 1986; Flynn et al., 1997; Voss, Åhlström & Blackmon, 1997) © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
and should therefore play a dominant role in manufacturing strategy (Voss, 1995). The implementation process of new practices is critical for the success of these programmes. Bessant and Francis (1999) and Savolainen (1999) even argue that it may not be the concept itself, but the way it is implemented that is essential for success. Furthermore, Davies and Kochhar (2002) suggest that the performance benefits of implemented practices increases the nearer they reach full implementation. Many studies have been carried out to better understand the implementation of best practices in manufacturing. Among the topics investigated in such studies are: • differences between small and large companies in the implementation of continuous improvement (Chapman & Sloan, 1999) • differences between advanced and developing countries in the implementation of enterprise resource planning (ERP) (Huang & Palvia, 2001) • success factors in ERP implementation (Nah, Lau & Kuang, 2001) • use of internet technology in implementing business process re-engineering (BPR) (Wells, 2000) • team learning and implementation of technology (Edmondson, Bohmer & Pisano, 2001)
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• implementation of total quality management (TQM) in the service industry (Huq, 2006) • implementation and persistence of TQM (Beer, 2003). Despite the considerable amount of implementation studies, they do not provide a complete understanding of the implementation process of (best) practices and the challenges and results of the implementation phase. Most studies assess implementation success in terms of, for example, how much of the programme has been adopted in the organization, rather than the performance effects of the programme itself. A problem with measuring performance effects is that there is often a time lag from beginning of implementation until performance effects are visible. Some authors, e.g., Gertsen (2001) and Pettigrew et al. (2003), even find that performance deteriorates during the early phases of the implementation of new concepts before performance gradually improves. It is not clear exactly why this happens, but one explanation could be that implementing a new practice requires the organization to learn. The time and cost involved in that go at the expense of operational and/or business performance. To address some of the problems addressed above, the research presented in this article aims to investigate the following questions: • How do best performing companies implement new practices? • Does the way such companies approach the implementation process affect performance and, if so, how? The first question stems from the observation that ‘best practice is what the best companies do’ (Laugen et al., 2005). In today’s market and competitive environment, the best companies are the ones that excel in terms of exploration (innovation, change) and exploitation (produce and deliver, improve) (Stacey, 1992; March, 1995; Boer & Gertsen, 2003). The second question investigates whether and, then, how implementation approach makes a difference in terms of performance effects. In addressing these questions we will regard the implementation of improvement programmes as a process. Hence, we are interested in investigating how the companies approach (e.g., ‘big bang’/turnkey or small steps), resource and manage this process, and how these choices affect the operational performance of firms. We focus on the implementation of improvement programmes within the new product development and manufacturing
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functions, or programmes in which these functions are involved.
Methodology As the research questions call for exploratory research, a case study presented the most suitable methodology. We decided to perform two case studies which we selected using two criteria. First, we aim to investigate high performers, measured in terms of sustained outstanding financial performance and market leadership. Second, since the scope of this research is on continuous innovation, it is important that the case companies perform product development and production activities, carry out improvement activities of these functions on-site, and have done so successfully during the last 10–15 years. This is because a major part of the challenge of continuous innovation is the balance and coordination between stability and change, between production and product innovation, and between exploitation and exploration. Furthermore, as most of our research is focused on medium-sized and large manufacturing and assembly companies (ISIC 28-35) in Denmark and Norway, we found it most convenient to select our cases in these industries. Two companies, one in Denmark and one in Norway, met our criteria. Both companies are market leaders in their respective segments, have been financially successful over the last several years, and have an excellent track record in new product development (exploration) as well as production and delivery (exploitation). The case narratives provide further details. Data was generated through interviews with three managers in each company. In total, 11 semi-structured interviews were conducted during the winter 2004/2005, spring and summer 2005. In Company A, the new product development (NPD) (once), new product introduction (NPI) (once) and production (twice) managers were interviewed. In Company B, the NPD (once), the product (twice) and manufacturing (four times) managers were interviewed. The interviews were conducted on-site following a semi-structured interview guide. The duration of the interviews varied from 45 minutes to more than two hours. Six of the eleven interviews were audio-taped and then transcribed in full-length for data analysis purposes. Thorough notes were written from the other five interviews. We performed, transcribed and analysed all interviews ourselves, in order to reduce the risk of misunderstandings and to benefit from the information rich© 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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ness an interview context provides. In addition, reports and documents from the companies were analysed in order to crosscheck information from the interviews and get additional information. The data were structured in tables similar to the checklist matrix, as suggested by Miles and Huberman (1994). To validate the case studies, analyses and findings, the case narratives, cross-case analysis and discussion were sent to all the six managers for review. In addition, the findings and interpretations were also presented to and discussed with one of the managers. The feedback we received was taken into account and the manuscript changed accordingly. The suggested modifications from the managers were few and minor, though. For reasons of anonymity, the case companies are labelled Company A and Company B. The two companies are briefly described below.
Case Company A Company A, located in Denmark, is a large and established manufacturer of technologically moderately advanced products. It can be classified as an ISIC 28 manufacturer of metal products. The company operates in a businessto-business environment and primarily delivers products to the high end of the market. Quality is the most important order winner, followed by technological features and price. NPD and manufacturing are carried out at the same location and are integrated through a new product introduction process. Company A is ISO 9001, 9002, 14001 and 18001 certified, and has received a large number of awards and prizes for operational excellence over the years. Most products are mass manufactured to stock. Only two percent is manufactured to order. However, the plant is moving towards production to customer order. The company has been high performing for a number of years, is worldwide market leader in its market segment and is well reputed. There are only four major competitors in the European market.
Case Company B Company B, located in Norway, is a mediumsized/large manufacturer of technologically advanced products. It can be classified as an ISIC 29 manufacturer of machinery and equipment. The products are sold in a business-tobusiness environment. Company B’s primary focus is on product quality and, to a lesser extent, delivery and cost. This performance focus is widely communicated throughout the © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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organization. NPD and manufacturing are located in the same building. All products are manufactured or assembled to order, and a considerable albeit declining part is designed to order. During recent years, Company B has outsourced parts of its production activities, but is still doing a considerable part of the component manufacturing in-house. The target is to outsource most of the manufacturing tasks and to keep only final assembly and testing in-house. The company has performed very well financially for many years. Its market share worldwide is approximately 25–30 percent. In Europe the market share is around 40–45 percent. Company B’s products have an outstanding performance and are well reputed.
Findings Action Programmes Currently Implemented in the Case Companies The two case companies perform a wide range of action programmes in order to improve their manufacturing performance (see Table 1 for an overview). The two companies are conscious of the need to implement different action programmes that reinforce each other, in order to achieve a higher level of performance improvement. The production managers in both companies argue that implementing single action programmes would have considerably lower performance effects, compared to when configurations of programmes are implemented. In Company A, 6 sigma, TPM (total productive maintenance), SMED (single minute exchange of die) and process leadership are implemented together in order to support the company’s ambition to achieve lean production. The production manager argues that it is absolutely necessary to see the programmes as a configuration, and that individual programmes will lead to a lower level of improvement than when they are supported by other programmes. In addition, various other programmes support the implementation of the other programmes. The company is currently reviewing its manufacturing strategy and performing a competence mapping process in relation to this. Further, Company A has been running a TQM programme for approximately ten years, which, according to the managers interviewed, has developed a culture for change and improvements in the organization. Finally, reviewing and improving the flow and processes through the implementation of CFM (continuous flow manufacturing) and SAP R/3 are again supporting the lean production programme.
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Table 1. Current Action Programmes in the Manufacturing Activities of Companies A and B Company A SAP R/3 Continuous flow manufacturing (CFM) 6 sigma Total productive maintenance (TPM) Process management TQM SMED Manufacturing strategy Strategic competence mapping
In Company B, lean production has been introduced in order to reduce lead time by 50 percent and increase productivity by 50 percent. However, the company realized that these development targets could not be reached without ensuring that the information and material coming into production from the development department and external suppliers had the right quality and were delivered on time. Consequently, they started up an improvement activity parallel to the lean activity, aimed at improving the quality, specifications and delivery reliability of raw materials. So, Company B uses several other programmes, including 5S, kaizen and flow management, to support and reinforce its lean ambitions. In addition, Company B also uses programmes in order to improve visual management and control, and prototyping in relation to lean production. Supporting the lean production, more general programmes are also implemented, more specifically organization design, internal communication, training employees in lean thinking, and project management.
Implementation in Company A For most action programmes, Company A uses a broad and incremental implementation approach. The production manager argues that the incremental approach is more successful than a ‘big bang’ approach, which Company A has experienced to be too overwhelming. An exception is the SAP R/3 programme, which was rolled-out full scale in the whole organization at the date of the launch. Regarding depth of implementation, in order to achieve their potential benefits, Company A normally implements all parts of
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Company B Visual management Prototyping Kaizen Total productive maintenance (TPM) Flow management Organizational (re-)design Communication Training Project management Product specifications Material quality Reliable deliveries (from suppliers)
the programmes they start. In addition, the company does not normally have problems continuing the implementation of the programmes even though the expected results are not immediately apparent. The production manager argues that persistence is very important when it comes to the implementation of large improvement activities. Top management is committed to and supports this strategy. Furthermore, he claims Company A is very good at allocating resources to implementing improvement activities. The production personnel get dedicated time to work on the implementation process as well as improvement activities. The production manager stresses the importance not only of educating people in the various activities, but also of allocating a considerable amount of time to spend on implementation. For example, the operators on the shopfloor have days available to work with TQM and evaluate the implications of this programme for their daily work. The level of detail with which the implementation of the different programmes is planned varies. For example, the SAP R/3 implementation was planned in great detail, and had an accurate date for when the implementation should be completed and launched within the organization. For the other programmes, the implementation was planned more loosely, and the driving forces of these programmes were overall goals and targets, often long term. The production manager finds it difficult, and has no intention, to set an end date for the implementation of lean manufacturing or to plan in great detail the implementation towards this end date. Instead, the various programmes have different targets and the planning of the implementation © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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Table 2. Scorecard for Operational and Financial Performance of the Component Manufacturing Department in Company A for the Period 2002–2005 (Achieved) and the Year 2005 (Target) Performance indicators
2002
2003
August 2004
2004
August 2005
Target 2005
Delivery to shipment Delivery to internal customers Delivery reliability supplier Absence Accidents per million working hours Machine efficiency (increase) Man efficiency (increase) Scrap (ppm) Profit before tax
92.3% 94.6%
93.8% 94.3%
90.3% 91.3%
91.3% 92.8%
91.1% 90.7%
95.6% 95.6%
90.9%
93.6%
90.8%
91.7%
NA
NA
7.6% 30
6% 20
5.4% 39.2
5.7% 35.9
5.6% NA
4.5% NA
3.9%
4.8%
1.9%
0.2%
5.8%
7.0%
3.8% 10313 5.4%
5.6% 8253 2.3%
-1.2% 9728
-1.0% 10118 7.4%
NA 9347 NA
NA 8500 NA
Note: NA = not available.
process is reviewed continuously based on experiences from phases completed so far and progress made.
Performance Effects As Table 2 indicates, none of the selected performance indicators reached their targets for 2004. One reason for this is that several of the targets were justified in 2004, based on a general improvement in performance from 2002 to 2003. However, even compared with 2003, the performance on all indicators but one (absence) deteriorated in 2004. To understand the figures, it is important to mention that annual turnover was significantly higher than expected in both 2002 (13.3%) and 2004 (34.8%), while on budget in 2003. This caused man efficiency to drop as temporary employees or personnel from other departments had to be used, who were insufficiently experienced in the tasks to be accomplished. The company’s profit before tax improved significantly in 2004 compared with 2003 despite poorer operational performance. The performance figures for 2005 produce a more promising picture. Absence, machine efficiency (productivity) and scrap improved compared to 2004, although only machine efficiency exceeded target. Only the figures for delivery performance deteriorated in 2005 compared with 2004. However, when investigating the figures more carefully, the performance for most of the year 2005 (January– May) is around or above target, while in June the delivery to shipment performance fell to © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
below 70 percent. According to the production manager, the reason for this is that after implementing SAP R3 in June, they have had problems gathering data that fit into the new measurement system. So, the decrease in the figures is not a consequence of poor performance, but primarily due to problems with measuring and fitting the data into SAP R3. In other words, Company A’s performance in general improved in 2005 compared with 2004.
Implementation in Company B A project group with a full-time project manager leads the implementation of the ‘lean production’ programme. The project manager used to be foreman in the production department and has considerable experience within the company. Even though a project group runs the programme, there is broad involvement from the rest of the organization. This is partly achieved by the ‘lean production’ programme moving through production and gradually rebuilding existing production cells into production lines, and partly through informing and training the workers. So far, 90 employees have been trained in (elements of) lean thinking. Regarding time resources, most of the activities in the ‘lean production’ programme are carried out in addition to the normal workload. Both the NPD and the production manager indicate this causes the implementation of ‘lean production’ to be set aside in periods with peak production. According to the production manager, this is not a major
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problem since the transformation and rebuilding of production happen gradually and do not involve many people simultaneously. With the focus on and effort put into a significant number of relatively large and challenging programmes, Company B is currently going through a radical change of its production system. The production manager argues that this is a consequence of too little improvement efforts over recent years. However, he foresees that these activities will create an understanding and culture for performing improvement activities on a more continuous basis. The production manager says that the implementation of the action programmes has created many positive spin-offs. The most important concerns increased cross-functional understanding that coordinated improvement activities are necessary to improve overall company performance. One element in this is more careful control of the delivery and quality performance of suppliers and component production in order to improve lead time. Another is the understanding that product management and NPD must provide more complete specifications in order for final assembly to reach the overall performance targets. If problems occur during the implementation phase and/or the results are disappointing, Company B will continue the process. The production manager says that consistency and persistence are important, and he believes that the targets pursued will pull the programmes through. The product manager argues that the implementation of the programmes will continue after the scheduled end date if the expected results are not achieved. In other words, the targets of the programmes are fixed, and Company B intends to achieve these targets, even if the duration of the programmes has to be extended. According to the three managers, the four improvement programmes are deliberately implemented together because they are related and fit quite well together. In addition, the programmes partly supply conditions for each other. One example is that ‘start right’ will lay the foundation for ‘lean production’ by providing high-quality raw material and product specifications. Furthermore, increased product standardization through ‘GO 80’ will increase the benefit of ‘lean production’. The three managers also agree in their belief that the organization is capable of performing these four large programmes simultaneously. The organization is quite willing to change, and they feel this is an important quality in order to succeed in the implementation of the improvement activities.
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Performance Effects On-time delivery (OTD) deteriorated slightly from the end of 2003, from a level where around 90 percent of products were delivered on time, until around August 2004, after which it stabilized at a level of around 78 percent delivered on time. According to the production manager, the main reason for the negative trend was increased focus on quality, delivery and cost (Q-D-C). Previously, delivery was considered more important than quality and cost. Despite being a secondary priority compared to delivery, quality performance was not particularly poor. However, delivery often went at the expense of cost performance. Because of the repositioning of quality and cost relative to delivery, delivery performance has decreased somewhat during the last two years, but is expected to increase again as the implementation of the various action programmes progresses. In addition to the slightly negative trend, there are a couple of periods with very poor OTD performance during the period January 2003–June 2005. According to the production manager, this was due to the relatively high number of orders that required customization or even design-to-order, and the specification of these projects arrived relatively late in the assembly process. This required a lot of rework, so that the products were not delivered according to plan. As mentioned previously, one of the overall targets of the action programmes is a 50 percent productivity increase by the end of 2006. Productivity had increased by 2.5 percent by December 2004 and by approximately 10 percent by June 2005, both relative to January 2004. The target for December 2005 is a further increase of 12.5 percent. According to the production manager, Company B is progressing according to plan in order to achieve this target. The main reason for improved productivity is reduced use of temporary employees, meaning that the same amount of work has to be done with fewer resources. In addition, the visual management activity emphasizes frequent revision of the performance figures, which encourages and motivates managers and shopfloor workers to improve these figures continuously. The 50 percent productivity increase by December 2006 is an ambitious target. The largest part of this increase will take place during 2006 after the rebuilding of the production facility, and productivity is expected to increase gradually when larger parts of the ‘lean production’ programme are implemented. Despite the ambitious target, the © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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production manager is convinced that Company B will achieve it.
Cross-Case Analysis This section analyses and discusses how the action programmes are implemented in the two case companies. The focus is on the implementation approach, the allocation of resources and performance effects.
Small Steps Versus the ‘Big Bang’ Approach Operational performance in Company A deteriorated from 2003 to 2004. Moreover, the target was not reached for any of the reported performance indicators in 2004. The disappointing performance effects might be due to the fact that Company A uses (a) a broad and incremental implementation approach of (b) essentially company-wide programmes. This means that it takes a while for the programmes to be implemented and for the transformation of the (entire) organization to fall into place. In 2005, most performance figures started to improve, which indicates that the implemented programmes in Company A have now started to pay off. In Company B, there is some variation in implementation approach. Some of the programmes are introduced following a ‘big bang’ approach, e.g., the lean implementation programme, a complete restructuring of the production, which is scheduled for completion in one and a half years. On the other hand, the implementation of TPM is introduced in small steps, starting with 5S. It is still too early to say anything regarding the performance effects of the lean programme, since the rebuilding of the factory started in the autumn of 2005. Delivery performance deteriorated somewhat during 2004 due to the higher focus on costs and quality going at the expense of delivery. From late 2004 and during 2005, delivery performance stabilized. This is probably due to the ‘start right’ programme, which is starting to gain effect through more reliable deliveries from suppliers and better quality of incoming materials. The lack of performance improvement in 2004 for Company A is also visible for those programmes in Company B that are implemented incrementally. As an example, both companies started with 5S as their approach to TPM. 5S is a suitable step-up to train workers in and prepare the organization for more challenging elements of TPM while they produce immediately visible results (good housekeeping). The effects on operational performance, however, are limited. The main reason for this © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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is that the company spends resources in training people in 5S, and sets aside time for the personnel to work on the action programme instead of focusing solely on their ordinary tasks. Achieving broad involvement of all workers within the organization also takes time and, hence, the performance effects do not appear immediately. According to the production manager, the reason for the small-step approach in Company A is that the company has had bad experiences with previous ‘big bang’ approaches. In their experience, such an approach is too much for an organization to cope with, while it is easier to succeed with a small-step approach. In contrast, the lean implementation in Company B can be classified as a ‘big bang’ project. According to the production manager, the decision to restructure the production radically now is due to two aspects. First, there have been relatively few improvement activities in recent years; hence there is a need for a step change. Second, cost aspects are becoming more important – competitors have started to produce affordable high-quality products too. Furthermore, the company has problems keeping its export volume high due to currency fluctuations. As mentioned earlier, Company B plans to complete the lean implementation at the end of 2006. After this step change, Company B intends to have ongoing improvement activities in order to maintain and gradually improve the performance of the plant. To achieve this, a more incremental approach will be chosen.
Resource Allocation Another reason for poor performance in the early phases of implementation in Company A is related to the balance between, and allocation of resources to, improvement and day-today activities. Company A performs a wide range of action programmes, many of which are company-wide and involve a lot of people. Especially in production, this can take the focus away from the day-to-day operations. According to the production manager, the improvement activities have high priority and are followed up, monitored and supported by top management. The production personnel are given dedicated time to work on the improvement activities. Consequently, a decrease in productivity and other performance criteria is probably unavoidable. This, however, is not the case in NPD, where the action programmes are performed in addition to normal activities. In NPD, however, it is too early to say anything regarding the effects on performance. As the process/flow manage-
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ment programme, which is the dominant action in NPD, has started with a mapping of the internal processes during 2004, the changes and improvement of the processes were not due to be effectuated until the end of 2005. The implementation of action programmes in Company B is also in addition to the workers’ ordinary tasks. Consequently, the implementation of improvement activities might be delayed in periods with more customer orders than usual. Company B has experienced this during the spring of 2005, where it has been necessary to put the improvement activities aside in order to maintain consistency in the strategic priorities (qualitydelivery-cost). In such situations, delivery (short-term priorities) gets priority over improvement activities (long-term priorities). Company B has experienced an increase in productivity in 2004 and during spring and summer 2005. However, with the number of action programmes currently under way, it would be reasonable to expect a decrease in productivity, similar to what we saw in Company A. This did not happen in Company B, which is probably because the workers do the implementation in addition to their ordinary tasks. Therefore, the improvement activities do not greatly influence the day-to-day activities. Rather, the influence is the other way around, i.e., there is a risk that the focus on day-to-day activities leads to a delay in the implementation of action programmes in Company B. At first sight, Company B’s way to allocate the resources, on top of normal tasks, seems to be the more successful of the two approaches. The question, however, is whether this approach is also successful and sustainable in the long term. Greater pressure on the employees is unavoidable, and it is questionable whether the organization can maintain the implementation of action programmes for a long period under such conditions.
Performance Development during Implementation There is a clear time lag between the (start of the) implementation and performance effects in both companies. Both production managers are aware of that and stress the importance of persistence, of not stopping the implementation even if the programmes do not pay off in the short term. The findings indicate that both case companies are now starting to gain positive performance effects of the implemented action programmes. In Company A, most operational measures are stabilizing or improving after a period of
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deterioration. There are two probable reasons for this. First, the programmes are being institutionalized and a part of the day-to-day activities in the firm, and new processes and ways of working are being established in the organization. Second, in later phases of the implementation more elements of the programmes are institutionalized, and, hence, more influential on performance. Most programmes really start to pay off when they are fully implemented (Bessant & Francis, 1999; Davies & Kochhar, 2002). In Company B, delivery performance has stabilized after slightly deteriorating during the earlier phases of the implementation of the programmes. In contrast, lead-time performance and productivity gradually increased during the same period, indicating that the implemented programmes have started to pay off more or less from the start.
Discussion There is little theory on performance effects during the implementation of (configurations of) action programmes. One of the few publications addressing this question is Gertsen (2001), who reports that firms experienced in continuous improvement perform better than firms which have just started the implementation of a continuous improvement programme. Medium experienced firms, however, are performing lower than both inexperienced and experienced firms. This is in line with Pettigrew et al. (2003), who argue that substantial time, patience and persistence are necessary for complementary changes to take effect. These authors report that performance effects follow J-curves, i.e., deterioration during the first part of the implementation of the programmes followed by gradual improvement to a level higher than before the implementation started. We find elements of the same development of performance throughout the implementation in our study. While the authors referred to above do not explain the performance effects they observed, our analysis suggests a strong link with implementation approach. We identified four approaches (see Table 3). The first approach, adopted in both companies, is an incremental, small-step, implementation process, with widespread employee involvement. The implementation activities are a formal part of the employees’ day-to-day work. This approach leads to disappointing performance effects in the early phases of the programme in terms of productivity/ efficiency, delivery and quality. The most likely explanation for this is that the early steps tie up © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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Table 3. Different Approaches to Implementation of Action Programmes in the Two Case Companies Part of the job
Add-on to the job
Incremental
Company A (most manufacturing programmes); Company B (TPM programme) 䊏 ‘hockey stick’ effect on operational performance 䊏 unpredictable project lead-time – learning has priority over operational performance
Company A: process streamlining/ management in new product development 䊏 difficult to maintain focus on implementation of programme
‘Big-bang’
Company A: SAP R/3 programme 䊏 decrease in delivery performance after launch, but rapidly increasing, and much less decrease/troubles than other similar companies experience after SAP R/3 launch
Company B (most manufacturing programmes) 䊏 positive effects on operational performance (delivery and productivity) 䊏 unpredictable project lead-time – operational performance has priority over project implementation
resources rather than produce results. Once a single action programme or a configuration of programmes takes shape and the new work routines are institutionalized, performance improvements begin to show. Thus, as there is a considerable time lag before the performance effects are visible, persistence in the implementation process is critical for the success of the programme. The second mode is a ‘big bang’ approach where the workers, led by a full-time dedicated project manager, carry out the improvement programmes in addition to their normal tasks. Adopted to implement most production improvement programmes in Company B, this approach leads to gradual performance improvements throughout the implementation phase. However, operational performance is considered most important. So, in times of high customer demand, the implementation and improvement activities are less emphasized or put on hold for some time. Although it seems beneficial in the short term, it is questionable whether the ‘big bang’ approach without dedicated time to perform the programmes is sustainable in the longer term. In the third approach, the programme is implemented incrementally and performed on top of the day-to-day activities. Company A’s experience with this approach suggests it might be possible to reduce the time lag from start of implementation to performance effects, and to reduce the deterioration in performance during the early implementation phases. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
Finally, we also observed a ‘big bang’ approach, where resources are dedicated to perform the improvement activities as part of the day-to-day activities. Company A adopted this approach to implement SAP R3 and experienced that such an approach increases the intensity of the implementation, and hence reduces the duration of the implementation phase. However, this goes at the expense of operational performance, at least initially.
Conclusion The research questions addressed in this article are: • How do the best performing companies implement new practices? • How does the way such companies approach the implementation process affect performance? We investigated these questions through case studies in two high-performing manufacturing firms, in which we studied the implementation approach, resource allocation, persistence and performance effects of the action programmes adopted. In both case companies, top management usually initiates the improvement activities. However, there is considerable room for the different functions to adapt and fit the programmes to their specific needs. More
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important, however, is top management commitment throughout the implementation process. An incremental, small-step approach appears to have negative effects on the performance in the early stages of implementation compared with an approach through which programmes are implemented in large steps (‘big bang’). The most likely reason for this is that resources are spent on parts of the programme that do not lead to performance improvement in the short term, e.g., 5S in early phases of TPM implementation. However, the small-step approach might well be more sustainable in the long term because it is easier to secure and keep the commitment of the workers, while it spreads the changes out in time and into smaller and more digestible pieces of work. Persistence is a prerequisite for this approach to work. Quitting the implementation too early because of disappointing performance effects only means that considerable amounts of resources have been spent to no avail and, more importantly, the company is losing in terms of exploitation performance, exploration performance, or both. When resources are allocated so that the workers have dedicated time to be involved in the implementation and perform improvement activities, performance, especially productivity, appears to decline in the first phases of implementation. If, in contrast, improvement activities are performed as an add-on to day-to-day activities, productivity performance is maintained or improved. However, the implementation process itself may suffer from this and take more time than planned, especially if short-term operational problems get priority. Furthermore, it is questionable whether the ‘add-on’ strategy is sustainable. The main reason for this concern is related to whether the workers’ overtime can be exposed to the usually high operational pressure while they are also expected to put considerable effort into implementation activities at the same time. So, implementation approach seems to make a difference in terms of: • short-term and long-term performance effects • operational versus implementation performance • management commitment, involvement and especially persistence required • pressure on employees involved in implementation and improvement activities. This study contributes significantly to the theory of implementation and organizational change, by explaining important relationships between different implementation approaches
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and their performance effects. The study also adds to the field of continuous innovation by providing empirical evidence on how firms actually can manage to remain high performing while carrying out large and companywide improvement activities simultaneously. For managers this study also brings up important aspects for the management of change. First, realizing that performance effect of improvement activities may take time to be realized, persistence in implementation is crucial for the programmes to become a success. Second, the allocation of resources, approach and involvement have considerable influence on the outcome of the improvement activities, and must be taken into consideration when such activities are designed and performed. Further research is needed to identify whether the findings reported here also hold beyond the case studies presented in this article. We suggest survey-based research spanning a wider range of contingencies, in particular industry type, company size, culture, and types, mix and innovativeness of action programmes. By doing this we have the possibility to verify whether the findings reported in this article also hold in a broader setting. Another important area concerns longitudinality. Considering there is a time lag from start of implementation to effects on performance, and as this study also shows a possible deterioration in performance in the early phases, it is important to take a long-term perspective on the study of change processes in order to get a more complete understanding of the factors at play. Following authors such as Pettigrew, Woodman and Cameron (2001), we suggest long-term case-based research where high-performing organizations are followed throughout the implementation of improvement programmes, so that the effects of the programmes on performance can be evaluated through time.
References Beer, M. (2003) Why Total Quality Management Programs Do Not Persist: The Role of Management Quality and Implications for Leading a TQM Transformation. Decision Science, 34, 623–42. Bessant, J. and Francis, D. (1999) Developing Strategic Continuous Improvement Capability. International Journal of Operations & Production Management, 19, 1106–19. Boer, H. and Gertsen, F. (2003) From Continuous Improvement to Continuous Innovation: A (Retro)(per)spective. International Journal of Technology Management, 26, 805–27. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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Chapman, R.L. and Sloan, T.R. (1999) Large Firms Versus Small Firms – Do They Implement CI the Same Way? The TQM Magazine, 11, 105–10. Christensen, C. (1997) The Innovator’s Dilemma. Harvard Business School Press, Cambridge, MA. Davies, A.J. and Kochhar, A.K. (2002) Manufacturing Best Practice and Performance Studies: A Critique. International Journal of Operations & Production Management, 22, 289–305. Edmondson, A.C., Bohmer, R.M. and Pisano, G.P. (2001) Disrupted Routines: Team Learning and New Technology Implementation in Hospitals. Administrative Science Quarterly, 46, 685–716. Flynn, B.B., Schroeder, R.G., Flynn, E.J., Sakakibara, S. and Bates, K.A. (1997) World Class Manufacturing Project: Overview and Selected Results. Journal of Operations & Production Management, 17, 671–85. Francis, D. and Bessant, J. (2005) Targeting Innovation and Implications for Capability Development. Technovation, 25, 171–83. Gertsen, F. (2001) How Continuous Improvement Evolves as Companies Gain Experience. International Journal of Technology Management, 22, 303– 26. Huang, Z. and Palvia, P. (2001) ERP Implementation Issues in Advanced and Developing Countries. Business Process Management Journal, 7, 276–84. Huq, Z. (2006) Managing Change: A Barrier to TQM Implementation in Service Industries. Managing Service Quality, 15, 452–69. Lant, T.K and Mezias, S.J. (1990) Managing Discontinuous Change: A Simulation Study of Organisational Learning and Entrepreneurship. Strategic Management Journal, 11, 147–49. Laugen, B.T., Acur, N., Boer, H. and Frick, J. (2005) Best Manufacturing Practices – What Do the Best Performing Companies Do? International Journal of Operations & Production Management, 25, 131– 50. March, J.G. (1995) The Future, Disposable Organizations and the Rigidities of Imagination. Organization, 2, 427–40. Miles, M.B. and Huberman, A.M. (1994) Qualitative Data Analysis: An Expanded Sourcebook. Sage, London. Nah, F.F.-H., Lau, J.L.-S. and Kuang, J. (2001) Critical Factors for Successful Implementation of Enterprise Systems. Business Process Management Journal, 7, 285–96. Pettigrew, A.M., Woodman, R.W. and Cameron, K.S. (2001) Studying Organizational Change and Development: Challenges for Future Research. Academy of Management Review, 44, 697–713. Pettigrew, A., Whittington, R., Melin, L., SánchezRunde, C., van den Bosch, F., Ruigrok, W. and Numagami, T. (2003) Innovative Forms of Organizing. Sage, London. Savolainen, T.I. (1999) Cycles of Continuous Improvement – Realizing Competitive Advan-
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tages Through Quality. International Journal of Operations & Production Management, 19, 1203– 22. Schonberger, R.J. (1986) World Class Manufacturing – The Lessons of Simplicity Applied. The Free Press, New York. Stacey, R.D. (1992) Managing the Unknowable. Strategic Boundaries between Order and Chaos in Organizations. Jossey-Bass, San Francisco, CA. Tripsas, M. and Gavetti, G. (2000) Capabilities, Cognition, and Inertia: Evidence from Digital Imaging. Strategic Management Journal, 21, 1147– 61. Voss, C.A. (1995) Alternative Paradigms for Manufacturing Strategy. International Journal of Operations & Production Management, 15, 5–16. Voss, C.A., Åhlström, P. and Blackmon, K. (1997) Benchmarking and Operational Performance: Some Empirical Results. Benchmarking for Quality Management & Technology, 4, 273–85. Wells, M.G. (2000) Business Process Re-engineering Implementations Using Internet Technology. Business Process Management Journal, 6, 164–84.
Bjørge Timenes Laugen is Associate Professor of strategy, innovation and operations management at Department of Business Administration at the University of Stavanger, Stavanger, Norway. He received his MSc in engineering in 2000, and his PhD in innovation management in 2006, both from Aalborg University, Denmark. His main research interest is the link between new product development, production, strategy, organizational development and continuous innovation. Dr. Laugen is a board member of CINet (Continuous Innovation Network), a global network set up to bring together researchers and industrialists working in the area of continuous innovation. Harry Boer is Professor of Organizational Design and Change at the Center for Industrial Production at Aalborg University. He holds a BSc in Applied Mathematics and an MSc and PhD both in Management Engineering. He has (co-)authored numerous articles and several books on subjects such as organization theory, flexible automation, manufacturing strategy, and continuous improvement/innovation. His current research interest is in continuous innovation, the effective interaction between dayto-day operations, incremental change and radical innovation.
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Role Models for Radical Innovations in Times of Open Innovation Hans Georg Gemünden, Sören Salomo and Katharina Hölzle In this paper, we study the influence of innovator roles in highly innovative ventures. In order to obtain a differentiated picture we take into account the degree of innovativeness as a moderating variable. To test our hypotheses we use a sample of 146 highly innovative new product development projects. We choose a rigorous sampling design and apply state-of-theart measures for the degree of innovativeness. Furthermore, we apply multi-trait-multimethod methodology (MTMM) to enhance the validity of our study. The results show that innovator roles have a strong influence on innovation success but these influences are positively and negatively moderated by innovativeness. The moderating influences depend on the type of innovativeness. Remarkably, with increasing technological innovativeness innovator roles which create inter-organizational links with the outside world appear to be more important than intra-organizational linker roles, and support from high-ranked organizational members turns out to have a significant negative effect on project success with higher degrees of technological innovativeness. Possible explanations for these findings are discussed and consequences for innovation research and innovation management are shown.
Introduction
I
nnovator roles have a long tradition in the innovation management literature. The research stream on champions (Schon, 1963; Chakrabarti, 1974; Rothwell et al., 1974; Maidique, 1980; Howell & Higgins, 1990a,b; Markham, Green & Basu, 1991; Shane, 1994; Markham, 1998, 2000; Markham & Griffin, 1998; Tabak & Barr, 1999; Sicotte & Langley, 2000; Howell & Shea, 2001; Markham & Aiman-Smith, 2001; Roure, 2001; Howell, Shea & Higgins, 2005) and gatekeepers (Allen, 1970, 1977; Aldrich & Herker, 1977; Tushman, 1977; Tushman & Katz, 1980; Tushman & Nadler, 1986; Domsch, Gerpott & Gerpott, 1989) documents that these roles are very critical for the success of innovations. Research in Germanspeaking countries has over the last 30 years developed four additional innovator roles which show a significant positive influence on innovation success (Klümper, 1969; Witte, 1973, 1977; Dumont du Voitel, 1976; Kaluza, 1979; Gemünden, 1981, 1985, 1994, 2003; Hauschildt & Chakrabarti, 1989; Gierschner, 1991; Pulczynski, 1991; Gemünden & Walter, 1996, 1998; Vitt, 1998; Walter, 1998; Ernst, Leptien &
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Vitt, 2000; Ernst & Vitt, 2000; Hauschildt & Schewe, 2000; Walter & Gemünden, 2000; Folkerts, 2001; Hauschildt & Kirchmann, 2001; Folkerts & Hauschildt, 2002; Scholl, Hoffmann & Gierschner, 2004; Gemünden, Hölzle & Lettl, 2006; Gemünden et al., 2006; Herrmann, Befurt & Tomczak, 2006; Papies, 2006; Rost, 2006; Rost, Hölzle & Gemünden, 2007; Schmidthals, 2007). These roles are called the expert, power, process, and relationship promoter. Another research stream has emphasized project management as crucial for the success of innovative projects. In particular, the characteristics of the project leader are assumed to strongly influence the success of innovative projects (Murphy, Baker & Fisher, 1974; Might & Fisher, 1985; Pinto, 1986; Baker, Murphy & Fisher, 1988; Gemünden, 1990; Gemünden & Lechler, 1997; Lechler, 1997; Cooke-Davies, 2002; Elkins & Keller, 2004; Prabhakar, 2005). There is strong evidence that the competence of the project leader has a significant positive influence on the success of innovative projects. However, all these research streams have not yet taken into account the degree of innovativeness of projects. There are some claims that innovator © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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roles are particularly important in the early stages of innovation projects and for highly innovative ventures (Hauschildt, 1999; Howell & Shea, 2001), but this has neither been elaborated theoretically nor tested empirically.
Theoretical Foundation Innovator Roles The management of innovation requires persons who commit themselves with enthusiasm and self-motivation to the new product or process idea. These persons may or may not have been officially assigned to the innovation process. They do, however, show a high personal involvement in the innovative project and foster and nurture the project often in addition to their official organizational position. The description of this behaviour led to the development of the champion role and the role of the gatekeeper. The champion concept has for a long time been a mono-personal concept where the success or failure of the innovation process is attributed to one single person: ‘. . . the champion must be a man willing to put himself on the line for an idea of doubtful success. He is willing to fail. But he is capable of using any and every means . . . in order to succeed’ (Schon, 1963, p. 84). Although many studies have analysed championship behaviour, Markham comes to the conclusion that the influence of champions on the success of the innovation process is not granted (Markham, 1998, p. 500). This may be explained by his very special definition of the champion which he uses in his studies, and by conceptual and methodological problems in previous research (Howell & Shea, 2001). However, recent research from Howell, Shea and Higgins (2005) does show a significant positive influence. In their excellent study, they clarified and validated the concept. They showed that, according to US managers, championship behaviour is characterized by (1) enthusiasm and confidence, (2) persistence, and (3) the capability to bring the right people together, and that this behaviour significantly increases the success of new product development projects. The technological gatekeeper was brought into the R&D management literature by Tom Allen and his research team. The technological gatekeeper is mainly active in the research and development area. Gatekeepers establish an information and communication exchange network, filter the information needed, assemble information from internal and external sources, and provide it to their organization and its workgroups (e.g., Allen, 1970; © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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Tushman & Katz, 1980; and the German replication study from Domsch, Gerpott & Gerpott, 1989). Although the influence of networking and the importance of knowledge import has become widely recognized in the era of ‘open innovation’, there has been no systematic follow-up study which considers the changes in communication by the use of the Internet. Researchers in German-speaking countries see the innovation process as no longer driven by only one but rather four persons who should work together. First, the power promoter who has the necessary hierarchical power to drive the project, to provide needed resources, and to help to overcome any obstacles that might arise during the course of the project. Second, the expert promoter who has the specific technical knowledge for the innovation process. Third, the process promoter who derives his influence from organizational know-how and intra-organizational networks. He makes the connection between the power and the expert promoter and has the necessary diplomatic skills to bring together the people necessary for the innovation process. And last but not least, the relationship promoter who has strong personal ties not only inside but especially outside the organization, i.e., to customers, suppliers and research partners. The relationship promoter shows some parallels to the technological gatekeeper, but whereas Allen and his team have concentrated on the knowledge import, Walter and Gemünden (2000) have stressed the external exploitation of knowledge via technology licensing, technology transfer, and technology-intensive B2B relationships. Thus the German research has stressed the export of knowledge. In the German approach promoters are defined by the type of barriers they help to overcome, the type of power bases on which their influence is grounded, and the type of characteristic value-creating functions they fulfil by their specific type of behaviour. Thus, the power promoter helps to overcome barriers of will, mainly by his legal power and his access to resources, the expert promoter helps to overcome barriers of ability by his expert knowledge, the process promoter helps to overcome bureaucratic and internal administrative barriers by means of his internal organizational networks, and the relationship promoter helps to overcome barriers of notknowing external partners, and not being able or willing to communicate with them, by means of his external, inter-organizational networks. The project manager is an institutionalized role model to foster innovative projects. In contrast to the other roles, a core assumption of this role is a formally assigned responsibility
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for an innovative task, and this usually includes leading a team which is formally assigned to an innovative project and its project manager. Leading a project not only comprises leadership of a team, it also includes planning and controlling, as well as cooperation with various stakeholders, particularly project sponsors, project clients and project suppliers. Many organizations aim to increase the professional level of their project management by enhancing the competencies of project managers. Examples of such efforts are career track models for project management and the certification and qualification of project managers (Hauschildt, Keim & Medcof, 2000). If project management competence matters, than the leaders of innovative projects should have more experience in leading projects and a higher competence. For our sample of radical innovations, we found that in the firms who showed higher growth and profitability figures, the leaders of innovative projects did indeed have a higher level of experience in leading projects. We therefore use a project manager’s leadership experience in previous projects as a characteristic of his professional project leadership qualification.
Project Innovativeness Recent state-of-the-art reviews show that innovativeness is best understood as a multidimensional phenomenon (Green, Gavin & Aiman-Smith, 1995; Avlonitis, Papastathopoulous & Gounaris, 2001; Danneels & Kleinschmidt, 2001; Hauschildt & Schlaak, 2001; Garcia & Calantone, 2002; Salomo, 2003) relating to market, technology, organizational change and environmental alterations. The innovation is radical for the market if the innovation satisfies former unsatisfied needs for the first time. There is a quantum leap in customer benefits. A completely new market may be created (market potential dimension). The new product may require considerable changes in customer behaviour as well as substantial financial investments from the customers. This may lead to resistance on the part of the customer (market barrier dimension). The innovation can be called radical in the technological dimension if the knowledge about the product architecture or its components significantly differs from existing knowledge. Existing knowledge may become obsolete to some degree. The innovation often relies on completely new technological principles, new architectures or new materials. Innovativeness on the organizational dimension relates to the internal change of the innovating organization. Changes may
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be required in strategy, structure, processes, competencies, incentive systems or culture. In addition to these dimensions, we suggest a fifth dimension relating to environmental alterations, such as the required establishment of a new infrastructure (e.g., hydrogen filling stations), regulatory changes or changes of value systems.
Hypotheses Innovator Roles and Project Success In order to reconcile and integrate the research streams from the United States and the German-speaking countries, we assume that the champion largely parallels the process promoter identified in the German literature. The player of this role is usually not the project manager, but a mid-level or upper-mid-level executive who sets up the project and supports it by persistently linking it with other upper-mid-level or top-level stakeholders. In contrast to the US literature, we see the champion as only one out of several innovator roles, and try to isolate the relative importance of this role instead of seeing it as the one and only important role. We further see two different kinds of inter-organizational boundary roles: the technology-related relationship promoter who parallels the technological gatekeeper, and a market-related relationship promoter who concentrates on the exploitation of know-how. In contrast to the gatekeeper literature, we see the task as not only importing knowledge, but also of mobilizing technological resources outside the own organization in order to develop new products or services. Thus, the technology-related relationship promoter also knows external technology partners that engage in cooperative projects, and has good personal relationships with them. He knows how to define, establish and run cooperative R&D projects, how to create and secure trust, and how to get third-party money for such projects, particularly from public research institutions (Gemünden et al., 2006). We thus analyse the influence of six innovator roles: expert promoters, power promoters, process promoters (champions), technologyrelated relationship promoters (an extension of technological gatekeepers), market-related relationship promoters, and project managers. The literature on champions, gatekeepers, promoters, and project managers usually posits a positive influence on the success of innovative projects. We therefore test the following hypothesis: Hypothesis 1: Success of highly innovative new product development projects increases © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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with increasing influence of: (a) expert promoters, (b) power promoters, (c) process promoters (champions), (d) technology-related relationship promoters (technological gatekeepers), (e) market-related relationship promoters, and with (f) increasing leadership experience of project manager from previous projects.
The Moderating Role of Project Innovativeness A core assumption of innovation management is that innovative tasks need to be managed in a different way from routine tasks. Were this assumption not true, there would be no need to make a distinction between management and innovation management. However, this basic assumption has not been challenged so far. There have been some investigations that have conceptualized and measured the construct ‘innovativeness’ (Green, Gavin & Aiman-Smith, 1995; Danneels & Kleinschmidt, 2001; Hauschildt & Schlaak, 2001; Garcia & Calantone, 2002), and there also exist some empirical studies that analyse interaction effects of success factors and innovativeness (Olson, Walker & Ruekert, 1995; Högl, Parboteeah & Gemünden, 2003). However, even in these studies radical innovations are underrepresented. This is not the case in our research project, where we took great care to ensure a sample with many highly innovative projects and which covers a broad range of innovativeness. This sample design allowed us to adequately test moderating, direct and indirect effects of innovativeness on project success. In general, with increasing innovativeness, ambiguity and uncertainty increase and more complex learning processes are needed. Processes for discovering, diffusing and incorporating new knowledge require longer and closer cooperation between the partners involved. Therefore, these projects require special organizational attention and support. Looking at the innovation process, we find a multitude of barriers that hinder the successful progress of innovation throughout the organization. The barriers of incompetence, ignorance, unwillingness and administrative rules tie up time, money and people, resources that are needed for the successful execution of the innovation process. This holds especially true for radical innovations, which challenge the organization in every way possible. We believe that radical innovations cannot become successful without the special backing of highly committed people within the firm. Consequently, the positive effect of innovator roles is expected to be higher for radical innovations
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than for their incremental counterparts (Lee & Na, 1994). Therefore we formulate the following hypothesis: Hypothesis 2: The positive impact of (a) expert promoters, (b) power promoters, (c) process promoters (champions), (d) technology-related relationship promoters (technological gatekeepers), (e) market-related relationship promoters, and (f) project manager’s leadership experience, increases with increasing project innovativeness.
Empirical Analysis Sample In order to answer our research questions, it is important to ensure that innovation projects with very high degrees of innovativeness are included in our sample. Previous quantitative research has relied mainly on mailed questionnaires to a large number of companies asking each company to provide specific information with respect to a recently completed new product development (NPD) project. Following such a procedure will more than likely result in a sample of incremental to moderate innovation projects, yet few radical innovations. While radical innovations are generally supposed to be critical for a firm’s long-term competitiveness, they are accompanied by high uncertainty on both the technological and the market dimensions (Leifer et al., 2000). Therefore, project termination is more likely and terminated projects are usually excluded in standard data collection procedures. Altogether, this may result in respondents being rather reluctant to disclose information about radical innovations to interested researchers. In order to avoid these sampling problems we took a stepwise approach. First, we asked over 20 experts from different technological fields to point out different specific technological areas of strong research and advanced development activity with great potential for radical innovations. A total of 45 promising technological areas were identified (e.g., 3D imaging technology or nanotechnology). The same experts were then asked to identify companies that are very active in pursuing technological development. We then contacted these firms and asked them to participate in our study with their most radical NPD projects in their respective technological areas (e.g., flight simulator with 3D vision). Additionally, we contacted companies that had won prizes for their NPD projects. In total, 276 German companies were contacted of which 104 agreed to participate in the survey with one ongoing or recently market-launched innovation project.
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The 104 interviews in 2001 were based on a questionnaire and an additional interview manual providing basic definitions for the central constructs of the study. The questionnaire had been successfully pre-tested with several R&D and marketing managers from selected companies. Using structured interviews for collecting the data allows us (a) to address respondents’ concerns about confidentiality which is especially important for data on radical innovations, (b) to create a common understanding of the central constructs of the study, and (c) to reduce potential halo effects as past project phases were identified with correct dates and the specific situation of each phase was discussed intensively with each respondent. In order to increase variance of the construct innovativeness, we gathered an additional 42 cases using questionnaires. The same questions and the same type of key informants were used. All selected companies were winners of innovation prizes. We focused on the following five industries: automotive (18%), mechanical engineering (26%), electronics (28%), software (18%) and biotech (10%) – the majority operating in a B2B environment. The sample included companies of all sizes: 38% generate revenues of more than 500 million Euro, 35% less than 50 million Euro, and the rest somewhere in between.
Measures Innovator Roles Data on characteristics of promoters were collected by assessments of the key informants. The rating scales for the measurement of innovator roles range from 1 to 7. The innovator roles and project management characteristics were measured by the indicators shown in Table 1. Project Innovativeness Project managers were asked to assess each aspect of product innovativeness as it was experienced ex ante. Project innovativeness was measured with the following dimensions and items: technology dimension (measured by new technological principle, quantum leap in performance, squeezing out of existing technology), market dimension I: market potential, market driver (creates totally new customer benefit, attracting many new customers, unique competitive advantages), market dimension II: market barrier (change in customer attitude and behaviour required, high learning expenditures for clients, parts of the value chain are not needed any more (e.g., B2B marketplace will replace traditional distributor)), organizational dimension (reorientation of corporate strategy, new
Table 1. Operationalization of Innovator Roles and Project Management Characteristic Power promoter
Expert promoter Process promoter
Technology-related relationship promoter
Market-related relationship promoter Leadership experience of the project leader
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Operationalization ‘The key person supports the project above-average from a higher hierarchical level.’ Hierarchical rank of the key person ‘The key person promotes the project by his/her high technological know-how.’ ‘The key person knows the organizational processes and campaigns above-average for the smooth progress of the project.’ ‘The key person acts as a link between decision makers and experts.’ ‘The key person has good relationships with important external cooperation partners.’ ‘The key person supports the search for external cooperation partners, information exchange with cooperation partners and the collaboration with cooperation partners.’ ‘The key person promotes the project by his/her market-related know-how.’ Experience in leading previous projects
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organizational structure, new qualifications for employees, major change of organizational culture), and environmental dimension (creation of a new infrastructure, altered regulation in order to implement innovation, critical debate of innovation in society). The values of the five innovativeness measures are taken as the arithmetic mean of the respective items. The five innovativeness measures correlate only moderately: discriminant validity according to the Fornell–Larcker criterion is fulfilled. This means project innovativeness is a multi-dimensional construct. Therefore, it makes sense to analyse the moderator effects of each innovativeness dimension separately. In our multi-trait-multi-method analysis, the domain of responsibility of the two kinds of informants (market versus technology) was used as the method factor, and the five innovativeness constructs were used as traits. Table 2 confirms the validity of our measurement: two-thirds of the variance of the items are explained by the traits, only 12% are explained by the informant’s domain of responsibility and knowledge background. Some 20% are unexplained error variance. The informant bias is therefore only a moderate one. A t-test for paired samples of the raw items did not show any significant differences at the 5% level between the marketing and technology respondent. It should be noted that the significance of this measurement test is higher than previous tests that we have conducted as we used not only the answers of one informant from the first data collection wave, but of two informants from both data collection waves, i.e., more than 400 cases were used. Project Success Respondents were asked to evaluate project performance in relation to their specific goals on seven-point Likert scales. Project success measures were the traditional triple constraints of time, budget and quality. For each criterion, success is calculated as the mean score of the up to three stage assessments. In addition, meeting target cost of the new product was used as a success measure. All these measures have usually been actively controlled in the analysed projects; this means that the informants can give reliable and valid assessments.
Data Analysis Methodology Given the relatively high number of main effects and interaction effects, and considering the six innovator roles, the five innova© 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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tiveness dimensions, and the four measures of success, a highly complex multivariate test design is evident. In order to reduce complexity, and to avoid overfitting of the data, we first tested simpler models, and looked at the characteristics of the scales. We found that the interaction effects differed strongly between the different dimensions of innovativeness, so that using only one second-order construct for innovativeness would not fit. Instead, it appeared necessary to treat the different dimensions of innovativeness as distinctive influences, with each having its own moderating effect. We decided to leave out environmental innovativeness from our analyses, because it had a highly skewed distribution. In a minority of the cases, this kind of innovativeness matters very strongly, but in the majority it does not matter at all. Market barriers did not show any main or interaction effects significant at the 5% level. Therefore we also omitted this variable from our analysis.
Empirical Results Main Effects Table 3 shows the results. Each column lists the results of one multiple regression, using time, quality, budget, and target cost as dependent variables. Only significant (bold, p < 0.05) and weakly significant (italics, p < 0.10) standardized estimated partial regression coefficients are shown. It is evident that the main effects of innovativeness are not significant, with the exception of a negative effect of organizational innovativeness on budget and target cost. Research in innovation management shows that especially radically new designs need to prove their suitability in practice before being accepted on the market (Lynn, Morone & Paulson, 1996; Veryzer, 1998). Only then can product process improvements be established which enable the firm to lower the costs in order to bring the product to the mass market. Therefore, it is not necessarily surprising that a high degree of innovativeness correlates negatively with budget and target costs, particularly for unexpected cost of organizational changes. Regarding the main effects of the innovator roles, we can see that, with the exception of the power promoter, all other innovator roles show significant positive influences and no significant negative influences. The expert promoter improves time and quality, the process promoter (champion) budget and target cost. Thus they are both very complementary. The technology-related relationship promoter increases quality and budget by fostering
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Technology T1: Technology 0.838 T2: Market Drivers 0.583 T3: Market Barriers T4: Organization Change T5: Environment Change Marketing T1: Technology 0.770 T2: Market Drivers 0.999 T3: Market Barriers T4: Organization Change T5: Environment Change Chi2 28.98 df 16 RMSEA 0.057 GFI 0.97 AGFI 0.92
T
0.705
0.852
T
Traits
Table 2. MTMM Analysis of the Innovativeness Measures
0.840
0.731
T4
0.865
0.959
T5
.263 0.701 0.258 0.091 -0.030
Techno.
-0.111 -0.043 -0.709 -0.277 -0.107 Mean
Marketing
Methods
0.593 0.998 0.497 0.706 0.748 0.676
0.702 0.340 0.726 0.535 0.919
Trait
0.012 0.002 0.503 0.077 0.012 0.124
0.069 0.491 0.067 0.008 0.001
Method
0.395 0.000 0.000 0.217 0.240 0.199
0.229 0.169 0.207 0.457 0.080
Error
Variance decomposition
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Table 3. Results of the Regression Analyses Time Main effects – Innovativeness Technological dimension Market potential dimension Organizational dimension Main effects – Role characteristics Expert promoter Power promoter Process promoter Technology-related relationship promoter Market-related relationship promoter Project leader experience Interaction effects – Technological innovativeness Expert promoter Power promoter Process promoter Technology-related relationship promoter Market-related relationship promoter Project leader experience Interaction effects – Market potential innovativeness Expert promoter Power promoter Process promoter Technology-related relationship promoter Market-related relationship promoter Project leader experience Interaction effects – Organizational innovativeness Expert promoter Power promoter Process promoter Technology-related relationship promoter Market-related relationship promoter Project leader experience Explained variance (corrected measure)
cooperations with technology suppliers, and the market-related promoter improves time performance by bringing in market-related time pressures. Finally, the experienced project leader acts as expected, and helps to fulfil the three traditional project success criteria of time, quality and budget. The unexpected result that the power promoter has no significant influence deserves some comment. The projects in our sample were often strategically important, therefore at least one power promoter was found in 72% of the cases, and in 35% of the cases two or more power promoters were supporting the project. The Likert-scale to assess power-promotion ‘The key person supports the project above-average from a higher hier© 2007 The Authors Journal compilation © 2007 Blackwell Publishing
Quality
Budget
Target cost
-0.22
-0.18
0.29
0.40
0.44
0.25
0.18
0.22 0.25
0.36
0.24
0.35
-0.23 -0.30 -0.31 0.20 0.19
-0.23
-0.24 -0.26 -0.25 0.17
0.24 0.29
0.35
0.20
-0.33
-0.31 0.31 0.18 -0.27 -0.16 24.8%
0.28 -0.26 14.8%
34.8%
14.9%
archical level’ goes from 1 to 7. In 51% of the projects the value ‘7’ was chosen, in 21% ‘6’ was chosen, i.e., there was a high amount of power promotion in most of the projects, thus there was no barrier of not wanting the innovation. In contrast to the many studies on normally innovative projects, we found that additional resources did not significantly correlate with any of our four success measures. To summarize: innovator roles have important main effects for improving the success of radical innovations. Only the power promoter showed no significant main effect, because lack of resources was not a critical success factor (see also Gemünden, Salomo & Krieger, 2005).
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Interaction Effects What are the moderating effects of innovativeness? Increasing technological innovativeness shows positive and negative interaction effects. The troika of expert, power and process promoter performs significantly poorer when technological innovativeness increases. This is quite surprising, because this troika has been advocated very often, and has been seen as the core part of the promoter models. Our findings cast doubts on this core model. We observe that the two externally oriented types of relationship promoters, and the experienced project leader, increase their positive impacts with increasing technological innovativeness. It is very likely that in cases of high technological innovativeness, a lot of new knowledge is created outside the organization, e.g., in universities and research institutions, or among competitors, suppliers and customers, so that the traditional internal troika cannot cope with these dynamics. Project managers, experienced in leading R&D projects, will nowadays also cope with cooperation partners, so that they can also handle the external sources of innovative uncertainty much better. Market potential innovativeness also shows positive and negative interaction effects, but these are much less significant. Higher degrees of expertise as reflected by the expert promoter allow exploiting the higher market potential significantly better within time and budget. However, if this expertise does not come from within the firm, but has to be acquired from outside by means of a technological relationship promoter, it will significantly lead to budget overruns with increasing market potential. Organizational innovativeness also shows positive and negative interaction effects, but in this case the negative interaction effects cannot be attributed to the internal innovator roles, and the positive ones to the externally oriented roles. Rather, other explanations are needed. Organizational innovation means that the organization needs to build up new competences. It has to change its processes, structures and/or its culture and value system. The negative interaction with the expert promoter indicates that relying on existing competences does not help, but will increase the problem of meeting target costs. By finding new technological partners, and fostering cooperation with them, technology-related promoters may bring in required new competences and thus save time and improve the quality of the new product. Process promoters, recognizing the value of new competences, and the need for organizational change and integration of externals, may also help to overcome the compe-
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tence gap. They may bring together the right people and support organizational change by means of their internal networks. Marketrelated champions stress the market opportunity, but they underestimate the problems of organizational change, and therefore show negative interaction effects. The experienced project leader may cope with his project demands, but the more a change of his permanent organization is required, the more helpless he becomes, and finally his activities show negative interaction effects. How do the innovator roles perform in the light of these findings? It can be seen that the expert promoter, who is often seen as the core actor, because technological expertise is a basic requirement of many innovations, particularly if the term ‘technology’ includes social technologies as well, does not always perform very well in cases of radical innovation. Where does this surprising result come from? The explanation is the source of expertise. If it comes mainly from inside the organization, based on research done in the firm’s own laboratories, or on a new combination of already well understood technologies, then the expert promoter is a clear success factor, particularly if only market potential innovativeness is high. However, when radically new technologies develop outside the organization, traditional core competences may become core rigidities. The experts of the past may prefer to stay on their traditional technological trajectories, instead of recognizing the value of new technologies, based on new technological principles, new architectures or new materials. Eberhard Witte’s second promoter in his two power centre theory, the hierarchical power holder, does not show any significant main effect, but two significantly negative interaction effects with technological innovativeness. In cases of radical technological change, power promoters appear to underestimate the technological uncertainty, which may lead to tremendous time and budget overruns. Prominent examples are Concorde, the A380, or the billing system Toll Collect for trucks using German motorways. Such negative evidence is not a completely new phenomenon, having already been found in the same data that Witte analysed, only in that case there was only a power promoter but no expert promoter (Gemünden, 1981). Gemünden and Lechler (1996) showed that power promoters set up projects which lacked strategic fit, they bypassed controlling procedures, and prevented the termination of projects which should have been terminated. On the product portfolio level, Ernst (2001) showed an inverted U-shaped relationship between top-management support and profitability, © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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because in cases of too many resources the additional projects do not cover the cost of capital. Scholl, Hoffmann and Gierschner (2004) document further defects of power promoters which result from demotivation, if some individuals are treated preferentially and get support while others do not. The often used naïve statement that top-management support is a ‘success factor’ thus needs to be qualified. Process promoters – who resemble champions in the US literature – have significant positive main influences on budget and target cost. However, with increasing technological innovativeness, they show significant negative interaction effects for time, quality and budget. These negative interaction effects with technological innovativeness are partly compensated by the fact that, in cases of increasing organizational innovativeness, process promoters appear to lower target cost, probably by bringing together people from different departments, better integrating externals, and by fostering required changes in structures and processes. Thus, the effect of process promoters depends very much on the kind of innovativeness and on their ability to open the organization to externally created innovations. Technology-related relationship promoters, who are an extension of technological gatekeepers, show a very positive performance picture. First, they positively and directly affect quality and budget. Second, the positive influence on budget increases with increasing technological innovativeness. Third, there is a positive interaction effect for time and quality with increasing organizational innovativeness. There is only one negative interaction effect for budget with market potential innovativeness. Market-related relationship promoters also show a very positive balanced scorecard, which is based on significant positive main effect for time, and positive interaction effects with technological innovativeness for time and quality. However, on the negative side, increasing organizational innovativeness shows negative interactions for time and quality.
Discussion and Conclusion Our study shows that innovator roles do have a positive influence on innovation success, thus supporting our first general hypothesis. However, this positive influence does not increase with all dimensions of innovativeness, and also not for all kinds of innovator roles. Rather, we see a much differentiated picture which cannot be easily explained. Thus © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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our second general hypothesis is not confirmed, but needs to be revised. It appears to be that the more internal models of promoter cooperation, i.e., Schon’s Champion, Witte’s tandem structure of expert and power promoter, and Hauschildt and Chakrabarti’s troika of expert, process and power promoter, do not fit all kinds of innovations. In the era of open innovation, technology and market-related relationship promoters are needed as boundary spanners for importing external knowledge resources, and cooperating technology partners, and for importing customer demands, and exploiting values created by innovating customers. Otherwise not-invented-here syndromes and group-think phenomena within the traditional troika may support sticking to the wrong innovation, which may be even worse than non-innovation. Furthermore, in the area of professionalized project and innovation management, formally assigned project leaders, and professionalization of innovator roles, professionalization of cross-functional teamwork, and a good innovation system also play a very important role. This has been overlooked in the champion, gatekeeper and promoter literature. Although our findings need to be confirmed by other studies, and by follow-ups which consider the long-term effects of radical innovations, we may already conclude that the profile of the innovativeness dimensions matters. This means that decisionmakers and researchers in innovation management must take a closer look at which types of requirements are posed by an innovative problem. Although it is desirable to create new customer value, which can be defended easily without changing the own knowledge base, it will often be necessary to invent and develop new technologies, to do this together with partners in strategic alliances, or to insource new technologies from outside. In cases of radical innovation, it is more likely that the innovators also have to master organizational and societal change, and changes in competition. How much change is required should be taken into account more thoroughly, higher market potential and value creation does not always imply higher barriers and more difficulties. It is a genuine task of finding the intelligent combinations. The aim of innovation management is not to create heroes, who finally prevail against all odds or ruin their organization. The aim is to find out which are the most valuable options, taking into account potential risks, and find ways to realize these options. In times of worldwide open innovation arenas this requires open innovators.
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Acknowledgements The authors dedicate this article to Prof. Dr. Oskar Grün, WU (Wirtschaftsuniversität Wien).
References Aldrich, H. and Herker, D. (1977) Boundary Spanning Roles and Organization Structure. Academy of Management Review, 2, 217–30. Allen, T.J. (1970) Communication Networks in R&D Laboratories. R&D Management, 1, 14–21. Allen, T.J. (1977) Managing the Flow of Technology: Technology Transfer and the Dissemination of Technological Information within the R&D Organization. MIT Press, Cambridge, MA. Avlonitis, G.J., Papastathopoulous, P.G. and Gounaris, S.P. (2001) An Empirically-Based Typology of Product Innovativeness for New Financial Services: Success and Failures Scenarios. Journal of Product Innovation Management, 18, 324–42. Baker, B.N., Murphy, D.C. and Fisher, D. (1988) Factors Affecting Project Success. In Cleland, D.J. and King, W.D. (eds.), Project Management Handbook. Van Nostrand, New York, pp. 902–19. Chakrabarti, A.K. (1974) The Role of Champion in Product Innovation. California Management Review, 17, 58–62. Cooke-Davies, T. (2002) The ‘Real’ Success Factors on Projects. International Journal of Project Management, 20, 185–190. Danneels, E. and Kleinschmidt, E.J. (2001) Product Innovativeness from the Firm’s Perspective: Its Dimensions and Their Relation with Project Selection and Performance. Journal of Product Innovation Management, 18, 357–73. Domsch, M., Gerpott, H. and Gerpott, T.J. (1989) Technologische Gatekeeper in der industriellen F&E, Poeschel. Stuttgart, Germany. dumont Du Voitel, R. (1976) Aktoren in der Initiierung von organisationalem Wandel. Ein empirischer Beitrag zu einer Theorie des geplanten organisationalen Wandels. Dissertation thesis, Universität Mannheim. Elkins, T.J. and Keller, R. (2004) Best Practices for R&D Project Leaders: Lessons from Thirty Years of Leadership Research. International Journal of Innovation and Technology Management, 1, 3–16. Ernst, H. (2001) Erfolgsfaktoren neuer Produkte: Grundlagen für eine valide empirische Forschung. DUV, Wiesbaden, Germany. Ernst, H. and Vitt, J. (2000) The Influence of Corporate Acquisitions on the Behaviour of Key Inventors. R&D Management, 30, 105–19. Ernst, H., Leptien, C. and Vitt, J. (2000) Inventors Are Not Alike: The Distribution of Patenting Output among Industrial R&D Personnel. IEEE Transactions on Engineering Management, 47, 184–99. Folkerts, L. (2001) Promoteren in Innovationsprozessen. Empirische Untersuchung zur personellen Dynamik. DUV, Wiesbaden, Germany. Folkerts, L. and Hauschildt, J. (2002) Personelle Dynamik in Innovationsprozessen – neue Fragen
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Gierschner, H.-C. (1991) Information und Zusammenarbeit bei Innovationsprozessen. Peter Lang, Frankfurt am Main, Germany. Green, S.G., Gavin, M.B. and Aiman-Smith, L. (1995) Assessing a Multidimensional Measure of Radical Technological Innovation. IEEE Transactions on Engineering Management, 42, 203–14. Hauschildt, J. (1999) Projektleiter als Prozesspromoteren. In Hauschildt, J. and Gemünden, H.G. (eds.), Promoteren. Champions der Innovation, 2nd edn. Gabler, Wiesbaden, Germany, pp. 211– 31. Hauschildt, J. and Chakrabarti, A. (1989) Division of Labour in Innovation Management. R&D Management, 19, 161–71. Hauschildt, J. and Kirchmann, E. (2001) Teamwork for Innovation – the ‘Troika’ of Promoters. R&D Management, 31, 41–49. Hauschildt, J. and Schewe, J. (2000) Gatekeeper and Process Promoter: Key Persons in Agile and Innovative Organizations. International Journal of Agile Management Systems, 2, 96–103. Hauschildt, J. and Schlaak, T. (2001) Zur Messung des Innovationsgrades neuer Produkte. Zeitschrift für Betriebswirtschaft, 71, 161–82. Hauschildt, J., Keim, G. and Medcof, J. (2000) Realistic Criteria for Project Manager Selection and Development. Project Management Journal, 31, 23–32. Herrmann, A, Befurt, R. and Tomczak, Th. (2006) Determinants of Radical Product Innovations. European Journal of Innovation Management, 9, 20–43. Högl, M., Parboteeah, K.P. and Gemünden, H.G. (2003) When Teamwork Really Matters: Task Innovativeness as a Moderator of the Teamwork– Performance Relationship in Software Development Projects. Journal of Engineering and Technology Management, 20, 281–302. Howell, J.M. and Higgins, C.A. (1990a) Champions of Technological Innovation. Administrative Science Quarterly, 35, 317–41. Howell, J.M. and Higgins, C.A. (1990b) Champions of Change: Identifying, Understanding and Supporting Champions of Technological Innovations. Organizational Dynamics, 19, 40–54. Howell, J.M. and Shea, C.M. (2001) Individual Differences, Environmental Scanning, Innovation Framing, and Champion Behaviour: Key Predictors of Project Performance. The Journal of Product Innovation Management, 18, 15–27. Howell, J.M., Shea, C.M. and Higgins, C.A. (2005) Champions of Product Innovations: Defining, Developing, and Validating a Measure of Champion Behavior. Journal of Business Venturing, 20, 641–61. Kaluza, B. (1979) Entscheidungsprozesse und empirische Zielforschung in Versicherungsunternehmen. Verlag Versicherungswirtschaft, Karlsruhe, Germany. Klümper, P. (1969) Die Organisation von Entscheidungsprozessen zum Kauf von Industrieanlagen. Universität Mannheim, Germany. Lechler, Th. (1997) Erfolgsfaktoren des Projektmanagements. Peter Lang, Frankfurt am Main, Germany. Lee, M. and Na, D. (1994) Determinants of Technical Success in Product Development when Innova© 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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tive Radicalness is Considered. Journal of Product Innovation Management, 11, 62–68. Leifer, R., McDermott, C.M., O’Connor, G.C., Peters, L.S., Rice, M. and Veryzer, R.W. (2000) Radical Innovation: How Mature Companies can Outsmart Upstarts. Harvard Business School Press, Boston, MA. Lynn, G.S., Morone, J.G. and Paulson, A.S. (1996) Marketing and Discontinuous Innovation: The Probe and Learn Process. California Management Review, 38, 8–37. Maidique, M.A. (1980) Entrepreneurs, Champions, and Technological Innovation. Sloan Management Review, 21, 59–76. Markham, S.K. (1998) A Longitudinal Examination of How Champions Influence Others to Support Their Projects. Journal of Product Innovation Management, 15, 490–504. Markham, S.K. (2000) Corporate Championing and Antagonism as Forms of Political Behavior: An R&D Perspective. Organization Science, 11, 429– 47. Markham, S.K. and Aiman-Smith, L. (2001) Product Champions: Truths, Myths and Management. Research Technology Management, 44, 44–50. Markham, S.K. and Griffin, A. (1998) The Breakfast of Champions: Associations Between Champions and Product Development Environments, Practices and Performance. Journal of Product Innovation Management, 15, 436–54. Markham, S.K., Green, S.G. and Basu, R. (1991) Champions and Antagonists: Relationships with R&D Project Characteristics and Management. Journal of Engineering and Technology, 8, 217–42. Might, R. and Fisher, W. (1985) The Role of Structural Factors in Determining Project Management Success. IEEE Transactions on Engineering Management, 2, 71–77. Murphy, D., Baker, N. and Fisher, D. (1974) Determinants of Project Success. Boston College, NASA, Boston, MA. Olson, E.M., Walker, O.C. and Ruekert, R.W. (1995) Organizing for Effective New Product Development: The Moderating Role of Product Innovativeness. Journal of Marketing, 59, 48–62. Papies, S. (2006) Phasenspezifische Erfolgsfaktoren von Innovationsprojekten: Eine projektbegleitende Längsschnittanalyse. DUV, Wiesbaden, Germany. Pinto, J. (1986) Project Implementation: A Determination of its Critical Success Factors, Moderators, and their Relative Importance across the Project Life Cycle. Dissertation, University of Pittsburgh, USA. Prabhakar, G.P. (2005) Switch Leadership in Projects. Project Management Journal, 36, 53–60. Pulczynski, J. (1991) Interorganisationales Innovationsmanagement – Eine kritische Analyse des Forschungsprojektes GROWIAN. Wissenschaftsverlag Vauk Kiel KG, Kiel, Germany. Rost, K. (2006) Sozialstruktur und Innovationen. Dilemmaentschärfung in Innovationsprozessen durch zielfördernde Ausgestaltung von Netzwerken, sozialen Rollen und Ressourcen. Dissertation thesis, TU Berlin, Germany. Rost, K., Hölzle, K. and Gemünden, H.G. (2007) Promoters or Champions? Pros and Cons of Role Specialization for Economic Progress. Schmalenbachs Business Review, in print.
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Rothwell, R., Freeman, C., Horlesey, A., Jervis, V.T.P., Robertson, A.B. and Townsend, J. (1974) SAPPHO Updated – Project SAPPHO Phase II. Research Policy, 3, 258–91. Roure, L. (2001) Product Champion Characteristics in France and Germany. Human Relations, 54, 663–82. Salomo, S. (2003) Konzept und Messung des Innovationsgrades – Ergebnisse einer empirischen Studie zu innovativen Entwicklungsvorhaben. In Schwaiger, M. and Harhoff, D. (eds.), Empirie und Betriebswirtschaft, Entwicklungen und Perspektiven. Schaeffer-Poeschel, Stuttgart, Germany, pp. 399– 427. Schmidthals, J. (2007) Technologiekooperationen in radikalen Innovationsvorhaben. DUV, Wiesbaden, Germany. Scholl, W., Hoffmann, L. and Gierschner, H.C. (2004) Innovation und Information – Wie in Unterne hmen neues Wissen produziert wird. HogrefeVerlag, Göttingen, Germany. Schon, D.A. (1963) Champions for Radical New Inventions. Harvard Business Review, 41, 77–86. Shane, S.A. (1994) Are Champions Different from Non-Champions? Journal of Business Venturing, 9, 397–421. Sicotte, H. and Langley, A. (2000) Integration Mechanisms and R&D Project Performance. Journal of Engineering and Technology Management, 17, 1–37. Tabak, F. and Barr, S.H. (1999) Propensity to Adopt Technological Innovations: The Impact of Personal Characteristics and Organizational Context. Journal of Engineering and Technology Management, 16, 247–70.
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Tushman, M.L. (1977) Special Boundary Roles in the Innovation Process. Administrative Science Quarterly, 22, 587–605. Tushman, M.L. and Katz, R. (1980) External Communication and Project Performance: An Investigation into the Role of Gatekeepers. Management Science, 26(11), 1071–85. Tushman, M.L. and Nadler, D.A. (1986) Communication and Technical Roles in R&D Laboratories: An Information Processing Approach. In Dean, B.V. and Goldhar, J.L. (eds.), Management of Research and Innovation, Vol. 15. Amsterdam, Holland. Veryzer, R.W. (1998) Discontinuous Innovation and the New Product Development Process. The Journal of Product Innovation Management, 15, 304– 21. Vitt, J. (1998) Schlüsselerfinder in der industriellen Forschung und Entwicklung – Strategien für das Akquisitionsmanagement in Unternehmen. DUV, Wiesbaden, Germany. Walter, A. (1998) Der Beziehungspromoter. Ein personaler Gestaltungsansatz fuer das Relationship Marketing. DUV, Wiesbaden, Germany. Walter, A. and Gemünden, H.G. (2000) Bridging the Gap between Suppliers and Customers through Relationship Promoters: A Theoretical and Empirical Analysis. Journal of Business & Industrial Marketing, 15, 86–105. Witte, E. (1973) Organisation für Innovationsentscheidungen. Das Promoteren-Modell, Vahlen, Göttingen, Germany. Witte, E. (1977) Power and Innovation: A TwoCenter Theory. International Studies of Management and Organization, 7, 47–70.
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Hans Georg Gemünden (hans.
[email protected]) is Professor of Technology and Innovation Management at the Berlin University of Technology. He holds a Diploma and a Doctorate in Business Administration from Saarbrücken University, and Habilitation degree from the University of Kiel. He has published several books and numerous articles in the fields of innovation and technology management, marketing, business policy and strategy, project management, entrepreneurship, human information behaviour and decision making, and accounting. He has received several Awards of Excellence for his research, which is published in refereed journals including, among others IEEE Transactions on Engineering Management, R&D Management, Research Policy, International Journal of Project Management, International Journal of Research in Marketing, Journal of Business Research, Journal of Engineering and Technology Management, Journal of Product Innovation Management, Management International Review, Organization Science, Schmalenbachs Business Review, Schmalenbachs Zeitschrift für betriebswirtschaftliche Forschung, and Zeitschrift für Betriebswirtschaft. Sören Salomo is Professor of Technology and Innovation Management at KarlFranzens University Graz, Austria. He holds a Diploma and a Doctorate in Business Administration from Kiel University, and Habilitation degree from the Berlin University of Technology. He received the Esche-Schümann-Commichau Foundation award for his doctoral thesis. His research interests cover corporate innovation management from a resource-based perspective with a special focus on process and organizational system mechanisms for supporting radical innovation. He also addresses research questions in the field of innovation marketing. His work has been published in Scandinavian Journal of Management, Creativity and Innovation Management, Journal of Product Innovation Management and other noted refereed journals. Katharina Hölzle is a PhD Candidate at the Chair for Technology and Innovation Management at the Berlin University of Technology. She worked for several years in the semiconductor, consulting and eBusiness industry before returning to university. She has published several articles in the field of relationship marketing and innovation management. Her PhD thesis deals with career path models for project managers in large corporations.
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Exploring Differences between Inventors, Champions, Implementers and Innovators in Creating and Developing New Products in Large, Mature Firms Edward W. Sim, Abbie Griffin, Raymond L. Price and Bruce A. Vojak This exploratory research investigates nine individuals participating as specialists in different phases of the invention and new product development (NPD) process in one organization. In-depth interviews were conducted with these individuals, as well as with 17 of their managers and co-workers, adding an external perspective about them. These nine individuals participated in four different divisions of labour in the innovation process: inventors who focus on scientific and technical invention prior to concept development, champions who are most adept at selling acceptance of projects into the organization, implementers who focus on facilitating the project through the firm’s formal development process, and innovators who operate across all three phases of invention, acceptance and implementation. The research finds differences in personality, perspective, knowledge base, motivation, and attitude toward politics that seem to be associated with these different specialist types. These differences lead to implications for the types of projects for which they might best be suited, as well as for how they might best be managed.
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uch of the product development research conducted over the last 15–20 years has taken the perspective that NPD could be managed like any other (complex) process. The underlying assumption is that standard methods and protocols could be put into place, and individuals and teams could follow a process to commercialize a stream of successful new products. That is, the field has worked to change the ‘art’ of product development into the ‘science’ or process of product development (Griffin, 1997). It is important to note, however, that the formal process view of NPD, and research on NPD processes, starts after invention, or after a technical capability has been generated, developed into a concrete
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concept and accepted as a project by the organization (Griffin, 1997). Previous research suggests that, especially for more innovative or radical new products where there is greater uncertainty, two distinct tasks precede project execution within new product development – capability invention and project acceptance. Invention occurs in the time before there is a well-formed concept, sometimes called the ‘fuzzy front end’ (FFE) (Smith & Reinertsen, 1992). It is the messy ‘getting started’ period of NPD. In technology-dependent firms, it is where technical possibilities are created and insights to match them to customer problems and market needs are generated. Gaining project acceptance requires developing a business plan for the proposed product or service and shepherding that plan © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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through the firm’s funding and staffing processes. Although several processes and structures for increasing the rationality of decision making have been developed, this task fundamentally remains one of managing the politics of gaining project acceptance in the firm. Once the project is accepted by the organization, getting the product to market is a matter of project execution and implementation. Indeed, incremental projects, where there are lower market and technical uncertainties, as the direction in which the product will evolve is more ‘obvious’, may consist only of project execution, with little or no front end required. Over the past several decades, researchers have striven to develop institutionally-supported formal frameworks of procedures and methods that allow product development teams to more routinely and efficiently take projects successfully from concept through commercialization. Invention, project definition and acceptance, and process execution each require different competencies to complete successfully (Schumpeter, 1934). The FFE requires technical competency and creativity. Project acceptance requires business, market and some technical knowledge, coupled with a driving political capability. Project implementation requires project management and facilitation skills. Thus, economic theory would suggest that the most efficient management of the overall process would be through a division of labour for these different parts of the invention and commercialization process that require different skills (Schumpeter, 1934; Chakrabarti & Hauschildt, 1989). Indeed, in a traditional NPD setting, different individuals, with different types of skills, undertake the different roles involved with moving an innovation opportunity through the laboratory, gaining political acceptance for it as a project, and managing the formal commercialization process. In the classical view of NPD, these
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stages are driven or managed by inventor technologists, champions, and implementers, respectively (Figure 1). As suggested earlier, however, not all projects may require all three types of individuals. For example, inventors may not be needed for incremental projects. In projects where there is high technical uncertainty but low customer or market uncertainty, i.e., there is a well-known problem in the marketplace, but as yet no good solution to the problem, a champion may not be necessary to obtain project acceptance. An example of this situation was the case of Pert+(tm). Both technologists and product managers at Proctor & Gamble ‘knew’ there was an unfilled need for a combination shampoo and conditioner – for many years, they just could not find a technology that solved both problems simultaneously. Thus, while the inventor was required to develop a solution, a champion for the project was not needed. Just as some projects may not require one or other of the different types of individuals to proceed through the organization, it also may be possible that different types of individuals gravitate to being involved with specific types of projects more than other types. This research investigates a small sample of specialist individuals who each repeatedly undertakes one of the different tasks in the NPD process, as well as several who have repeatedly driven projects across all three sets of tasks. The research question addressed is whether there are systematic personal, interpersonal and/or background differences in individuals that may support them being more successful participating in just one new product phase than in another – or in being able to drive projects across all three tasks single-handedly. Using in-depth interviews, this research is an initial investigation into what some of these differences may be. From the firm’s perspective, research along these lines may help them sort through which
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individuals, because of their inherent personal and background characteristics, may be intrinsically more successful at one or the other of the phases. Additionally, this type of research may help managers in firms construct organizational processes and systems to better support individuals specializing in the different tasks.
Literature Review This section first reviews the literature on labour division in the innovation management process. It then reviews what is known about the characteristics of individuals who act as inventors, champions and implementers in the innovation process. After that, evidence is presented that some projects proceed with no division of labour at all. Finally, research on these individuals who participate across all phases of the project, termed ‘innovators’, is reviewed. A significant body of research has investigated how the division of labour should be made in the innovation management process and how project success relates to having specific individuals responsible for each of the different kinds of labour. Starting with Schumpeter’s (1912) categorization of inventors versus entrepreneurs, at least 20 investigators have proposed labour division schemes for the process of innovation management. These schemes range from a division of the process into just two roles to schemes citing five different roles necessary for technology creation and commercialization success. Following their extensive review of this literature, Chakrabarti and Hauschildt (1989) concluded that there are two basic premises for how the division of labour in innovation management could be made: (1) based on phases in the process or (2) based on power relations in the organization. For an innovation management process, where the ‘innovation management process’ resides before the start of the formal NPD (implementation) process, they concluded that: ‘The basic concept for the division of labour starts from a three-person constellation. It can be reduced or expanded according to contingent conditions’ (Chakrabarti & Hauschildt, 1989, pp. 165–6). These individuals are the technical expert, responsible for the creative technical development, the champion, responsible for promoting the project within the organization, and the sponsor, the senior manager who starts the process of decision making and provides resources for the project. The champion is seen as providing the communications link between the expert and the senior level
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sponsor. This structure would seem to combine a bit of both of the phase and power base premises for dividing labour. Some of the labour division schemes identify roles that extend out of the R&D lab and into the execution and implementation phases of NPD. For example, Rogers & Shoemaker (1971) include ‘executors’ in their categories, Uhlmann (1978) includes ‘realisator,’ and Galbraith (1982) includes ‘orchestrators’ in his labour division scheme. Research extending across both innovation management and product commercialization needs to take into account the tasks associated with product execution. Because we are interested in increasing our understanding of individuals who are involved with completing the day-to-day tasks of innovation management and new product development, the division of labour used in this research is based on the process phase orientation. Therefore, the divisions of labour underlying this investigation are the technical invention, done by individuals we will call ‘inventors’, gaining project acceptance and resourcing, which is done by ‘champions’, and project execution, done by ‘implementers’. The next part of the literature review summarizes what is known about each of these groups. For technology-dependent firms, the context of interest here, inventor technologists tend to be the originators of innovative capabilities and ideas in the fuzzy front end of NPD (Schon, 1963; Maidique, 1980; Rice et al., 2001). An inventor creates a technical capability that can be used to create products or features that solve a customer problem or market need. Industrial inventors typically have technical degrees, and frequently have undertaken advanced training and degrees in a field. These individuals must have enough depth (and perhaps breadth) of technical understanding to be able to solve the critical problems that emerge during development and they exhibit creativity in the way in which they solve those technical problems (Tidd, Bessant & Pavitt, 1997). According to McCall (1998) and Kerr, Von Glinow and Schriesheim (1977), these types of technical professionals have also been found to merit and seek a measure of autonomy in defining how they approach their inventing tasks. They have a commitment to their work and their profession, and may identify more with their profession and technical peers than with their firm. They aspire to be ethical, unemotional and unselfish in the conduct of their activities. Most frequently, inventors reside in the R&D laboratory, or sometimes in the engineering development group (Babcock, 1991). While highly creative technically, inventors have little market or © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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business knowledge, and frequently operate in isolation from others (O’Connor & Rice, 2005). Once an innovative capability is developed, it must cross the initiation gap and gain corporate support as a formal new product development project (Markham & Kingon, 2004). A champion who understands the technology connects it to a market need, recognizing its potential. As defined by Schon (1963), a champion is a person who puts himself on the line for an idea and uses any and every means of informal tactics and pressure in order to make it succeed. Prior research suggests that champions usually do not create innovative ideas on their own, but find them elsewhere in the organization (Markham, 1998; Ardichvili, Cardozo & Ray, 2000; Markham & AimanSmith, 2001; O’Connor & Rice, 2001). Chakrabarti (1974) found that champions must have technical competence, knowledge about the company, knowledge about the market, drive and aggressiveness, and political astuteness. Howell and Higgins (1990) found that champions are most likely to use a transformational leadership style. After the initial concept has been defined and has management support, a formal project is launched to implement the concept and bring it to market, usually following some sort of formal product development process (Griffin, 1997). At this point in the NPD process, a project manager generally is assigned formally to the project. His responsibility is to organize the execution of the project and ensure that each task and milestone is completed on time and within budget. Research has suggested that these individuals are task-oriented (Turner & Müller, 2005), yet also must have the ability to influence others on the team (Crawford, 2003). Lee and Sweeney (2001) found that the most frequently used influence tactics by project managers were rational reasoning, consultation and
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inspirational appeals. Higher project success is associated with project managers who exhibit higher proficiency in planning, a more participatory and motivating management style, and skills in the technology domain (Thieme, Song & Shin, 2003). The picture that emerges is one of different types of people, with different knowledge bases, sets of skills, and leadership styles, who tend to perform the different tasks in NPD. However, some of the early empirical research on labour division in the innovation process also found evidence of projects with no division of labour at all (Chakrabarti & Hauschildt, 1989), implying that, at least in some cases, that one individual is responsible for the entire innovation and commercialization effort. Research on intrapreneurs (Pinchot, 1985) and hero scientists (Leifer et al., 2000), also suggests the existence of individuals who perform effectively across multiple stages of the NPD process, and act in multiple roles (Figure 2). These individuals, whom we term ‘innovators’, invent, champion and facilitate projects through the implementation process. Innovators are important to understand, since their strong depth and breadth of technical, market and business knowledge can result in superior products that bring strong results to the firm (Griffin et al., forthcoming). Initial research on innovators produced a framework with six elements that seem to be important in understanding them and how they operate in the context of mature firms (Figure 3 from Griffin et al., forthcoming). They bring to the corporate world their special personality, perspective or worldview, preparation and motivation (the four elements inside the circle of Figure 3). Working in the context of the corporation, they develop both a political capability and process for innovation that enables their working across all stages of product development.
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Figure 2. Serial Innovator Activity in the NPD Process © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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Process
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Figure 3. The Six Elements of Innovators: MP5 These individuals tend to be very driven systems thinkers, who are creative and curious about many different topics. They have a somewhat idealistic worldview – they want to use technology to solve problems and improve business outcomes and peoples’ lives. They also take the perspective that technology is a means to an end, and that new technology must make money for the corporation. Because of their preparation, they are technically competent, having both technical breadth and depth, but are also able to connect technology to business concepts and customer problems (Vojak et al., 2006). Innovators are intrinsically motivated by their desire to solve important real world problems, where ‘important’ is defined by people external to the corporation, such as potential customers (Hebda et al., 2007). Innovators understand the reality of the political process of project acceptance. They prefer to use facts and other positive influencing mechanisms in managing the politics of innovation. Their process focuses on using extensive customer interaction to fully understand potentially interesting problems and extensive exploration of possible solutions, before launching into the implementation phase. They act in whatever role is needed at any particular point in time, much like entrepreneurs. Finally, innovators follow the new product into the marketplace, helping to market and sell it. Overall, their process focuses on the tasks that are completed before a typical formal NPD implementation process, and extends beyond that process as well (Griffin et al., forthcoming). In summary, while the vast majority of innovation projects divide the total labour among
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different ‘specialist’ individuals, some innovation projects are substantially the responsibility of just one individual, who has capabilities that allow him to drive all the phases of the project. Some of the literature has investigated various characteristics of technical inventors, another has investigated champions, a third has suggested some characteristics associated with successful project managers, and a recent body of research has started to identify particular characteristics of innovators and how they span the innovation process in its entirety. The literatures on inventors, champions and implementers have primarily focused on background, orientation, operational and managerial characteristics, while the innovator research also has investigated personal and interpersonal characteristics. Initial comparisons of characteristics from the literature suggest there are a number of differences across these specialist types, implying that each specialist type may have to be managed somewhat differently, including innovators. To date, these different types of specialists (including innovators) have been investigated only individually in various studies, and each specialist type has been investigated by different sets of investigators, even though inventors, champions and implementers will all interact in the innovation process. This research investigates nine individuals from one organization who have over time acted as repeat inventors (2), champions (2), implementers (2), and innovators (3), exploring what types of people they tend to be and what some of the differences between them may be. This may have implications for how each of these groups is managed.
Methodology Sample This study focused on the employees at an autonomous division of a Fortune 500 engineering services firm located in the Midwest. The division, originally a spin-off from a university, was acquired by the parent company over a decade ago. It uses advanced scientific theory as a basis for new products, which are sold primarily to the government. The division is set up rather independently of, and geographically distant from, the parent corporation, with a mandate to grow revenues through the creation of more innovative products and services. The division’s structure is flat. The 60 people in the division are organized by functional specialty and then assigned into project teams as needed. Respondents were selected based on our dependent variables. That is, the division © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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manager identified individuals whom he believed exemplified the descriptions of the activities undertaken by serial innovators (three subjects), inventors, champions, or project implementers (two subjects each) for a total of nine subjects. Preliminary conversations with them confirmed that they were categorized appropriately into the different task specializations. Respondents were required to have been involved in bringing multiple products to market in their various roles. Eight of the nine subjects had MS degrees or higher in engineering, while the remaining person (a champion) had an MBA with an undergraduate degree in social sciences. Each subject was male with at least 10 years of work experience, not necessarily at the same company. All 17 of the managers and co-workers interviewed also were male.
Research Instruments In-depth interviews were conducted with each individual to investigate their approach to new product development projects. Subjects were asked about their thoughts, actions and environments within the context of two to three different projects in which they had played a key role. Subjects were then asked questions about their personalities and background, including educational history and career path. The interview outline can be found in the Appendix. Interviews varied in length from 30 to 120 minutes, averaging about 70 minutes. The protocol and research instruments were approved by the university’s human subjects committee. After completing their interviews, each of the subjects identified one to two co-workers with whom they had worked closely in the past and who knew them personally, rather than by reputation. Co-workers were prompted to discuss two to three projects in which they worked with the subject that exemplified the subject’s actions and behaviours as perceived by the co-worker. Additionally, the co-worker was asked about their perceptions of the subject’s personality, work styles, and contributions to the organization. Each subject’s manager was also interviewed in a manner similar to the peer interviews. A total of 17 additional interviews were conducted for the nine primary respondents.
Analysis All interviews were recorded and transcribed. The transcripts were reviewed twice to uncover key themes (Miles & Huberman, 1994) by two members of the research team. Phrases in the transcripts were coded, using © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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the six dimensions of the Innovator Capability Model as a framework for organizing the information (Griffin et al., forthcoming). The objective was not to test the validity of the model across the four specialist types, but just to use the framework to organize the data. Statements from each interview were categorized into one of these six categories. The data for each specialist type were aggregated. Finally, aggregate results were examined to uncover similarities and differences among the four different roles.
Limitations For the purpose of this study, individuals were assigned to specialist types according to the activities that they most frequently performed and at which they were the most successful, based on input from their managers, their peers and themselves. However, an individual’s ability to act in a certain role on a particular project may depend on the individual’s availability, or different project factors such as the technical subject matter or market space. Additionally, these individuals were all characterized as being high performers, whatever their specialist capability. It is thus unclear whether differences would be as pronounced for a more ‘average’ population. Another concern stems from the retrospective nature of the method, which lends itself to potential reporting biases. Finally, the small sample of individuals investigated for each role and the use of individuals from one firm limits the generalizability of the findings. These results should thus be treated as exploratory and preliminary.
Results Inventors The two inventors both had PhD degrees in one area of expertise and both had earlier held post-doctorate positions. Additionally, they had a strong grasp of a secondary, unrelated field of engineering, which allowed them to have unique insights in their primary focus area. They each had extensive experience in the engineering theory relevant to the division’s products. This knowledge granted them special insight in applying engineering theory and allowed them to develop creative technical concepts. These inventors focused on technology and technical development tasks. Both subjects were part of a ‘think tank’ that was created for the purpose of developing platform technologies for next-generation products. They were seen as technical experts in the company, although they interacted very
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little with other parts of the organization. The group was given a great deal of freedom, but reported to one of the implementers in this study for administrative purposes. Most of the group’s work focused on developing new engineering tools from complex theory under the leadership of the most senior member of the think tank – one of the innovators in this study. The general areas on which they worked typically were determined by the innovator, and then the inventors were given significant leeway in deciding how to move their projects forward technically. These individuals rarely interacted with customers, although they would occasionally participate in meetings where customer needs were discussed. However, both inventors relied strongly on their own intuition for determining the direction(s) in which new technology should be moved and which features should be included in products. While they both showed an understanding of ‘obvious’ trends or needs in the marketplace (‘tools need to be simple to be accepted and used’), they were less aware of need details, again relying on their own intuition of what they believed would be useful. Both indicated a strong preference for ‘figuring stuff out myself’ rather than working as part of a collaborative team. Politically, these inventors relied primarily on others to sell their ideas to upper management. The inventors in this study expressed a strong interest and appreciation for technical work. They enjoyed solving challenging technical problems and deliberately avoided management roles in order to focus on technical subjects. They enjoyed being on the cutting edge of technology and desired to push the state of the art. However, at least one of the inventors occasionally struggled to see the larger context and was described by others in the firm as having a penchant for over-engineering. Both inventors came from well-educated families, and related that dinner conversations ranged across numerous topics, helping pique their educational interests. They both could be described as ‘lifelong learners’, in technical topics as well as in broader topics, preferring fact-based reading to fiction. Their offices contained little more than the technical resources they needed to work, and a few productrelated artefacts. They indicated that they had little social life outside of their family.
Champions The two champions interviewed acted in business development roles. At the time of the study, both had been with the company less
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than a year and were brought in for the purpose of reaching new customer segments. Both were senior managers with administrative responsibilities and teams reporting to them. They were accomplished business people with strong communication skills and an ability to sell their ideas. The two champions had very different backgrounds from the other subjects in this study. One champion had an electrical engineering degree, but did not have much experience in engineering design. The other had no formal technical education, but a great deal of applied technical experience prior to receiving his MBA. Both champions had extensive experience in business development and had received informal training in sales and customer interaction. The champions focused their efforts on people and communication, preferring to work in small groups rather than either alone or in large groups. Their motivation is to create products and services that will be successful, meaning that people will buy them. They were known for being successful managers who directed their subordinates efficiently. They viewed product development primarily through the lens of meeting customer needs, and were adept at anticipating changing market conditions. As is found in the literature, these champions rarely created a new technical concept, but instead would recognize the merit of others’ ideas and could navigate the political environment, both internally in the organization as well as externally with potential customers, to secure support for their ideas. When the government is the customer, navigating the external political environment is at least as important as successfully navigating the internal political environment. One could describe them as acting as brokers, finding organizational capabilities that matched the needs of the firm’s customers. They had good relationships with customers and knew how to interact with them and follow up appropriately. As a result, they had a strong understanding of customer needs and how to set priorities among them. However, their ability was to define the functional needs rather than create exact specifications or technical requirements for the product. When presenting ideas or concepts to customers, they tended to focus more on the benefit to the customer of having the problem solved, rather than the particular solution chosen. Champions usually stayed out of the finer technical details and chose to delegate invention to inventors and development activities to implementers. The champions preferred to provide vision and direction at a high level. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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The champions interviewed were passionate and personable. They were described as competitive and driven, as well as somewhat stubborn. They would ‘do what it takes to get the job done’. Their co-workers and managers described them as creative, although not necessarily in the technical arena. Coming from diverse, but generally lower middle-class backgrounds, they have become well-rounded individuals with interests in many different fields, and were expressive about their hobbies, aspects of which spilled into their offices, as well as did other memorabilia. Both champions were active socially. Of the four specialist types interviewed, champions seemed to be the most focused on visible success and recognition.
Implementers The two implementers could best be described as technical project managers. Both have MS degrees in electrical engineering with at least ten years of technical design experience and performed the role of project engineer before being promoted to technical project managers. They are simultaneously technology and people focused, oriented towards ensuring task completion. Each managed a team of engineers and was responsible for the improvement of existing flagship products. Both implementers took on a great deal of administrative responsibility for managing and work planning, in addition to providing technical oversight for their projects. They had frequent contact with customers for the purpose of improving current product features and functionality and for providing assurance to them as to how the project was progressing versus the scheduled milestones. They were responsible for the final product that would be delivered to the customer. Because of their expert status, they were often involved in many different tasks. Both individuals focused on dayto-day project management and development rather than radical idea generation for new methods of reaching new markets or using new technologies. As a result, most of their projects were either characterized as incremental innovation or the execution of concepts established by others in the organization. These implementers were described as having strong organizational, people and communication skills, with a competent grasp of the engineering theory behind their product. Past experience gave the implementers a deep knowledge of the product and an understanding of how the customer used it. They understood technical details and were often deeply involved in that capacity. Although they had © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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good communication skills, they tended to avoid the political aspects of the NPD process. Their managers and co-workers believed that they had an unusual union of technical and people skills, which made them unique and valuable to the company. Both individuals came from ‘average’ middle to lower-middle income families, with parents who had not graduated from university. They were described by co-workers as diligent, hardworking and detail oriented. They both found great satisfaction in developing technical products, but also enjoyed interacting with people. They both functioned as mentors and teachers in the organization on top of their development responsibilities. They enjoyed work, but were not obsessed with it, focusing their emotion on other things, such as family. Their managers described them as being reliable, dependable, and instrumental in the development of short-term products. The implementers’ offices could best be described as ‘sparse’.
Innovators The three innovators interviewed as part of this study were directly responsible for creating and commercializing radical innovations. Out of the four roles, the innovators had the most diverse backgrounds. One innovator had a PhD in electrical engineering and previously had been a university professor. This innovator had a strong grasp of computer programming, which was rare for a faculty member during the time in which he created his first radical innovation. The second innovator reported to the first innovator while he was working on his MS in computer science, but did not have any formal education in core engineering theory. Similarly, the last innovator also lacked the formal theoretical training of the first, but had a degree in systems engineering and the most experience in working with customers. Despite their varied backgrounds, each had extensive experience in engineering design, which differentiated them from the champions. While the innovators were recognized as technical experts, each also had a deep understanding of the customer. They were simultaneously technology and market oriented. These individuals had an ability to decipher customer needs both generally and in detail, and to probe further for appropriate information. The innovators interviewed had a strong ability to see across several different technical fields and predict market trends, allowing them to synthesize new ideas. Innovators were deeply involved during the concept generation
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phase, spending a great deal of time refining and understanding customer requirements. They would then collaborate with others and iterate between technical reality and customer needs. Once the concept was solidified, they might pass on some development details to implementers, but would remain involved in both the technical and market issues at a supervisory level. Similarly to the champions, innovators understood the political system and effectively built support for their ideas both internally as well as with their external (potential) customers. All three innovators were well-respected by the other members of the organization and were given considerable freedom. One innovator held a position of special autonomy – he was allowed to work on whatever projects he found interesting. The other two innovators were also managers of groups, with a great deal of formal authority. Despite their positions of authority, the innovators most often would build support for their ideas using informal persuasion, rather than their authoritative position, according to their co-workers. Interestingly, each of the innovators spoke of some traumatic early childhood experience that greatly shaped their personalities and perspectives. The death of a twin brother early in life might be one such type of trauma about which an innovator could have spoken. According to their accounts, these experiences taught the innovators to be pragmatic and to adapt to their surroundings. They also forged into them a desire to help make the world a better place. The innovators shared characteristics of both the champions and the inventors. They had a deep love of working on customer problems, like the champions. Like inventors, they were passionate technical problem solvers. However, they were more motivated to use their technical knowledge to create solutions that would meet customer needs. On the other hand, like the implementers, innovators also
have excellent people skills. This meant that they ultimately were likely to be promoted into management positions, which limited their ability to participate in the technical aspects of their projects to the extent that they would have liked. Innovators were confident and sure of their own abilities, but were often described by co-workers and managers as being humble and down-to-earth. The innovators also had a deep interest in one or more hobbies. Their offices were clearly used as a creative outlet.
Discussion and Managerial Implications To our knowledge, this is the first piece of research to explore, in one study, some of the characteristics of the different specialist types of individuals who are involved with innovation management and new product development. Tables 1 and 2 summarize the results across the four specialist types. Table 2 recasts some of the findings into the organizing framework of the Motivator Capability Model, for ease of comparison and discussion. The differences we find across these specialist types do in fact seem to have implications for the types of projects they may gravitate to and be likely to perform on most successfully, as well as for how the firm might best manage them. While the major characteristics of the inventors and innovators in this research closely resemble their profiles from the assembled literatures, the champions and implementers differ a little. In the literature, champions have been portrayed as working predominantly internally within the firm. The literature says nothing about their customer- and marketbased activities. However, in this investigation the champions seemed to act more as brokers between the firm and their customer, with extensive customer interaction and strong knowledge of needs. Perhaps this was because of the customer context of selling large
Table 1. New Product Development Roles and Skills Core skills Technical expertise Market expertise Political guiding Process implementation
Inventor
Champion
Implementer
• •
•
Serial innovator
•
Primary skill • Secondary sensitivity
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Some technology, customer and business Financial success and reputation Embracing Political acceptance and high level directing
Technology is the end goal
Avoidance
Invention only
Motivation
Attitude toward organizational politics
Process
Profit, success Product
Lower-middle class
Business and political Strong extrovert Small group Communication
Champion
Technology
Well-educated family, early exposure to many topics Life-long learning Profession
Technology Strong introvert Individual Task
Inventor
Knowledge base from preparation
Worldview Source of identity
Perspective Childhood background
Personality Creative ability Openness Work style preference Orientation
Table 2. Differences across the Roles
Facilitate development after concept
Find rational answers
Earn a good living
People and process
Work to live Firm, family
First generation college
Execution and coordination Extrovert Small group Task and people
Implementer
Participate in all facets
Acceptance – positive influencing
Create solutions to customer problems
Technology, customer, market and business
Traumatic childhood experiences Make the world a better place Customers
Multi-faceted – Either Multiple
Innovator
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systems to government agencies. In this context, the firm does not first try to build a product and then sell it. The firm first obtains the contract for the product, and then builds it to specification. There is more pre-selling before the product is developed than there is post-selling, with champions strongly involved. The project management literature suggests that effective project managers must have the ability to influence others on the team (Crawford, 2003). Higher project success is also associated with more participatory and motivating management styles (Thieme, Song & Shin, 2003). However, the implementers in this research go far beyond those base interpersonal requirements, describing themselves as ‘people persons’ or extroverts who genuinely seem to enjoy the human part of the job. Again, it is unclear whether the extant literature has missed this, or whether this finding is due to the particular context of this piece of research. Innovators are rather similar to champions, but with the benefit of a much stronger technical background and desire to move technology forward, akin to the inventors’ attitudes. This allows them to consider a wider range of technical solutions to meet customer needs and be more engaged technically in the NPD process than champions. The innovators studied sought connections between markets and technology, believing that technical development serves primarily to satisfy a market need. According to the division manager, an innovator would be more likely to reach a new customer by developing a better product, while a champion would attempt to use a better sales pitch with a current product. Conversely, an inventor might gain support for his or her invention by pushing its technical merits, while an innovator would be more likely to demonstrate its ability to solve a customer problem. Implementers opt out of this aspect of the process completely. One major difference across the roles is the form that creativity takes across the four different types of people, as suggested in the first row of Table 2. Inventors exhibit high levels of creativity, but narrowly applied, restricted to creativity across their technical fields. Champions do not necessarily exhibit technical creativity, but they are creative in business and managing the politics of NPD. Implementers prefer to operate in more certain environments with higher control and less uncertainty. However, they may be seen as exhibiting executional creativity and creativity in the way they orchestrate and coordinate people to work together to produce results. Finally, innovators exhibited technical, customer, market, political and business creativity.
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According to their own accounts and the accounts of their co-workers and managers, each of these nine subjects tended to take a significant leadership role, albeit in different ways, in product development, as suggested in the last row of Table 2. While many of these individuals perhaps could have performed effectively in other stages of the NPD process, they each seemed to be drawn to work repeatedly in one particular specialist part(s) of the process. This aspect of innovation management was the part that they enjoyed the most and where they felt they could have the greatest impact. The inventors preferred to not worry about the details of customer needs and developing specific solutions for them. Champions tend to be more ‘big picture’ and orchestrating in nature, driven by a desire to make an alreadyidentified solution work elsewhere. Implementers are by nature detail and people oriented, less comfortable with ambiguity than the inventors and innovators. Finally, innovators are drawn to the new and different, wanting to do the radical, comfortable with ambiguity in order to make the world a better place. Each specialist type tends to stick to their phase of development, time and again. Thus, it seems that firms may contain ‘serial’ innovators, as well as serial inventors, serial champions, and serial implementers. Interestingly, the different specialist types seem to map to individuals choosing also to focus on different types of projects, as illustrated in Figure 4. The framework is analogous to Ansoff’s matrix for strategic growth (1965), differentiating projects by their levels of market and technical uncertainties. Inventors disliked project management, favouring instead to focus their efforts on working with advanced theory. They also deemphasized marketing and customer interaction, and
Figure 4. The Four Types of NPD Leadership and Their Associated Area of Expertise © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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would only talk to customers when others felt it was necessary. They seem to prefer projects with high technical uncertainty, but where market uncertainty may be lower. The champions surveyed believed the work of implementers and inventors to be essential but boring, and enjoyed the challenge of expanding their business into new market areas. They preferred projects where market uncertainty was higher, but approached the solutions from a lower technical uncertainty orientation. Implementers preferred working on projects with very little ambiguity and would avoid projects that involved highly theoretical technology or significant market development. They focused on incremental projects that required teamwork and for which the outcomes could be predicted and managed. For these implementers, this preference seemed to be based on motivation as opposed to skill. Innovators relished connecting new technology capabilities to solving real customers’ problems, using technology as a means to an end of making the world a better place, naturally gravitating to more radical innovation development. In practice, then, it would seem that inventors may be best suited to perform purely technical development, champions to work in market development, implementers to execute incremental NPD, and innovators to develop radical innovations. This does not mean that each specialist type is only capable of being successful at one type of project, nor does it imply that individuals always work on their preferred project type. Rather, it appears that the uncertainties and issues associated with each project type may be best addressed by individuals who possess matching strengths and preferences. These findings also suggest that the firm may want to manage the different specialist types in somewhat different ways. For example, inventors probably should not be managing people, but should be allowed to concentrate on moving technology forward. They seem to prefer insulating themselves from the outside world, so mechanisms by which they can be integrated gently back into it to gain more of a customer-driven understanding of where the technology may need to go may need to be put into place. The reward system should support their continued technical output focus and provide means for them to keep learning about the technical fields. Champions need access to customers and the inventors, meaning that they need the freedom (and funds) to make excursions both inside and outside the organization. Their desire for (financial) success and reputation © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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needs to be addressed by the reward system, especially when they score a big hit. Office prestige may matter to them, in size, accoutrements and proximity to division leaders. Implementers may prefer ‘rational’ management structures and egalitarian reward systems that provide them with predictable improvements in rank, salary and bonuses. Fancy offices do not mean much to them, but since people are so important to them, they need to be located centrally, with easy access to their team. Finally, innovators need the most managerial freedom of all. Because they move across the different innovation labour specialities, it may be difficult to fit them into a particular box on the organizational chart. Their need to continue learning across multiple fields means that obtaining access to information, both within the firm and external to the firm, across many topics, will be important to them. As they are motivated by creating solutions to customer problems, they need to get out into the field, not just to gather customer information, but also to see that their product solutions have worked. In summary, then, it would seem that different management strategies need to be developed to allow each of these specialist types to function to their potential, and subsequently feel appropriately rewarded. It is unlikely that someone who is adept at managing inventors will be adept at managing champions, or that a good manager of implementers could also manage innovators. And yet, inventors, champions and implementers need to interact effectively in order for a technology to proceed from capability to successful product in the marketplace. Knowing how to get all these specialist types to work together is important to the firm. This research opens up many additional questions that could be addressed in the future. Most obvious is to replicate the qualitative inquiry across multiple firms for generality. A longitudinal participant observation study of people in each of these specialist areas might also provide a richer set of differences. Finally, research to further understand what these differences mean for how each specialist type is managed and assigned to different types and stages of projects would be important to firms.
Acknowledgements Funding for this research was provided by the Marketing Science Institute and by the Institute for the Study of Business Markets.
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Belliveau, P., Griffin, A. and Somermeyer, S.M. (eds.), The PDMA ToolBook2 for New Product Development. John Wiley & Sons, Hoboken, NJ, Chapter 3. Miles, M.B. and Huberman, A.M. (1994) Qualitative Data Analysis, 2nd edn. Sage Publications, Thousand Oaks, CA. O’Connor, G.C. and Rice, M.P. (2001) Opportunity Recognition and Breakthrough Innovation in Large Established Firms. California Management Review, 43, 95–116. O’Connor, G.C. and Rice, M.P. (2005) Towards a Theory of New Market Creation for Radical Innovation. RPI Working Paper. Pinchot, G. III (1985) Intrapreneuring. Harper & Row, New York. Rice, M.P., Kelley, D., Peters, L. and O’Connor, G.C. (2001) Radical Innovation: Triggering Initiation of Opportunity Recognition and Evaluation. R&D Management, 31, 409–20. Rogers, E.M. and Shoemaker, F.F. (1971) Communication of Innovations: A Cross-Cultural Approach. Free Press, New York. Schon, D.A. (1963) Champions for Radical New Inventions. Harvard Business Review, 41, 77–86. Schumpeter, J.A. (1912) Theorie der Wirtschaftlichen Entwicklung. Duncker and Humblot, Leipzig, Germany. Schumpeter, J.A. (1934) The Theory of Economic Development. Harvard University Press, Cambridge, MA. Smith, P.G. and Reinertsen, D.G. (1992) Shortening the Product Development Cycle Source. ResearchTechnology Management, 35, 44–49. Thieme, R.J., Song, X.M. and Shin, G.-C. (2003) Project Management Characteristics and New Product Survival. Journal of Product Innovation Management, 20, 104–19. Tidd, J., Bessant, J. and Pavitt, K. (1997) Managing Innovation. John Wiley & Sons, Chichester, UK. Turner, J.R. and Müller, R. (2005) The Project Manager’s Leadership Style as a Success Factor on Projects: A Literature Review. Project Management Journal, June, 49–63. Uhlmann, L. (1978) Der Innovationsprozess in westeuropäischen Industrialändern, Vol. 2. Der Ablauf Industrieller Innovationsprozesse, Ifo-Institut, Berlin and Munich. Vojak, B., Griffin, A., Price, R.L. and Perlov, K. (2006) Characteristics of Technical Visionaries as Perceived by American and British Industrial Physicists. R&D Management, 36, 17–24.
Abbie Griffin (abbie.griffin@business. utah.edu) holds the Royal L. Garff Presidential Chair in Marketing at the David Eccles School of Business at the University of Utah, where she teaches businessto-business marketing and 1st-year core MBA marketing. Professor Griffin’s research investigates means for measuring and improving the process of new product development. She is a member of the Board
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of Directors of Navistar International, a $13 billion manufacturer of diesel engines and trucks, and was the editor of the Journal of Product Innovation Management, the leading academic journal in the areas of product and technology development from 1998 to 2003. Prof. Griffin is an avid quilter, hiker, swimmer and scuba diver. Edward W. Sim received a Master of Engineering degree from the University of Illinois at Urbana-Champaign in 2003. After spending four years as a management consultant at Bain & Co., he is now obtaining his MBA from Northwestern University. The data collected for this project formed the basis for his master’s dissertation. Raymond L. Price was appointed to the William H. Severns Chair of Human Behavior in the College of Engineering in the fall semester 1998. As the Severns Chair, his primary charter is to provide opportunities for engineering students to understand and develop skills in human behaviour: interpersonal skills, leadership and management skills that will be useful to them in their careers. Before joining the College of Engineering, Dr. Price had a career in industry working in management and organization development and human resources. Most recently he was VicePresident of Human Resources at Allergan, Inc. and before that he was Director of Employee Training and Development for Boeing Commercial Airplane Group. He also held various management positions with Hewlett-Packard, including Manager of Engineering Education. Dr. Price graduated from Brigham Young University with a BS degree in Psychology and an MA degree in Organizational Behavior. He earned a PhD degree in Organizational Behavior from Stanford University. Bruce A. Vojak is Associate Dean for External Affairs in the College of Engineering and Adjunct Professor of both Electrical and Computer Engineering and Industrial and Enterprise Systems Engineering at the University of Illinois at UrbanaChampaign. Previously he held various technical and management positions at MIT Lincoln Laboratory, Amoco and Motorola. Before joining the University of Illinois in 1999 he was Director of Advanced Technology for Motorola’s frequency generation products business. He has authored or co-authored over 60 peer-reviewed journal publications in the general fields of electronic materials, components and subsystems and, more recently, in the field of technology management. He received BS, MS and PhD degrees in electrical engineering from the University of Illinois at Urbana-Champaign and an MBA from the University of Chicago.
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Appendix: Outline of Interview Guides Indirect Interview Guide Identify the respondent’s most recent, most successful, and most notable project failures. Ask all questions for each case (3 times). 1. How did this project get started? How were you involved? Why did you get involved? 2. What was your contribution to the project? Official role? De facto role? 3. Who did you work with on the project? What was your relationship to them? To whom did you go for advice? 4. What was your role in the strategy planning for this project? 5. How did you gather information for (invention, championing, or development)? Customer interactions? Info from other employees? 6. What roadblocks were encountered? How did they come about? What were your initial (emotional/intellectual) reactions? Others’ reactions? How did you address these issues? How was it finally resolved? 7. How did you gain support for this project? 8. Describe your interactions with . . . Peers? . . . Managers? . . . Executives? 9. How long were you involved with this project? Why did you leave? How did you monitor the project after you left?
Direct Interview Guide 1. Do you have any significant hobbies or avocations? Describe them. 2. Do you participate in any routine activities outside work (reading, exercising, etc.)? 3. What activities would you do if you had more time? 4. What clubs or organizations do you participate in . . . Social? . . . Political? . . . Religious? 5. Do you prefer large or smaller group situations . . . Socially? . . . Professionally? 6. Describe your ideal work environment. 7. Describe your physical work environment currently. What would you change about it if you could? 8. What is the best time of day for you? Why that time? 9. How do you organize . . . Your time? . . . Your Activities?. . . . Your thoughts? 10. What is your attitude toward learning new things? 11. What unique educational experiences have you had? 12. As a child: a. Did you perceive yourself as being different from others your age?
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13. 14. 15.
16. 17.
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b. Did others perceive you as being different? Why, do you think? c. Do you still think those perceptions are true of you now? Did you have anyone that had a major impact on who you became? Tell me about that? What mentors have you had? Academic? Social/Relational? What are some significant life experiences you have faced? What did you learn from them? How did they change you as a person? What are your . . . Greatest strengths? . . . Greatest weaknesses? What formal education have you had? For each, ask the following: a. Why did you undertake this degree?
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b. What were some of the skills that you developed during this time? c. What were the best lessons you learned during this time? d. Would you have done anything differently? 18. What jobs have you had? For each, ask the following: a. Why did you take that job? b. How much influence did you have in defining the specifics of the position? c. What were some of the skills that you developed during this time? d. What lessons did you learn from this job? When/why did you leave? e. What would you have done differently in this job, if you could have?
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Individual Inventors in the R&D Factory Hans Andersson and Christian Berggren Are individual inventors still important in today’s lean R&D organizations? A study of three R&D organizations in two Swedish companies, both committed to increasingly leaner R&D and with an innovation focus, certainly indicates that a small group of extra innovative inventors in each organization outperform their colleagues in terms of patents applied for. In this paper we discuss how managers can leverage these important individuals and how the fragile inventive space needed for the growth of the next generation of key inventors can be nourished.
Introduction
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ninhabited processes, structures and projects dominate the literature on new product development (NPD) and management of innovation. Teams are important, but team members are viewed as ‘generic engineers’ (Steiner, 1995), a set of functional competencies and skills without any traits of individuality. With increasing competition and the spread of lean product development (Reinertsen & Shaeffer, 2005; Baines et al., 2006), reducing the slack necessary for high levels of innovation (Lawson, 2001), the vision of R&D defined by processes and standards is becoming stronger, downplaying the role of the individual inventor (Leenders et al., 2007) and the importance of his/her autonomy (Katz, 2005). At company Alpha in our study, this development was described as a journey towards the predictable, fast-paced, or takted, resource efficient ‘R&D factory’. In the histories of technology-based companies, however, individual inventors often figure prominently as examples, role models or myths. Are individual inventors still important in the rationalized R&D operations of modern, internationally competing firms? And if they are, how can managers support and leverage not only their technical value but also their organizational value? And finally, in the age of lean ‘R&D factories’, how can the inventive space needed for the growth of next generation inventors be nourished? These three questions frame this paper.
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We agree with Van de Ven’s statement that ‘innovation is not an individual activity – it is a collective achievement’ (1986, p. 597), but we think that it is a mistake to too easily accept the view of the generic engineer. Nor do we think that it is sufficient to regard the inventor as just an idea generator who quickly disappears behind processes and structures at the expense of the other roles or functions necessary for innovation (Roberts & Fusfeld, 1981). Thus, the interest guiding our research is the role of individuality in contemporary R&D, i.e., that individuals differ in technical creativity and combinatorial skills (Angle, 1989). We start with an overview of the relevant literature, followed by a presentation of our methodology. Next we present our findings regarding the importance of individual inventors in the companies, and a discussion on leveraging inventors. Finally, we discuss some mechanisms, which support innovative space within the ‘lean R&D factory’.
The Need to Populate the NPD World In the mainstream new product development literature, cross-functional teams are seen as a very important factor – and the smallest relevant unit of analysis. Brown and Eisenhardt (1995) explicitly state that while project members do the actual work, the focus of much research is on the team. If any individuals are celebrated, it is not the technically
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inventive engineer, but instead the heavyweight project managers (Clark & Fujimoto, 1991), product champions (Schon, 1963; Markham & Griffin, 1998), gatekeeper (Nochur & Allen, 1992) or leaders (Mumford & Licuanan, 2004). Even if idea generating is one of the work roles or functions critical to innovation (Roberts & Fusfeld, 1981), the idea generator(s), i.e., inventor(s), and patenting do not appear to be salient in the NPD literature. Nor are individual inventors prominent in the literature on lean product development (Karlsson & Åhlström, 1996; Sobek, Liker & Ward, 1998) with its focus on process flow and waste reduction (Reinertsen & Shaeffer, 2005). Liker and Morgan (2006) discuss ‘people systems’, emphasizing among engineers and developers the importance of technological knowledge and the ability to improve processes. However, even if, as Liker & Morgan say, people ‘provide the intelligence and energy to any lean system’ (2006, p. 12), the discussion remains on a systems level. From this, it is no surprise that the importance of key inventors and researchers in R&D has been neglected (Narin, 1993) and that, consequently, there has neither been much discussion about individual inventors in large organizations, nor about their differences (Ernst, Leptien & Vitt, 2000). Even if the discussion about lean product development tends to be oriented mainly towards ‘smaller developmental programs based on a high degree of legacy knowledge’ (Oppenheim, 2004), which is in accordance with Benner and Tushman’s (2002) findings regarding process management in general, we do not think that is a good argument for not paying attention to productive inventors and their importance (Narin & Breitzman, 1995) in R&D driven companies. Recently, there seems to have been a renewal of interest in the role of the individual in the innovation process. Vojak et al. (2006) present a study of how the characteristics of ‘technical visionaries’ are perceived by others. The Journal of Engineering and Technology Management (vol. 21, 2004, issue 1–2), and R&D Management (vol. 35, 2005, issue 5) have dedicated special issues to the theme of individuals in innovating organizations. In more general terms, the role of specific employees as instrumental in creating competitive advantage has been discussed from a resource-based perspective (Barney & Wright, 1998; LopezCabrales, Valle & Herrero, 2006) and within HRM (Söderlund & Bredin, 2006). With few exceptions (Cooper, 2005; Sapienza, 2005), none of these articles focuses on inventors in large firms, nor do they consider the changing
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conditions for innovative activities brought about by the ‘leaning’ of R&D. Even in the literature on radical or discontinuous innovation, where the personal input could be assumed to be of particular importance, the research is mainly preoccupied with abstract processes and usually loses sight of the individual inventors (Veryzer, 1998). One exception is O’Connor and McDermott (2004) who explicitly discuss how companies can ‘. . . leverage the human element necessary for radical innovation’ (p. 12). O’Connor and McDermott refer to entrepreneurial people as well as maverick individuals whose passions and talents are human aspects of radical innovation to leverage. The mechanisms they discuss for leveraging are continuity within and connectivity across roles, team composition, informal networks, and risks vs. rewards for team members. O’Connor and McDermott focus on what we refer to as technical value, i.e., generally related to product characteristics and performance. The same goes for Borredon and Ingham (2005) in their discussion on mentoring in an R&D context. They advocate the central role of dialogue between senior and junior inventors, which in their terms is something ‘far beyond the classical exchange of ideas and information’ (p. 499), implying that there is more to the generative dialogue than technical matters. One such aspect is what O’Connor and McDermott (2004) describe as knowing ‘how to work the system’ (p. 26) which distinguishes some action-oriented people who thrive in the context of a large R&D organization. From another perspective, Verona (1999) points out that resource-based scholars have discussed the impact of organizational capabilities on product development processes, but have not paid attention to how agents leverage these capabilities during product development. It seems plausible to include not only mangers but also inventors among the leveraging agents, as turning an idea into an invention normally requires action, and interaction, from the inventor(s) in addition to generating the idea. Creative ideas are the beginning of all innovation (Amabile et al., 1996), but it takes action to develop a creative idea into a (patentable) invention and marketable innovations, and normally the inventor’s actions are essential in that process. Talke, Salomo and Mensel (2006) have developed a model of initiatives for innovation, which is analogous to Amabile’s (1988) three-component model for individual creativity. Apart from the skills an individual must possess to be creative, they advocate that a set of competencies are required for initiating initiatives. In their model, the individual’s action © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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competence is critical for the emergence of initiative competence together with task-related and cognitive competencies. Talke, Salomo and Mensel argue that action competence can be enhanced in different ways, mainly by different motivational measures. The idea of a specific competence for action taking is thus highly relevant for the discussion on the leverage of key inventors. The metaphorical concept of inventive or innovative space introduced in the introduction is meant to denote the room for manoeuvre available to realize inventions. This room is not simply there, but is created in the intersection of individual actors and organizational conditions. Inventive space is thus a matter of organizational conditions and an individual’s ability to act upon them (cf. Archer, 1995). A sufficient amount of slack (Nohira & Gulati, 1996; Lawson, 2001) is often regarded as favourable to innovation. Even if slack seems to be similar to inventive space, the concepts are not interchangeable. Slack should be regarded as a facilitating condition, while an innovative space is created by individuals with certain competencies and interests. What happens with this space when the R&D system becomes ‘leaner’ and more resource efficient, i.e., when what is referred to as slack is reduced? Reinertsen and Shaeffer (2005) argue that while R&D in many ways differs from manufacturing, with care it is possible to apply the lean principles to R&D and define ‘lean R&D’ as the optimized combination of the logic of lean principles with the economics of R&D. They specifically emphasize two elements of lean thinking as central: reducing waste and creation of flow. In a similar sense Haque and James-Moore (2004) focus on waste reduction and flow of value in their detailed overview of what the principles of lean may mean for product development but do not discuss aspects such as inventing or innovating. The dual focus on waste reduction and flow encompasses much of the development that has taken place in the R&D departments in our study and thus what is referred to as the ‘leaning’ of R&D. To sum up, few studies in product development pay much attention to individual inventors and those who are interested in individuals have not observed the trend towards leaner R&D organizations. This lacuna has inspired our interest in an investigation into inventive individuals in modern firms, how managers can ‘get the most’ out of them, and balance the drive towards R&D factories with the need for preserving innovative space. In the paper, we use ‘inventor’ as synonymous with ‘patentee’. An innovation means that the idea or invention is realized in © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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a product or solution. Nearly all interviewees in this study were more than inventors (patentees) and participated in this wider innovation process. In the following, ‘inventive’ and ‘innovative’ will be used interchangeably.
Research Design: A Micro-Level Patent Data Based Study In this study we use patent application statistics to identify companies as well as inventors inside the selected companies. To file for a patent in the name of a large company means that the invention is accepted internally, involves an inventive step, i.e., is not obvious to those skilled in the art (EPO, 2005), and is considered to represent a potential value to the company, i.e., demands similar to those for creativity in a company context (Ford, 1995). Further, it takes considerable effort from inventors as well as from others, for an application to be developed and submitted. Thus patent applications, like patents, provide some kind of objective measure of innovative or creative activity (Huber, 1998). Further, using patent applications instead of patents that have been granted makes it possible to use more recent data. As we are not interested in evaluating or comparing companies or industries, the disadvantage of using patent-related data (e.g., different propensities to patent between companies or industries, or areas where companies do not patent for reasons of confidentiality, e.g., manufacturing processes), do not apply. The general advantages and disadvantages of patent-related data have been discussed extensively elsewhere (see Patel & Pavitt, 1991; Hagedoorn & Cloodt, 2003). Swedish national statistics of patent applications from the years 2000–2004 were used to identify ‘patenting intensity’ among companies in Sweden. A pattern emerged where a small number of companies consistently applied for more patents than others. Two companies, Alpha and Beta, were selected on the basis of their high patenting intensity and their focus on R&D effectiveness. Both companies are big, successful global players, and although they compete in mature industries, which could imply an orientation towards process innovations (Abernathy & Utterback, 1978), both consider product innovation capability to be a key to their competitiveness. Fierce competition creates a strong pressure on both of them to make product development more efficient. Patenting is regarded as being important in both companies and is actively encouraged by top management.
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The first company, Alpha, was characterized by three factors which hypothetically implied a low significance for inventive individuals in its R&D: large size, focus on NPD process streamlining, and the integrated system character of its products (cf. Hobday, Davies & Prencipe, 2005), which limits the room for radical or discontinuous innovations (Garcia & Calantone, 2002). Whereas Alpha delivers highly integrated systems, Beta mainly develops and manufactures advanced components or subsystems, which combine state-of-the-art materials science with in-depth mechanical knowledge, for customers with high demands on reliability and trouble-free operations. In many respects the two companies represent the modern technology-oriented firm, and at the same time they differ with regard to technology and product system scope. Within the two companies, we used their internal statistics for patent applications in the period 1999–2004 to find the most inventive individuals. Ernst, Leptien and Vitt (2000) present a way of distinguishing among different types of inventors based on patent analysis (see Figure 1). In finding interviewees, we have been interested mainly in the activity aspect of Ernst et al.’s model (Figure 1). In discussions with patent officers and R&D managers, the quality aspect, interpreted as usefulness, has been explicitly considered. Invariably, the most productive inventors had also generated highly valuable innovations. At each company, the most productive inventors were interviewed, and further interviewees were selected among other inventors to get a variation in age and field of technology, and to include female inventors in these male-dominated organizations. The reasons for this were to cover all the key inventors’ fields of technology and to have both experienced and younger inventors represented. Even if the female share of patents
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Figure 1. Inventor Portfolio (Ernst, Leptien & Vitt, 2000)
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is small today, it is expected to increase as more women engineers and researchers are recruited to R&D organizations. We thus regard the views of different categories of inventors relevant even if the sample is not large enough to be analysed based on the different categories. The most productive inventors are of special interest in this study, but all categories in Figure 1 are represented. In total, 34 formal tape-recorded interviews were conducted, 24 with inventors, and 10 with managers, from section heads to corporate VPs. Among the managers, several were former inventors, holding a number of patents themselves. With regard to the inventors, there was a wide variation in their backgrounds. Some had started out as skilled workers and then, after a number of years in the workshop, had become designers. Others were PhDs recruited as specialists straight from university. While the formal position of most of the non-managerial interviewees was researcher and/or developer (some are formally recognized as experts), they could also be part-time project managers and/or gatekeepers responsible for a specific field of knowledge at the same time. Roles are not so clear-cut and in many cases they change over time. In addition to interviews, a number of informative meetings and one extended workshop have taken place with R&D managers and patent officers. For the inventors, we used one or two of their recent patents both for preparing ourselves and as a starting point for the interviews. By asking them to tell their story of the process of their specific inventions, we entered into semi-structured discussions mixing detailed technical and scientific explanations with various observations on issues such as networking, idea sharing, competence development, discovery of interesting deviations when doing experiments, changing R&D conditions, etc. Both inventor and management interviews were coded independently by both of us. A number of themes emerged in our subsequent discussions, among those the ones forming the basis for this paper.
The Importance of Individual Inventors Do individual inventors matter in these highly organized companies, which compete in mature markets? Data from the companies studied certainly indicate the existence of extra-inventive individuals. Figure 2 shows the patenting activity for the 25 researchers and engineers within each organization, who had applied for most patents © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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Figure 2. Number of Patents Applied for by the Most Inventive Engineers 1999–2004. (‘Whole counts’ not adjusted for co-inventions between two ore more persons. Cf. Narin & Breitzman, 1995)
during the six years from 1999 to 2004 (Beta is illustrated by two lines, one for each of its two R&D organizations). While 50 per cent of the individuals represented in the diagram account for four or fewer patent applications (in one case, the tail is much longer than shown in the graph, with almost 100 individuals applying for at least two patents), a small number of individuals in each organization applied for more than twice as many as the average. In spite of different R&D structures and products, the distribution of patenting activity among their R&D personnel turned out to be remarkably similar in the two companies. This pattern is consistent with the claim by Ernst, Leptien and Vitt (2000, p. 184) that ‘inventors are not alike’, and Narin and Breitzman’s (1995) findings that normally managers can point out the few important individuals driving their laboratories. One manager commented on the diagram in Figure 2: There are five individuals that form the first five [referring to an ice hockey term describing the team’s strongest formation] that you have to take care of. (Top manager Beta) Several other factors indicated the importance of individual inventors and productive patentees for the two companies. First, in recent years both companies had changed their © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
patent offices from corporate legal departments to supportive units close to the R&D operations, staffed by experienced engineers/ researchers with patenting expertise. The inventors interviewed illustrated the importance of this reorientation, and how the patent officers actively helped inventors to identify new, unexplored (or at least unprotected) areas for further inventive activity. At Alpha, the VP of R&D (himself an inventor) has created a ‘wall of fame’, with signs showing the names of all inventors/patentees and instituted an annual Patentees Party to celebrate recent progress. At Beta, company policy required new products to be protected by proprietary patents and one of its two R&D operations expected new employees to submit a patent application within two years of being hired. Both companies readily acknowledged the importance of extra-inventive individuals. At Beta, one manager referred to one of the R&D engineers as being critical for the company’s financial success over the years. Yes, I think he has accounted for a great deal of our company’s profitability. A great deal. (Middle manager, Beta)
Leveraging Inventors The inventors in our study repeatedly stressed the value of dialogue with management. They
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might not need the manager’s formal approval to test a new idea, but in order to bring an idea into a patentable invention, supportive managers are essential. Several inventors emphasized the ability of their managers to challenge and stimulate them professionally. By asking relevant questions, they can be very important as inspirers, but can also help inventors to integrate their inventions in the overall corporate efforts. This integrative role was supported by the fact that so many managers had been successful inventors themselves. He has got ideas himself and he tries to get the employees to work on their own ideas as well. You get stimulated by a manager like this, it raises the work effort, this is important. (Engineer Alpha) The competency profile of managers is an important prerequisite for this dialogue. Nearly all the inventors interviewed stressed the value of deep technological competence, to enable managers to ask the right questions and to support their ideas in other parts of the organization. Generalist ‘MBA managers’, however skilled in coaching, were not attractive to these inventive engineers and scientists with their interest in professional dialogue and scrutiny. Apart from this on-going dialogue, managers described other ways to leverage their most innovative employees and their knowledge in the organization. At Beta, the need for formalization and explicit documentation was emphasized: Today much here is based on individuals. We try to change work practices and get away from this strong reliance on particular people. Our goal is to build organizational knowledge. Instead of contacting George (the most respected inventor at the department) you will know there is a system where you can find the information in databases. (Middle manager, Beta) The support for a knowledge management approach was ambivalent, however. The same middle manager also stressed that junior engineers need to foster personal contacts with the senior inventors, not just to share their knowledge, but also to learn from their way of observing and reasoning, and be inspired by them as role models. Several of the informants had stories to tell about how important one or two older and more experienced inventors had been to them early in their careers, and later as peers. These contacts were important not only for their technological knowledge, but also for sharing their ways of perceiving problems and deviations from the expected, and introducing them to their networks.
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A selective way of leveraging inventive individuals was to combine several of them in small, creative teams. According to the experience at Beta, this had delivered extraordinary results in several cases: We put together a team of these two guys, another guy for detailed design and a previous product manager. They got two years to develop components for a generation of totally new machines. It was fun to watch their activities and the workshop for new ideas they created; ‘Stop, yes, combine this, combine that’. Within these 2 years we had at least 6–8 priority patents. (R&D executive Beta) The idea in this case was not to organize cross-functional ‘high performance teams’, but ‘high creativity teams’ acting as innovation hot-houses, with hand-picked inventive engineers/scientists stimulating and challenging each other. The importance of knowing ‘how to work the system’ (O’Connor & McDermott, 2004) is related to actionable individuals, and this knowledge seems to describe many of the inventors in our study. By definition these inventors are creative, but they also know what to do to get things going. One inventor, now a manager, told us how he used his network to squeeze his tests into a batch processed in the manufacturing facilities instead of waiting three weeks until a proper lab scale test could be done. He got enough information back to confirm the basic ideas which made him continue the initiative. Action competence and knowledge of ‘working the system’ are not far from Verona’s (1999) notion of agents leveraging organizational capabilities. In this study, we started by asking how managers can leverage the inventors’ organizational value, but maybe this question should be reframed to include how inventors themselves may leverage the capabilities of the organization.
Protecting Innovative Space in Streamlining Organizations My boss does not know anything about what I am doing. We have an agreement – I deliver what we have agreed upon and what I do the rest of my working hours is up to me. It is play and fun. (Engineer Alpha) The quotation above illustrates a convenient division of labour, where organizational slack is enough to permit inventors to pursue their own agenda as long as they feed the development factory. With increasingly lean R&D © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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organizations, however, the challenge to maintain innovative space needs a more sophisticated repertoire. When interviewing inventors and managers about this subject, a common answer was that engineers/ researchers with a track record of successful patents create their own space irrespective of organizational structures. The difficult issue is how to safeguard enough space to allow the growth of the next generation of inventors. The streamlining of R&D demands a lot of managerial attention, requires structure and standards, and tends to reduce slack and individualized ways of working. At the same time, top managers in our study, particularly at Beta, were aware of the fragile nature of the innovative culture and recognized that it could easily be eroded by excessive organizing, process-mapping and time-based project control. Sure, you can take this culture out by too much organizational control. I think it is a much smaller challenge to take it out than to make it happen. Most of these guys don’t feel good about too many structures, frameworks, and static demands. . . . It is really a very delicate system. (R&D executive, Beta) R&D executives at both companies emphasized the importance of ‘free’ innovative space where individuals may explore the unexpected. As the VP of R&D at Alpha explained: I expect people in R&D to experiment informally, and what you may call skunk works. In a way, it’s a self-adjusting system. Most ideas won’t catch on. You have to be lucky and have the right timing. With experimenting going on, the ideas that have survived the pre-selection process are reasonably good, and enjoy some degree of established trust. When you start a systematic evaluation, the basic technical idea development is already finished. (VP R&D, Alpha) At Beta, the attitude was similar and one top manager described the important zone between the formalized product and competence projects: There is a zone in between we call skunk works. Work that is not scheduled and not sanctioned all the way, but still takes place with our consent. Especially if you have that profile [of being extra innovative], you have more room for skunk work. Actually, it is to sanction the testing of ideas and trying to bring more input into the big treadmill. . . . Most innovations probably come from competence and skunk work and I think that is where we have time and space © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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for creativity. In product development there is more control and time restrictions. (VP R&D, Beta) At Beta, a formal way to explore new and unique knowledge and processes, especially in one of its departments, was to engage R&D employees in product development and so-called competence projects simultaneously. In some cases, competence projects were treated as pre-studies to commercial product projects, but in other cases, the competence projects were run as autonomous activities for knowledge-generation. The model contributes strongly to the generation of innovative space, to opportunities for experimentation and explorative activities, and thus to the company’s long term competitiveness. It also facilitates transfer of knowledge and problems between projects, departments and individuals. Product development problems inform competence projects, and solutions developed in a competence project could find the relevant problem in the next round of product projects. There is also, according to several managers, a spillover of drive and sense of urgency from product development projects to the otherwise less intensive competence activities. At Alpha, one of the most renowned innovation managers emphasized the importance of also being engaged in product development projects, ‘where you have the money, the focus and the concentration on reaching a target’. The increasing importance and visibility of patenting in both companies could be used to increase innovative space, since patenting in many cases may mean a detour from the most direct product development road. Other initiatives and characteristics seemed to serve the same purpose, for example, the promotion of inventors (patentholders) to executive positions, especially at Beta, and strategies of rotating recently employed researchers among various sections to expose them to a variety of problems and help them build broader networks. At both companies there were also considerable effort to create an ‘open innovation culture’ by collaborating with outsiders in R&D activities and forging open-ended partnerships with universities.
Discussion This paper has explored three issues related to the importance of individual inventors in large, technology-based organizations. The first question, ‘Do they still matter?’, can be answered affirmatively. Both companies
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invested heavily in making their R&D more efficient and predictable, but there was also a considerable room for ‘heroes’, far from Steiner’s (1995) ‘generic engineer’. The second question, how managers can leverage these inventors was illustrated by examples as ongoing management dialogues and the organizing of innovative hot-houses. This question was also elaborated into a question of how individual inventors can act and ‘work the system’ or, in more formal terms, leverage organizational capabilities in their environment. The third question, how to maintain and nourish the fragile inventive space in increasingly lean R&D organizations, proved more difficult to answer. At both companies in our study, top managers demonstrated a strong commitment to the leaning process, but also a keen awareness of the dilemma and the need to maintain space for innovative behaviour. This balancing act seems to require a repertoire of cultural and organizational means. One of the companies had devised an ingenious dual structure of focused product projects and explorative competence projects. The change of the two companies’ patent offices into proactive and supportive units working closer to the R&D operations is another component in balancing the seemingly opposing needs. By adding patenting as a third process, the inventors’ situation can be described as three mutually supporting but differently paced processes. The three processes can be viewed as streams of activities, or actions, which in different ways interact with and influence each other (see Figure 3). While the product development process is described comprehensively in the literature, long-term competence and knowledge development are often regarded as a problem in project-based R&D organizations (Acha, Gann & Salter, 2005). The role of patent departments and patenting in relation to inventors and their managers in the innovation process is discussed by Ransley and Gaffney (1997) and
Product development
Patenting Competence and technology development
Figure 3. Three Mutually Supporting but Differently Paced Processes
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Ernst (2003), but do not seem to have attracted much attention in the literature on innovation and product development. The product process is paramount as it generates products and revenue, but all three are important for the development of product, knowledge and competence in the organization. The view from Beta is that having its inventors involved in all three processes is a way of working which satisfies both individual and organizational needs. Individuals are not restricted to one process with only formally organized points of intersection with the other processes. Instead they are more or less involved in product development projects and competence development projects all the time, while patenting activities are not equally frequent and/or time consuming even if patenting is a never-ceasing issue. Thriving in a situation like this, as the interviewed key inventors seem to do, imply that they are able to handle several processes in parallel, to be part of several groups or teams, and fulfil different roles in different projects, i.e., not only generate ideas but to act upon them as well. To handle and balance these three generic processes may thus be the key to success from both a company/managerial and an inventor point of view in the face of the ‘lean R&D factory’. A strong commitment to R&D effectiveness does not have to mean an orientation towards just minor improvement, provided that the ‘lean R&D production line’ is balanced with a web of formal and informal mechanisms creating a web of innovative resilience.
References Abernathy, W.J. and Utterback, J.M. (1978) Patterns of Industrial Innovation. Technology Review, June– July, 40–47. Acha, V., Gann, D. and Salter, A. (2005) Episodic Innovation: R&D Strategies for Project-Based Environments. Industry and Innovation, 12, 255– 81. Amabile, T.M. (1988) From Individual Creativity to Organizational Innovation. In Grönhaug, K. and Kaufmann, G. (eds.), Innovation: A Cross Disciplinary Perspective. Universitetsforlaget, Oslo. Amabile T., Conti, R., Coon, H., Lazenby, J. and Herron, M. (1996) Assessing the Work Environment for Creativity. Academy of Management Journal, 39, 1154–84. Angle, H.L. (1989) Psychology and Organizational Innovation. In Van de Ven, A.H., Angle, H.L. and Poole, M.S. (eds.), Research on the Management of Innovation, Harper & Row, New York, pp. 135–70. Archer, M. (1995) Realist Social Theory: The Morphogenetic Approach. Cambridge University Press, Cambridge. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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Baines, T., Lightfoot, H., Williams, G.M. and Greenough, R. (2006) State-of-the-Art in Lean Design Engineering: A Literature Review on White Collar Lean. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 220, 1538–47. Barney, J.B. and Wright, P.M. (1998) On Becoming a Strategic Partner: The Role of Human Resources in Becoming a Strategic Partner. Human Resource Management, 37, 31–46. Benner, M.J. and Tushman, M. (2002) Process Management and Technological Innovation: A Longitudinal Study of the Photography and Paint Industries. Administrative Science Quarterly, 47, 676–706. Borredon, L. and Ingham, M. (2005) Mentoring and Organizational Learning in Research and Development. R&D Management, 35, 493–500. Brown, S.L. and Eisenhardt, K.M. (1995) Product Development: Past Research, Present Findings, and Future Directions. Academy of Management Review, 20, 343–78. Clark, K.B. and Fujimoto, T. (1991) Product Development Performance – Strategy, Organization and Management in the World Auto Industry. Harvard Business School Press, Boston, MA. Cooper, P. (2005) A Study of Innovators’ Experience of New Product Innovation in New Organizations. R&D Management, 35, 525–33. EPO (2005) Guidelines for Examination in the European Patent Office. European Patent Office, Munich. Ernst, H. (2003) Patent Information for Strategic Technology Management. World Patent Information, 25, 233–42. Ernst, H., Leptien, C. and Vitt, J. (2000) Inventors Are Not Alike: The Distribution of Patenting Output among Industrial R&D Personnel. IEEE Transactions on Engineering Management, 47, 184– 99. Ford, C.M. (1995) Striking Inspirational Sparks and Fanning Creative Flames. In Ford, C.M. and Gioia, D.A.(eds.), Creative Action in Organizations. Sage, Thousand Oaks, CA, pp. 330–54. Garcia, R. and Calantone, R. (2002) A Critical Look at Technological Innovation Typology and Innovativeness Terminology: A Literature Review. Journal of Product Innovation Development, 19, 110– 32. Hagedoorn, J. and Cloodt, M. (2003) Measuring Innovative Performance: Is There an Advantage in Using Multiple Indicators? Research Policy, 32, 1365–79. Haque, B. and James-Moore, M. (2004) Applying Lean Thinking to New Product Introduction. Journal of Engineering Design, 15, 1–31. Hobday, M., Davies, A. and Prencipe, A. (2005) Systems Integration: A Core Capability of the Modern Corporation. Industrial and Corporate Change, 14, 1109–43. Huber, J.C. (1998) Invention and Inventivity Is a Random, Poisson Process: A Potential Guide to Analysis of General Creativity. Creativity Research Journal, 11, 231–41. Karlsson, C. and Åhlström, P. (1996) The Difficult Path to Lean Product Development. Journal of Product Innovation Management, 13, 283–95. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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Katz, R. (2005) Motivation Technical Professionals Today. Research-Technology Management, 48, 19–27. Lawson, B. (2001) In Praise of Slack: Time Is of the Essence. Academy of Management Executive, 15, 125–35. Leenders, R.T.A.J., van Engelen, J.M.L. and Kratzer, J. (2007) Systematic Design Methods and the Creative Performance of New Product Teams: Do They Contradict or Complement Each Other? Journal of Product Innovation Management, 24, 166– 79. Liker, J.K. and Morgan, J.M. (2006) The Toyota Way in Services: The Case of Lean Product Development. Academy of Management Perspectives, 20, 5–20. Lopez-Cabrales, A., Valle, R. and Herrero, I. (2006) The Contribution of Core Employees to Organizational Capabilities and Efficiency. Human Resource Management, 45, 81–109. Markham, S.K. and Griffin, A. (1998) The Breakfast of Champions: Associations between Champions and Product Development Environments, Practices and Performance. Journal of Product Innovation Management, 15, 436–54. Mumford, M.D. and Licuanan, B. (2004) Leading for Innovation: Conclusions, Issues and Directions. The Leadership Quarterly, 15, 163–71. Narin, F. (1993) Technology Indicators and Corporate Strategy. Review of Business, 14, 19–23. Narin, F. and Breitzman, A. (1995) Inventive Productivity. Research Policy, 24, 507–19. Nochur, K.S. and Allen, T.J. (1992) Do Nominated Boundary Spanners Become Effective Technology Gatekeepers? IEEE Transactions on Engineering Management, 39, 265–69. Nohira, N. and Gulati, R. (1996) Is Slack Good or Bad for Innovation? Academy of Management Journal, 39, 1245–64. O’Connor, G.C. and McDermott, C.M. (2004) The Human Side of Radical Innovation. Journal of Engineering and Technology Management, 21, 11–30. Oppenheim, B.W. (2004) Lean Product Development Flow. Systems Engineering, 7, 352–76. Patel, P. and Pavitt, K. (1991) Large Firms in the Production of the World’s Technology: An Important Case of ‘Non-Globalisation’. Journal of International Business Studies, 22, 1–21. Ransley, D.L. and Gaffney, R.C. (1997) Upgrade Your Patenting Process. Research Technology Management, 40, 41–46. Reinertsen, D. and Shaeffer, L. (2005) Making R&D Lean. Research Technology Management, 4, 51–57. Roberts, E.B. and Fusfeld, A.R. (1981) Staffing the Innovative Technology-Based Organization. Sloan Management Review, 22, 19–34. Sapienza, A.M. (2005) From the Inside: Scientists’ Own Experience of Good (and Bad) Management. R&D Management, 35, 473–82. Schon, D.A. (1963) Champions for Radical New Inventions. Harvard Business Review, 41, 77–86. Sobek, D.K. II., Liker, J.K. and Ward, A.C. (1998) Another Look at How Toyota Integrates Product Development. Harvard Business Review, 76, 36– 49.
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Söderlund, J. and Bredin, K. (2006) HRM in ProjectIntensive Firms: Changes and Challenges. Human Resource Management, 45, 249–65. Steiner, C.J. (1995). A Philosophy for Innovation: The Role of Unconventional Individuals in Innovation Success. Journal of Product Innovation Management, 12, 431–40. Talke, K., Salomo, S. and Mensel, N. (2006) A Competence-Based Model of Initiatives for Innovation. Creativity and Innovation Management, 15, 373–84. Van de Ven, A.H. (1986) Central Problems in the Management of Innovation. Management Science, 32, 590–607. Verona, G. (1999) A Resource-Based View of Product Development. Academy of Management Review, 24, 132–42. Veryzer, R.W. (1998) Discontinuous Innovation and New Product Development Process. Journal of Product Innovation Management, 15, 304–21. Vojak, B.A., Griffin, A. Price, R.L. and Perlov, K. (2006) Characteristics of Technical Visionaries as Perceived by American and British Industrial Physicists. R&D Management, 36, 17–26.
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Hans Andersson (
[email protected]) is assistant professor at Linköping University, Sweden where he also received his PhD in Business Administration. He is a member of the KITE (Knowledge Integration and Innovation in Transnational Enterprise) research team and his research interests concern product development, innovation and creativity. Christian Berggren (christian.berggren@ liu.se) is Professor in Industrial Management at Linköping University, Sweden. He received his PhD at the Royal Institute of Technology, Stockholm. His current research comprises studies of innovation and technology strategies, project management, manufacturing outsourcing and integrated solutions. Professor Berggren is leading the KITE (Knowledge Integration and Innovation in Transnational Enterprise) research programme.
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Leadership in R&D Projects Diana Grosse This article describes the results of an empirical study regarding a suitable style of R&D project leadership, especially what tasks project leaders should perform by themselves and what tasks they should delegate, what personal characteristics they should be endowed with and what kind of relationships they should have with their team. Fifty interviews were held in German institutions short-listed for an award for their innovative products by the Saxon government. In contrast to the assumption of the Social Identity Theory, in these institutions good R&D project leaders are not the ‘prototype’ of their team, but successfully balance the interests of the company and the R&D project team.
Introduction
A
s Japanese automotive companies captured the European market in the 1970s, German managers began to search for the reasons that enabled the Japanese to drastically reduce the developmental period of a new vehicle, sometimes reducing the time by one and a half years. One of the reasons, according to a widely accredited study by Clark and Fujimoto (1991, p. 78), was that the Japanese create teams which are focused completely on the project task. In this way, the problem of employees’ prioritization of their respective departmental goals that arises in the German functional departmental organizations, was avoided in these Japanese firms. In addition, interface problems were hampering innovation in German institutions, such as the production department’s goal of cost reduction, which could hardly be reconciled with the goal of implementing new production methods, whereby one must test new methods even when these new methods induce higher costs. In order to overcome these interface problems, most organizations worldwide and also in Germany nowadays employ project management for R&D and product and process development tasks. Clark and Fujimoto (1991), and others before and after them, also highlighted their finding that the success or otherwise of the project depends critically on the project leader. They outline that what successful project leaders are composed of, if anything, is that they generally must be a heavyweight, i.e.,
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they can assert themselves within the organization (Clark & Fujimoto, 1991). In this article we first of all further define the attributes of (R&D) project leaders, leading to a number of propositions which were explored in the context of R&D projects in innovative German institutions.
Theoretical Background The responsibilities of a leader include decision making, instruction and control, motivation, and the initiation of new assignments (Kosiol, 1976, p. 100 et seq.). These actions must be accomplished by a project leader, albeit within the scope of a project. Therefore, s/he must fulfill a task which is characterized by the following attributes: • time limit, • complexity, and • relative novelty (Corsten, 2000, p. 2). When dealing with the development of a new product, the attribute of interdisciplinarity must be added because employees from several different departments must work together. This requires a modification of the leadership functions. Instead of giving instructions, a project leader must integrate and work with the different team members. Motivation consists primarily of the willpower to overcome the barriers to innovation posed by the employees (Witte, 1988). An important function is the co-ordination of the project assignments in conjunction with the main products of the company.
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Leadership Theories In the literature, three opinions differentiate the key characteristics of a successful leader: personality, leadership skills and relation to employees. Essentially, all three characteristics are of significance; however, during their scientific research, the scientists’ focus has changed several times. According to the Personalistic Approach, a leader distinguishes himself through very particular characteristics which differentiate him from the people he is leading. This approach has a long philosophical tradition: Plato already advocated the view that only a ruler with a wise personality could be the head of a state. Max Weber’s concept of a leader, who is equipped with the characteristic of charisma, plays a significant role. Due to his visionary dedication in conjunction with his visual judgement and the sense of responsibility, this leader surmounts the strong restraints of bureaucracy. According to past research traditions, these statements do not have any empirical foundation. In the following decades, numerous studies attempted to eliminate this disadvantage. In particular, after analysing 200 of these studies, Stogdill had ascertained that for a project to be successful a project leader should exhibit the following attributes (Wunderer & Grunwald, 1980): • • • • •
aptitude and intelligence, performance and dedication, responsibility, sympathy, and status, socio-economical position
Furthermore, studies also revealed that some of the employees also possessed the same characteristics. Hence, the notion was disproved that leaders can be identified based on their characteristics and that their characteristics differ from those of the employees. Furthermore, many different characteristics turned out to be lead to success depending on which concept of success was taken into account (Gebert, 2002). If the main purpose of the project is to generate a large profit, it is then necessary for the project leader to possess analytical-calculative skills. On the other hand, if the project is geared towards satisfying the employees, then the project leader must exhibit characteristics such as sympathy and to be able to make compromises. The measurement of success which is applied to the project arises from the situational context in which the project is embedded; this is the goal that the company has established. Due to the fact that the situational context varies with each project, each individual project requires a specific type of
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project leader who manages the project in his own specific way. These conclusions have been the basis for numerous elaborations in the field of leadership research (Nippa, 2006). The goal of these investigations was to identify a leadership style for every relevant situation that results in the successful outcome of each project. It was quickly realized that this plan was impractical. Therefore, further investigation was limited to two types of leadership styles: the task-oriented and the people-oriented leadership styles. Thereafter, researchers in the field of leadership styles tried to establish leadership styles that are suitable for certain situations. Moreover, the study by Fiedler (1967) is worth mentioning. He discovered that in situations with a very clear or with a vague task structure, a task-oriented leadership style provides the necessary goal orientation. Yet, the project leader can try to balance out the interests of all of the employees involved in the project in ambivalent situations, thus implementing a person-oriented leadership style (Fiedler, 1967). However, Fiedler also discovered that the choice of the appropriate leadership style depends not only on the structure of the tasks but also on the personalities of the employees. It is important not only what the project leader assigns but also how the employees interpret and implement these instructions (Rickards & Moger, 2006, p. 11). To list which attributes employees must possess is just as absurd as situation-oriented leadership styles, as the list would be endless. However, the approach of conceiving the behaviour as a result of the self-concept offers a possibility to produce a general characterization of employee attributes. According to the Self Categorizing Theory, people prefer actions which coincide with their self-concept as the sum of the cognitive representations that an individual has from within. The self-concept comprises three levels: • the self-assessment of one’s own personality, • the group to which one would like to belong, and • the awareness that one is a human being (Utz, 1999). In this context, the level of the reference group is relevant. If subordinates perceive the project team as a reference group, they will then contribute to the team and especially support the project team and their actions (Tajfel & Turner, 1979). To achieve the acceptance of each team member, the whole group situation, especially the leadership style of the project leader and the work atmosphere within the team, must allow each member to behave in accordance with his self-perception. © 2007 The Author Journal compilation © 2007 Blackwell Publishing
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Situation
Cognition Leader
Behaviour Leader
Cognition Team
Behaviour Team
Behaviour colleagues
Cognition colleagues
Success
Figure 1. Leadership as an Interaction Between Leader and Employees
A part of self-perception is or should be dedication; what you see as the purpose of your own life. Of course, a project leader cannot answer the question of the meaning of life. However, the Charismatic Leadership Theory requires the project leader to define the meaning of the project and to communicate its meaning to his employees. If successful in communicating the meaning, then the project leader is able to unleash unexpected innovative energy which results in more creative and happier employees (Gardner & Avolio, 1998; Berson & Linton, 2005). But a charismatic leadership style is always in danger of allowing the employees to develop too close a connection with the project leader, and, in particular, they might not be able to accept criticism. The project leader must guard against these tendencies of integration. The above depicted network that exists between the project leader and his/her employees is portrayed in Figure 1.
Proposition Development Since the projects are to be executed within the company, they must fit into the organizational structure. Therefore, the job duties and the decisional competencies of the project leader and his employees must be predetermined. This occurs using the Transaction Cost Theory which states that the organizational structure must be shaped in such a way that the cost of the transactions – especially the information, co-ordination and the motivational costs – are minimal (Milgrom & Roberts, 1992, p. 29). The transactions which are analysed in this context are the transactions between the project leader and the team members. This approach is similar to the theory of transactional leadership (Burns, 1978). The difference between the two theoretical concepts is that the Transaction Cost Theory is more general. For instance, it is only assumed that employees maximize their utility whereas the transactional leadership theory allows for a closer look at the specific goals of the project leader © 2007 The Author Journal compilation © 2007 Blackwell Publishing
and the team members. As the disadvantage of being non-specific is balanced by the advantage of making recommendations about the organizational structure of a project, it was decided to state the propositions here in terms of Transaction Cost Theory. The Transaction Cost Theory implies situational factors such as uncertainty and opportunistic behaviour. This article makes allowance for these facts because it is dealing with R&D projects (uncertainty) and because it analyses incentives that are supposed to motivate the employees (the opportunistic effect is reduced because team members have signed an employment contract; see Baron & Kreps, 1999, p. 538). Moreover, it is assumed that organizational structures are influenced by the behaviour of the employees because they try to accomplish the role allocations that are implied by the structure elements. Consequently, seven propositions have been formulated about the behaviour of a successful project leader. These propositions describe the main elements of an organizational structure: job duties, decision-making authority, hierarchical rank and communicative relations. (Rickards and Moger identify this as an important aspect of leadership, Rickards & Moger, 2006, p. 5.) According to Adam Smith, productivity can be increased if a task is split into sub-tasks and, thereafter, given to several employees who will be able to realize the effects of learning. These sub-tasks can be divided into managing and executing sub-tasks within a project. The managing of sub-tasks should be taken over by the project leader. The newer the project, the more difficult the prediction of success. Therefore, the results can only be rated and controlled by a leader who can evaluate the working processes because they are involved in the R&D process. This leads to the first proposition: Proposition 1a: Successful R&D project leaders carry out decision-making, instructing, controlling, and initiating tasks and, additionally, actively participate in the project.
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Similarly, the employees need to overcome the principle of specialization. Due to the novelty of the project, unexpected outcomes will occur. Hence, close communication and co-operation among all employees is essential. This leads to: Proposition 1b: Successful R&D project organizations combine project members into one team which is characterized by overlapping fields of responsibilities and a common interest identity (Högl & Gemünden, 1999; Amason, 1996). After the job duties are defined, the next proposition deals with the degree of decisionmaking authority. Proposition 2: In the case of a dynamic environment and highly motivated employees, successful R&D project leaders delegate tasks to the employees who are most competent. Highly qualified employees will produce lower costs for information acquisition. The cost reduction will be significant enough to compensate for the costs of delegating the decision-making authority to the employees. In a dynamic environment, the data that need to be acquired are constantly changing. Laux has mathematically proven this correlation (Laux & Liermann, 1990; McGrath, 2001). The delegation of decision-making authority proves to be beneficial for R&D projects. The dynamic of R&D projects allows the organizational rules to become obsolete. Thus, the company needs employees who are capable of acting independently and without fixed rules. According to Allport, these capabilities, or attributes, provide people with the ability to process stimuli from the environment in such a way to derive consistent actions from them (Heckhausen, 1989, p. 39). Proposition 3 describes the attributes which the selfdetermined employees, especially a project leader, should have, in order to manage the project tasks efficiently. Proposition 3: Successful R&D project leaders possess the following features: • knowledge • creativity • experience • self-confidence, a positive self-concept • risk tolerance, ability to manage conflicts • commitment, intrinsic motivation for performance • ability to assert oneself • sympathy • sense of responsibility. These attributes result from transferring Stogdill’s leadership characteristics into the
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situation of a complex project and also from evaluation of other empirical studies (Judge et al., 1999; Sternberg et al., 2004). Their theoretical foundation is the following: information and control costs can be reduced if project leaders have expert knowledge. They are better able to motivate their employees if they themselves are dedicated and capable of tolerating uncertainty. In particular, co-ordination costs can be saved in a matrix organization if the project leader can be assertive amongst the other department leaders. Proposition 4: Successful R&D project leaders use the leadership style of ‘management by objectives’. The goals are determined in co-operation with the employees at the beginning of the project. Since they can use their specific knowledge to their benefit, project leaders can save on informational costs. The employee can choose his way to individual success. This will increase the motivation of scientists who like to work independently. A delegation of decision competencies is connected to some risks. The project leader has the risk that the employee will follow their own personal goals rather than the goals of the company while working, but also the employee has the risk of failure. Additionally, the employee does not know about their boss’s loyalty in the event of a disappointment. According to the Principal Agent Theory, the first risk can be reduced if the employee takes a share in the project’s success. Thus, their own interests are connected to the goals of the organization. The second risk will be lower if the team members have already gained experience in previous situations in which the project leader has supported them. Proposition 5: Motivational costs can be saved when the employee is given incentives; thus, allowing them to be able to satisfy Maslow’s postulated needs of provision of goods, safety, sense of community, appreciation, and self-actualization with their project task. The next proposition deals with the longing for support, which can be derived from several Maslovian needs. Support of the superior is shown by understanding when the results, over the course of the project, turn out to be different from those originally planned. Instead of punishing the employees, the superior changes the plans and implements new guidelines (Hauschildt, 1997, chapter 11). In this regard, a continuous process control is necessary not only for motivational reasons but also because of cost efficiency. The production of a product that the market does not © 2007 The Author Journal compilation © 2007 Blackwell Publishing
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accept, which would create large losses, can be impeded by a constant acclimatization of the project plan to reality. Proposition 6: Co-ordination costs as well as motivational costs can be saved when a continuous process control rather than a rigid result control is conducted, by which final results are demanded. These are sometimes difficult to achieve, especially in innovative projects. Team members, who may explain deviations from planned data as in a continuous process control, feel more self-assured. Hoog and Haslam expand the idea that the project team becomes an identification group for its members when it corresponds to their own self-concept to a Social Identification Theory of Leadership. Initially, they establish the specifics of the composition of a group. A professional tennis club can become the identification group for an ambitious tennis player because many other ambitious players are also mmbers, and, therefore, dedication for sports is a typical member characteristic. Furthermore, they state that if the project leader fits this prototype, then the team members will willingly follow him because they can identify with him (Haslam, 2001; Hoog, 2001). Proposition 7: The employees will identify with the project leader when s/he prototypically expresses the behaviour of her/his team, especially their self-concept. This alleviates her/him from the execution of his/ her leadership functions and, additionally, reduces the leadership costs.
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Table 1. Project Success Criteria of Success Exceeding the planned time Exceeding the planned costs Economic expectations fulfilled Technical expectations fulfilled
Average
1 yes
4,5
6 no
1 yes
5
6 no
1 yes
4
6 no
1 yes
4
6 no
p. 16). We analysed the data of the supervisors because they seemed to be more objective, supervisors having a better overview of the projects. The supervisors were asked to rate the leadership skills of an R&D project leader for a specific project because the ability to remembering is better if you have to remember a particular incident. If their ratings correspond with our propositions and if the project was assessed as being successful, then this can be considered as an indication of the validity of the propositions. If the necessary data were available, regression analyses have also been conducted.
Results Methodology
Project Success
To test these propositions, 50 semi-structured interviews were conducted at institutions throughout Germany between the period of September 2002 and March 2003. These are institutions that have been short-listed for an award for their innovative products by the Saxon government. This ensured that R&D projects were being actively conducted there. As the projects were rather small, the team size was small too: 5–15 members. The supervisors of the project leaders, i.e. a member from the steering committee, and the team members were interviewed. But the project leaders were not questioned in order to avoid possible self-delusion. The validity of the results was checked by comparing the answers of the two groups. There were only slight deviations between the two groups and, therefore, it is sufficient with regard to validity to interpret the results from only one group (Schuler, 1995,
The projects that the interviews are based on can, on average, be classified as successful in the sense that they essentially implemented the guidelines of the plan (see Table 1).
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Job Duties and Delegation of Tasks (Propositions 1, 2) All projects were executed in teams, which were presided over by the project leader. This project leader would also assign developmental tasks. Therefore, Propositions 1a and 1b can be considered valid. In order to determine the distribution of the decision-making authorities, we asked who had to make the final decision, the project leader or a team member. Of course, close communication has to precede each decision (for the list of the tasks, see de Pay (1995), p. 61). The answers are shown in Table 2.
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Table 2. Delegation of the Project Decision-Making Authority PL 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20.
TM
Feasibility study for the project Conclusion of a contract for external projects Practical implementation and definitions of the project Co-ordinated determination of the connection of the project on the line organization Planning of the project goals Planning of the time Planning of the costs Recruitment of the employees Acknowledgement of the incentives for the employees Searching for ideas Evaluation of the ideas Creation of the concept Decision: stop or go Creation of the prototype Acceptance of the prototype Handing over to production Project control Take responsibility for the project in the communication with external authorities Final invoice Documentation
PL = project leader, TM = team member.
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Most of the decisions are made solely by the project leader. In contrast, the employees may decide which ideas they choose to follow, how they proceed with the creation of the prototype, and, ultimately, how they match their concept with the requirements of the series production during the developmental work, and which results they document. Proposition 2 can be considered valid because employees were dealing with tasks for which they had better knowledge.
Table 3. Effect of Characteristics (Dependent Variable: Efficiency)
Leadership Skills (Proposition 3)
Note: level of significance: ** 0.05, * 0.10.
The assumption about leadership skills has been verified on two levels: does a project leader have to have special characteristics, and if so, what kind of characteristics? Most of the interviewees agreed that there are leadership qualities and that they are important. Whether these statements are valid was proven by regression analysis. The results show that there is a positive linear correlation between the variables ‘efficiency’ (planned data are fulfilled, see Table 1) and ‘leadership characteristics’. Obviously, projects led by project leaders
with the appropriate attributes could maintain their planned data. This correlation is significant (see Table 3). In Table 4 these qualities are listed according to their rank of importance. It is apparently more important for a project leader to understand the project in detail than to possess all of the leadership qualities. The reason is the
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Independent variable
Specification
Constant Characteristics R2 = 4.9 F-value = 3.52 No. of investigations: 48
4.2** 0.2*
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Table 4. Leadership Qualities
Table 5. Management by Objectives (Dependent Variable: Efficiency)
(MbO)
Rank Independent variable Knowledge Creativity Commitment; intrinsic motivation Risk-tolerance, ability to manage conflicts Sense of responsibility Sympathy Self-confidence, positive self-concept Ability to assert oneself in communication with supervisor Experience
1 2 3 4 5 6 7 8 9
novelty of the project. Given the fact that one cannot fall back on experience as with a routine project, the supervision should be conducted by an expert. A survey of 215 companies with project management, conducted by Keim (1997), confirmed that it is very important for a project leader to show technical and managerial capabilities (Keim, 1997, p. 263). The fact that the characteristic of sympathy was assigned a lower rank is related to the fact that the interviewees assumed the granting of incentives to be more important than showing sympathy. These incentives were closely connected to the success of the project (see Table 6), ensuring that the team members worked hard to reach the project goals. As most companies preferred the leadership style of management by objectives, negotiations about and controlling of these project goals were important management devices.
Specification
Constant MbO R2 = 3.74 F-value = 3.10 No. of investigations: 54
3.5** 0.2*
Note: level of significance: ** 0.05, * 0.10.
Measures of Incentives (Proposition 5) The statement that the employees are further motivated when they can implement personal goals within the project was tested through two questions. 1. Are agreements made with the employees about the goals that they can personally realize by working on the project? In 90 percent of the cases there are such ‘goal agreements’. 2. Are the listed measures of incentives in Table 6 given, and which meaning will be attributed to them? Thus, these incentives are set by the companies which satisfy every level of Maslow’s hierarchy of needs – except for a flexible work schedule. This results from the fact that the projects are conducted by firms. Their projects have to fit in the product portfolio of the company. Therefore, the R&D employees do not have much flexibility either in regard to their R&D topics or their working hours.
Process Control (Proposition 6) Management by Objectives (Proposition 4) All R&D project leaders execute the leadership style of ‘management by objectives’. They attach a great meaning to the definition of goals in accordance with the employees – both project goals as well as personal goals. Thereafter, these goals are independently pursued by each team member. These statements could be proven by a regression analysis. As shown in Table 5, there is a significant linear correlation between the independent variable ‘leadership style: management by objectives (MbO)’ and the dependent variable ‘efficiency’ (MbO is measured on a scale from 1 = no to 6 = yes). Thus Proposition 4 is confirmed. © 2007 The Author Journal compilation © 2007 Blackwell Publishing
An open-ended question was posed to find out how the control is conducted. The interpretation of heterogeneous answers shows that a process control is normally performed which is conducted as follows. At certain points in time – for the most part at the beginning of the week – the sub-tasks are determined and distributed to the employees. In periodical, short phases the project leader checks on their accomplishment. In this way, the project leader always maintains a close eye on the achievement of further specified milestone results. The project leader uses their specialized knowledge for a contextual examination. Would they have done it the same way? Interesting but not urgent questions are saved in a dataset to be analysed as soon as time permits.
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Table 6. Measurement of Incentives for the Employees Category Personal development
Tangible incentives
Social status
Flexibility
Measures
Relevance (average)
– Presentation on the project – Advanced training
1 2 3 4 5 6 irrelevant relevant
– Interest – Bonus for a successful project – Salary increase
1 2 3 4 5 6 irrelevant relevant
– Promotion – Recognition – Permanent contract
1 2 3 4 5 6 irrelevant relevant
– Flexible work schedule – Time for personal research
1 2 3 4 5 6 irrelevant relevant
Table 7. Group Identification (GI) (Dependent Variable: Efficiency) Independent variable Constant GI p-value No. of investigations: 49
Specification 0 -0.001 0.99
If necessary, the planning data are adjusted to the altered requirements.
they must be assertive amongst the management and the customers, they also have to consider their goals. It is therefore required that they are able to maintain a balance of the interests among all three groups. Neither for their own interest, nor for the company’s interest, can they solely follow their employees’ wishes (Mumford et al., 2002, p. 738: he writes that a leader must play multiple roles). 2. If project leaders and the group are too close, the phenomenon ‘group think’ might occur. The group might no longer be open to proposals nor criticism. The quality of the project will go down which is damaging to the interests of the company (Schulz-Hardt, 1997).
Prototypical Leader (Proposition 7) The assumption of a prototypical project leader was tested by the question: ‘How strong should each team member identify with his project leader?’ (Group identification). Later, the correlation between these answers and the dependent variable ‘efficiency’ was investigated through a regression analysis. As can be seen in Table 7, there is no significant correlation between these two variables. These calculations are not sufficient to disprove the thesis of the ‘prototypical project leader’. However, two arguments tend to imply the opposite: 1. Project leaders are not only interested in realizing the wishes of their employees. As
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How can this danger of too close an integration, which is high according to the statements of the interviewees, be removed? Some possibilities are suggested in Figure 2. On the one hand, Ollila’s advice should be adopted. A project leader should take some time to reflect on their leadership style and the group processes (Ollila, 2000). On the other hand, they should implement actions such as gatekeepers, control measures and substituting team members. The last measure is not considered to be beneficial by the interviewees, probably because of a loss of specialized knowledge. In summary, one can characterize the relationship between the project leader and their © 2007 The Author Journal compilation © 2007 Blackwell Publishing
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Unfortunately, no statements can be made regarding the charismatic leadership style because the interviewees did not consider this leadership style to be appropriate for their projects which only had a low level of novelty. Therefore, future research needs to be conducted on this leadership style, especially on the relationships between charismatic and transactional leadership styles. The leader– employees relationship should also be further analysed.
Relevance 4,5 4 3,5 3 2,5 2 1,5 1 0,5 0 a
b
c
d
Indication
Key: a = Risk of groupthink b = Control through external instances c = Substitution of team members d = Gatekeeper Figure 2. Instruments Against Groupthink employees as follows: project leaders must be accepted as the leader by their employees. According to Heider’s Attribution Theory, the prerequisites for acceptance are that project leaders shows capability and commitment (Heckhausen, 1989, pp. 397f). Conversely, it is not necessary that they prototypically reflect the self-concept of the employees.
Conclusion Based on the empirical surveys, six out of seven propositions seem to hold in the German institutions where our empirical data were gathered. Confirming the recent literature, a successful R&D project leader has the following profile: s/he should possess leadership qualities; in addition to the leadership functions, s/he should contribute to the project; s/he should lead by means of ‘management by objectives’; leave the decisions of the projects in which the employees have more of an understanding to the employees; continuously control the completion of the tasks; provide incentives for the project; and s/he should obtain acceptance as the project leader from the employees through commitment and specialized knowledge. Based on these findings management can be recommended to: • carefully recruit R&D project leaders making sure that they possess the necessary attributes, and • give each project leader the freedom to determine the project structure. © 2007 The Author Journal compilation © 2007 Blackwell Publishing
References Amason, A.C. (1996) Distinguishing the Effects of Functional and Dysfunctional Conflict on Strategic Decision Making. Academy of Management Journal, 39, 123–48. Baron, J. and Kreps, D. (1999) Strategic Human Resources. John Wiley, New York. Berson, Y. and Linton, J. (2005) An Examination of the Relationship Style, Quality and Employee Satisfaction in R&D Versus Administrative Environments. R&D Management, 35, 51–60. Burns, J.M. (1978) Leadership. Harper & Row, New York. Clark, K. and Fujimoto, T. (1991) Product Development Performance. Harvard Business School Pr., Boston, MA. Corsten, H. (2000) Projektmanagement. Oldenbourg, Munich. Fiedler, F. (1967) A Theory of Leadership Effectiveness. McGraw-Hill, New York. Gardner, W. and Avolio, B. (1998) The Charismatic Relationship: A Dramaturgical Perspective. Academy of Management Review, 23, 32–58. Gebert, D. (2002) Führung and Innovation. Kohlhammer, Stuttgart. Haslam, S.A. (2001) Psychology in Organizations. Sage Publications, London. Hauschildt, J. (1997) Innovationsmanagement. Vahlen, Munich. Heckhausen, H. (1989) Motivation and Handeln. Springer, Berlin. Högl, M. and Gemünden, H.G. (1999) Determinanten and Wirkungen der Teamarbeit. Zeitschrift für Betriebswirtschaft – Ergänzungsheft, 2, 35–59. Hoog, M.A. (2001) A Social Identity Theory of Leadership. Personality and Social Psychology Review, 5, 184–200. Judge, T.A., Thoresen, C.J., Pucik, V. and Welbourne, T. M. (1999) Managerial Coping with Organizational Change: A Dispositional Perspective. Journal of Applied Psychology, 84, 35–59. Keim, G. (1997) Projektleiter in der industriellen Forschung und Entwicklung. Gabler, Wiesbaden. Kosiol, E. (1976) Organisation der Unternehmung. Gabler, Wiesbaden. Laux, H. and Liermann, Z. (1990) Grundlagen der Organisation. Springer, Berlin. McGrath, R. (2001) Exploratory Learning, Innovative Capacity and Managerial Oversight. Academy of Management Journal, 44, 118–31.
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Milgrom, R. and Roberts, J. (1992) Economics, Organisation and Management. Prentice-Hall, Englewood Cliffs, NJ. Mumford, M.D., Scott, C.M., Gaddis, B. and Strange, J.M. (2002) Leading Creative People: Orchestrating Expertise and Relationships. The Leadership Quarterly, 13, 705–50. Nippa, M. (2006) Lessons from the Search for the Perfect R&D Leader. On the Need to Turn Away from Adding to a Patchwork of Loosely Coupled Insights to Distinct Research Agendas. Paper presented at the 66th Annual Meeting of the Academy of Management, Atlanta, USA, August. Ollila, S. (2000) Creativity and Innovativeness through Reflective Project Leadership. Creativity and Innovation Management, 9, 195–200. de Pay, D. (1995) Informationsmanagement von Innovationen. Gabler, Wiesbaden. Rickards, T. and Moger, S. (2006) Creative Leaders: A Decade of Contributions from Creativity and Innovation Management Journal. Creativity and Innovation Management, 15, 4–18. Schuler, H., Funke, U., Moser, K. and Donat, K. (1995) Personalauswahl in Forschung und Entwicklung. Hogrefe, Göttingen. Schulz-Hardt, S. (1997) Realitätsflucht in Entscheidungsprozessen von Groupthink zu Entscheidungsautismus. Huber, Bern.
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Sternberg, R., Kaufman, J. and Pretz, J. (2004) A Propulsion Model of Creative Leadership. Creativity and Innovation Management, 13, 145–53. Utz, S. (1999) Soziale Identifikation mit virtuellen Gemeinschaften. Pabst, Berlin. Tajfel, H. and Turner, J.C. (1979) An Integrative Theory of Intergroup Conflict. In Austin, W.G. and Worchel, S. (eds.), The Social Psychology of Intergroup Relations. Brooks/Cole, Monterey, pp. 33–47. Witte, E. (1988) Innovationsfähige Organisation. In Witte, E., Hauschildt, J. and Grün, O. (eds.), Innovative Entscheidungsprozesse. J.C.B. Mohr, Tübingen, pp. 144–61. Wunderer, R. and Grunwald, W. (1980) Führungslehre, Vol. I. de Gruyter, Berlin.
Diana Grosse (
[email protected]) is a professor of Business Administration at the Technical University of Freiberg. Her research area is the organization of routine and innovation projects; her theoretical basis is institutional economics.
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Book Reviews Caenegem, W. van (2007) Intellectual Property Law and Innovation. Cambridge University Press, Melbourne, Australia. 222 + xviii pp, Paperback: ISBN-13: 978-0-52183-757-6, £40.00.
This is in several respects an attractive publication. In over 200 pages, a wealth of insights is offered to the reader about the legal instruments to support and protect industrial innovations. The text is supplemented by a list of acronyms, tables of statutes and cases, an extensive bibliography and an index. The focus on industrial innovation refers to the innovation in function (or ‘technological’ innovation) and in novel product appearance (or ‘product’ innovation). Areas like art, literature, dramatic and musical entertainment fall outside the scope of the book. Therefore, it might have been preferable to use the expression industrial property law in the title. The author, Professor of Law at Bond University, Australia, addresses the application of relevant legal instruments (IP law) to protect useful products and processes. According to the Preface, the book is aimed at a variety of readers with an interest in innovation policy, innovation management and core legal issues. The author has succeeded in reaching this goal: indeed the book is of interest to law school and business school students, teachers, professionals such as consultants, policy makers, business staff and production managers. The decision to focus on substantive issues instead of procedural matters, as is often seen in legal texts on IP, is also welcomed. The author does not pretend to present definitive answers or conclusions; the book is meant to be a vehicle for sharing ideas and insights developed in years of research. Indeed, the readers are able to benefit from the knowledge of a broadly-oriented scholar. Chapter 1, the introduction, is a well-written essay of 24 pages on all relevant aspects of law, society, imitation and innovation. Chapter 2 is on trade secrets, confidential information related to product and process innovation: ‘to what is sometimes known as “know-how”’. It is a good idea to explain the policy context and the legal ins and outs of relying on secrecy in the first place because breach of confidence actions could be an alternative to having the grant of a patent. It is very © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
useful that the book also gives attention to the question of how employees should handle confidential knowledge, during employment and ‘post-term’. Chapter 3 is devoted to patents. One attractive feature of the book is that the introduction of a chapter’s subject starts with the demonstration of the connection between the present and the previous chapter: essential differences exist between trade secrets law and patents law. Among other things the distinct tests of novelty and inventiveness are explained. It is very interesting that the Australian patents system offers a choice between a standard patent and an innovation patent, the latter being rather less inventive, less costly but faster to obtain. This chapter also addresses questions of employer–employee entitlement to a patent. Chapter 4 is entitled ‘Copyright and designs’. It explains important legal instruments supplemental to the area of patents law which has its limitations and impossibilities. For instance, a copyright is indispensable for the protection of the design of computer programs. Also the specific legal meaning of ‘design’ is explained and attention is given to a possible copyright-designs overlap. The final Chapter 5 deals with a small number of specific issues. The legal Latin expression ‘sui generis’ is used here, meaning body of rules or regimes with singular, quite special legal characteristics. One subject is the legal possibilities to protect computer hardware innovation and software program designs. A second subject, perhaps surprisingly, deals with plant varieties. Surprisingly, because plants are not easily or immediately associated with industry, though of utmost importance in the sector of agriculture and novel food products. The final pages of this chapter and the book are on the limited possibilities trade mark registration has to offer to a business enterprise seeking to protect the results of innovative efforts and investments. The Preface states rightly: ‘Innovation is a central theme of our times, and within it IP law plays a significant, if difficult to evaluate role’. Certainly, it is a disadvantage that the book is
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mostly limited to Australian law. From the position of a continental European business law professor, Australian law is of modest relevance. However, the disadvantage is not very inconvenient: IP law has become more and more international in nature as a result of advantageous developments within WIPO (World Intellectual Property Organization) and the WTO (World Trade Organization): ‘The “main game” in intellectual property policy formulation has shifted from Canberra to Geneva . . .’ (p. 18). To produce most adequate IP law protection for all kinds of
industrial innovations is a task for specialized lawyers. The decisions to rely on secrecy, to accept the risks of imitation and reverse engineering by competitors or to consult IP lawyers have to be made in the management boardroom. The value of this book is that lessons can be learned about how to prepare well-reasoned opinions on the protection of corporate assets resulting from industrial innovation. Antoni Brack University of Twente, The Netherlands
Utterback, J., Vedin, B.A., Alvarez, E., Ekman, S., Sanderson, S.W., Tether, B. and Verganti, R. (2006) Design Inspired Innovation, World Scientific Publishing Co., Hackensack, NJ. 259 pp, Paper: ISBN-13: 978-981-256-695-9, $28.00.
After reading this book I realized why the world of design and engineering is still the same stimulating, exciting and rewarding place now as it was in the days when I started out as a designer. Being a designer was and is having the drive to realize self-fulfilment by creating better products and services, but nowadays aided by insights and improvements that were not available then. The authors of this book have tried to capture the spirit of the design function as it stands today. This book is aimed at designers/ engineers, their managers, students and scholars in the design field. It is written as a journey through the world of design and engineering, emphasizing the diversity of industries, forms of organization, and cultural differences in different countries. The design journey takes off with a concise overview of successful products in the past and present and the reasons why these products became successful. The first sentence of chapter 1 provides a leitmotif that runs throughout the book: ‘a design-inspired product delights the customer’. In later chapters this is broadened to: ‘delight the user’, which is perhaps a better statement with the ‘user’ being defined as ‘everyone involved with the product (including the designer!)’. ‘Design’ is defined as the integration of technology, needs and language, while ‘DesignInspired Innovation’ is characterized by products having simplicity of function, elegance and excellence. These aspects are not defined directly, but characterized for several product examples in subsequent chapters. Indeed, most of the work of a designer/ engineer is in the communication area with other users of the product-to-be. The authors discuss strategies for successful implementa-
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tion of design-inspired innovation, including the physical, virtual and social environment of the designer/engineer. The book gives several examples from different countries of alternative approaches for new products: from a ‘system point of view’, and focusing on product simplicity and elegance. As a reader of this book, one should be open-minded towards alternative approaches from different contexts, in order not to miss certain key points. The authors perceive a growing trend towards design contracting as a follow-up to contract manufacturing. Emphasis is laid on the growing number of design firms, for example in the Boston area of the United States. Requirements for the start-up and development of these firms are discussed. This type of organization may be ideal for designers/engineers, since it deals with the basic question for every designer: ‘Do I want to work for a small manufacturing company with restricted technical possibilities but with a great potential for personal creative freedom, or do I work for a large firm with state-of-theart technology but embedded in a large, complex organization?’. The majority of designers today still face this choice, but with a movement towards design-inspired innovation with a growing contribution of design contract firms, as foreseen by the authors, things may change to a situation where a designer can have both: access to a broad range of technologies and the chance to optimally deploy his/her creativity in a small organization. The authors expect designers to be in close contact with the user/customer. What the role of the marketing function would then be is not made clear. The purchasing function too is not © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
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mostly limited to Australian law. From the position of a continental European business law professor, Australian law is of modest relevance. However, the disadvantage is not very inconvenient: IP law has become more and more international in nature as a result of advantageous developments within WIPO (World Intellectual Property Organization) and the WTO (World Trade Organization): ‘The “main game” in intellectual property policy formulation has shifted from Canberra to Geneva . . .’ (p. 18). To produce most adequate IP law protection for all kinds of
industrial innovations is a task for specialized lawyers. The decisions to rely on secrecy, to accept the risks of imitation and reverse engineering by competitors or to consult IP lawyers have to be made in the management boardroom. The value of this book is that lessons can be learned about how to prepare well-reasoned opinions on the protection of corporate assets resulting from industrial innovation. Antoni Brack University of Twente, The Netherlands
Utterback, J., Vedin, B.A., Alvarez, E., Ekman, S., Sanderson, S.W., Tether, B. and Verganti, R. (2006) Design Inspired Innovation, World Scientific Publishing Co., Hackensack, NJ. 259 pp, Paper: ISBN-13: 978-981-256-695-9, $28.00.
After reading this book I realized why the world of design and engineering is still the same stimulating, exciting and rewarding place now as it was in the days when I started out as a designer. Being a designer was and is having the drive to realize self-fulfilment by creating better products and services, but nowadays aided by insights and improvements that were not available then. The authors of this book have tried to capture the spirit of the design function as it stands today. This book is aimed at designers/ engineers, their managers, students and scholars in the design field. It is written as a journey through the world of design and engineering, emphasizing the diversity of industries, forms of organization, and cultural differences in different countries. The design journey takes off with a concise overview of successful products in the past and present and the reasons why these products became successful. The first sentence of chapter 1 provides a leitmotif that runs throughout the book: ‘a design-inspired product delights the customer’. In later chapters this is broadened to: ‘delight the user’, which is perhaps a better statement with the ‘user’ being defined as ‘everyone involved with the product (including the designer!)’. ‘Design’ is defined as the integration of technology, needs and language, while ‘DesignInspired Innovation’ is characterized by products having simplicity of function, elegance and excellence. These aspects are not defined directly, but characterized for several product examples in subsequent chapters. Indeed, most of the work of a designer/ engineer is in the communication area with other users of the product-to-be. The authors discuss strategies for successful implementa-
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tion of design-inspired innovation, including the physical, virtual and social environment of the designer/engineer. The book gives several examples from different countries of alternative approaches for new products: from a ‘system point of view’, and focusing on product simplicity and elegance. As a reader of this book, one should be open-minded towards alternative approaches from different contexts, in order not to miss certain key points. The authors perceive a growing trend towards design contracting as a follow-up to contract manufacturing. Emphasis is laid on the growing number of design firms, for example in the Boston area of the United States. Requirements for the start-up and development of these firms are discussed. This type of organization may be ideal for designers/engineers, since it deals with the basic question for every designer: ‘Do I want to work for a small manufacturing company with restricted technical possibilities but with a great potential for personal creative freedom, or do I work for a large firm with state-of-theart technology but embedded in a large, complex organization?’. The majority of designers today still face this choice, but with a movement towards design-inspired innovation with a growing contribution of design contract firms, as foreseen by the authors, things may change to a situation where a designer can have both: access to a broad range of technologies and the chance to optimally deploy his/her creativity in a small organization. The authors expect designers to be in close contact with the user/customer. What the role of the marketing function would then be is not made clear. The purchasing function too is not © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
BOOK REVIEWS
envisioned. Since these company functions require skills that differ greatly from the designer function, conflicts and problems may arise here. (See, for example, Urban & Hauser (1993) Design and Marketing of New Products, Prentice-Hall, Englewood Cliffs, NJ.) The authors conclude that only 5 percent of all new products can be categorized as ‘successful’ (meaning that the product stays on the market considerably longer than products in the same segment). The book lists several examples, ranging from Lego to the Douglas DC3 and Apple’s iPod. The authors make a strong point of design being more than styling of a functional proto-product. Design is viewed as realizing the vision of that product, as perceived by the user/customer and fulfilling customer needs. New technology is not always required for this process. The book continues with a discussion about the possible forms of organization and management around the emerging design functions and firms. Emphasis is laid on networking through related firms as well as through informal contacts with other designers. Managing these design processes poses a new challenge. With the growing complexity of designs, a system point of view is inevitable, as well as modularity and transparent interfaces. Open standards and open-source innovation is needed, as the authors prove with extensive research. The journey takes the reader to Sweden, where the clustering of design firms and their relations and networks are reviewed. An analysis is made of the type of work design firms perform, ranging from performing the finishing touch on a design to helping define corporate innovation strategies. The development of the Tetra-Pak is taken as an example of modern design/engineering. In the next chapter, the evolution of the ‘designdiscourse’ (the relational network of manufacturing and design firms) in Lombardy is discussed. Since the region around Milan is characterized by many companies that depend on a high rate of innovation, many examples of design-inspired innovation originate here. Products representing a ‘feeling’ or an ‘idea’, such as the Metamorfosi lamp by Artemide are good examples of these innovative designs. Giving ‘meaning’ to a design creates brand value. The authors state that products with ‘meaning’ may change cultures ‘to some degree in a direction closer to the system of values and beliefs of the entrepreneur’.
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The cognitive model of all the actors involved in achieving the correct interpretation of this ‘meaning’ is analysed, as well as the emergence of new visual, audio and body languages, needed for new types of communication. These trends are illustrated by the development in recent years of the modern wheelchair. New ideas about function, materials and ‘meaning’ of a wheelchair design are presented (and well documented in Appendix B). In the final part of chapter 7, a brief discussion about ‘meaning’, motivation and hierarchical needs of the product user is undertaken. The philosophical route is clear and backed up with references that are indeed basics in this field. The Q-word (Quality) as being the relation between object and subject, is briefly hinted at, but not fully developed to a QFD system. This makes enjoyable reading. The final chapter, ‘Design, Vision and Visualizing’, discusses the role of technology, as perceived by the user and its implementation by the designer. The vision behind the philosophy does not follow a straight line; it is more of an array of random thoughts, which, standing alone, make sense. There is a brief hint of a more basic discussion between creationism and the theory of evolution by comparing the design process with biological evolution, but the authors do not discuss this further. Communication through sketching and visualization completes this chapter, which ends rather abruptly in the middle of a discussion. In conclusion, this book is surely a good starting point for further reading and contemplation on the subject of ‘design-inspired innovation’. Compact discussions, good examples and a broad overview of the field are presented. Despite the fact that the book deals with only about five percent of the designer/ engineer’s work (not dealing, for example, with the enormous task of making a product ready for all customer requirements, including ergonomics, resistance to heat, moisture, shock, fulfilling environmental standards, produceability, etc.), it gives a fair insight in the world of designers/engineers as it is perceived today. The vast number of positive reviews of this book is truly deserved. Readers interested in the subject will definitely be inspired by this book. Bram Snitslaar Enschede, The Netherlands
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