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Creating and Justifying Research and Development Value: Scope, Scale, Skill and Social Networking of R&D Aard J. Groen, Petra C. de Weerd-Nederhof, Inge C. Kerssens-van Drongelen, Rob A.J. Badoux and Gerard P.H. Olthuis In this paper we describe a framework for analysing the creation and justification of Research & Development. The 4S framework is developed for analysing the scope, scale, skills and social network aspects of Research & Development value. The framework is based on social system theory, a process contingency model, and recent Research & Development metrics. We present a first empirical assessment based on a workshop using the 4S framework for leveraging Research & Development. Results that assist in the assessment of value creation utilising R & D within networks are very relevant in high tech industries. The multi-dimensional process approach of this framework seems promising for understanding and managing R&D value creation, but needs further operationalisation. Case studies are described and a Dutch network on leveraging R&D has been initiated.

Introduction

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t is increasingly argued that the management of Research & Development is becoming more complex. Market developments including globalisation, mass-customisation, changing dynamics in demand (Kotler 2000, Volberda, 1996) combine with technology demands such as shorter technology life cycles, virtualisation of research and global standards to accentuate this process. (Teece et al., 1997). There are concerns to make innovation more market oriented, more network related and to apply the newest project management techniques, thus increasing the complexity of the process. Balancing Research & Development investments is increasingly difficult. Firms can fall in the renewal trap by investing too much in Research & Development without clear direction of development (for example 3M according to Volberda, 1996, 1998). On the other hand firms fall into the competence trap (Levinthal & March, 1993) by relying too much on routines. Core competencies become core rigidities (Leonard-Barton, 1992). The balance between cutting current costs and gambling on long term gains with Research and Develop-

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ment goes to the heart of the strategic flexibility discussion. Furthermore, the growing competition in many technology intensive markets adds to the pressure on Research & Development management to justify Research & Development investments (Kerssens-Van Drongelen, 2000). In large firms Research & Development managers often are not able to determine by themselves in which direction and to what extent Research & Development projects are started, continued or ended. More often this is an interaction process with general management. They discuss the issue of how much and where to invest in Research & Development in integral decision making processes using input from several internal and external sources (Griffin, 1997; Wood, 1998). Understanding these decision-making processes is a prerequisite for Research & Development managers to be able to use relevant indicators of value creation when justifying Research & Development expenditures. This implies a thorough insight in firm strategy making processes, where networks of internal and external actors influence processes of decision making. # Blackwell Publishers Ltd 2002. 108 Cowley Road, Oxford OX4 1JF and 350 Main St, Malden, MA 02148, USA.

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Not only strategic aspects of justifying research and development expenditures demand more insight in research and development value creation processes short and long term. The management of the value creation process itself would gain from this. The growing multi-disciplinarity of technological innovation on the one hand and the necessity to specialise due to fast technological development on the other, mean that Research & Development activities are more often carried out in heterogeneous networks of large and small firms, universities and other knowledge institutes (Rip & Groen, 2001; Klein Woolthuis, 1999; Huff, 2000). Creative combination of new and already existing different techniques, technological strategies and distributed bodies of knowledge might open up promising fields for application and the creation of new markets. The speed of development in high tech fields, such as ICT, biotech, micro technologies, and medical technologies, also generates many new startup firms. The need for efficient and effective processes of shared knowledge development in networks of SMEs, knowledge institutes and large firms, is high in these fields. Changing institutionalised patterns of technological regimes (Rip et al., 1995) and existing dominant designs within those regimes asks for elaborate insight into the networks of actors and instititutions. Using the metaphor of Rip and Groen (2001) ‘many visible hands’ construct new knowledge, technologies, and products. For the manager it is important to have sufficient insight on which of those ‘hands’ are relevant, and what kind of contribution they could make for his own value creation process. In this article we present a multiple facetted framework for analysis of value creation and justification of research and development in a network perspective, based on a combination of earlier academic and practical work of the authors. This framework is the basis of a series of ongoing projects in several Dutch companies in a network on leveraging R & D. The first results of discussing this framework with the participating academics and practitioners in a workshop revealed the relevance of this approach.

Assessing Value and Justifying Research & Development Performance To analyse value creation of Research & Development from a network perspective, we developed a framework inspired by multidimensional social system theory derived

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from classical sociological theory on the functional analysis of social systems (Groen, 1994, 2000). Furthermore, to specify organisational aspects and functional requirements we build upon the process-based contingency model tailored to New Product Development (NPD) (De Weerd-Nederhof, 1998). The third inspiration basis first helps us in defining the problem of current methods for performance measurement systems in a networked economy. Secondly, it is a source of definition and selection of metrics to assess Research & Development performance. This is based on earlier work of Kerssens-van Drongelen (1998) and Kerssens-van Drongelen et al. (2000). In this article we do not deductively define a new theory, but we do give a description of the background of the models and construct a framework to assess the value of R & D in a multi-dimensional way. We specifically address the tensions between operational effectiveness and strategic flexibility. Furthermore, we will not address other strands of literature on assessment models for R & D, although we are aware of other approaches, some of which are dedicated to R & D (e.g. Chiesa et al., 1996), others are more general (e.g. EFMDmodel of total quality, Balanced scorecard from Kaplan & Norton, 1996). Instead we choose here to describe this method in development and we will address these two issues elsewhere. First, we will describe elements of theory erecting the 4S-framework. After that we will describe the analytical framework we constructed for analysing the value of research and development and some first operational sets of indicators to build up a performance measurement system.

Analysis of Value of Research and Development As stated above a source of inspiration is found in the work of Parsons (1964, 1977; Groen, 1994). The starting point of the set of assumptions we use, is that actors act purposefully in interaction with other actors (see also Granovetter, 1992). A social system originally was defined as: ‘. . . a social system consists in a plurality of individual actors interacting with each other in a situation which has at least a physical or environmental aspect, actors who are motivated in terms of a tendency to the ‘‘optimization of gratification’’ and whose relation to their situations, including each other, is defined and mediated in terms of culturally structured and shared symbols’ (Parsons, 1964, pp. 5–6) Four mechanisms are embedded in this definition: interaction between actors, striving

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for goal attainment, optimisation of processes, and maintaining patterns of culturally structured and shared symbols. Each of these mechanisms produces it own type of processes and within those processes its own type of capital – goal attainment processes establishing the scope of the actions use (or result in) strategic capital which is based on power or authority (Simon, 1976). Actors are motivated to do certain things. This determines the desired scope of the social system. The nature of goals and ability (by power or authority) to influence behaviour of other actors in alignment with these goals leads to strategic capital. Having explicit strategic goals, power bases, authority or influence bases together lead to an indication of strategic capital of an actor in his network (a.o. Simon, 1976; Etzioni, 1988). It is important to know about the goals and power basis of actors in the research and development context. In order for example, to be able to estimate cooperation or conflict based on communalities or differences of goals of actors involved in the Research & Development process. Furthermore, to be able to estimate differences in power or authority of the actors involved. The estimation of the contribution of Research & Development to the strategic capital of the own company, or to a strategic alliance partner may be a strong indication for value of Research & Development. – economic optimization (seeking the efficient scale) is performed using financial capital (money). Actors strive for optimization of the situation. We see this as striving for economically efficient behaviour. Optimisation of costs and gains lead to more or less monetary economic capital of the actor. Important questions here are related to the necessary scale of an operation: How can more efficient production of Research & Development products be realised, and what kind of financial contribution can be expected, and for who? – pattern maintenance is fed with cultural capital based on closeness to societal norms, knowledge, skills and experience, Knowing how to do things in a more or less effective and efficient way leads to relatively fixed patterns of skills. To maintain these patterns is also a basic mechanism in a social system. However, actors are capable of learning (Parsons, 1977). So

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successful practice leads to institutionalisation of that patterns of behaviour. Continuous evaluation of the situation (think of changing technology, or market circumstances) leads to adaptations in the patterns. Knowledge and experience with successful behavioural patterns lead to cultural capital. Note that successful patterns might have their origin in long standing traditions or in new practices just applied for the first time. Closeness to societal values and norms of the social system indicates ability to build upon earlier traditions (Bourdieu, 1973). Another part of cultural capital is based on knowledge and experience of new technologies. Knowledge management is an important process in this respect. Capital in this dimension relates to the ‘absorptive capacity’ (Cohen & Levinthal, 1990) of a firm, and builds on explicit and tacit knowledge. – the interaction mechanism needs social capital which is based on positional and cohesive relations of actors in social networks Only in interaction with other actors can individual actors exist. Interaction with other actors leads to the integration of actions in the larger system and to mutual adjustment of actions. The kind of mutual adjustments depend on the specific characteristics of the actors and the processes they are involved in. The ability of actors to interact with other actors leads to social capital. Network relations can be described in relational patterns or positional analysis. Relational aspects are, for example, the intensity of the relation, multiplexity of the relation, meaning how many types of content (roles) are embodied in one relation (for example friend, consultant, controller), or look at the range of a network. Structural positional analysis looks at aspects such as equivalency of position (for example two competitors often have similar networks, but no relation with each other). Also aspects such as hierarchy, brokerage relations, or analysing the redundancy of networks (for example searching structural holes which are unique positions without any redundant relations) can be evaluated using network theory (Burt, 1982, 1992; Granovetter, 1973, 1985, 1992) For Research & Development management this leads to questions about the use and improvement of networks of the company by interacting (co-operating) with certain actors in or outside their own company. Assessing the relational and structural position is possible in its own right (showing redundancies, holes, or specific

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cliques in the network), but its relevance is determined by the content of the interaction. Therefore, interaction patterns get meaning through the social integration of scope, scale and skills of the actor (see figure 1). All four mechanisms work concurrently and influence the outcomes of a social system in a structured, but not deterministic, way. Actors develop positions using resources in interaction with others. In interaction actors use these capitals more or less successful, which leads to recursive relations between capital use in one situation and possibilities later in time. Each actor acts in a space in which physical and environmental constraints apply. One consequence of these constraints is found in the assumption of bounded rationality (Simon, 1976). Therefore, actors may behave suboptimally due to bounded rationality, and although a social system might look stable when looked at from a high level of analysis, in specific interaction processes they need not be in stable balance. The interesting point of the original version of Parsons is the explicit attention for multi-dimensionality of social system interaction and the approach of multilevel analysis. The basic hypothesis in social system theory is that only when all four mechanisms are developed sufficiently, can a social

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system last. Concentration on only one dimension will lead to losing of functionality. An example of such concentration on one mechanism is the focus of many managers on reducing costs, Hamel and Prahalad labelled that as managerial anorexia and showed that results are very often disastrous. Also Etzioni (1988) in his famous work ‘The Moral Dimension’ warns about a monolithic attention on economic efficiency. We assume that this is valid for each of the dimensions, so also a monolithic focus on culture, networks or strategy/politics will lead to the same kind of problems. In our view this concurs with practical experiences in R & D management. Goal attainment, patterns of culture and knowledge, economics and interaction in networks all are important facets on multiple aggregation levels of analysis such as the level of the R&D department, the firm, and the networks in and around the firms. However, to make this more operational for the R & D setting we have to define in an R & D context how we can assess the four mechanisms and the gains or losses of capital in the four dimensions. In the process contingency model we found several possible specifications.

The process contingency model The second inspiration described here is the process-based contingency model. It focuses

Figure 1. Two Actor Model of Network of Actors in Social System Perspective

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on organisations as actors. Like the social systems model, it too treats organisations as purposeful systems of people and resources which, using multiple technologies, together perform certain ‘activities’ or ‘processes’ to transform inputs into outputs (Boer & Krabbendam, 1991). The main assumption underlying the model explicitly refers to the link between effectiveness and configuration; an organisation is supposed to be effective if the constituent elements of the organisation are compatible with each other and with the environment. So this theory focuses on the organisation as unit, relations to the environment are developed in a more ad hoc fashion, but on a number of dimensions the process contingency approach specifies important elements for assessing value of research and development. The operationalisation of the process-based contingency model is tailored to NPD (de Weerd-Nederhof, 1998). It contains separate mapping tools for the description of goals (strategic, adaptive and operational) (defining scope), processes (primary, management and support) (defining scale and elements of pattern maintenance), people (NPD workers and managers), tools & techniques (techniques, IT, equipment), and organisational arrangements (all three elements of skill / pattern maintenance). Organisational arrangements are described in a multi-level way: at the individual ( jobs, roles), group (teams, procedures) and organisational (structure, culture) level. Analysis of this NPD system is facilitated by assessing performance fit as well as configurational fit, both in terms of the performance dimensions Operational Effectiveness and Strategic Flexibility. Operational Effectiveness refers to the effectiveness of today’s work: the degree to which NPD contributes to realising goals set by the organisation. Strategic flexibility refers to the readiness of the NPD system to adapt to, anticipate or even create future performance requirements (tomorrow’s innovation) (de Weerd-Nederhof, 1998). These two performance dimensions offer an evaluation scheme, which is not at hand in the social system view, but which is very relevant in the context of R & D as described in the introduction. Performance fit is the degree to which the strategic, adaptive and operational goals set for the product concept performance (fit with market demands and firm competencies) and the NPD process performance (speed, productivity, flexibility) match with actual performance at both performance dimensions. Configurational fit is determined by identifying the features of the NPD configuration which contribute to the matches (or cause the

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gaps) in the performance fit. Note that the concept of fit is dynamic, meaning that it should be possible to deal with (continuous) changes in Operational Effectiveness and Strategic Flexibility issues. In fact, it is stressed that NPD management is an act of balancing short- and long-term issues as well as finding a balance in satisfying internal and external stakeholders. In line with this, shortcomings in one configurational element can be dynamically combined with and balance strengths in another. For example it was found that badly designed horizontal linkages hindering in-depth contacts between members of cross functional teams representing the same business function, may – especially in small organisations – be overcome and balanced by an innovative climate and strong leadership (de Weerd-Nederhof, 1998). In earlier work on the use of performance indicators (a.o. Chiesa et al., 1996) it was shown that performance measurement should distinguish between process and product oriented performance analysis. Using the process based contingency model it was shown that not only management control of product development output functions are important, but also learning and alignment with primary objectives expressed in NPD strategy should be monitored (Kerssens-van Drongelen & de Weerd-Nederhof, 1999). Operational Effectiveness and Strategic Flexibility are considered as basic elements (performance dimensions) of a solid NPD/Research & Development strategy. From case studies we know that many Research & Development managers consider their strategic flexibility as especially problematic. More insight in learning processes is necessary to manage and justify on the basis of enhancing Strategic Flexibility. Essential points from the process based contingency model are twofold here: first the concept of dynamic fit and the connected view on balancing short term and long term issues, directs the Research & Development manager to address the timeline of Research & Development value creation and to align justification with that. Furthermore, it confirms that fit is not a linear concept for which one could state an end-goal. Instead dynamic fit is created in interaction between actors’ alignment of goals, cultures, economies and networks. In learning processes fit is constantly re-assessed. This brings us to the second point: the focus on learning processes calls for extra attention on assessing learning in Research & Development context. This is coherent with our interpretation of social system theory, specifically changes in cultural capital indicate learning.

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Research & Development value justification metrics The third source of inspiration for the 4S framework was found in Research & Development performance indicator literature (a.o. Kerssens-van Drongelen, 1999). On the one hand we find a method of designing a performance measurement system, and on the other an overview of existing practices and the related problems were described in this work (see also Kerssens van Drongelen et al., 2000) Many of the developed metrics focus on economic assessment of Research & Development. Quinn in 1960 has already mentioned: ‘Research & Development output in terms of expected economic value compared to costs and eventual profits obtained from technologies actually adopted by the business.’ The widely used Brown and Svenson framework (1988) also focussed on economical value of the processing Research & Development system, leading to patents, products, processes, publications, facts / knowledge. Furthermore, they consider outcomes from the receiving system (marketing, business planning, manufacturing, engineering and operations) such as cost reduction, sales improvement, product improvements and capital avoidance. These kind of indicators still are important, but as shown in the discussion based on the process contingency model short term and long term balancing complicates this very much. Thus a strategic dimension is necessary. Furthermore, the organisational learning aspects are discarded too often. The social system model accommodates the economic and strategic dimension and adds the cultural pattern maintenance as a dimension for systematically treating learning and maintaining experience on multiple levels of aggregation level. For the organisational level some indicators are developed in the process based contingency model (e.g. descriptors of organisational arrangements). Next it seems that many assessment tools take the firm as unit of analysis (e.g. Brown & Svenson, 1988; Chiesa et al., 1996), where the assessment of network complexity is underdeveloped. Via the network dimension the 4S assessment explicitly addresses this. However, to develop metrics to assess network characteristics is not an easy task. Although many network measurement methods and techniques exist (see a.o., for quantitative models Burt, 1982, 1992 or for a more qualitative approach Ha˚kansson & Snehota, 1995) it will take considerable work to develop metrics to assess the value of certain network structures and relational interaction patterns in a quantitative way. Network

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assessment using qualitative instruments is part of the 4S approach. Assessing the nature of the scope, skill and scale effects through social links is possible. Furthermore, elements of network theory can be used for example to assess redundancy of relations, brokerage effects, clustering of cliques and equivalency of positions of competitors. It is important to note that due to several types of measurement problems it is difficult to accurately isolate the contribution of Research & Development to company performance. To mention some problems: time lag of cause and effect might be large (e.g. Papas & Remer, 1985); politics might interfere; value is created in intertwined teams (Hodge, 1963). The intertwined effort made inside companies to realise market performance is already difficult to disentangle. In complex networks of firms, universities, co-developers, even competitors working together in knowledge intensive Research & Development, this is even more difficult. Subjective measurement on an ordinal scale might be the maximum reachable measurement level. We see this as a fact, that does not take away the potential usefulness of such measurement. Depending on the level of openness in a network, discussing Research & Development value creation and justification in the network (or parts of it) can contribute to understanding each others position. The role of trust and openness in such processes can not be overestimated (see Klein Woolthuis, 1999; Nixon, 1998) (for a more elaborate discussion of measurement problems see Brockhoff et al., 2000, pp. 267– 270) The use of good measurement theory is very important in such cases: to be able to define as clear as possible how the complexity can be unravelled to discuss in what way cause and effect of Research & Development value creation are justifiable. This is the aspect our contribution is focussing on. Our approach can be characterised as a process oriented, predominantly (inter-) subjective and qualitative approach. However, this does not mean that part of the value creation and justification assessment is not quantitative or based on objective numbers. Important in our view is to generate discussion on what value is and how it best can be created to enhance learning processes. In our view it is not automatic that often mentioned general performance indicators such as innovativeness (Bolwijn & Kumpe, 1990), time-to-market, quality; productivity, cost, and quantity (Gerritsma & Omta, 1998) are used in an assessment. Although in general these concepts have much face value it depends on the firms strategy, skills, scale

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and social position to what extent which indicator is relevant. Where one recognises the co-evolutionary aspects of technology and social developments general concepts such as quality or costs are in themselves multidimensional and should be operationalised using a coherent multi-dimensional theory.

Towards a framework for leveraging Research and Development Combining the basic ideas of the three strands of literature above leads us to a multidimensional framework for analysis of value creation and justification of research and development. As discussed above we do not claim to be able to make a general applicable set of specific indicators, but in stead we propose a process-oriented method of defining and assessing Research & Development

efforts. The aim of this process is twofold: first it aims to support Research & Development managers in defining how they can create value, and second how they can justify their claims on assets of the firm and/or of other actors in their Research & Development oriented network. The four mechanisms described in social system theory are used as a starting point for analysing the need of information on value of research and development. For each of those mechanisms we use earlier work on mapping tools for assessing new product development systems (de Weerd-Nederhof, 1998), and other auxiliary theory. For each of the dimensions we will recapitulate the mechanism; define the type of capital; and construct a set of mapping tools to analyse a networked research and development unit. In table 1 we describe the first set of mapping tools per dimension. This

Table 1. 4S Mapping Tools for Research & Development Assessment Social networking Mechanism: Actors interact with other actors occupying network positions and filling the relation(s) in a multiplex way, and are dependent on other actor’s actions. Capital: Social capital relates to available relations and network position in network structure. Mapping tool: Which actors are relevant to a certain research or development (short and long term)? Define units of analysis: what aggregation level is important for the development? What position in networks of knowledge, power or economy are actors in? Type of relations: who is interacting with whom how frequent, duration, intensity, strength of ties? Analyse positional structures, who is equivalent? How redundant / unique are relations? Scope / goal attainment Mechanism: Actors set goals and try to attain them, but they are also constraint by goals of other actors. Capital: Strategic capital relates to power, authority and influence of actors involved. Mapping tool: Which goals do actors involve have on strategic, adaptive and operational levels (short term and long term)? Establish a map of power, authority and influence distribution in the relevant network? Map dynamics of goal attainment to assess the role of research and development output in it. What is the contribution to realising short and long term goals of actors involved? Skills & values / pattern maintenance Mechanism: Actors maintain patterns of behaviour and value patterns (but are influenced by patterns of others). Capital: Cultural capital relates to experience and knowledge accumulation and cultural values and to how the current processes are maintained. Mapping tool: How are people selected, trained, and appraised on technical, administrative and social skills? What (short and long term) contribution is made to technical and organisational /network knowledge? What kind of hardware and software is maintained? Compare informal practices and formal procedures. Attitudes towards important network goals (e.g. innovation, entrepreneurial orientation). Scale / efficiency adaptation Mechanism: Actors adapt their processes to work as efficient as possible, but have to use or compete for production systems of others too (make or buy / competition). Capital: Financial capital is money. Mapping tool: What is the expected net present value of the output of R&D? Map speed and productivity performance. Which sources of economic income are generated (sales, licensing, subsidies)?

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set of questions is used as point of departure for discussion in workshops and case studies for analysis of both operational effectiveness and strategic flexibility. In the remainder of this article we will describe the first attempts to find more explicit indicators for assessing the value of R & D. This was done in a workshop labelled as a small event on creating and justifying value of Research and Development.

First Assessment of Empirical Relevance Introduction To assess relevance of this topic and framework we organised a small event (workshop) in January 2001. 25 participants from 11 different companies came together to discuss leveraging Research & Development. Table 2 shows the sort of company and the field the company works in. The participants came from a wide variety of companies. About 25% of the participants possess a general management function and 50% work as R & D managers, the other 25% were consultants or researchers. The desired outcome of this event was a first evaluation of the 4S framework in aiding Research & Development managers to steer value creation and to justify claims on scarce resources. As preparation for this small event we constructed a framework as depicted in appendix 1. We gave a description of leveraging Research and Development issues (including an earlier version of this paper). Furthermore, they received a set of basic questions as shown in table 1 and we asked the participants to prepare a first analysis of their value creation and justification R & D system. They could

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use table 2 as a sort of reporting tool. With three of these companies we had an interview to introduce the framework. The rest only received explanations in writing. Seven of the eleven companies delivered such a first analysis. Two of seven only used the columns of operational effectiveness and strategic flexibility and did not fill in the column on measurements. In the workshop, in presentations and discussions the indicators were mentioned. At the end of the workshop we evaluated the presented framework on relevance. We will start with this last topic as it shows some broad relevance indications. This will be followed by a short description of the outcomes from self-assessments made by the participants. This will lead us to the conclusions and further developments in the last part of this paper.

Relevance and current availability of mapping tools On the relevance of the topic we asked a few questions about the importance of leveraging R & D in each of the 4 S dimensions. Furthermore we asked them if they already had indicators on the dimensions in place. The scores in general showed that each of the dimensions were evaluated as important (see table 3). However, the availability of indicators was not so homogeneous. Economical aspects of R & D value are measured in 90% of the firms, and the firms who did not do this do not do formal R & D (two consultants). Knowledge aspects and strategic aspects were measured explicitly by 60% of the firms. In other words approximately a third of the firms who did measure economic value of Research and Development did not measure the strategic or cultural value of research and

Table 2. List of Participating Companies Sort of company

Field

Large companies

Chemical Energy IT Electronics Medical Accountancy Environment Project management Energy / environment Industrial equipment

Consultancy companies Technology transfer institutes Small firms

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Table 3. Importance and Use of Indicators of Aspects of R & D Value in Companies

– – – –

Importance of these aspects on a 1–5 scale

Percentage of firms who use indicators for these aspects

4.3 4.2 4.3 4.2

60% 20% 90% 60%

strategic aspects (scope) network aspects (social networking) economical aspects (scale) knowledge aspects (skill)

development, although they seem to find these aspects and economic issues of equal importance. Even more noticeable is the discrepancy between the felt importance of network issues, which is also high, and the availability of indicators of network aspects in only 20% of the cases. We might conclude that the participants became more aware of strategic, cultural and social value of research and development in this workshop. This was corroborated by statements of participants. Furthermore, four participants granted access to students performing a case study on their organisations, showing interest in going deeper into the question of how to create and justify research and development value.

Results of self-analysis In the following part of the article we will describe per dimension which kind of indicators are in use in the companies. The results of the inventarisation of the firms shall be given in this part for every social system dimension on the performance dimensions operational effectiveness and strategic flexibility. We give examples of reasoning of different firms of the issues they think are

important. This will show some of the heterogeniety of the outcomes.

Strategy / Scope Almost all respondents could give insights in strategic issues, only two companies left the performance dimension Operational Effectiveness blank and a different company left the field on strategic flexibility blank. Goals to be attained by Research and Development in the performance dimension operational effectiveness can be summarised as matching current market demands. This was worded different giving some ideas about different sets of justification indicators. The medical technology company mentioned very explicitly matching the patent port folio to the product road map for the coming years. Others just spoke in general terms about ‘license to operate’, and improvement of efficiency. For the performance dimension strategic flexibility the chemical company mentioned ‘Re-establish technological leadership in the market’ and the medical company ‘provisioning of new technologies an architectural concepts to enable leadership’. Also ‘product/ patent portfolio’ was mentioned more often.

Table 4a. Results workshop Monitoring added value creation

Strategy / Scope Which strategic goals are to be attained? What contribution to strategic capital (power base of company) is made?

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Proof of added value

Operational effectiveness

Strategic flexibility

Measurement

– better matching of technology, patent and publication portfolios to product roadmaps – Maintaining ‘licence to operate’ – Improvement of efficiency

– Enhancing market value by technological developments Technological leadership – Sustaining a product / process portfolio

– nr. of patents and licenses – business opportunity rating – strategic compatibility of Research & Development

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Table 4b. Results Workshop Monitoring added value creation

Social networks Which position and relational contacts are used/useable? What contribution is made to social capital?

Operational effectiveness

Strategic flexibility

Measurement

– Network with local knowledge institutes, – Using contacts from symposia, conferences etc. in projects – Providing knowledge & reputation to other departments

– Future access to knowledge networks – Networking around core competence areas – Rapid receipt of knew developments – Enhance the positive image

No indicators mentioned

The energy company wrote about this ‘The work performed by Research & Development supports the policy and strategic goals of the company. Research & Development provides the company with innovation and technical knowledge in order to enhance the market value of natural gas’. Social network Most of the companies had little experience in making their network position explicit. Only four companies gave a result for the performance dimension, Operational Effectiveness. With the performance dimension Strategic Flexibility more response occurred. The electronic company showed in their contribution to the small event, called ‘the networking company’, that they think that this is an important dimension in the 4S-model. Three of the four companies had described a result in the operational effectiveness dimension that can be summarised as ‘the development and maintaining of networks’. The IT company describes this as ‘creating access to local knowledge (institutes) to the benefits of the company’. The environmental consultant wrote down ‘networking by participating in symposia and congresses and using these networks inside the companies for projects and participation’. The energy / environment technology transfer company describe this as ‘developing and maintaining networks’. The energy company looked in a different way at the social network. They looked at how the Research & Development department could give added value to the social network and not as the other three to get something (mostly information) from the social network. They describe this as ‘Experts from Research & Development lend their expertise in dealings that other departments

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have with external organizations. In this fashion Research & Development lends significant additional weight to company argument’. The results on the dimension Strategic Flexibility can in most of the situations be characterised as ‘network development’. But the purpose of developing these networks is rather vague. The IT company describes this as ’enable future access to local knowledge (institutes) to the benefit of the company’. While the medical company say that they ‘aim at building knowledge for core areas’. The environment consultant says that ‘the knowledge within the network makes the company more flexible’. The Energy / environment technology transfer company does not give a goal for developing a network and only give as result ‘developing and maintaining network’. Also in the dimension of strategic flexibility the energy company looked from a different point of view at the social network. The energy company describes this as ‘The interaction of researchers in their various networks results both in rapid receipt of new information (‘sensor function’) and its ability to influence the outside parties in the network. Furthermore, the respect that Research & Development has earned and continues to earn based on its expertise enhances the positive image of the company’. In network theory terminology we see that the responses relate to the network from a ‘ego-network’ point of view: dependencies on other actors, possible effects of network structures, redundancies or holes are not addressed issues here. Skills, Competencies & Values Most of the companies had big difficulties with assessing human/cultural capital and

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especially in the dimension of operational effectiveness. Only three companies filled in a result in this performance dimension. In the dimension of strategic flexibility the results diverged strongly. Two of the seven companies made a distinction by separating this dimension in human capital and cultural capital. The management technology transfer company stated that ‘the human capital expresses itself in the other three dimensions’. Two companies filled in a result which had to do with ‘response’. The IT company said ‘to be able to respond to specific innovative questions from the market and customers (strategic market support). While the medical company, who made a distinction between human and cultural capital, mentioned under cultural capital ‘regular reviews of projects to check response conditions and progress’. The chemical and the medical company, both made a distinction between human and cultural capital, described as human capital: The chemical company mentioned ‘focus teams for know-how transfer (technical, commercial) in all countries involved’. While the medical company made two remarks ‘concentrate on core skills and knowledge’ and ‘improved ways of working by improving: employability and working conditions/environment’. Two different kind of results can be recognised in these responses. The first can be summarised as ‘focus on know-how’ and was seen by both. While the second only seen by the medical company can be summarised as ‘improving ways of working’. Within the strategic flexibility dimension the results were not quite clear. The chemical company described as cultural capital the ‘core

project team (involving all functional areas) with strong support from senior management’ and for human capital as only the ‘core project team (involving all functional areas)’. While the IT company sees as indicator for this dimension ‘To develop competencies that allow the right products for the company group in the future’ and ‘To create an innovative image in the (labour) market to attract the people of choice’. The energy company wrote down as ‘Research & Development is an environment in which young people can learn various facets of the business as well as sharpening their analytical skills. Both aspects enhance their value to the organization upon being transferred’. The medical company was the second company that made a distinction between human and cultural capital. They had three remarks on human capital ‘value people as vital assets’, ‘image to be the employer of choice for a hightech career’ and ‘act as a knowledge base’. On cultural capital they made two remarks ‘always striving for clear definitions of research’ and ‘always setting business objective as a prime objective’. The environment consultant mentioned about this that ‘Research & Development is attractive for higher educated employers’ and ‘many people from Research & Development flow into different parts of the organization’. While the energy / environment technology transfer company said about this ‘developing market orientation of researchers’. Two results can be abstracted out of these diverge results. The first can be summarized as ‘education’. The IT, energy and environment consultant noticed this. The medical company and environment consultant noticed

Table 4c. Results Workshop Monitoring added value creation

Skills, competencies and values How and which patterns are to be maintained (adaptive goals)? What contribution is made to cultural and human capital?

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Operational effectiveness

Strategic flexibility

Measurement

– Regular reviews of projects – Focus teams on knowledge sharing – Improve employability and working conditions

– Maintain interdisciplinary development team across functional areas – R & D contributes to core compentence – more attractive for higher educated employees also for rest of company

– project quality – sharing volume of facts and knowledge – satisfaction with education/ training – growth technical level – planning quality – clear roles and procedures – team cohesiveness – spin-out of personnel to rest organisation

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Table 4d. Results Workshop Monitoring added value creation

Scale / economic efficiency Which economic scale is necessary? (operational goals) What contribution can be expected to economic capital?

Operational effectiveness

Strategic flexibility

Measurement

– Working more efficient – Budget & timing control – Enhancing ROI

– Enhancing performance on ROI , time to market, return on knowledge, developing new products

– NPV of projects – Sales and profits generated – Licensing income / year – Investment/year – Time till completion

the second result. They noticed that Research & Development makes a company more attractive for higher educated people Scale / economic efficiency In this dimension most of the companies did not have a problem with giving results, which we expected already. In most companies the added value of Research & Development is predominantly justified on this dimension. Two sorts of results could be recognised in the dimension of operational effectiveness. The first can be called ‘control’. The chemical company described this as ‘budget and timing control’. While the medical company mentioned ‘clear measurement contribution to business effects’. The environment consultant said just ‘budget control’. The other sort of result can be described as ‘working more efficient’. The energy company described this as ‘the work performed by Research & Development department allows the company to use their resources with higher efficiency. Higher efficiency enables the company to reduce operating costs’. The management technology transfer company described this in terms of better ROI, time-to-market and return-on-knowledge. While the Energy / environment technology transfer company describes this as ‘effective use of government subsidies’. In the dimension strategic flexibility two groups of results can be recognised. The first group can be summarised as ‘better performance’. The chemical company describes this as ‘SupDi-toolkit, a new approach for colour formulation process’. The energy company mentioned ‘the work performed by Research & Development allows the company to manage their processes in a better way. Better management enables the company to reduce operating costs’. The medical company describes this as ‘maximize sustainable profit-

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ability’. While the management technology transfer institute describe this as ‘better ROI, time-to-market and ROK’. The second group that could be recognised is ‘developing new products’. The IT company describes this as ‘To develop technology that allows the company group to develop the right products in the future. The environment consultant said this as ‘Making developments that enables the company to make successful (advice) products’. While the Energy / environment technology transfer company wrote this down as ‘securing continuity by generating income for future development.

Conclusion First of all it is clear that leveraging R & D is an important issue for R & D managers. However, the creation and explicit justification of added value of R & D in relation to scope, skill, scale and social networking is not yet common practice. First indications from the workshop are that it is promising to develop this method further. Clearly further operationalisation of this framework is necessary to come to a practical instrument. The fact that three companies after an interview on the use of this framework were better able to use it shows that clarification is necessary and useful. Furthermore, the basic assumptions of the approach, placing value creation explicitly in a network perspective, is not only theoretical of importance, but is also in practical sense an useful addition. The observation that the importance of network aspects as seen by the managers in the workshop was high, but the use of explicit network analytical tools is low, supports this. Scientifically this approach combines in a systematic way internal and external developments and mechanisms to influence value

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creation. The combination of social system theory and elements of the process based contingency theory and the metrics developed in that perspective lead to a fruitful framework. The process orientation, combination of qualitative and quantitative analysis, multi-dimensionality and multi-level analysis, lead to a complex model of value creation in R & D. We conclude that the complex situation of R & D in high tech fields corresponds with this complexity. Further development is necessary to develop the theory from a predominantly analysis tool to a management tool. Therefore further operationalisation is necessary. First steps to do so are taken, four case studies are begun and also the R&D network will continue its activities. The case studies address complementary issues: one case study focuses on the interactions between the four basic mechanisms, three R & D units of companies present in the workshop are analysed in more depth on this topic. One other case study is an in depth study of an industrial network in which an innovation is introduced. In the case study an assessment tool of this network is made, leading to pointers for marketing and portfolio management in R & D. Recently two case studies began analysing the internal and external networks of research and development units in automotive and electronics firms. In a later paper we will come back to the results of these case studies and the feed back we will get from the leveraging R & D network in which coming events will be used to present and evaluate these cases. Using a design oriented approach (Kerssens-van Drongelen, 1999) we expect to construct a design method of an assessment tool for value creation and value justification in research and development systems. This method will enable network-oriented assessment in a multiple dimensional way revealing value for scope scale and skill of actors active in these networks.

Note 1. We would like to thank Mark ten Broeke, student at the University of Twente for his assistance in gathering and processing the data from the workshop.

References Boer, H. and Krabbendam, J.J. (1991) Organising for market-oriented manufacturing. POMS Conference. New York City, USA, November 11–13.

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Bolwijn, P.T. and Kumpe, T. (1990), Manufacturing in 1990’s – Productivity, Flexibility and Innovation. Long Range Planning, 23, 44–57. Bourdieu, P. (1973) Cultural reproduction and social reproduction. In Brown, R. (ed.), Knowledge, education and cultural change. Tavistock/ London, UK. Brockhof, K.K., Pearson, A.W. de Weerd-Nederhof, P.C. and Kerssens-van Drongelen, I.C. (2000) Readings in Technology Management, a selection of 10 European Doctoral Schools. Twente University Press, Enschede. Brown, M.G. and Svenson, R.A. (1988) Measuring Research & Development productivity. Research Technology Management, 31, 4, 11–15. Burt, R.S. (1982) Toward a Structural Theory of Action, Network models of social structure, perception and action. New York, Free Press. Burt, R.S. (1992) Structural holes: the social structure of competition. Harvard University Press, Cambridge MA. Chiesa, V., Coughlan, P. and Voss, C.A. (1996) Development of a Technicval Innovation Audit. Journal of Product Innovation Management, 13, 105–136. Cohen, W.M. and Levinthal, D.A. (1990) Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quartely, 35, 128–152. Etzioni, A. (1988) The Moral Dimension. The Free Press, New York. Gerritsma, F. and Omta, S.W.F. (1998) The content methodology facilitating performance measurement by assessing the complexity of Research & Development projects. In Levebvre, L.A., Mason, R.M. and Khalil, T. (eds) Management of Technology, Sustainable development and Eco-efficiency. Pergamon, Oxford, pp. 101–109. Granovetter, M. (1973) The Strength of Weak Ties. American Journal of Sociology, 78, 1360–1380. Granovetter, M. (1985) Economic action and Social Structure: The Problem of Embeddedness. American Journal of Sociology, 91, 3, 481–510. Granovetter, M. (1992) Problems of Explanation in Economic Sociology. In Nohria & Eccles, 1992. Griffin, A. (1997) PDMA research on new product development practices: updating trends and benchmarking best practices. The Journal of Product Innovation Management, 14, 6, 429–459. Groen, A.J. (1994) Milieu en MKB: Kennis en Kennissen, milieuinnovatie in de grafische industrie: modelmatig verklaard. Groningen Thesis in economics, management & organization. WoltersNoordhof, Groningen. Groen, A.J. (2000) Marketing en Prestaties van de onderneming; net werken of netwerken? Tijdschrift voor Bedrijfskunde, 72, 2, 72–80. Ha˚kansson, H. and Snehota, I. (eds.) (1995) Developing Relationships in Business Networks. Routledge, London. Hodge, M.H. Jr. (1963) Rate your company’s Research Productivity. Harvard Business Review, November–December, 109–122. Huff, A.S. (2000) Presidential address: Changes in Organizational Knowledge Production. Academy of Management Review, 25, 2, 288–294.

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Kaplan, R.S. and Norton, D.P. (1996) The Balanced Scorecard: translating strategy into action. Harvard Business School Press, Boston, MA. Kerssens-van Drongelen, I.C. (1999) Systematic Design of Research & Development Performance Measurement Systems. Thesis University of Twente, Enschede, 16 April 1999. Kerssens-van Drongelen, I.C. and de WeerdNederhof, P.C. (1999) The use of performance measurement tools for balancing short- and long term NPD performances. International Journal of Innovation Management, 3, 4, 397–426. Kerssens-van Drongelen, I.C., Nixon, B. and Pearson, A. (2000) Performance Measurement in Industrial Research & Development. International Journal of Management Reviews, 2, 2, 111– 144. Klein Woolthuis, R.K.W. (1999) Sleeping with the Enemy. PhD Thesis, University of Twente. Kotler, P. (2000) Marketing Management. Prentice Hall, New York. Leonard-Barton, D. (1992) Core capabilities and core rigidities: A paradox in managing new product development.. Strategic Management Journal, 13, Special Issue, 111–125. Levinthal, D.A. and March, J.G. (1993) The Myopia of Learning. Strategic Management Journal, 14, Special Issue, 95-112. Mitchell, R.K., Agle, B.R. and Wood, D.J. (1997) Toward a theory of stakeholder identification and salience: defining the principle of who and what really counts. Academy of Management Review, 22, 4, 853–886. Nixon, B. (1998) Research and Development Performance Measurement: a case study. Management Accounting Research, 9, 3, 329–355. Papas, R.A. and Remer, D.S. (1985) Measuring Research & Development productivity. Research Technology Management, 28, 3, 15–22. Parsons, T. (1951) (1964) The Social System. The Free Press, New York. Parsons, T. (1977) Social Systems and the Evaluation of Action Theory. The Free Press, New York. Quin, J.B. (1960) How to evaluate research output. Harvard Business Review, March–April, 69–80. Rip, A., Misa, T.J. and Schot, J.W. (eds.) (1995) Managing Technology in Society. The Approach of Constructive Technology Assesssment. Pinter Publishers, London. Rip, A. and Groen, A.J. (2001) Many Visible Hands. In Coombs, R., Green, K., Walsh, V. and Richards, A (eds.), Demands, Markets, Users and Innovation. Edward Elgar.

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Simon, H.A. (1976) Administrative Behaviour. The Free Press, New York. Teece, D.J., Pisano, G. and Shuen, A. (1997) Dynamic capabilities and strategic management. Strategic Management Journal, 18, 509–533. Visser, S., Keerssens-van Drongelen, I., WeerdNederhof, P. de and Reeves, J. (2001) Design of a Performance Measurement System: the case of NIAB. Creativity and Innovation Management, 10, 4, 259–268. Volberda, H.W. (1996) Toward the Flexible Form: How to remain vital in hypercompetitive environments. Organization Science, 7, 4, 359–374. Volberda, H.W. (1998) Building the Flexible Form: How to remain competitive. Oxford University Press, Oxford. Weerd-Nederhof, P.C. de (1998) New Product Development Systems. Operational Effectiveness and Strategic Flexibility. PhD Thesis University of Twente, Enschede, The Netherlands. Wood, R. Industrial Research Institute’s Research & Development trends forecast for 1998. ResearchTechnology Management, 41, 1, 16–20.

Aard J. Groen is associate professor of Entrepreneurship and is director of NIKOS: the Dutch Institute for Knowledge Intensive Entrepreneurship at the University of Twente, The Netherlands. Inge Kerssensvan Drongelen is management consultant at Cap Gemini Ernst & Young in Utrecht, the Netherlands, and assistant professor at the Faculty of Technology and Management at the University of Twente, Enschede, the Netherlands. Petra C. de Weerd-Nederhof is associate professor New Product Development at the faculty of Technology and Management, University of Twente, The Netherlands. Rob Badoux is currently Program Director for the Natural Gas Strategy Course at Gastransport Services, The Netherlands. Before this he was Manager of R&D Services at Gasunie Research, The Netherlands. Gerard P.H. Olthuis was technology officer at Philips International, Eindhoven, The Netherlands. He retired in 2001.

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Appendix 1: 4 S framework Monitoring added value creation

Proof of added value

Operational effectiveness

Strategic flexibility

Measurement

Strategy / Scope Which strategic goals are to be attained? What contribution to strategic capital (power base of company) is made?

–

–

–

Social networks Which position and relational contacts are used/useable? What contribution is made to social capital?

–

–

–

Skills, competencies and values How and which patterns are to be maintained (adaptive goals)? What contribution is made to cultural and human capital?

–

–

–

Scale / economic efficiency Which economic scale is necessary? (operational goals) What contribution can be expected to economic capital?

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Triggering Creativity in Teams: An Exploratory Investigation Sven F. Kyle´n and A.B. (Rami) Shani Triggering, developing and maintaining creativity in teams is critical to the economic performance of the firm. This article presents an exploratory action research effort in a health care organization that focused on interaction patterns amongst team members, creativity and performance. The results indicate that the teams’ inquiry and dialogue into their interaction patterns have the potential of influencing creativity. Team interaction patterns were found to influence team performance. Directions for future research are discussed.

Introduction

M

ost companies are dependent on development driven by creative ideas, designs, solutions, products and services. Survival and success of organizations, especially in a long-term perspective, depend on creativity and the management of creativity (Ekvall, 1997; Oldham & Cummings, 1996; Scott & Bruce, 1994; Unsworth, 2001). In the context of this paper, creativity is viewed as the development of ideas that are unique or novel and are deemed to be useful in a work situation (Amabile, 1983) where the ‘standard action’ is not appropriate (Kyle´n, 1999). Guilford suggested four measures of creativity. Fluency is the ability to generate many ideas. Flexibility is the ability to generate a wide range of ideas. Originality is the ability to generate a novel idea. Elaboration is the ability to develop or embellish ideas (Guilford, 1967). This divergent thinking perspective helps describe a broad range of creativity, and takes on greater importance due to the increasing pace of change in organizations. Creativity, in the context of work, has been viewed historically as an individual phenomenon. Managers of work teams have been struggling continually with overcoming the system’s inertia which has been cited as a major barrier to individual creativity. The focus on creativity within the individual is consistent with a variety of cognitive or attributional biases that lead us to ignore the social or contextual factors of creativity (Purser & Montuori, 1995). During the past decade, as the pressures for creativity in-

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creased, the role that teams at work can play in overcoming some of the contextual barriers has been advanced (Sosik & Aviolio, 1998). Surprisingly, the relatively little research on team creativity that can be found in the literature seems to focus on ad hoc rather than permanent teams at work (Paulus, Brown & Ortega, 1996). Within the emerging environmental changes, and the evolving nature of the work organization as a teambased entity, managers and scholars alike are challenged to find ways to foster team creativity. This manuscript reports on the results of an exploratory study in a health care organization in the southwestern part of Sweden. The attempt was to develop team creativity capability, taking into account the environmental context within which the teams functioned. Building on Argyris & Schon (1974, 1978), seminal work on creative learning and action science theory (Argyris et al., 1985), an exploratory investigation with 14 teams was carried out. In the next section, we review and synthesise the relevant literature. Next, the study methodology is presented, followed by the study results. The discussion focuses on the identification of some direction for future research and action.

Framing team creativity and interaction patterns According to Leonard and Sensiper (1998), ‘creative ideas do not arise spontaneously from the air but are born out of conscious, # Blackwell Publishers Ltd 2002. 108 Cowley Road, Oxford OX4 1JF and 350 Main St, Malden, MA 02148, USA.

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semiconscious, and unconscious mental sorting, grouping, matching, and melding’. The quality of interpersonal interactions at the conscious level is likely to stimulate and enhance creativity (Kao, 1991). Over time, teams develop implicit ways of working and learning together, with collective tacit knowledge that often appears in the form of unconscious norms (Leonard & Sensiper, 1998). Thus, triggering creative behavior in teams is a process that might be influenced and managed, yet is not fully understood (Shani, Sena & Stebbins, 2000). Few studies have attempted to understand organizational barriers to team creativity (Woodman, Sawyer & Griffin, 1993; Shani & Lau, 2000). As organizations evolve and mature, structures and processes are developed to address strategic goals and deal with emerging issues and challenges. However, this is sometimes done in a way that will hinder creativity. Olin & Wickenberg (2001) show that several product development project teams bend and break rules in an attempt to be more free and creative in their job, especially in organizations using stage gate models. Over time, many policies, for example the stage gate model, and work culture begin to impact the capabilities of teams to work in an effective way. For example, Mohrman et al. (1995) argue that the team-based organization is better able to adapt to change. Problem solving is enhanced as well. But teams do not work alone. There is no magic in group interaction so team-based organizing seems to require training in order to fullfill its promises (Hackman, 1991). Argyris (1969) provides a foundation for understanding how different ways of interaction promote or hinder creativity in teams. In his studies, teams were classified into two main categories of interaction patterns according to data from interviews, evaluations and observations. Interaction pattern A was described as the general interaction shown by the majority of groups. Pattern A meant less risk taking, experimenting and openness than pattern B. Pattern A also meant holding back feelings and a low degree of security and trust in the other members of the group, which was not the case in the B groups. Pattern A showed more rigid group norms, a high demand for conformity and little support provided by members of the group to other members. The interaction pattern B groups were characterised by a greater expression of feelings (high degree of openness) and encouragement to take risks and experimentation. There was also a lower demand for conformity, and antagonism in the group was less pronounced. Argyris confirmed that pattern A was more common,

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representing the general pattern. Only a few of the groups studied showed a B pattern. The consequences of pattern A, according to Argyris, was a less effective interpersonal interplay and poorer problem solving ability, especially in the case of important and sensitive subjects. Argyris argued that pattern B did exist, although rarely, and that ineffectiveness would decrease if organizations could foster work teams with pattern B-behavior. Bion (1968) – using psychodynamic theory as a basis for his work, identified two function levels in teams and groups that are similar to Argyris’ division of two interaction patterns A and B. Bion used the terminology ‘the rational work group’ (B-pattern according to Argyris) versus ‘the basic assumption group’ (A-pattern according to Argyris) in which the task falls into the background in order to deal with the emotional needs of the team members. Katzenbach and Smith (1993) define a work team from a performance perspective that leads to discussion as to whether the team has a committee-performance (cp) or a team-performance (tp). In the cp, there is an individual plus individual thinking that builds up the actions while the tp means that the interaction makes it possible to go into collective action. This leads to the team performance resulting in more than the sum of the individual contribution. This means that new knowledge is continually created about the team’s ability to fullfill its purpose/ mission and how it can be improved. Docherty (1996) takes this further when describing two primary levels of learning: adaptive learning and knowledge development. Adaptive learning is seen as the first level’s learning where a new work method is introduced into an otherwise unchanged context. Knowledge development, the second learning level, takes place when cognitive aspects are introduced. The change receives a meaning, and the new work method gives new viewpoints to the task so that it is seen in a new context. Ekvall (1997) and Kirton (1989) argue this similarly, but with the focus on two creativity types emerging from an adaptive or innovating cognitive style. The findings of Argyris, Bion, Docherty, Kirton and Katzenbach and Smith demonstrate two states of reasoning and citings that lead to different kinds of output. This raises some questions: Is it possible to change A-groups, basic assumption-groups, adaptive learners and ‘committees’ into B-groups, rational working groups, knowledge development, innovating style and real work teams? Does this change of interaction and action lead to a more adequate output, i.e. an improved performance?

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This manuscript tries to address the above questions and builds on the notion that team creativity/innovativeness could be developed by following the concept of the change competence process, step by step as was refined by Kyle´n, (1993): 1. Make team-members aware of what kind of impact interaction patterns (IP) have on team performance. 2. Intervene so that IP changes from A-pattern to B-pattern which makes creative processes possible to trigger. 3. The triggered creativity makes it possible to go into adaptive innovation, meaning making improvements in the way of working that leads to a better performance. 4. When the change competence is stronger, frame-breaking changes (radical changes) in ways of working are likely to happen and, in the long run, a different reasoning around the team purpose, competence and performance will emerge.

Interaction pattern theory A number of researchers have emphasised the importance of changing mental conceptions by communication and dialogue to enable knowledge creation and learning on a higher level. If the frameworks cannot be broken because of too little openness, the needed accomodation which supplements assimilation cannot develop. Thus, thinking is preserved (Piaget, 1972). Argyris and Scho¨n’s (1974) labled this phenomenon as the ‘self-sealing process’. Argyris (1990) states that self-sealing thinking brings about action that, with time, becomes ‘standardized’ in the organization, which increasingly risks affecting interaction and learning in a negative way. ‘Interaction is the same as actions and reactions to actions that are woven together in a mutual impact’ (Aubert, 1979). Regularly occurring actions and reactions to those actions form an interaction pattern. The interaction pattern is, thus, built up by an over use of certain actions that are chosen (for different reasons) over others (Kyle´n, 1999), which forms the limits for the team’s capability to be creative and innovative. A foundation for interaction that allows greater possibilities for triggering team creativity and developing innovativeness on a qualitatively higher level needs, therefore, to be found in an interaction pattern and context that supports team creativity and innovation. To achieve innovativeness, there must be ideas. These ‘embryos’ emerge from individual team members and can be refined and developed by others through dialogue. The

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next step in the process occurs when the ideas become usable entering the innovation phase where communication leads to experiments. Thus, an important part of being able to interact, transforming creativity into innovation, is the ability to communicate. Galbraith (1972) sees communication as an important key to effective interaction. In a study of interaction in product development, Gupta, Ray and Wilemon (1985) found problems concerning communication barriers and an insensitivity to others’ abilities, desires and views. It is particularly serious when communication difficulties occur in development situations as these are often organized so that interaction (cooperation) is the coordinating factor. Coordination in modern organization is primarily to be achieved by mutual adjustment (Mintzberg 1983). Norrgren (1990) and Stymne (1988) argue that production groups, need both increase in technical competence and improved interpersonal and interactive skills for the new work organization in order to fully utilize the potential embedded in the advance of technological systems. A result of a certain IP can lead to coordination and communication difficulties, thereby also affecting the conditions for learning and knowledge creation. The more defensive an IP, the more difficulty in coordination, communication and cooperation, thus affecting openness and the flow of ideas. According to Argyris (1990), defensive interaction patterns (DIP) are defined as regularly used interactions that block learning creativity, innovation and change (Kyle´n, 1999). DIP are a consequence of an over-protection of ourselves and others. This protection has to do with handling threats and embarassing situations. We get caught in a defensive interaction pattern (Argyris, 1990) that decreases the possibilities for adding value to others’ ideas, new knowledge and meaning because of filtering out information. Few other researchers focused on defensive IP:S. Holter (1970), focused on defense resistence techniques and discussed mobilisations of techniques that inhibit awareness. Menzies (1970) showed how anxiety is handled and provided a description of how social defensive interaction is built into an organization as a protective and anxiety reducing approach. Frost and Egri (1991) described political processes in technological, social and scientific innovation. They use the approach that the actors have used to improve their position and increase their influence. This approach very often leads to other ideas out of which the best is chosen due to the defensive actors and interactions. Knowledge creation interaction

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patterns (KCIP) are defined as regularly used interactions that support learning and change (Kyle´n, 1993). While DIPs are based on private, closed thinking that creates obstacles, KCIP leads to externalised thinking. Reasoning is made public and conclusions are openly tested. KCIP does not mean that there will always be decisions about doing things differently. Great parts of work life require holding agreed upon standards that perhaps mean ‘things are done well enough rather than as well as possible’. It is also doubtful whether it is advisable to be open and straightforward in situations that involve survival in the face of organizational political games. The function of KCIP is to allow a climate and actions that enable both creativity and innovativeness when this is adequate and suitable by making adaptable improvements or creating new knowledge.

Interaction Patterns and Performance Interaction patterns affects the team performance and outcome through consequenses on the behavior. The defensive interaction pattern causes behavioral consequences that hinders team creativity through low openness and destructive feedback which leads to a non-innovative performance while the knowledge creation interaction pattern gives a behavior that enables team creativity through openness and construcvtive feedback. This gives higher quality on ideas and enables innovation. The question then becomes to find a method that enables as many teams as possible to change to, or develop a knowledge creation interaction pattern. How could this be achieved? Consequences on behaviour

Interaction pattern characterised by:

E

E

How to change the Interaction Pattern (IP)? According to Argyris, the following social skills support knowledge creation interaction patterns: 1. The ability to help others increases their capacity to confront their own ideas and to offer support in taking risks by exploring hidden assumptions about the surrounding world, to see people capable of self-reflection. 2. The ability to argue for one’s own ideas or position while combining this with active listening (inquiry), saying what one is actually afraid to say, arguing for principles, values and norms in a way that invites others to do the same. (Argyris, 1990, p. 19) The existence of these social skills leads to an ability of working with issues that otherwise often are undiscussable. This openness increases the correction of mismatches and errors (Argyris, 1982) through discussions about what functions well and what works poorly. A study, based on empirical observations (Kyle´n, 1993) of what helps KCIP, concluded that work teams showed ‘an interplay that proceeds from the task and is characterised by balance between individual freedom and the togetherness of the collective team’. This helps to increase the production of ideas and the capacity to refine ideas. Work teams need, in addition, to offer ‘social support’ to give individuals ‘thought support’. Another observation is that the team should have ‘standard behavior that supports trying out and testing ideas’. Attempts to blame others, to see oneself as a victim of circumstances should be stopped because the team has ‘rules of play that emphasise the individuals as actors’. Consequences on performance/results

Defensive IP (Interaction pattern A)

Insulting feedback High degree of errors/mistakes Few dialogues Work method not given Any consideration

Low interaction Few ideas Few refined ideas for methods/ products Low quality Few improvements ‘Normal or worst practice’ No radical changes

Knowledge creation IP (Interaction pattern B)

High interaction Constructive feedback Few errors/mistakes Many dialogues Well-considered work method

Many ideas Refined ideas for methods/products High quality Many improvements ‘Best practice’ and radical changes

Figure 1. Consequences of Interaction Patterns on Behaviour and Results

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Accepting the fact that the IP sets limits for a team’s capability to initiate creativity and innovation, one might ask how to generate motivation to put time and energy into changing the IP. First, the motivation for change of IP could rise through clarification of how IP affects team performance. This means that it is important that everyone understands why a change of IP is needed. The motivation should also be to improve what the team is intended to perform. Improving the IP alone, without putting it in its context, is most often not sufficient as a starting point. A change should first and foremost proceed from the work team’s purpose and mission – and then, preferably, in core activities/core processes. Schein (1991) and Beer et al. (1990), reason that the starting point for the development of work teams should be the target picture that justifies the existence of the team, the reason why the team was put together, the core activities in the mission, and the forms of the team’s relations with the world around it. Schein further writes that the focus should only be on interpersonal processes when it is obvious to the team that this is necessary for being better able to carry out its work. Adler and Docherty (1998) argue that such work teams’ tasks should preferably have a connection to the ‘business’ and a customer contact. Taken together, the above indicates that it is important that the IP is related to the desired performance/outcome rather than only to psychosocial goals. The above implies that work team development should take place alternately between developing an awareness of what the mission requires with respect to type of IP and how the psychosocial climate should be in order to make ‘good interaction’ possible. This development requires common skills in the form of concepts/language, view of information/task and desire to work with things that are not functioning well enough. Argyris (1985, pp. 266–270) describes how treating defenses can begin by finding the right starting point so that the participants do not become afraid but don’t think the questions are uninteresting. Argyris further describes a number of skills/competences with regard to intervention. These are given briefly here: 1. Identifying defensive routines by focusing on ‘hard data’, which, according to Argyris, is ‘relatively simple, directly observable data’ about which the parties can ‘agree upon a meaning’, which makes it simpler to allow conclusions to be made public knowledge.

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2. Reflecting upon one’s own reasoning or actions to minimise inconsistency between intentions and behavioral consequences. 3. Reflecting upon the thoughts in point 2 in order to change one’s way of reasoning and acting. 4. Constructing maps that show how patterns of reasoning and action create defensive routines on the individual, group, between-group and organizational levels. 5. Having the right timing in the choice of when to disclose defenses and when it is reasonable to learn. 6. Effectively handling one’s own and other’s feelings with empathy. 7. Contributing toward the creation of an environment and conditions in which others can use the skills named above. In summary, the environmental context that Argyris argues needs to be created can be assumed to be dependent on a balance between work teams’ purpose/mission and psychosocial climates. The defensive interaction pattern with its closedness and inability to discuss certain issues and the incongruity between words and action causes a lack of change competence. A work team’s performance of creativity and innovation would probably be made more difficult by this interaction (Kyle´n, 1993). The knowledge creation interaction pattern was characterised by an openness to new ideas and making improvements and changes in the interplay between members of the team with the purpose of both developing work methods and services. An awareness of the significance of the behavior for performance/results, a shared view, mutual adjustment and a feeling of participation seem to be dominant traits in a team that demonstrates this kind of interaction (Kyle´n, 1999).

Methodology The findings shown in this document is one study in a stream of research projects (Kyle´n, 1993, 1999; Shani et al., 2000) that focus on establishing creative interaction in work, management and project teams in order to enable innovation, learning and change through collective action. The goal of the project was to see if it was possible to measure and change interaction patterns and action routines and how this affected performance and output criteria. The aim in this study was to focus on creating an IP that builds change competence so that the work team chooses between holding itself to its ‘standard’ behavior or

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acting in a way other than the norm. The main thought has been to support an interaction and work forms that enable an evaluation of whether usual reasoning and practice should be used (being cautious and incremental = adaptive behavior) or whether another, more radical approach should be applied (taking calculated risks, through knowledge creation/ innovative change). The methodology used was anchored in a synthesis of action research and clinical field research orientations. The primary health care organization consisted of medical health care and odontological clinics working in teams with a median of nine members. The business context, during the study was complex and created increasing performance pressure on the teams. The organization viewed this study as a way to enable the teams and help them meet better the requirements for cost effectiveness, and shorter treatment leadtimes. This situation occurred as a result of a combination of governmental economic demands, restructuring of hospitals and an influx of refugees with health problems. This was seen as a situation that needed to collectively bring forward new actionable knowledge because of the improvement/ change dilemma. Thus, the context provided an opportunity to learn more about the importance of interaction patterns and its possible impact on creativity/innovation, and to develop and test an intervention method. As such, the interventions for change IP (from DIP to KCIP) were based on the following cornerstones (Kyle´n, 1999): 1. Start by reflecting upon the purpose/mission. What will the team be doing? What does the team do? What is the general feeling about performance? Are customers and employers satisfied? What would external parties and members of the team like to be different? 2. What kind of actions exist? Is there interaction that supports carrying out the task? What is the relationship between the work team’s work forms/processes and ‘best practice’? Formulate a collective diagnosis and some intial measures to be taken. Experiment with and train alternative ways of acting. Think about how performance could be changed if the action alternative tested was the one normally used. 3. Think about why actions are the way they are. How did they start? Do they have any extra value for the team and members of the team? What should be kept, made stronger or be reduced in the interaction pattern? Experiment and train. Interrupt

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ordinary activities and make ‘learning mirrors’ for what was done and consider whether it can be done in another way. 4. Think about what values and basic assumptions lie behind the team’s interaction. What are the controlling thought models in the team? How does the team make conclusions and how does this affect work performance? The IP change efforts were worked through by six steps and carried out as the following brief description shows: 1. Identification using a questionnaire All members of the work team filled in a questionnaire that was considered to be the work team’s own questionnaire in that researchers were the only external people who had access to it. Great importance was put on being able to guarantee confidentiality. The questionnaire information was compiled in the form of a simple mean value profile. 2. Feedback The teams were given a half day of information that had been collected about the workplace. Time was devoted to understanding the meaning of the results and to giving thought to whether the description agreed with each of the team member’s own experience. The work could be ended after this if the team so decided. 3. Common judgement and suggestions for measures The work teams developed a collective view of how the work functioned, what could be improved and how this might take place. A plan for carrying out some kind of improvement was made on the basis of a defined and familiar improvement area (e.g. lack of openness at meetings, competence inventory, change in reception routines, how to deal with the greater flow, forms of treatment of new patients). 4. Performance I One day was devoted to development in the work team according to the agreement above. 5. Performance II This was a continuation of development efforts, carrying out exercises etc., that took place to different degrees on the basis of motivation and need. 6. Evaluation of the effort An evaluation was made of the process from the time of distributing the questionnaire up to and including the final efforts. Had the effort given any concrete results? Should the effort be continued? If so, how, and with what?

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How to measure changes in IP, improvements and radical changes The measurements started with studying the effect of the interventions with respect to changes in interaction patterns and whether performance had been affected. An instrument with 25 items (Kyle´n, 1999) was used to measure and map out the interaction patterns. The change in the interaction pattern was examined via comparisons between the preand post-measurement values of the IP and analyzed by using t-test and the Wilcoxon test (Siegel, 1956). Changes in performance were studied by analysing productivity, quality and delivery assurance with the expected value (3 – no change) and the key person’s estimation (1–5) of these performance criteria using the Wilcoxon test. Key individuals were asked to assess the change in terms of team produc-

tivity, quality and delivery assurance. The key individuals answered the question of whether they considered the improvement effort to have resulted in 1 – confirmed deterioration, 2 – probable deterioration, 3 – no change, 4 – probable improvement or 5 – confirmed improvement of the above performance criteria.

Results Fourteen teams participated in the initiating pre-measurement procedure. The teams then decided whether they wished to receive help or whether they could manage themselves. Eleven teams wanted development support but one were not allowed to do so which meant that ten teams became ‘fully treated’. The table below reports KCIP and DIP from the pre- and post-measurements, the differ-

Table 1a. Changes in Interaction Patterns and Performance Criteria in Health Care Teams Team

Measurement

Action routines

KCIP/DIP-

Difference

KCIP

DIP

Difference

In change Pre-/Post

6.8 6.8

4.2 4.0

2.6 2.8

Pre-measure Post-measure

6.3 6.9

3.8 3.8

Pre-measure Post-measure

6.2 6.1

Pre-measure Post-measure

Occasion

Productivity

Quality

Delivery assurance

+0.2

4

3

3

2.5 3.1

+0.6

4

3

3

3.9 3.5

2.3 2.6

+0.3

5

4

.

6.4 6.3

4.2 3.9

2.2 2.4

+0.2

5

3

5

Pre-measure Post-measure

5.6 7.2

3.6 1.7

2.0 5.5

+3.5**

4

4

4

Pre-measure Post-measure

6.3 6.3

4.5 3.4

1.8 2.9

+1.1*

3

4

4

Pre-measure Post-measure

5.8 5.8

4.1 4.7

1.7 1.1

– 0.6*

4

4

4

Pre-measure Post-measure

5.7 5.8

4.3 4.4

1.4 1.4

+/– 0

4

5

4

Pre-measure Post-measure

5.8 6.2

4.8 4.0

1.0 2.2

+1.2**

3

3

3

Pre-measure Post-measure

5.3 5.9

5.0 4.8

0.3 1.1

+0.8*

4

5

4

Treated teams E1 Pre-measure Post-measure E2 E3 E4 E5 E6 E7 E8 E9 E10

Key person’s estimation of change:

** = significant on the 1% - level, * = significant on the 5% - level. Key person’s estimation of change in performance criteria: 5 – confirmed improvement, 4 – probable improvement, 3 – no change, 2 – probable deterioration, 1 – confirmed deterioration.

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ence between the measurements and key persons’ estimations of the effect of interventions on the performance criteria of productivity, quality and delivery assurance. The team that were not allowed to have treatment, (E14) was considered by management to be in less need of help. Development resources were scarce and it was felt that several other teams needed greater attention, with the result that this team did not continue. Of the other three teams that did not wish to receive development support, two (E11, E12) felt that they could manage by themselves. The other team felt it did not need to make changes in its activities (E13). The table below reports KCIP and DIP from the preand post-measurements of the ‘non-treated group’ of teams but differences between the measurements and key persons’ estimations of the effect of interventions on the performance criteria of productivity, quality and delivery assurance cannot be shown because of the lack of contact with these teams. The results will be divided into the overall level and the work team level, focusing on changes in IP, adaptive team creativity leading to improvements and thereby change of performance, radical team innovation leading to frame breaking changes.

Changes in IP on the overall level It can be noted that five of 14 teams showed poorer post-measurement values than premeasurement values. Four of these teams were among the non-treated team group. A total of seven of the 14 participating teams showed a significant change in the postmeasurement, four in a positive direction

and three in a negative direction. One team’s development was negative in the group of teams that received treatment. The other two, with a confirmed deterioration in performance criteria, were among the non-treated group. No non-treated team showed a confirmed positive change. Taken together, the significance tests among the treated teams on the overall level showed a statistically confirmed positive change (on the 5% level). Seen on the organizational level, it can thus be said that the interventions achieved an improvement in interaction patterns.

Adaptive team creativity leading to improvements and performance changes on the overall level If the assumption is made that an intervention of this type should lead to positive changes in performance, or that the intervention in a critical situation should reduce a negative development of performance because of improvements upstarted by team creativity, the key persons should report no improvement (3), probable improvement (4) or confirmed improvement (5) to a higher extent than probable deterioration (2) or confirmed deterioration (1). As no key person reported a poorer situation but many an improved one, it can be considered that a confirmed positive affect occured in performance development (on the 1% level) for productivity, quality and delivery assurance. An example of a positive change in the overall interaction pattern was the dramatic increase in the number of suggestions for improvements (report of the health care organizations

Table 1b. Changes in interaction patterns and performance criteria in health care teams Team

Measurement

Action-

Routines

KCIP/DIP-

Difference

KCIP

DIP

Difference

In change Pre-/Post

E11

Pre-measure Post-measure

6.3 5.4

4.2 4.9

2.1 0.5

– 1.6*

E12

Pre-measure Post-measure

5.9 5.5

4.1 5.0

1.8 0.5

– 1.3**

Pre-measure Post-measure

6.3 6.0

3.6 3.7

2.7 2.3

– 0.4

Pre-measure Post-measure

8.2 7.6

2.3 2.2

5.9 5.4

– 0.5

E13 E14

** = significant on the 1% - level, * = significant on the 5% - level.

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council on suggestions for quality and effectiveness development) that were submitted during the year in which the project was carried out. 60 ideas and suggestions for improvements were submitted, which can be compared with 14 during the year before and three during the year before that. The latest year’s results meant that the area of primary health care reached a top position in that region of the country. The possibility of changing and improving work methods and interaction patterns in the work teams led to the complete disappearance of complaints concerning the psychosocial work environment. From having had approximately ten per year, no complaints were lodged. However, it should be pointed out that this may have a bias of the ongoing change in structure and the fear that this generated.

Radical innovations leading to frame breaking changes on the overall level Two work teams wanted to change their management structure and go into a collective leadership, taking turns on being the one in charge. This was highly frustrating to the health care director and the management team. It was finally allowed since it was seen as a consequence of the decentralization and very open change strategy, and that it was important to show that the teams were in charge of the change process. Another radical innovation was when one team put a nurse as their leader instead of the obligatory physician, which previously were an undiscussable topic. A very important work organization experiment was to organize fast tracks during certain hours a day when everybody could visit the health care center. This forced the change and mutual adjustment of roles in a very radical way. Some small teams decided quite rapidly to leave the policy of fast tracks because of the situation in licenses and personnel, which also was an interesting deviation because of the strong norm of conformity. Instead, these teams tried out different ways of delegating tasks and made competence as important as the license of physicians and dentists. This became a tough question to deal with in many of the teams. The odontological work teams, as well as the physiotherapist teams, were often very successful in doing this difficult change in a non-hazardous way. The odontological work teams also developed a holistic view of competence development. They helped each other (between teams) out of difficult situations, making this a frame breaking change.

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Partial Overall Summary The change of IP and team performance criteria developed in a positive direction in the organization, which is supported by reports on intensified improvement efforts, despite ongoing rationalisations and changes in requirements/work tasks on the organizational level. The development of the teams, with a confirmed improvement on the overall level, seems to point out that a more adequate IP supports team creativity, which gives incremental improvements. The frame breaking radical changes stress even more that the way of building change competence is by triggering the teams’ innovative creativity as well.

Positive changes in IP on the team level The E5, E6, E9 and E10 teams showed great improvements in interaction pattern (significant changes on the 5% level). The positive change took place in different ways. E5 increased its KCIP considerably and decreased the defensive one in a clear way; performance criteria were reported to have probably improved (4.4.4). The smallest workplace investigated received greater autonomy than earlier as a result of the move of a manager during the time of the project. The team had come a long way in its delegation work, which created more balanced work forms than had previously been the case. For this reason, there was great motivation to deal with the collective work task. This team worked primarily with dental care for school children, and used the project chiefly for developing a sense of belonging in the team and their relations with the surrounding environment (the school and parents). E6 did not show a change in its KCIP, although a decrease in its DIP was noted, and they reported that two of their performance criteria were probably improved and that one was unchanged (3.4.4). There were a number of problems in the team that had to do with difficulties in the members’ private lives and poor relations at work. Efforts were made on the individual level to solve private problems, and meeting times/forms at work were changed. Administrative questions were made clearer and continuous improvement activities were held. E9 increased its KCIP and decreased its DIP. No change was reported in the performance criteria (3.3.3). The workplace suffered from conflicts between the manager and one of the employees. This was treated in the project as the team felt that it was most important to change this part of the situation. There were also general conflicts concerning

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how work should be done and what methods should be used. Discussion around central questions were avoided and passive resistance was used against new ideas and directives. A great deal of time was devoted to forming a shared view and significant changes were made in reception activities. The work method was markedly changed during the year. No improvements in performance were reported, possibly because there was a conflict between the researcher and team manager. The manager felt that the researcher one-sidedly supported the work team in a particular conflict. E10 increased its KCIP and decreased its DIP somewhat. Performance was confirmed to be improved in one case and probably improved in two cases (4.5.4). The work team was in crisis. Many of the employees did not feel well; they felt that neither performance at work in the team nor work on the administrative level was satisfactory. There was a risk that the team would be phased out. The situation had long been problematic and the inability to solve the problems was reflected in the DIP. At the time that the project started, an experienced manager was given the task of trying to save the team. Improvements were made in the order of administrative tasks and different efforts were made to raise work performance and improve the climate. The dramatic improvement in the work and climate of the workplace ensured the survival of the team for the time being.

Teams showing no change in IP E1, E2, E3, E4 and E8 showed little or no improvement in KCIP or DIP. E1, E2, E3 and E4 exhibited good values in the pre-measurement and concentrated more on improvements in work forms than treating interaction patterns and climate. The situation did not address important, unsolved problems, and the teams functioned well. This led to low motivation in treating the interaction patterns. Work focused more on improvement activities in other directions. These teams report five cases of no change, three cases of probable improvement and three cases of confirmed improvement in the performance criteria. The positive pre-measurement values indicate that these were teams with a good capacity for change. Very important development work was also done in E2. The team increased its KCIP somewhat (not a statistically significant change), had an unchanged level in DIP and reported no change in performance in two cases and a probable improvement in one case. The smaller care center in the rural area had tested other work forms than had the larger centers in the city.

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The team had solved problems in their reception routines and the family doctor work form in a different way. It chose to focus its change efforts on communication and quality issues, and worked with ‘continuous improvement tools’. In the final phase of the project, it was found they that had made many improvements that changed the work situation in a positive direction. It was also felt that the flow of patients had increased. E8 had a different starting point with lower KCIP and higher DIP. The team had permanent, long-term problems in relations between employees. This made it difficult to start any change efforts. It was, in general, a workplace with rigid positions. Consequently, many old conflicts and ill-tempered individuals had to be addressed. The general picture of the interaction pattern was that the personal conflicts experienced did not have to do with the work team. The desire was to treat these individually outside the workplace. This was done, and the result was that the work team’s IP remained unchanged. The key person reported two cases of probable improvement and one case of confirmed improvement in the performance criteria (4.5.4). The researcher who had worked with the team questioned this – in his opinion – too positive a picture of the development work in the team.

Teams with negatively changed IP E7 was a large dental clinic that had started development work earlier. Their manager actively promoted the work, although he had been temporarily moved to work on other tasks during the time of this project. The substitute manager continued improvement efforts in a way that frightened many of the employees, with the result that the rooms (pairs of dentist and nurse, sometimes hygienist) closed themselves off from the rest of the team. Development work was done that was not submitted for consideration in the whole work team. The work team chose to wait for the return of their usual manager to start dealing with their cooperation issues, which caused irritation among those employees who were most enthusiastic about the changes and wanted to start work on interactive issues. There was an improvement in performance (probable improvement, 4.4.4) but several important ‘hot’ questions were left untreated and the DIP grew.

Discussion The study was conducted as an exploratory investigation in order to gain insights into the

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possible relationships between interaction patterns and team creativity. The study focused on productivity, quality and delivery assurance improvements. As such, many issues could be addressed, far beyond the space limitation of our paper. Thus, we have chosen to focus the discussion on the following issues: Team dialogue as a trigger for team creativity, team interaction patterns and team performance, and team-interactionbased intervention, team creativity and adaptive/radical innovation.

Team dialogue as a trigger for team creativity The survey instrument and the team dialogue centred on the task of developing a shared mapping of team interactions, which served as triggers for both creative ideas and team performance. Yet, due to the nature of the study, and since it was carried out as an exploratory field study, the conclusions that can be drawn are limited. The study seems to indicate that a more systematic and comprehensive research project into the phenomenon of team creativity is needed. The possible relationships between team inquiry into their interaction patterns and the dialogue around the development of shared team mapping has the potential of triggering and enhancing team creativity. Triggering ongoing team creativity requires the exploration of alternative mechanisms. Furthermore, a systematic inquiry into the types and kind of intervention processes is needed. This is likely to result in certain IPs that have the potential to trigger the development of the right behaviors needed for the team ability to accomplish its purpose and mission.

Team interaction patterns and team performance The study shows an intervention that led to statistically confirmed positive changes in the teams’ interaction patterns and performance on an overall level. In spite of the worry and fear created by ongoing restructuring of the health care organization, it was possible to achieve a development of activities using the

intervention method tested here. Of the ten teams treated, three show both a statistically confirmed positive change in the interaction pattern and improvements in performance criteria. One team exhibited a statistically confirmed improvement in their interaction pattern, but no change in performance criteria. Four teams reported a confirmed improvement and five teams a probable improvement in performance. Of all the teams treated, one showed a confirmed deterioration of the interaction pattern. None of the teams that were not treated showed a confirmed improvement, two of the non-treated teams had a negative IP development and the other two showed no significant change. The fact that there was not a stronger change of IP could be explained by two different reasons. 1) The total situation was so harsh that many would have become more defensive and less creative without the team training efforts. This would have affected the improvement efforts in a negative way. 2) The relatively low positive changes in IP could be due to the fact that many of the teams had reasonably high Knowledge Creation IP and low Defensive IP from the start, which makes it harder to improve. This could also lead to a higher motivation of focusing on improvements and more radical changes. The evaluation of IP changes and team performance is important in this exploratory investigation and the Health care teams are, therefore, compared to a database of KCIP and DIP measurements. This database consists of 113 work teams, project teams and management teams from industry and the public sector. The data is collected in environments working with R&D, production, administration, education and health care. The comparison shows that 11 of 14 HC teams were higher (better) in KCIP, ten were lower (better) on DIP and 11 had higher (better) KCIP/DIP-difference than the mean of the 113 ‘normal practice teams’. This could be said to have what Argyris (1969) described as a common non-creative interaction pattern A (IP A). Table 2 shows that the teams already had a more creative interaction pattern (Argyris

Table 2. A Comparison Between the Health Care Teams and ‘Normal’ IP A Teams Mean Values

Defensive IP Knowledge Creation IP IP-difference

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113 IP A teams

Difference

4.0 6.2 2.2

4.3 5.7 1.4

0.3 0.5 0.8

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IP B), which explains that the ability to improve and change IP was difficult due to the pre-existing situation. On the other hand, there were fewer reports of teams that succeeded to be more radically innovative, doing frame-breaking changes. This could mean that the findings show an existence of an Interaction Pattern ‘b’ and Interaction Pattern ‘B’, which could be of relevance when developing teams through IP interventions. We suggest a further investigation to find out if there are three (or more) distinctive IPs and not two as argued by Argyris (1969), Bion (1968), Katzenbach and Smith (1993). One IP is the defensive IP (IP A, DIP) which, through selfsealing processes and closeness, inhibits knowledge creation and learning. Another IP is the adaptive learning IP (IP b, kcip) that triggers team creativity so that adaptive innovation can take place. (learning processes lead to improvements and incremental changes, Docherty, 1996). This is the level where many teams in this study starts, some are taken to and most of them end up in. The third IP (IP B, KCIP) is when team creativity allows radical ideas to be ‘worked through’ so that new meaning can be added that gives new ways of using knowledge or supports new knowledge combinations (knowledge development) or helps new knowledge to be created (knowledge creation). It is interesting to wonder what it would take to bring as many teams as possible to the third IP-level. Is it just an extrapolarisation (Swedish is extrapolering) of the higher openness, idea flow, task/mission orientation, calculated risk taking and experimentation, or is some kind of ‘wisdom’ added into the team interaction pattern that is waiting to be described and increased?

Team-interaction-based intervention and the motivation to be creative To summarize, it can be stated that the intervention achieved a positive change, although this led to more widespread improvements in productivity, quality and delivery assurance than with interaction patterns and radical changes. An important factor in this is the motivation to change. Some of the teams were less comfortable in dealing with interaction in the work team than others . Some teams did not understand that changing was that important. Certain teams also had such a well functioning interplay that it was felt more important to make improvements and, therefore, did not focus on IP changes. All ten teams who took part in the interventions, however, realised

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that higher performance was necessary, while still maintaining good quality. This may also have strongly motivated and influenced the results of more improvements than IP changes and also less radical innovation. Rating interaction patterns requires an awareness of the signficance of interaction that is difficult to find if there is no experience of workplace development. Planned developments in activities had not been done earlier in more than a few of the teams in question here (apart from medical/odontological quality efforts). There must also be a desire and motivation to improve and develop. It was difficult for many to deal with the interaction pattern perspective because what they had was adequate for their current work conditions. The increasing amount of work that had to be done is a pattern that is likely to continue. Employees felt that they could remain comfortable for the short term. For interaction patterns to be developed in a positive manner in work teams, in a more confirmed way than was shown in this study, would require a broader effort to treat motivation and awareness before other work toward change is begun.

Conclusion Although there are many proponents of team work and many who believe in the merit of team creativity, triggering, developing and maintaining team creativity is a major challenge. Some research reported in the literature, using well-controlled studies comparing interactive and noninteractive modes of idea generations, has found that interaction usually inhibits idea generation (Paulus, Brown & Ortega, 1995). Some research on teams supports the efficacy of collaborative knowledge sharing. Yet, a clear demonstration on the possible causal relationships between different types of team interactions and their possible effect on team creativity requires further inquiry. This study reported on an action researchbased effort to learn more about the process. Anchored in Argyris theory of interaction patterns and defensive routines, we have refined a dynamic intervention process that was implemented, using an experimental design in a health care organization. A total of seven of the fourteen participating teams showed a significant change in the postmeasures. Taken together, the treated teams showed an overall positive change. At the organizational level, the intervention achieved significant improvement in interaction patterns.

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Team creativity depends on creative individuals, processes, situations, the culture, interaction patterns and the interplay between them. Thus, team creativity is a complex process with diverse outcomes. This study focused only on one element – the interaction patterns. While we have gained some new knowledge, this study documented the much needed scientific investigations in and around the complex phenomenon of team creativity.

Acknowledgements We would like to thank Helene Eriksson, Joseph Schaller, Flemming Norrgren and Elaine Shani for supporting the authors during the research and publication process.

References Amabile, T.M. (1983) The Social psychology of creativity: A componential coceptualization, Journal of Personality and Social Psychology, 45, 357–376. Argyris, C. (1969) The incompleteness of socialpsychological theory: Examples from small team, cognitive consistency, and attribution theory. American Psychologist, 24, 10 oktober. Argyris, C. and Scho¨n, D. (1974) Theory in Practice Increasing Professional Effectiveness. Jossey-Bass Publishers, San Francisco, California. Argyris, C. and Scho¨n, D. (1978) Organizational Learning: A theory of Action Perspective. Adison, Reading, Mass. Argyris, C. (1982) Reasoning, learning, and actionindividual and organizational. Jossey-Bass Publishers, San Francisco, California. Argyris, C., Putnam, R. and McLain Smith, D. (1985) Action Science. Jossey-Bass Publishers, San Francisco, Cal. Argyris, C. (1990) Overcoming Organizational Defenses. Allyn and Bacon, Cambridge, Mass. Aubert, W. (1979) Sociologi: Socialt samspel. AWE/ Gebers, Stockholm. Beer, M., Eisenstat, R.A. and Spector, B. (1990) The Critical Path To Corporate Renewal. Harvard Business School Press, Boston, Mass. Bion, W.R. (1968) Experiences in teams. Tavistock Publications, London, England. Docherty, P. (1996) La¨roriket, va¨gar och va¨gval i en la¨rande organisation. Arbetslivsinstitutet, Solna. Ekvall, G. (1996) Organizational Climate for Creativity and Creation. European Journal of Work and Organizational Psychology, 5, 1, 105–123. Ekvall, G. (1997) Organizational Conditions and Levels of Creativity. Creativity and Innovation Management, 5, 4, 195–205. Frost, P.J. and Egri, C.P. (1991) The Political process of creation. Research in Organizational Behavior, 13, 229–295. Guilford, J.P. (1967) The Nature of Human Intelligence. Mcgraw-Hill, New York.

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Gupta, A.K., Ray, S.P. and Wilemon, D. (1985) The R&D-Marketing Interface in High-Technology Firms. Journal of Product Creation Management, 2, 12–24. Hackman, J.R. (ed.) (1990) Teams That Work. Jossey Bass, San Francisco. Holter, H. (1970) Motsta˚nds- och fo¨rsvarstekniker i sociala organisationer. I Tidskrift for samfunnsforskning, Oslo. Kao, J.J. (1991) Managing Creativity. Prentice-Hall, Englewood-Cliffs, NJ. Katzenbach, JR. and Smith, D.K. (1993) The Wisdom of Teams – Creating the high-performance organization. Harvard Business School Press, Boston. Kirton, M.J. (1989) Adaptors and Innovators: Styles of creativity and problem-solving. Routledge, London. Kyle´n, S. (1993) Arbetsgrupper med fo¨ra¨ndrings- och utvecklingsuppdrag. Fra˚n defensiva till offensiva rutiner!. Psykologiska institutionen, Go¨teborgs universitet, Arbetsvetenskapliga Kollegiet, IMIT, Go¨teborg. Kyle´n, S. (1999) Interaktionsmo¨nster i arbetsgrupper, offensiva och defensiva handlingsrutiner. Psykologiska institutionen, Go¨teborgs universitet, FENIX forskningsprogram, IMIT, Go¨teborg. Leonard, D. and Sensiper, S. (1998) The role of tacit knowledge in group innovation. California Management Review, 40, 3. Menzies, I. (1970) The functioning of social systems as a defense against anxiety. Tavistock Institute, London, England. Mintzberg, H. (1983) Structure in Fives. PrenticeHall, Englewood Cliffs, NJ. Mohrman Albers, S. and Cohen, S.G. and Mohrman, Jr., A.M. (1995) Designing Team-Based Organizations. Jossey-Bass Publishers, San Francisco. Norrgren, F. (1990). Designing and implementing the software factory – a case study from telecommunications. R&D Management, 20, 3, 263–273. Oldham, G.R. and Cummings, A. (1996) Employee Creativity: Personal and contextual factors at work. Psychological Bulletin, 103, 27–43. Olin, T. and Wickenberg, J. (2001) Rule Breaking in New Product Development – Crime or necessity? Creativity and Innovation Management, 10, 1, 15–25. Paulus, P.B., Brown, V. and Ortega, A.H. (1996) Group Creativity. In Purser, R.E. and Montuori, A. (eds.), Social Creativity. Hampton Press, Greskill, NJ. Piaget, J. (1972) The Principles of Genetic Epistemology. Routledge & Kegan Paul, London. Purser, R.E. and Montuori, A. (1996) Social Creativity. Hampton Press, Greskill, NJ. Rogers, C.R. (1959) Towards a Theory of Creativity. In Andersson, H.H. (ed.), Creativity and its Cultivation. Harper & Row, New York, pp. 69–82. Schein, E.H. (1991) Organizational Culture and Leadership. Jossey-Bass, San Francisco, California. Scott, S.G. and Bruce, R..A. (1994) Determinants of innovative behavior: A path model of individual innovation in the workplace. Academy of Management Journal, 37, 580–607. Senge, P.M. (1990) The Fifth Discipline. DoubleDay/ Currency, New York, NY.

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Shani, A.B. and Lau, J.B. (2000) Behavior in Organizations an experential approach. Irwin McGraw-Hill, Boston. Shani, A.B. (Rami), Sena, J. and Stebbins, M. (2000) Knowledge work teams and groupware technology: Learning from Seagate’s experience. Journal of Knowledge Management, 4, 2, 111–124. Siegel, S. (1956) Nonparametric statistics for the behavioral sciences. McGraw-Hill, New York. Sosik, J.J. and Aviolio, B.J. (1998) Inspiring Group Creativity. Small Group Research, 29, 1, 3–32. Stymne, B. (1988) Demands on the training of managers in situations of profound technological change: The case of ‘TELI’. EFI paper 6385. Stockholm. Unsworth, K. (2001) Unpacking Creativity. Academy of Management Review, 26, 2, 289–297. Woodman, R.W., Sawyer, J.E. and Griffin, R.W. (1993) Towards a theory of organizational

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creativity. Academy of Management Review, 18, 2, 293–321.

Sven F. Kyle´n is a lic. psychologist and PhD in psychology at Gothenburg University. He works as Research Director at the FENIX Research Program at Chalmers University of Technology and National Institute of Working Life, region west, Sweden. A.B. (Rami) Shani is a professor of organization behavior and change at California Polytechnic State University, San Luis Obispo, California USA and a visiting research professor at the FENIX research program, Stockholm School of Economics, Stockholm Sweden.

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Creativity in Multidisciplinary New Product Development Teams Geert Vissers and Ben Dankbaar New product development is usually teamwork. Product development teams are created that are cross-functional, representing different functional units, or multidisciplinary, involving several disciplines, or both. In any case, conceiving and developing new products is a joint effort, which means that the traditional view of creativity may not apply. This view, characterized by a focus on individuals as agents of creativity and by the assumption that creativity is a unilateral quality, not a reciprocal or interactive phenomenon, continues to be influential. As a result, much of the dynamics of ‘newness-generation’ and ‘newness-reception’ in organizations remains to be studied. This paper describes the organization of new product development in a number of medium-sized companies. It will discuss the theoretical issues of newness generation in multidisciplinary new product development teams and newness reception in the larger organization, and present the results of a series of exploratory interviews.

Introduction

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reativity and innovation are related, yet the nature of this relationship is intricate. Innovation refers to organizational processes while creativity is traditionally viewed to be a personal attribute. This traditional view implies that an organization has to rely on highly creative individuals for product and process renewal. According to this view, creativity can be fostered only indirectly, by taking care of a creative individual’s working conditions. Over the years, approaches have developed that seek to stimulate group creativity more directly. These approaches, however, seem to preserve two important elements of the traditional view of creativity. One is the tenet that, at the end of the day, creativity resides in individuals’ heads. The second is the assumption that a more or less objective distinction can be made between creative and less creative ideas or products. The latter element leads to the view that the identification of creative ideas by the organization is unproblematic. As a result, organizational assessment of creative ideas or products tends to be ignored, and little is known about the dynamics of ‘newnessreception’ in organizations. These issues of group creativity and organizational reception will be addressed in this paper. It is argued that both relate to the way new product

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development (NPD) processes are organized, which includes internal characteristics of the product development team and the team’s position in the larger organization. Special attention will be given to multidisciplinarity as an aspect of team composition that, although likely to influence NPD processes, is largely ignored in innovation studies. Section 1 gives an overview of the literature on the role of new product development teams in product innovation. Section 2 discusses the issue of group or team creativity. Section 3 examines aspects of group composition in relation to creativity. It is concluded that both group creativity and multidisciplinarity are phenomena that need further reflection before measurement attempts are undertaken. Section 4 will give an account of interviews with leaders of the product development team or department in a number of medium-sized companies, conducted to gain an idea of the variety of ‘models’ in use to organize innovation, the ambitions and criteria underlying these models, and the composition and performance of new product development teams.

The organization of innovation In the literature on NPD, the product development team features as one of the central # Blackwell Publishers Ltd 2002. 108 Cowley Road, Oxford OX4 1JF and 350 Main St, Malden, MA 02148, USA.

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actors. However, the term ‘product development team’ needs clarification. It may denote a company’s R&D or product development department (or a part of such a department), or may refer to a cross-functional team. In this paper, considering the size of the companies to be discussed, we will not make a distinction between R&D department and NPD department. We will speak of ‘R&D team’ to indicate such a department, or a part of it. While not too much is known about the composition and the functioning of R&D teams, a wealth of studies is available to address cross-functional NPD teams (McDonough, 2000). Such teams, ‘project groups with members from more than one functional area such as engineering, manufacturing, or marketing’ (Brown & Eisenhardt, 1995, p. 347), are created to enhance interfunctional integration, which is supposed to improve new product development. They support external communication, making the NPD process more responsive, increase the amount and variety of information available to those involved in the design process, and help to prevent downstream problems (Brown & Eisenhardt, 1995; Jassawalla & Sashittal, 1998). Cross-functional are temporary, usually, and they represent various departments (which will imply that diverse sources of information are present as well as diverse interests). Cross-functional NPD teams have to be distinguished from R&D teams which, in contrast, consist of members of one department (research) only, and usually do not have a pre-defined life-time as they are not linked to a specific innovation, but to a line of research. Often, membership of a crossfunctional team is not a full-time assignment, and the team is created for the purpose of defining, planning, and monitoring some development project, whereas an R&D team consists of full-time members who work together in the same problem area for several years. In the NPD literature of the last decade or so, cross-functional teams have received much more attention than R&D teams. However, exploring the functioning of R&D teams is perhaps more relevant if the relationship between creativity and innovation is to be examined. The members of a cross-functional team may act primarily as representatives of their functional units, and they may confine themselves to listing ideas to be incorporated in a new product concept, and criteria to be met. These ideas and criteria are not always compatible, a problem that may be recognized by the cross-functional team already (Lovelace et al., 2001) but that often will not become manifest until ideas, criteria, and specifications are to be translated into a single

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product. This is more likely to be the case in the R&D team. In addition, the fact that R&D teams usually have a longer life-span than crossfunctional teams makes them highly interesting from the perspective of creativity. ‘Group tenure’ (or ‘group longevity’) has been associated with team identification (Scott, 1997), coherence (Moore, 1997), tacit knowledge (Mascitelli, 2000), and organizational memory (Moorman & Miner, 1997), all issues that are thought to influence the capacity to generate new ideas. Group tenure also relates to the dilemma that ‘(A)ny innovator needs to balance the development of competencies (i.e. the development of a sufficient absorptive capability) with the imperative to achieve the results expected from the projects and programs in the portfolio’ (Debackere, 1999, p. 19). Here, the term absorptive capability or capacity (Cohen & Levinthal, 1990) denotes the ability to perceive and incorporate ideas or products generated elsewhere. Only if group tenure is sufficiently long do the advantages of competence development outweigh the costs thereof in terms of time not directly spent on the completion of projects. In the earlier literature on innovation, cross-functional teams played a much less prominent role. Most of the attention went to the role of the research laboratory or the engineering department. There are two strands in this literature that may be important for our line of argument: the discussion about the role of technology push vs. market pull (Chidamber & Kon, 1994), and the discussion about organic structures being more appropriate organizational structures for innovation than mechanistic structures (Burns & Stalker, 1960). Burns and Stalker argued that an innovation process in its early stages requires an organic structure (they used the word ‘organistic’), characterized by fluid job descriptions, loose organization charts, high communication, few rules – in short autonomy. There is a parallel, of course, between the argument that organic structure fosters innovation and the argument that group autonomy fosters group creativity. In the recent NPD literature there is a tendency to reject organic structures in favor of a more formalized organization. NPD is a broad designation that may encompass activities ranging from first attempts to conceive a new product concept to prototype testing and implementation. The process is often described in terms of a stage model, that is ‘a series of stages in sequences with clear delimiters’ (Tang, 1998, p. 299). The stage model has flaws, yet it is widely used. It helps to make the innovation process transparent

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and manageable, a quality in agreement with the position that ‘ad hoc organizations or loose, organic structures often recommended for innovation simply will not do, for the long run. Even if ad hoc arrangements might once have worked, their repeated success would be impossible, given the complexity of relations, technologies, and product changes’ (Schoonhoven & Jelinek, 1990, p. 98). Distinguishing between mechanistic and organic structure is not just theoretically relevant. Adding structure to the NPD process through detailed plans will allow development tasks to be broken down into increasingly specialized subtasks. If that happens, collaboration is reduced to ‘putting the pieces together’ after all subtasks are completed. Moreover, plans can be made to meet production- and marketing-derived targets, which may limit an R&D team’s ability to conceive and develop new products that are primarily technologically inspired. These remarks are not made to support either a mechanistic or an organic structure. Rather, they demonstrate that profoundly different models for organizing innovation are conceivable – which is significant since different models may support different degrees of product newness: highly formalized innovation processes are believed to suit incremental, not radical innovation (Khurana & Rosenthal, 1998; O’Connor, 1998). It is also significant in relation to creativity (Woodman et al., 1993, p. 302): under an organic structure, more than under a mechanistic structure, the R&D team is likely to be the principal source of new ideas, concepts, and products.

Creativity Discussions of stages and models should not divert attention from actual innovation processes of ‘generating new and useful ideas or products’, a phrase that connects innovation to creativity (Amabile, 1983; Oldham & Cummings, 1996). Including ‘newness’ and ‘usefulness’ in a definition of creativity, however, means the introduction of terms that are difficult to define. In creativity research, the question of ‘newness’ has given rise to two opposed views or perspectives, a personal and a social view of creativity (Mayer, 1999, p. 450). The personal view means that the creating person must perceive newness and usefulness. In the social view, not the creator but the social or cultural environment defines the conditions for newness and therefore creativity. Both views were already present in the early 1950s, when Thurstone supported the personal and Stein

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the social view (Torrance, 1988). Recently, the social view has been defended by Csikszentmihalyi (1999, p. 314): ‘Originality, freshness of perceptions, divergent-thinking ability are all well and good in their own right, as desirable personal traits. But without some form of public recognition they do not constitute creativity. In fact, one might argue that such traits are not even necessary for creative accomplishment.’ This position directs attention to the question of product or idea reception, more specifically the question who will have to accept a proposed idea or product. Johannessen et al. (2001) suggest the concept of ‘relevant unit of adoption’ to answer this question, relying on Kotabe and Swan’s (1995) distinction between ‘newness to the company’ and ‘newness to the market’. This distinction resembles Boden’s (1991) distinction between P-creativity (‘new to the person’) and H-creativity (‘new to the world’). Together, these two distinctions suggest a broad array of ‘relevant units of adoption’, including an individual engineer, R&D team, organization, industry, etc. It can be gathered that ‘newness’ is a relational quality, that depends on the choice of a reference system (or ‘relevant environment’). This line of thought can be extended. It is possible to specify several ‘relevant units of adoption’ within a single organization. Reception or acceptance then comes to be viewed as part of an ongoing process of mutual influencing. However, factors and mechanisms that shape intrafirm reception of new ideas have been studied only occasionally in the context of innovation research (Williams & Yang, 1999, p. 385). However important, reception may not be relied on as the exclusive criterion for creativity. In a recent discussion, Ford (2000) has defended the social, Drazin et al. (2000) the personal view. The latter define creativity as ‘a person’s psychological engagement in creative activity’. This ‘creative actor’-centered view is closely related to attempts to identify personal characteristics that can be associated with creativity (cf. Oldham and Cummings, 1996). According to the social view of creativity (or innovation), on the other hand, such personal characteristics can be ignored: What matters is whether an idea is recognized as new and useful, not where it stems from. Ford does not defend such an extreme position; he acknowledges mutual influence between personal creativity and organizational recognition. And indeed, it is likely that not only the outcomes of the efforts of a creative team will shape the reception by others, but also how these outcomes were accomplished, and how they are promoted.

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There is a second reason not to rely on reception as the only criterion for creativity. Suppose a development team that happens to have its work judged by management that is reluctant to engage in radical change (indeed, there are risks, see Henderson & Clark, 1990), and that finds many of its proposals rejected. After some time the situation changes (management turnover, the team is outsourced, whatever), and suddenly a much larger rate of proposals is accepted. According to an outcome-related definition, the team has become more creative, even if its development work has not changed, a consequence of defining creativity by reception that is clearly unsatisfactory. Closely related to reception in the context of product creativity is the question of (degree of) newness. According to Johannessen et al. (2001), the question ‘new to whom’ relates to the question ‘how new’: ‘In order to operationalize the distinction between incremental and radical innovations, we must also determine the relevant unit of analysis’ ( Johannessen et al., 2001, p. 23). However, the discussion following this remark seems to suggest that changes in dominant design (industry level) and degree of departure from existing practices (organization level) allow radical as well as incremental changes. A similar distinction is made by Henderson and Clark (1990), who argue that ‘core concepts’ may change (modular innovation), or the linkages between ‘core concepts’ and ‘components’ (architectural innovation), or both (radical innovation). It is too easy, perhaps, to say that there will always be differences of opinion about what is a ‘core concept’ or dominant design. Still, this may be an important aspect of crossfunctional discussions about new ideas or products. This is one reason to make a distinction between radical and incremental innovation. A second reason is that different models to organize innovation have been associated with different degrees of product newness, as mentioned (the argument that formalized innovation processes suit incremental, rather than radical innovation). A similar argument may apply to within-team processes: It can be conjectured that processes of newness generation will differ between ‘highly novel’ and ‘moderately novel’ ideas or products. An instrument for measuring team creativity, therefore, should allow a distinction to be made between radical and incremental newness. That is necessary to discriminate factors that favor radical and factors that favor incremental newness. Concerning the measurement of innovative activity, Johannessen et al. (2001, pp. 22–23)

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warn against the use of ‘proxies’. They are critical of the use of measures like total R&D expenditures, relative R&D expenditures, number of patents, number of innovations, number of new product and service introductions. And indeed, the reasons given for rejecting each individual measure are convincing. For example, not every innovation can be patented, and innovations that can are not always patented. Still it is desirable to have an instrument, however imperfect, that allows external assessment of creativity, because the criteria in internal (team or organization) assessment of creativity, and the rigor of their use, may vary considerably between teams and between organizations. It may be possible to develop a measure that comprises a wide variety of indicators (e.g. research proposals written, papers published, designs produced, products designed, presentations made, patents received, awards won, projects completed, see Brown & Svenson, 1998). In addition, measures to capture internal assessment (and criteria used for that) can be used. Here, an additional instrument would be useful to control for ‘degree of mildness in judgment’.

Multidisciplinarity issues Two strands of research seem to have shaped the thinking about group creativity, one deriving from studies on the effectiveness of brainstorming in groups, the other stressing group diversity, and originating from such different sources as research on heterogeneity in small groups and studies on the effects of demographic attributes like gender, age, or ethnicity. Studies on group brainstorming started soon after 1957, the year Osborn introduced his technique, but brainstorming was not widely studied until McGrath (1984, p. 131) concluded that ‘individuals working separately generate many more, and more creative (as rated by judges) ideas than do groups (. . .). The difference is large, robust, and general.’ Later research has amended this finding, stressing the role of the interaction medium (face to face or electronic), the task to be performed, group composition and longevity (Guzzo & Dickson, 1996), group member characteristics, and process characteristics such as anonymity and facilitation (Sosik et al., 1998). Studies on group brainstorming used to be experimental (Sutton & Hargadon, 1996). Group diversity research, in contrast, relies on field research. Diversity is a fairly recent concept, used to capture various sources of

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difference between group members. Among the many ways to categorize diversity, the distinction between ‘social category diversity’ and ‘informational diversity’ (Williams & O’Reilly, 1998; Jehn et al., 1999) seems particularly suitable to the study of R&D teams. Social category diversity involves phenomena like self-classification and self-identity, satisfaction, attraction, commitment, morale, group involvement, cohesiveness, ingroup/outgroup conflict, and personnel turnover. Informational diversity, in contrast, ‘refers to differences in knowledge bases and perspectives that members bring to the group. Such differences are likely to arise as a function of differences among group members in education, experience, and expertise’ ( Jehn et al., 1999, p. 743). The view that heterogeneity of knowledge and experience will enhance creativity can be subsumed under the heading of informational diversity. Payne (1990) claims that intragroup diversity fosters an R&D group’s creative performance. Jackson et al. (1995, p. 207) argue that ‘R&D teams bring together experts from a variety of knowledge backgrounds with the expectation that, in combination, they will produce more creative thinking and innovation.’ Reagans and Zuckerman (2001) speak of an ‘optimistic’ view that has a counterpart, however. In the ‘pessimistic’ view, demographic diversity is seen as problematic as it introduces differences that produce communication problems and tension, thus hindering effective teamwork. Conspicuously parallel is the debate on multidisciplinarity, which can be viewed as an instance of informational diversity – a highly relevant one (Leonard, 1995, p. 64). When an R&D team is examined, one of the first topics of interest will concern the disciplines that are present. Just like diversity ( Jehn et al., 1999), multidisciplinarity is widely acclaimed, and warmly recommended. More than a few articles conclude with an appeal to engage in multidisciplinary cooperation, and ‘hardly a research initiative, call for papers, management textbook or departmental prospectus appears without making some claim to support or offer an interdisciplinary approach’ (Knights & Wilmott, 1997, p. 9). Here, the phrase ‘interdisciplinary research’ can be seen as distinct from ‘multidisciplinary research’ (Berger, 1972, p. 25), but it is often used as a synonym. Moreover, many scientific journals have ‘multidisciplinary’ or ‘interdisciplinary’ in their title. Universities create multi- or interdisciplinary courses, or even research institutes (e.g. Hall & Martin, 2000). And in business, ‘multidisciplinary alliances’ are increasingly common (Kanfer et al., 2000).

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Many reasons are given in support of multidisciplinarity. Kanter (1988, p. 176) notes that ‘creativity often springs up at the boundaries of specialties and disciplines, rather than squarely in the middle.’ Jansen and Goldsworthy (1995) and Nissani (1997) argue that multidisciplinary collaboration helps to bridge gaps that result from disciplinary specialization, helps to integrate results from different disciplines, and allows issues to be addressed that lie beyond the disciplinary skills of individual scientists. Diversity research suggests knowledge complementarity as a creativity-enhancing mechanism ( Jackson, 1996, p. 60). Studies on minority influence propose a less overt mechanism: In a group, a dissenting opinion will give rise to sensemaking attempts (why does someone think that way?) and to attempts to show that the dissenting opinion is wrong. Thus, new perspectives are explored in response to dissent, and new ways to look into an issue that is disputed (De Dreu & Beersma, 2001, p. 270). This mechanism is described for majority-minority situations, which adds team member distribution to the picture sketched in diversity studies. Stressing the benefits of diversity may cause the difficulties of heterogeneous team collaboration to be underrated. Such difficulties have frequently been reported, particularly communication, coordination, and efficiency problems (Reagans & Zuckerman, 2001). It can be hypothesized that, in the context of R&D teams, disciplinary differences have a stronger effect on collaboration than other ‘demographic diversity’ variables. This effect may be positive (a result of breadth of knowledge and skills present in the team, and of access to external resources), or negative – as disciplinary differences in knowledge, language, and style are often accompanied by truth or competence claims. Before this hypothesis can be tested, however, a measure for ‘degree of team multidisciplinarity’ has to be developed – which is intricate since disciplines do not have ‘neat boundaries’, and because such a measure will have to take into account that the distances between disciplines may vary considerably (Heckhausen, 1972).

Empirical observations derived from the study Testing the supposition that team multidisciplinarity fosters team creativity requires an appropriate instrument for data collection. Such an instrument will have to allow assessment of the impact of organizational conditions (structure in Burns and Stalker’s

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terms, newness reception patterns, general innovativeness), and team composition (multidisciplinarity, group size, roles, tenure, member diversity, proportion rates, Forrester, 2000; De Dreu & Beersma, 2001) on R&D team creativity, mediated by team communication (Reagans & Zuckermann, 2001). To explore the level of detail needed for the study of actual creativity of R&D teams (hence, the level of detail a data collection instrument will have to provide for), a series of interviews were held with NPD supervisors in a number of medium-sized companies. These interviews were loosely structured; they were designed to offer a general account of how medium-sized companies organize their NPD processes. A checklist of issues to be covered included (1) the very existence and the position of R&D teams; (2) the process of initiating or assigning new products to be developed; (3) the composition and task organization of R&D teams; (4) the design, development, and evaluation processes within R&D teams; (5) the perception and judgment of newly developed products by various organizational actors, and the criteria used for that. The companies we visited were not selected as part of a representative sample. The only selection criteria used were that companies were of medium size (between 100 and 1000 employees), were involved in NPD, and that some companies would be market-, some rather technology-oriented. Size as a criterion stems from the idea that medium-sized companies are less likely than very large companies to have a highly structured R&D department, including the assignment of precisely described subtasks to specialized (often monodisciplinary) teams. Mediumsized companies were expected to exhibit a greater diversity of ways to organize NPD. But small companies are also important in

their own right. A frequently repeated finding is that small companies are more efficient innovators than large companies. Even if the analysis underlying this finding can be disputed (see Tether, 1998), smaller companies’ capacity for innovation deserves to be considered carefully. What follows is an overview of findings obtained from interviews with managers from five companies: Vredestein (car tires), Gazelle (bicycles), Nedap Agri (technical systems livestock industry), Nemef (hinges and locks), Itho (climate control systems). All these companies are at least fairly successful in their own market, all tend to concentrate on markets in The Netherlands, Germany, or both, all have a reputation to protect, and all attach considerable importance to innovation. However, the companies seem to differ in degree of innovativeness. For reasons of confidentiality, findings are presented in a way that prevents tracing them back to individual companies. Occasionally, a distinction is made between ‘more innovative’ and ‘less innovative’ companies. This distinction is loosely based on ‘the company’s sense of urgency to innovate’ as conveyed during the interviews.

General Conditions In recent years, two of the companies regained independence after having been a subsidiary of a large foreign company in the company’s own line of business. In one company a management buyout had been conducted, the other was taken over by a Dutch investment company. Both companies very much valued the resulting freedom to act. One company immediately installed an R&D team, starting the development of products in areas previously not allowed by the holding company. The other company

Table 1. Aggregated Data about Companies Number of employees ranges from 200 to 650 One company daughter of multinational, the others are independent Two companies with several divisions, the others have no division structure Four companies with own R&D department, one of which in early stage of development; number of employees ranges from 5 to 70 Four companies with own production department, one of which in early stage of development; of these, three have outsourced parts of production; one company only involved in assisting production in other companies Two companies invest in interfirm R&D collaboration, the others do hardly or not One company contacts end-consumers, the others contact buyer associations and/or retailers One company technology oriented, three market oriented, one in-between

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now was able again to manufacture highquality products, after a period of managers from abroad who emphasized low production costs rather than high product quality. In both companies, product innovation had been severely restricted, it was felt. All companies view themselves to have a core competence, and four companies have a core product (in which case the company name is also a brand name). Having a core product seems to both facilitate and hamper product innovation. A core product’s architecture and the components within that architecture are fairly well-defined. A core product, then, fosters innovation as it provides a frame of reference for improvement and new application finding, but it may also limit a company’s capacity to innovate. One reason is the risk that major changes will harm product recognition (or brand image) by customers. A second is that radical product change may have the effect that current means of production become obsolete – which includes equipment, procedures, knowledge and skills, but also, as Leonard (1995) points out, managerial systems, and values. In this regard, a salient difference between innovative and less innovative companies appears to be that the latter tend to be proud of the products they make while the former cherish their mastering of the process of NPD. Related to this is that the more innovative companies tend to think in terms of product systems rather than products.

The innovation process NPD is quite commonly described as a somewhat chaotic process. Actual development tasks require experience (often of a tacit nature), product requirements emerge as the process evolves, and unanticipated events are rule rather than exception. As a result, planning tends to be incremental and planning decisions are often taken rather intuitively. A factor to reinforce a sense of chaos is the perception that R&D is stuck between sales and production departments, one stressing what should, the other what can be done. In most of the companies, this seems to be viewed as ‘the way things are’ for an R&D department. In a way this chaos (or lack of process predictability) is not unwelcome. A sense of being engaged in pathfinding activities may contribute to enthusiasm, and to the willingness to invest much time: ‘This is not a nine-to-five job.’ Still, the companies are trying to make the innovation process more transparent, mostly by means of procedures for NPD. Such procedures are sometimes

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used as a guide to the development process, sometimes only as a checklist to be consulted afterwards. In the latter case, it is believed that procedures should not determine the sequence of steps to be taken in product development. There is a general feeling that elaborate procedures may result in formalism, and will preclude efficient development of high-quality products. Therefore, NPD procedures are not always strictly obeyed. Central management is involved in the early stages of product development, but its role varies between the companies observed: from permission to enter a new branch of industry, via permission to develop a new product, to priority setting, or even deciding on the direction of specific developments. This involvement may include discussion rounds and consultation of internal stakeholders, but it can also be a matter of accepting or rejecting a submitted proposal. Various groups are involved in the early stages of NPD, which is in agreement with the idea of installing cross-functional teams and with the concept of comprehensive NPD (Buijs & Valkenburg, 2000). However, the reasons differ between companies. While the NPD literature emphasizes product quality and efficient production, in one company a remarkable further reason was given: early involvement of other groups, particularly from the production department, helps to prevent the frustrating idea taking root that ‘we are only needed here to perform production tasks.’ The product range may constrain the NPD process. Companies that produce a variety of products or product types will have to handle large numbers of components, often originating from several suppliers. Making sure, then, that all components are in the right place, and in time, is an exacting task, that is even more difficult if component changes are put through. Every change will bring its set of initial problems, and especially so a chain of changes (e.g., a supplier who has to install new equipment in order to produce a new component). A ‘normal’ response is to limit the number of changes, and/or to define a production cycle (e.g. a year) in which, as a rule, no changes are made. This is how most companies tend to respond – but it is a response that restricts the innovation process. Another response, observed in one company, is to implement innovations constantly, thereby taking logistic problems for granted.

The product development team The R&D departments of these companies ranged in size from 5 to 70, the largest of these

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consisting of two highly different units – one creating new materials, the other prototypes. One company had no distinct R&D department; a small, stable group of employees from various departments would contribute to concept definitions, to be worked out by an engineering office. The company with the smallest R&D unit reported a broad range of activities; here, the R&D manager indicated that people from other departments are often willing to help, providing all kinds of knowledge (product, market, useful contacts). Providing such help, however, is not part of their regular task, nor ‘officially’ rewarded. In what follows, the word ‘team’ will be used to designate the group of people in a company that is engaged in NPD on a regular basis. The R&D team was generally portrayed as ‘informal’. For example, dressing habits were mentioned, and being on first-name terms. In some cases it was also emphasized that positions are assigned on the basis of personal qualities, not education level. This ‘rule of informality’ seems to reflect the view that content, not form, is important in R&D, and that formal ways of behaving are pointless. But a ‘rule of informality’ may also reflect the recognition that team members must be able to collaborate. Frequently, measures are taken to enhance team spirit and the team’s internal functioning, like assigning people with complementary work styles to a particular task, or inviting team members to an overseas testing session even if they are not directly involved in testing. Moreover, giving a team responsibilities in areas of acquisition and firm reputation was mentioned as an instrument to foster team members’ morale (besides that it may serve other purposes as well). Team roles, complementary work styles, and different levels of experience were seen as important aspects of intra-team cooperation. Discipline-related knowledge differences were also mentioned, but not as a factor that is manageable. Instead, it was observed that discipline-based perspectives are sometimes incompatible (‘at right angles’) – which was viewed as ‘simply inevitable’. The disciplines mentioned were mechanical engineering and electrotechnical engineering. Interestingly, these differences of perspective were not considered a big problem. There is always a supervisor who is entitled to make a decision, if necessary. And what is more, such a decision is not very difficult, usually. The point is that engineers tend to pursue sophisticated solutions to problems they see: solutions that match technological standards in their own field of competence. As a rule, disciplinary differences appear once a level of high complexity is reached – in which case

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the supervisor can say that the design is getting too complex. Yet, in all companies the presence of various disciplines was rated highly. New products often require knowledge from different domains of knowledge, and it is useful if in-house competence can be relied on. But knowledge can be bought, from universities, engineering offices, or other companies. It is here that a multidisciplinary R&D team is considered of great value: Without competence in relevant domains it is difficult to decide what knowledge to buy, and where. Generally speaking, multidisciplinarity is seen as useful for a number of reasons, most of these relating to the notion of ‘absorptive capacity’ – but extending its use. The more multidisciplinary an R&D team, the more this team will be able to discern relevant advances made elsewhere, and the better the chances to take up a new development. But also, the team will be more able to judge the quality of products delivered by suppliers and to propose adjustments if necessary. And if other means fail, having a multidisciplinary team may serve to put pressure on suppliers: ‘If you fail to comply with our requirements, we can do it ourselves.’ A multidisciplinary team will also enhance the prospects of codevelopment activities, with suppliers or with other, ‘horizontally positioned’ companies. And finally, being able to draw upon different fields of competence can be an advantage in negotiations with customers. Instead of having to accept specifications provided by the customer (meaning that only price and delivery conditions are open for discussion), a company may suggest adjustments that serve its own interests as well as the customer’s – at least that is what will be claimed. These alleged virtues of multidisciplinarity in spite, the R&D teams do not contain a wide range of disciplines. Companies tend to concentrate on engaging employees in areas directly related to the current core product. Noteworthy is the difficulty experienced by one company when hiring product developers with higher formal education than the other team members. The newly-appointed members developed product concepts that were different from prevailing products, precisely what they were supposed to do. But these new concepts were not implemented – for that would require new production installations, and it would affect the prevailing ‘product paradigm’ (cf. Petroski’s concept of ‘design paradigm’ (Busby, 1998, p. 106), or Metcalfe and De Liso’s ‘normal design configuration’ (Coombs & Hull, 1998, p. 238)). The presence of a strong ‘product paradigm’ is likely to relate to a company’s

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tendency to keep to itself. Salient, then, is Rothwell’s observation that ‘there is considerable evidence to show that innovation today has become significantly more of a networking process’ (quoted by Newell & Swan, 2000, p. 1288), which suggests that an open window to developments elsewhere is important, if not necessary, for the innovation-related capacities of perceiving, appreciating, generating, and using new ideas. Of the companies interviewed, the more innovative are those that accept their network to develop – which is hardly a process that can be steered or controlled by those supervising. Considering in-house NPD, the level of multidisciplinarity is limited. If a development project requires different fields of expertise, the disciplines involved often contribute consecutively rather than simultaneously. Thus, ‘regular’ ways to organize product development do not encourage ‘discussion among members with diverse perspectives’ ( Jackson, 1996, p. 60).

Generation of new ideas Many studies on NPD underline the importance of idea generation, and sometimes the use of idea generation techniques is advocated. The assumption seems to be that new ideas are scarce. Significant, then, is that in our interviews almost everyone said to have more ideas than they can handle. Only one manager indicated that some new ideas could be used. The companies that had sufficient ideas mentioned a variety of sources: 1. Information from customers. Here, it must be added that although all companies claimed to be market-oriented, only one has a marketing department. (Several companies rely on the sales department as a source of market information, even when it is realized that this information may not always be accurate). 2. Direct questions from customers or from buying associations. New features may be added to existing products, or an existing product is brought into a new domain of application. Seldom, a fully new product is suggested. Suggestions from retailers are rare, even if a company insist that these will be taken seriously. 3. New products launched by competitors (for most companies one reason to be present at fairs and exhibitions; the other, obviously, is to show one’s own products). 4. Reviews and test results in trade journals. 5. Contacts with ‘knowledgeable third parties (universities, research institutes, ‘pro-

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6. 7.

8. 9.

fessionals in the street’ like physicians, architects) – which help to broaden the range of applications of current products, and to anticipate future developments. Cooperation or co-development with suppliers or other companies. ‘Brainstorming sessions’ (not necessarily meeting Osborn’s guidelines) and, more often, random meetings that happen to become useful discussions. One company mentioned employees from the production department as a source (but an infrequent source) of new ideas. Inspiration from ideas or products developed in other industries (particularly high-tech industries, e.g. automotive, aircraft).

In addition, government regulations were frequently mentioned as a source of new ideas, or at least as a factor that stimulates idea generation. Initially seen as a burden, usually, such regulations may force old thinking habits to be abandoned, and result in competitive advantage (‘we only have to be faster than our competitors, or able to come up with a product that more fully meets the new regulations’). This effect is most obvious if regulations are local enough (‘in The Netherlands we are far ahead of competitors abroad’), or if a company’s path dependencies are more easily overcome than those of competitors. Top management always assumes responsibility for deciding on which idea to pursue, what product to make, what specific development trajectory to follow. Once priorities have been set and product development has started, management and other departments tend to stay involved, particularly so in companies using cross-functional teams. Different organizational arrangements do entail different ways to evaluate the product development process, but in all cases multiple criteria are used for product specification, and later, for testing. Newness, rather than ‘creativity’ is mentioned as an important criterion (in most cases this means ‘sufficiently new’, not ‘radically new’). Often mentioned, next to newness, are robustness, reliability, durability, and safety. The presence of multiple criteria means that trade-offs are necessary. For instance, in the case of car tires ‘air’ is important: more air means better roadholding, especially when roads are wet, but it also means more noise. Such trade-offs can be viewed as the result of an optimization process in which technological and commercial demands are balanced, or they can be viewed as the outcome of multidisciplinary discourse.

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Conclusion There is reason to assume that the presence of various disciplines will enhance a product development team’s creativity, but research in support of such a relationship is largely absent. This lack of research is understandable, since ‘group creativity’ and ‘multidisciplinarity’ are difficult concepts to measure. From interviews with NPD supervisors in medium-sized companies it appeared that, as expected, an instrument for measuring group creativity in organizations will have to include the issue of creativity reception by other groups. A less expected finding was that group creativity appears to be highly related to openness and external contacts. Companies have developed quite different organizational modes in their innovation processes, which are clearly related to the type of innovation pursued by the company, e.g. technology-driven or market-driven. These modes are also related to the strength of the prevailing ‘product paradigm’ – which was found to produce important organizational and cognitive restrictions. Next, the interviews showed that multidisciplinary communication in R&D teams is less problematic than expected, but also less frequent and less intensive, even in teams that are multidisciplinary in composition. These observations call for further investigation of intra-team processes, as they suggest communication problems in multidisciplinary R&D teams that seem to differ from the problems frequently reported in the literature on concurrent engineering (e.g. Wang et al., 1996). Finally, communication with various partners outside the company turned out to be very important, making new ideas more likely to be developed, and more likely to be accepted.

References Amabile, T.M. (1983) Social psychology of creativity: A componential conceptualization. Journal of Personality and Social Psychology, 45, 357–377. Andrews, F.M. (1979) Motivation, diversity, and the performance of research units. In Andrews, F.M. (ed.), Scientific Productivity. Cambridge University Press, Cambridge, pp. 252–287. Berger, G. (1972) Introduction. In Apostel, L., Berger, G., Briggs, A. and Michaud, G. (eds.), Interdisciplinarity; Problems of Teaching and Research in Universities. OECD, Centre for Educational Research and Innovation, pp. 23–26. Boden, M.A. (1991) The Creative Mind: Myths and Mechanisms. Basic, New York. Brown, M.G. and Svenson, R.A. (1998) Measuring R&D Productivity. Research-Technology Management, November/December, 30–35.

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Brown, S.L. and Eisenhardt, K.M. (1995) Product development: past research, present findings, and future directions. Academy of Management Review, 20, 343–378. Buijs, J. and Valkenburg, R. (2000) Integrale Productontwikkeling, 2e ed. Lemma, Utrecht. Burns, T. and Stalker, G.M. (1961). The Management of Innovation. Tavistock, London. Busby, J.S. (1998) The neglect of feedback in engineering design organisations. Design Studies, 19, 103–117. Chidamber, S.R. and Kon, H.B. (1994) A research retrospective of innovation inception and success: The technology-push, demand-pull question. International Journal of Technology Management, 9, 94–112. Cohen, W.M. and Levinthal, D.A. (1990) Absorptive capacity: a new perspective on learning and innovation. Administrative Science Quarterly, 35, 128–153. Coombs, R. and Hull, R. (1998) ‘Knowledge management practices’ and path-dependency in innovation. Research Policy, 27, 237–253. Csikszentmihalyi, M. (1999) Implications of a systems perspective for the study of creativity. In Sternberg, R.J. (ed.), Handbook of Creativity. Cambridge University Press, Cambridge, pp. 313–335. De Dreu, C.K.W. and Beersma, B. (2001) Minority influence in organizations: Its origins and implications for learning and group performance. In de Dreu, C.K.W. and de Vries, N.K. (eds.), Group Consensus and Minority Influence. Blackwell, Oxford, pp. 258–283. Debackere, K. (1999) Technologies to Develop Technology. Maklu, Nijmegen Lectures of Innovation Management/Antwerpen. Drazin R., Glynn, M.A. and Kazanjian, R. (2000) Purpose-built theories: A reply to Ford. Academy of Management Review, 25, 285–287. Ford, C.M. (2000) Creative developments in creativity theory. Academy of Management Review, 25, 284–285. Forrester, R.H. (2000) Capturing learning and applying knowledge: An investigation of the use of innovation teams in Japanese and American automotive firms. Journal of Business Research, 47, 35–45. Guzzo, R.A. and Dickson, M.W. (1996) Teams in organizations: recent research on performance and effectiveness. Annual Review of Psychology, 47, 307–338. Hall, S. and Martin, D. (eds.) (2000) Proceedings of the American Society of Business and Behavioral Sciences Conference. Track section of deans & accreditation, interdisciplinary, and legal studies. February 17–21, 2000, Las Vegas, Nevada. Proceedings of the American Society of Business and Behavioral Sciences, 7, 8. Heckhausen, H. (1972) Discipline and interdisciplinarity. In Apostel, L., Berger, G., Briggs, A. and Michaud, G. (eds.), Interdisciplinarity; Problems of Teaching and Research in Universities. OECD, Centre for Educational Research and Innovation, pp. 83–89. Henderson, R.M. and Clark, K.B. (1990) Architectural innovation: The reconfiguration of existing

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product technologies and the failure of established firms. Administrative Science Quarterly, 35, 9–30. Jackson, S.E. (1996) The consequences of diversity in multidisciplinary work teams. In West, M.A. (ed.), Handbook of Work Group Psychology. Wiley, Chichester, pp. 53–75. Jackson, S.E., May, K.E. and Whitney, K. (1995) Understanding the dynamics of diversity in decision-making teams. In Guzzo, R.A., Salas, E. and associates. Team Effectiveness and Decision Making in Organizations. Jossey-Bass, San Francisco, pp. 204–261. Janssen, W. and Goldsworthy, P. (1995) Integrating and Managing Multidisciplinary Teams in Agricultural and Natural Resource Management Research. International Service for National Agricultural Research, ISNAR Briefing Paper 23. Jassawalla A.R. and Sashittal, H.C. (1998) An examination of collaboration in high-technology new product development processes. Journal of Product Innovation Management, 15, 237–254. Jehn, K.A., Northcraft, G.B. and Neale, M.A. (1999) Why differences make a difference: A field study of diversity, conflict, and performance in workgroups. Administrative Science Quarterly, 44, 741– 763. Johannessen, J.-A., B. Olsen, G.T. Lumpkin (2001) Innovation as newness: what is new, how new, and new to whom? European Journal of Innovation Management, 4, 20–31. Kanfer, A., Bruce, B.C., Haythornthwaite, C., Burbules, N., Wade, J., Bowker, G.C. and Porac, J. (2000) Modeling distributed knowledge processes in next generation multidisciplinary alliances. In Proceedings of Next Generation Enterprises Virtual Organizations and Mobile/Pervasive Technologies (April 27–29, 2000). AIWorc, Buffalo, NY. Khurana, A. and Rosenthal, S.R. (1998) Towards holistic ‘front end’ in new product development. Journal of Product Innovation Management, 15, 57–74. Knights, D. and Wilmott, H.C. (1997) The hype and hope of interdisciplinary management studies. British Journal of Management, 8, 9–22. Kotabe, M. and Swan, K.S. (1995) The role of strategic alliances in high technology NPD. Strategic Management Journal, 16, 621–636. Leonard, D. (1995) Wellsprings of Knowledge. Harvard Business School Press, Boston. Lovelace K., Shapiro, D.L. and Weingart, L.R. (2001) Maximizing cross-functional new product teams’ innovativeness and constraint adherence: A conflict communications perspective. Academy of Management Journal, 44, 779–793. Mascitelli, R. (2000) Harnessing tacit knowledge to achieve breakthrough innovation. Journal of Product Innovation Management, 17, 179–193. Mayer, R.E. (1999) Fifty years of creativity research. In Sternberg, R.J. (ed.), Handbook of Creativity. Cambridge University Press, Cambridge, pp. 449– 460. McDonough, E.F. (2000) Investigation of factors contributing to the success of cross-functional teams. Journal of Product Innovation Management, 17, 221–235. McGrath, J.E. (1984) Groups: Interaction and Performance. Prentice-Hall, Englewood Cliffs, NJ.

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Moore, R.M. (1997) The positive effects of cohesion on the creativity of small groups. International Social Science Review, 72, 3/4, 84–93. Moorman, C. and Miner, A.S. (1997) The impact of organizational memory on new product performance and creativity. Journal of Marketing Research, 34, 91–106. Newell, S. and Swan, J. (2000) Trust and interorganizational networking. Human Relations, 53, 1287–1328. Nissani, M. (1997) Ten cheers for interdisciplinarity: The case for interdisciplinary knowledge and research. Social Science Journal, 34, 201–216. O’Connor, G.C. (1998) Market learning and radical innovation: A cross case comparison of eight radical innovation projects. Journal of Product Innovation Management, 15, 151–166. Oldham, G.R. and Cummings, A. (1996) Employee creativity: Personal and contextual factors at work. Academy of Management Review, 39, 607– 634. Payne, R. (1990) The effectiveness of research teams: a review. In West, M.A. and Farr, J.L. (eds.), Innovation and Creativity at Work. Wiley Chichester, 101–122. Reagans, R. and Zuckerman, E.W. (2001) Networks, Diversity, and Productivity: The Social Capital of Corporate R&D Teams. Organization Science, 12, 502–517. Schoonhoven, C.B. and Jelinek, M. (1990) Dynamic tension in innovative, high technology firms: Managing rapid technological change through organizational structure. In von Glinow, M.A. and Mohrman, S.A. (eds.), Managing Complexity in High Technology Organizations. Oxford University Press, pp. 90–118. Scott, S.G. (1997) Social identification effects in product and process development teams. Journal of Engineering and Technology Management, 14, 97– 127. Shaw, J.B. and Barrett-Power, E. (1998) The effects of diversity on small work group processes and performance. Human Relations, 51, 1307–1325. Sosik, J.J., Avolio, B.J. and Kahai, S.S. (1998) Inspiring group creativity. comparing anonymous and identified electronic brainstorming. Small Group Research, 29, 3–31. Sutton, R.I. and Hargadon, A. (1996) Brainstorming groups in context: Effectiveness in a product design firm. Administrative Science Quarterly, 41, 685–718. Tang, H.K. (1998) An integrative model of innovation in organizations. Technovation, 18, 297– 309. Tether, B.S. (1998) Small and large firms: Sources of unequal innovations? Research Policy, 27, 725– 745. Torrance, E.P. (1988) The nature of creativity as manifest in its testing. In Sternberg, R.J. (ed.), The Nature of Creativity. Cambridge University Press, pp. 43–75. Wang, F.C., Wright, P.K. and Richards, B.C. (1996) A multidisciplinary concurrent design environment for consumer electronic product design. Concurrent Engineering, 4, 347–359. Williams, K.Y. and O’Reilly, C.A. (1998) Demography and diversity in organizations. In Staw,

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B.M. and Sutton, R.M. (eds.), Research in Organizational Behavior, 20. JAI Press, Stanford CT, pp. 77–140. Williams, W.M. and Yang, L.T. (1999) Organizational creativity. In Sternberg, R. (ed.), Handbook of Creativity. Cambridge University Press, Cambridge, pp. 373–391. Woodman, R.W., Sawyer, J.E. and Griffin, R.W. (1993) Toward a theory of organizational creativity. Academy of Management Review, 18, 293–321.

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Geert Vissers is a research fellow in the department of business administration, Nijmegen School of Management (University of Nijmegen). Ben Dankbaar is professor of business administration and dean of the Nijmegen School of Management (University of Nijmegen).

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Brainsketching and How it Differs from Brainstorming Remko van der Lugt Brainsketching is an idea generation technique, based on brainwriting, that uses sketching as the primary means of recording ideas. During brainsketching, participants sketch their ideas individually on large sheets of paper pasted on the wall. After a few minutes, the participants explain their idea sketches, switch places and continue sketching. Usually, about five such rounds of idea sketching take place. In an experimental set-up brainsketching was compared to brainstorming. Linkography was used as a method for analyzing the process characteristics of both techniques. Results show that during brainstorming, participants generated significantly more ideas, and that during brainsketching participants generated significantly more connections with earlier ideas. Also, during brainsketching participants made more incremental connections while maintaining a similar level of ‘wild leap’ connections. Conclusion of this study was that brainsketching does not necessarily provide a better idea generation process; rather, it provides a different process, which may serve different purposes. Some steps towards further development of the brainsketching technique are indicated. Suggestions are provided for stimulating the group to reflect on their ideas. Finally, some suggestions are made for applying the brainsketching technique with groups of nondesigners, mainly directed at removing the participants’ hesitation to draw in public.

Introduction

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hen designers need to generate ideas, they take paper and pencil, and start to produce idea sketches. Or, they may call an idea generation meeting. The available body of idea generation techniques is heavily based on writing as a working medium. Customarily the facilitator of the meeting writes down brief descriptions of ideas on a flipchart. However, many design researchers regard sketching to be instrumental to the creative process of designers. The research project reported here started with the notion that idea generation techniques for design could be enhanced if sketching could be included in such idea generation meetings. Sketching consists of the production of quick and messy drawings of ideas. In design, the activity of sketching is regarded to not only provide a means for representing mental images of ideas. Instead, sketching is regarded to facilitate the actual generation of such mental images. In a review of the research on drawing and design, Purcell & Gero (1998) focus on research concerned with

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investigating the ways in which the activity of sketching stimulates creativity in design thinking. They point out underlying themes regarding the role of sketching in design. The principal theme deals with the positive role that sketching plays in re-interpretation. A second theme is that re-interpretation provides new knowledge and that this new knowledge leads towards further re-interpretation. Various researchers propose such cyclical models of re-interpretation, each with a slightly different connotation, ranging from a dialectic type of argumentation between seeing-as and seeing-that (Goldschmidt, 1991), interactive ‘conversations’ with the paper on which the designer draws (Scho¨n & Wiggins, 1992), and movement from description to depiction (Fish & Scrivener, 1990). In addition to the individual, cognitive functions of sketching, typical group functions can be identified. According to Scrivener & Clark (1994), sketching provides representations of design solutions that allow for a range of interpretations of elements. By sketching, temporal decisions are made which allow for evaluation and interpretation # Blackwell Publishers Ltd 2002. 108 Cowley Road, Oxford OX4 1JF and 350 Main St, Malden, MA 02148, USA.

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of a design solution, without excluding alternatives. For instance, the sketch in figure 1 was produced in an experimental design group meeting (Cross, Christiaans & Dorst, 1996). The objective was to design a bike rack for carrying a hiking back-pack. This sketch of the rear of the bicycle was used to discuss various issues regarding the rack design. At a certain point, one of the designers comes up with the idea to use one over-sized hollow tube to support the rack, rather than a wire-frame. He adds a rough sketch of the tube to the drawing (see the arrow), without crossing-out, or excluding in any other kind of way, the already present sketch of the wire frame. This allowed the designer to explore the implications of his one over-sized tube idea, without dismissing the wire-frame idea. Finally, by having more distinctive features, sketches are more easily recognized among other sketches, which means that sketches facilitate the designers’ access to earlier ideas. Easier access to earlier design ideas is likely to stimulate increased use of these earlier design ideas. According to McKim (1972) building and maintaining a – what he calls – ‘collective graphic memory’ fosters the group’s creative process by providing an immediately accessible database of ideas. In order for these functions of sketching in design to apply also to idea generation meetings, the process of idea sketching needs to be compatible with the process of divergent thinking. The processes are not compatible if including sketching degrades the structure of the idea generation process. Whether or not this is the case can be examined by assessing the extent to which the structure of the idea generation process meets the four guidelines to divergent thinking (Osborn, 1953).

In a first exploratory study (Van der Lugt, 2000) three graphic variations to the brainstorming technique (in which sketching was used) were applied in experimental meetings. In a fourth meeting regular brainstorming was applied as a control condition. The graphic variations applied were: . Visual brainstorming. Instead of the facili-

tator writing down ideas on the flip-chart, the participants make sketches of their ideas on jumbo-sized post-it notes. . Brainstorming with a graphic facilitator. Instead of the facilitator writing down ideas on the flip chart, a ‘graphic facilitator’ (Lakin, 1988) records ideas by producing sketches of the ideas mentioned. . Brainstorming with added sketches. This is a hybrid technique, in which the facilitator writes down ideas on a flip chart, but the participants are encouraged to add sketches on post-it notes. The fully graphic variations (graphic facilitator and visual brainstorming) performed substantially less well on parameters that reflected the four guidelines of divergent thinking, compared to regular brainstorming. Not only did the graphic variations produce substantially fewer ideas, but there were also substantially fewer connections made between ideas, which meant that the idea generation process was less integrated. (We consider ‘integration’ to be a key indicator for the quality of the idea generation process). This led us to conclude that the processes of idea sketching and divergent thinking are not fully compatible. The functions of sketching in design activity cannot simply be added to the brainstorming process, as sketching appears to induce a structurally different process of idea generation. In this paper, we will develop brainsketching, an idea generation technique that may be better suited for incorporating sketching in creative problem-solving. We will briefly report the results of an empirical study that compares this technique with a representative of idea generation techniques with written language as the primary working medium. Finally, we will propose directions for further improvement of brainsketching, intended to stimulate group reflection and we will provide some suggestions for using brainsketching in groups of non-designers.

Brainsketching Figure 1. Example of the Co-existence of Different Alternatives within One Sketch

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The basic brainsketching technique is a visual modification of the more widely known brainwriting technique (Geschka, Schaude &

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Schlicksupp, 1973). Van Gundy (1988) mentions how this technique came into existence by students in his college class making a variation to an existing sentential technique. According to Van Gundy, they did so in order to satisfy their need for visual expression while generating ideas. A similar development occurred independently at the creative problem-solving course at the Delft School of Industrial Design Engineering. During brainsketching, group members individually sketch their ideas on sheets of paper. After a few minutes, the group members pass on the sheets and continue to sketch ideas, After a couple of minutes the group members shift flipcharts and continue to sketch ideas. The idea sketches already present on the flipchart are used as a source of inspiration for new ideas. Usually about five such rounds of idea sketching take place. In between rounds, the facilitator may especially emphasize the ‘building on other ideas’ guideline. Either, the sheets of paper are passed around between rounds, or the group members change position. This is the case when sheets are posted on the wall, as in figure 2 and 3. The predominant mode of expression used during brainsketching is, predictably, sketching. However, written annotations are used, for instance, for clarification or elaboration of a sketch (see figure 4). Brainsketching allows the participants to be involved in a group idea generation process while at the same time it allows them to generate ideas individually, thus allowing them to engage in what Scho¨n & Wiggins (1992) describe as a ‘reflective conversation’ with their drawings. The version of brainsketching that has been reported in the literature is entirely nonverbal. Participants sketch ideas in silence

Figure 2. Brainsketching in Action

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Figure 3. One of the Resulting Flipcharts with Ideas

and then pass on their sheets of ideas. Building on earlier ideas is stimulated by asking the participants to first browse through the earlier ideas on the sheet of paper, before generating new ideas. We hypothesized that, by allowing the participants to briefly explain their ideas after each round of idea sketching, more of a group-oriented process could be achieved. Such a round of sharing ideas can increase the participants’ understanding of each other’s ideas, which may enhance the amount of building on each other’s ideas taking place. To explore whether this adaptation to the brainsketching technique indeed provided a more group-oriented idea generation process, a small pilot study was executed (see Van der Lugt, 1999 for a detailed report of this pilot study). In line with expectations, compared to

Figure 4. Idea Sketch with Annotations Made in a Brainsketching Meeting. This is an Idea for the ‘How to Make Traveling by Car Fun for Children?’ Problem used in one of the Empirical Studies. The Idea Entails Placing a Racetrack Upside Down on the Ceiling of the Car

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‘traditional’ brainsketching, when involved in the adaptation, group members made substantially more connections with each other’s ideas. The revision of brainsketching indeed appeared to enhance the group process.

Empirical study: Differences between the processes of brainstorming and brainsketching To achieve a more thorough understanding of the differences in structure of the idea generation processes which use either sketching or writing as the primary working medium, we compared our adaptation to brainsketching as a representative of idea generation techniques that use sketching, to brainstorming with post-its (Isaksen et al., 2000) as a representative of idea generation techniques that use writing as the primary working medium. In each of four experimental meetings both the brainsketching and the brainstorming were applied which allowed us to perform a paired comparison analysis of the results for each participant (n = 20). Each meeting consisted of five advanced product design students who were involved in a course in facilitating creative problem solving meetings. Each meeting was moderated by an experienced professional creative problem solving facilitator. The following design assignment was developed with these requirements in mind: ‘How to make travelling by car fun for children?’ The participants were asked to generate ideas for products to make traveling by car fun for children. The assignment involved generating ideas for a particular multi-functional family car, which was given the fictional name ‘Vista’.

Method of analysis The main reason for organizing a group meeting is for the group members to interact in their problem solving efforts. This makes the ‘building on each other’s ideas’ guideline for divergent thinking (Osborn, 1953) especially relevant to this research project. Investigating the ways in which the participants build on each other’s ideas provides direct process clues regarding the functioning of the techniques applied. Linkography (Goldschmidt, 1995; 1998) is a research approach that specifically addresses the ways in which designers build on each other’s input. We have adapted this method for application in our research of creative

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problem solving meetings. In this paper we cannot go into detail regarding either the empirical study or the linkography method. For a more elaborate description of both the empirical study and research method used we refer to earlier work (Van der Lugt, 2000; 2001). Here we will limit ourselves to a brief description of the method. In linkography for each idea direct connections or ‘links’ with all earlier ideas are determined by gathering and evaluating evidence of such connections. This leads to a matrix display of a link system like in figure 5. Once the link systems are finalized, link indices are calculated. The link indices provide insight into the general characteristics of the meeting process, regardless of the specific qualities of the separate meetings, like the number of participants or the number of ideas generated. The following indices were developed and used: . The link density is an indicator of the

integratedness of the process. A high link density indicates that ideas have many connections with earlier ideas. . The self-link index is the ratio of links that the participants make with their own earlier ideas, in relation to the total number of links made. Together with the link density, the self-link index indicates to what extent the ‘building on each other’s ideas’ guideline is met. . The link-type indices (Supplementary, Modification, and Tangential) indicate the nature of the connections that are made, based on a categorization of the nature of ideas provided by Gryskiewicz (1980). Tangential links indicate wild leaps into a different direction, modification links indicate direct variations and supplementary links indicate small alterations.

Results What, then, were the differences found? During brainsketching, designers produce ideas that have significantly (p < 0.0005) more connections with the earlier ideas (Link density: Brainstorming x = 0.84, SD = 0.23; Brainsketching: x = 1.27; SD = 0.35). The designers produced a significantly (p < 0.005) lower number of ideas when brainsketching, in comparison to brainstorming (Number of ideas generated per person: Brainsketching: x = 9.60, SD = 2.30; Brainstorming x = 13.05, SD = 4.32). This means that brainstorming with post-its complies better with the ‘strive for quantity’ guideline for generating ideas, and brainsketching complies better with the ‘build on each other’s ideas’ guideline.

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Figure 5. Example of a Link Matrix for a Brainsketching Segment

From the link type indices we learned that during brainsketching designers make significantly (p < 0.01) more supplementary connections, which are hardly present in the brainstorming segments (Link type index Supplementary: Brainsketching x = 0.25, SD = 0.15; Brainstorming: x = 0.11, SD = 0.11). These incremental steps do not mean that there is a lower proportion of tangential connections made as no significant difference between the techniques was found (Link type index Tangential: Brainsketching x = 0.31, SD = 0.15; Brainstorming x = 0.36, SD = 0.17). In that sense, brainsketching appears to entail a more balanced problem solving process. The differences in the idea generation processes become clearer when inspecting the variations in types of linking throughout the progress of the segments. Figure 6 presents the mean link type indicators for each ten percent of ideas generated for the brainstorming condition and figure 7 does the same for the brainsketching condition.

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The brainstorming process quickly reaches a mature condition, in which the levels of tangential and modification links are more or less equal. The development of the link types in the brainstorming condition suggests a process of continuous inspection for, and exploration of, new search directions. In the brainstorming condition, throughout the meetings, few idea development steps take place, as signified by the low level of supplementary linking. The brainsketching process develops from tangential linking in the first part of the meeting, to modification-type linking in the middle, with a focus on supplementary-type linking in the end. This suggests that during brainsketching, designers make connections in accordance with the ways in which design processes are typically described (e.g. Goel, 1995): starting out with a broad search for new directions in the beginning, followed by the exploration of some of these directions, leading to specific

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Figure 6. Average Progress of Link Types for the Brainstorming Condition improvements of concepts in the later parts of the process. The different characteristics of the brainsketching and brainstorming processes suggest that they may serve different purposes. Brainstorming-like techniques may better serve the traditional role of idea generation techniques, which is to generate a large number and variety of design ideas, of which some can be selected to further develop into design solutions. Brainsketching may be more suitable when, instead of a large number of ideas, a smaller but more refined collection of novel ideas are desired. For instance, graphic techniques may be applied in a design project start-up meeting to provide a quick simulation of the design process to come. Such a

simulation allows the members of a team to gain a shared understanding of the design task by discussing possible pathways towards solutions that came up when generating ideas.

Discussion: differences in structure between the brainsketching and the brainstorming process Now that we have found differences in the structure of the brainsketching and the brainstorming process, how can these differences be explained on a theoretical level? Here we will examine the theoretical differences in the basic activities that take

Figure 7. Average Progress of Link Types for the Brainsketching Condition

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Figure 8. The Creative Problem Solving Stage of Idea Finding

Figure 9. The Basic Structure of the Geneplore model (From Finke, Ward, & Smith, 1992)

place in graphic and sentential idea generation meetings. A representation of the current view on the activities in the creative problem solving stage of idea-finding is provided in figure 8. The stage consists of a divergent phase that focuses on idea production and a convergent phase of idea evaluation and -selection. An alternative view is provided by Finke, Ward, & Smith (1992), who propose, what they call, a ‘heuristic model of creativity’ called ‘Geneplore’ (see figure 9) in their efforts to develop a creative cognition approach to understanding creativity. ‘Geneplore’ is a combination of the verbs ‘generate’ and ‘explore’. Finke et al. argue that creative cognition involves a repeating cycle that contains a generative phase in which so-called pre-inventive structures are constructed, and an exploratory phase, in which the generated pre-inventive structures are interpreted. The results of these interpretations lead to insights that can be used to either focus on specific issues, or to expand conceptually, by modifying the pre-inventive structures. In the model, product constraints can be imposed at any time during the generative or exploratory phase. The pre-inventive structures are central in Finke et al.’s theory. They observe:

pre-inventive structures. With the Geneplore model in mind, we can now start to infer differences in activities for the brainsketching and the brainstorming conditions. In figure 10 the two phases of the Geneplore model are included in the idea-finding stage. The depictive characteristics of sketches provide a rich basis for analysis by allowing the designers to envision the consequences of the ideas. Fish & Scrivener (1990) consider that: ‘The necessity to sketch arises from the need to foresee the results of the synthesis or manipulations of objects without actually executing such operations’ (p. 117). Written language, which is descriptive in nature, refers to classes of objects rather than specific objects, which does not allow the designers to envision the consequences of the specific ideas. This stimulates the generation of ideas by allowing the designers to make free associations, but the inability to envision the consequences of the generated ideas, makes writing as a working medium less supportive of the interpret phase in the Geneplore cycle. This corresponds with our findings from the empirical study, which show that during brainstorming, significantly more ideas are generated, and significantly fewer connections

These (pre-inventive) structures can be thought of as internal precursors to the final, externalized products of a creative act. They can be generated with a particular goal in mind or simply as a vehicle of open-ended discovery. They can be complex and conceptually focused or simple and relatively ambiguous, depending on the situation and the requirement of the task. (Ward, Smith, & Finke, 1999, p. 192) According to Ward et al. (1999), both idea sketches and words – or, as they call them, ‘verbal combinations’ – can represent such

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Figure 10. A Cyclical Model of the Creative Problem Solving Stage of Idea-finding

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with earlier ideas were made. Conceivably, there is little place for interpreting ideas during brainstorming. Participants do build on each other’s ideas – this is supported by one of the guidelines – but the nature of such connections made can be regarded to be mostly concerned with brief inspections that spur further associations, rather than more detailed interpretation of the ideas. The guidelines for divergent thinking stimulate this, by dismissing any type of judgment from the divergent phase. According to the creative problem solving method, interpretation is regarded to be a kind of judgment, as interpretation involves assessing the consequences of the idea for the further generation of ideas. The brainsketching process appears more closely connected to the generate-interpret cycle. In design research, various idea-sketching cycles have been proposed, which suggest that designers reflect on what they are sketching, while they are sketching it. For instance, Goldschmidt (1990) refers to design sketching activity as a ‘dialectic of sketching’, and in her research she showed how designers switch between making graphic propositions and language-like interpretations of these graphic propositions. Scho¨n and Wiggins (1992) considered the designer to be involved in a ‘reflective conversation’ with the drawing surface, meaning that the designer interprets the consequences of a drawing act while he or she is making the mark. Reflecting on these previous theories, a basic model of idea generation through sketching can be considered to consist of two basic steps between which the designer shifts continuously. One step is related to producing (part of) a sketch of an idea on the paper and the other step consists of exploring and interpreting the sketch made in order to find directions for further idea sketching.

Stimulating group reflection in brainsketching The ‘magical moment’ for brainsketching, in which group members share their ideas before going into the next round of idea generation, may have more potential than used so far. In the interactive brainsketching technique applied in this study, this moment was only used for the designers to briefly explain their ideas. During these moments, the designers listened as one at a time they shared their ideas. It may be possible to make more use of the step of sharing ideas as a group activity, by more actively engaging in a constructive group reflection on the ideas generated. Considering that brainsketching may involve a more deliberate and develop-

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mental idea generation process, such moments of creative interaction between designers – which in the present technique are not solicited during the step of idea sharing – can be used more deliberately as an essential element of the brainsketching technique. In the present brainsketching technique, designers are discouraged from going into discussion in the periods for sharing ideas. Sometimes, however, the designers could not be stopped. A good example is found in meeting 1 of the empirical study. The relevant ideas for this example are provided in table 1. While C is explaining his ‘observation turret’ idea, designer E makes a verbal remark of adding a gun to the turret. Then designer D pretends to be playing with a gun turret. He does not appear to try to communicate through his gestures; the gestures appear to be some kind of simulation in support of his individual process. After C is done explaining his idea, designer D explains how the earlier idea 34, ‘virtually shooting other road users’, in combination with idea 44, can provide a gun turret game. The facilitator then asks D to add an annotation of that idea to designer C’s sketch of the observation turret. While D is doing this, designer A suggests developing this idea into a computer game, ‘car wars’. In this moment of sharing ideas, all of a sudden there is a lot of interaction taking place and energy in the room. There is laughter and quick verbal responses and four out of five designers pretend to be holding and shooting toy machine-guns. Instead of seeing such moments as an irregularity in the brainsketching process, such moments could be fostered as moments of creative group interaction. In her research on the reflective practice of design teams, Valkenburg (2000) uses Scho¨n’s (1983) ‘reflective practice’ theory of designing. She reports: Scho¨n’s basic assumption is that the designer determines his position in the design situation. By interpreting the design situation in his own subjective way, the designer creates a context for further activities. By constantly considering his activities and their implications, the designer can adjust the activities, or adjust his interpretation of the situation (p. 229). Valkenburg stresses the importance of framing and reflecting in team design activity. Reflection, in Scho¨n’s opinion, relates to evaluating, for example, the appropriateness of the design activities that are taking place, rather than judging the quality of the ideas generated. Framing relates to (temporarily) following a certain guiding principle for focusing the design activities.

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Table 1. Fragment of Brainsketching Protocol from Meeting 1 in the Second Study Idea/ Designer/ Chart

Label

Time/protocol text

35/C/I

Virtually shooting other road users

54.29

44/C/II

Seat rises into observation turret

Sketch (translation of annotation)

C: I thought . . . yes . . the youth of today is getting more aggressive anyway, so if you can make some kind of a virtual picture on the window, which you can shoot at .. and that it can kind of recognize the outline of the surroundings and that you get to hear through the headset that someone is hit or that the target is destroyed or something . . . that you can interact with the surroundings by shooting at it

(+ headset, sound effects when you hit someone) (virtually shooting other road users)

1: 00.07 C: I thought that in the back . . . if you make a chair that comes up automatically, into a glass- or seethrough turret . . . that you can see beyond the whole car. Then you can see the signs with city names better. And you can type those into a key-board immediately . . .

(observation post on top of car with chair that rises up) (keyboard to type in town names for information)

1.04.15 E: With some kind of gun on it 45/D/II

Gun turret

1.04.27 D: Yes! . . . (unintelligible) . . . that one (points at idea 35) in combination with that one (points at idea 44) . . . let’s say . . . a gun turret.

(gun turret)

1.04.45 A: You can also sell a computer game . . . Car Wars . . . that you see all these Vistas with turrets fighting each other . . . pappa, let’s go driving!

Frames can be detected throughout idea generation meetings, but they are not explicitly used as a device for structuring the idea generation activity. The absence of the explicit use of frames may be related to one of the main criticisms of Nijstad (2000) regarding brainstorming meetings. He describes the brainstorming process as a sequence of ‘trains of thoughts’. According to him, such a ‘train of thought’ is: . . . a rapid accumulation of semantically related ideas. When such a train of thought no longer leads to new ideas, a new search of memory is undertaken, which may lead to the activation of a new image. This, in turn, may lead to a new train of thought. This process continues until the brainstorming session is ended. (p.139)

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As a possible explanation of production loss in brainstorming groups, he proposes that such trains of thoughts are prematurely aborted when an idea cannot be expressed immediately, because the group member has to wait to take his turn. If we assume that a ‘frame’ shares much of the characteristics of such a ‘train of thought’, then during an idea generation meeting a ‘frame’ may be prematurely abandoned, just because another group member starts a new line of associations. Possibly, by dealing with frames more deliberately, a more directed and well-integrated search for ideas can be achieved. For brainsketching, this could mean that rather than merely inspecting the group’s ideas for leads to further individual idea generation and interpretation, the designers could interpret and reflect on their ideas

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together. After such a step of group reflection, the designers could return to their individual idea sketching accompanied by a shared understanding of the directions for further idea generation. If the brainsketching technique included such an activity of group reflection, the ‘gun turret’ example discussed before (see table 1), could have been dealt with by the designers recognizing a ‘frame’ of ‘virtually shooting other road users’. Then, the designers could have determined whether this frame was sufficiently explored by proposing a gun turret and a ‘car wars’ video game, or whether in the next idea generation round efforts should be made to further explore the frame, and if so, which are interesting directions. Then, in the next round of generating ideas, the designers could have returned to their individual idea generation, but with directions that were generated in the group, for instance, to further explore video games in which the Vista car is the subject.

Some remarks on the applicability of brainsketching for participants without a design background The studies performed involved advanced product design students, who have at least basic sketching skills due to their education. In the first two years of the program, Delft product design students receive about 120 hours of drawing instruction. The question remains whether non-designers are able to fully participate in techniques that involve sketching. In theory on design sketching, the designers’ ability to sketch is highly valued (e.g. McKim, 1972; Muller, 2001), and nondesigners themselves tend to be eager to disqualify themselves; when asked to make a sketch of a certain topic, many people tend to respond with resolute remarks like, ‘Oh, but I can’t draw!’ One may expect that ideas from designers with good sketching ability are used more often for making connections than ideas from designers with poorer sketching ability. Better quality sketches look more attractive, which may draw attention to the idea, and the information conveyed through the sketch may be more easily accessible. But, contrary to expectations, the self-perceived sketching qualities of a subject and the average ratio of links made with their ideas did not correlate at all (R =70.16, p = 0.50). Perhaps, in these early phases of generating ideas, the quality of the sketches are not very important, especially if the participants have the opportunity to explain their idea sketches.

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In various creative problem solving meetings that we have facilitated in the past years, we have included techniques that involve sketching, among which the brainsketching technique. Usually these were meetings within the domains of engineering and marketing, with participants from a variety of backgrounds. Our experience is that non-designers can very well engage in sketching activity, provided that they are given the proper directions. The main problem encountered, when applying brainsketching in groups with nondesigners, is that these participants are inclined to immediately accept the first idea sketch on the paper as the basic direction for further idea generation. For instance, brainsketching was applied during a new business development meeting of a large consumer products company. The goal of this meeting was to explore opportunities regarding ‘health monitoring’. After an initial step of redefining the problem, the group members generated ideas by using an adaptation to brainsketching in which participants were asked to sketch ideas in pairs. Four rounds of generating ideas took place. In between rounds the participants were asked to briefly explain their ideas. Figure 11 shows one of the resulting flipcharts. In this meeting, the participants tended to use the previous ideas as a frame for further idea generation. They tended to make amendments to earlier ideas, without challenging the frame set by the earlier idea. In the example, the initial idea sketched was to perform health

Figure 11. Brainsketching Flipchart from a New Product Development Idea Generation Meeting with Non-designers

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monitoring through a ring on one’s finger. In the next rounds, various additions were provided. For instance, having medication in the ring, in order for the ring to not only function as a monitor, but also as a dispenser. Another idea was interaction with the health monitoring through a personal computer. Two possible reasons for this early fixation taking place are: 1) It requires effort for the participants to set up an entirely new sketch. Using an existing idea as a basis for sketching, and making adjustments to that earlier sketch is much easier. 2) Because a sketch provides an idea with more detail than written notations, participants are not able to reflect on the idea in any other way than by judging it. Unlike the designers, the participants appear to be unable to regard the sketch as a mere snapshot of an idea generation process, and interpret it accordingly. The following guidelines for using idea generation techniques that involve sketching with non-designers have helped overcome the difficulties of using brainsketching with non-designers: 1) Proper warming-up activity. To take away apprehension of using sketching as a means for expressing ideas, a warming-up activity is needed. Such an activity can show that nondesigners can properly communicate through sketching, and that the quality of the sketch itself is not so important, because much of the information contained in a sketch is provided when the participant who drew the sketch explains it. 2) Emphasizing interpretation and exploration of ideas, rather than evaluation of ideas. As the participants may be inclined to assess the value of the idea sketches as finished product proposals, it is especially useful to ask the participants to stay away from value judgments regarding the quality of the idea. Ask the participants to freely imagine the consequences, or suggestions that the idea sketch provides for the generation of new ideas instead. Questions like, ‘what unique qualities are in this sketch that you would like to explore further?’ direct the participants towards constructive interpretation, rather than critical evaluation of the idea sketches produced. 3) Invite making new drawings, rather than drawing on the existing one. If participants are very focused on working within the same basic sketch, one can ask them to make new sketches, instead of adding features to the earlier sketch. This can even provide a steering mechanism: Drawing on the existing sketches emphasizes idea development and making

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new sketches emphasizes differentiation of ideas, as participants will not be inclined to produce replicas of the existing sketches.

References Bly, S.A. (1988) A use of drawing surfaces in different collaborative settings. In Greif, I. (ed.), Second Conference on Computer-Supported Cooperative Work. Association for Computing Machinery New York, pp. 250–256. Cross, N., Christiaans, H. and Dorst, K. (eds.), (1996) Analysing design activity. Wiley, Chichester, UK. Finke, R.A., Ward, T.B. and Smith, S.M. (1992) Creative cognition: Theory, research, and applications. MIT Press, Cambridge, MA. Fish, J. and Scrivener, S. (1990) Amplifying the mind’s eye: Sketching and visual cognition. Leonardo, 23, 1, 117–126. Geschka, H., Schaude, G. R. and Schlicksupp, H. (1973) Modern techniques for solving problems. Chemical Engineering, August, 91–97. Goel, V. (1995) Sketches of thought. MIT Press, Cambridge, MA. Goldschmidt, G. (1991) The dialectics of sketching. Creativity Research Journal, 4, 2, 123–143. Goldschmidt, G. (1995) The designer as a team of one. Design Studies, 16, 2, 189–210. Goldschmidt, G. and Weil, M. (1998) Contents and structure in design reasoning. Design Issues, 14, 3, 85–100. Gryskiewicz, S.S. (1980) A study of creative problem solving techniques in group settings. Unpublished doctoral dissertation, University of London. Hocevar, D. (1979) Ideational fluency as a confounding factor in the measurement of originality. Journal of Educational Psychology, 71, 2, 191–196. Isaksen, S.G., Dorval, K.B. and Treffinger, D.J. (2000) Creative approaches to problem solving. Kendall & Hunt, Dubuque, IA. Lakin, F.A. (1988) Performing medium for working group graphics. In Greif, I. (ed.), Computersupported cooperative work: A book of readings. Morgan Kaufmann Publishers, San Mateo, CA. McKim, R.H. (1972) Experiences in visual thinking. Wadsworth, Boston, MA. Muller, W. (2001) Order and meaning in design. Lemma, Utrecht, Netherlands. Nijstad, B.A. (2000) How the group affects the mind: Effects of communication in idea generating groups. Doctoral dissertation, Utrecht University. Osborn, A.F. (1953) Applied imagination. Scribner’s, New York. Osborn, A.F. (1963) Applied imagination (3rd edn). Scribner’s, New York. Purcell, T. and Gero, J.S. (1998) Drawings and the design process. Design Studies, 19, 4, 389–430. Scho¨n, D.A. (1983) The reflective practitioner. Basic Books, New York. Scho¨n, D.A. and Wiggins, G. (1992) Kinds of seeing and their functions in designing. Design Studies, 13, 2, 135–156. Scrivener, S.A.R. and Clark, S.M. (1994) Sketching in collaborative design. In MacDonald, L. and

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Vince, J. (eds.), Interacting with Virtual Environments. Wiley, Chichester, U.K. Stroebe, W. and Diehl, M. (1994) Why groups are less effective than their members: On productivity losses in idea-generating groups. In Stroebe, W. and Hewstone, M. (eds.), European Review of Social Psychology, volume 5. Wiley, London, pp. 271–303. Tang, J.C. and Leifer, L.J. (1988) A framework for understanding the workspace activity of design teams. In Greif, I. (ed.), Second Conference on Computer-Supported Cooperative Work. Association for Computing Machinery, New York, pp. 244– 249. Valkenburg, R. (2000) The reflective practice in product design teams. Doctoral dissertation, Delft University of Technology. VanGundy, A.B. (1988) Techniques of structured problem solving (2nd edn). Van Nostrand Reinhold, New York. Van der Lugt, R. (1999) Graphic tools for creative problem solving in design groups. Paper presented

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at the European Association for Creativity and Innovation Conference, December 12–15 Lattrop, The Netherlands Van der Lugt, R. (2000) Developing a graphic tool for creative problem solving in design groups. Design Studies, 21, 5, 505–522. Van der Lugt, R. (2001) Sketching in design idea generation meetings. Doctoral dissertation, Delft University of Technology. Ward, T.B., Smith, S.M. and Finke, R.A. (1999) Creative cognition. In Sternberg, R.J. (ed.), Handbook of creativity. Cambridge University Press, Cambridge, UK, pp. 189–212.

Remko van der Lugt is Assistant Professor in Design Methodology at the Department of Industrial Design Engineering, Delft University of Technology, The Netherlands.

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Users as a Hidden Resource for Creativity: Findings from an Experimental Study on User Involvement Per Kristensson, Peter R. Magnusson and Jonas Matthing The main objective of this article is to report the empirical findings from a study on user involvement in service innovation. In doing this, we seek to answer the question of how user involvement affects the originality of new service ideas. An experimental investigation was carried out which included 54 participants arranged into three groups of creative users, ordinary users and professional service developers. The empirical data revealed that the users produced more original ideas than the company’s professional service developers. It is thus suggested that business organizations attempt to innovate original products would benefit from involving their customers.

Introduction

A

ll innovation begins with creative ideas (Amabile, 1996; Amabile, Conti, Coon, Lazenby & Herron, 1996). The development of successful services, the implementation of new processes, the design of new products and their introduction onto the market all depend on a person or a team coming up with a good idea and developing this idea beyond its initial state. Launching a novel product, based on an original idea, in the field will increase the chances of gaining market share, thus implying a major financial advantage for a company. One critical phase in product and service development is the early idea phase. Nevertheless, one of the least understood aspects of innovation is real leaps of creativity (Cooper, 1993). Research concerning products that are perceived as being creative reveals that they elicit a distinct set of aesthetic responses from observers, e.g. surprise, satisfaction, stimulation and savouring (Amabile, 1996). Early findings (Guilford, 1950; Barron, 1955) concluded that originality was an important dimension of a creative new product. Creativity results in the production of some novel out-

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put that is satisfying and represents a real leap forward from the current state of the art (Stein, 1974). The originality of a product is explained by its uncommonness in a particular situation and its applicability to a given problem (Amabile, 1996). Recent research has identified some explicit product characteristics (dimensions), as discriminating signs of a creative product (Amabile, 1996; Besemer & O’Quin, 1987). The employment of dimensions in order to assess creative products is ultimately considered as the most useful procedure for creativity research in general (Amabile, 1996). According to Besemer and O’Quin (1987), dimensions that capture a new product, product ideas, or creativity in general, are characterized by novelty, resolution, and elaboration. The degree of originality is implied by the dimension novelty. In the literature (e.g., Isaksen, 1987) novelty is commonly and frequently referred to as the most obvious attribute of creativity in products. The extensive interest in the novelty dimension is perhaps explained by the fact that uniqueness of ideas is being held as an important criterion for product success (Booz, Allen & Hamilton, 1982). In other words, the future of a company today, is to a great extent # Blackwell Publishers Ltd 2002. 108 Cowley Road, Oxford OX4 1JF and 350 Main St, Malden, MA 02148, USA.

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determined by the potential of their product portfolio under development. Hence, one important objective for an organization is to have the capability to present unique, and thus innovative, products. As many companies have the ambition to be innovative, originality is the concept that enfolds the innovative dimension. Today, both scholars and practitioners have placed an emphasis on unique ideas (Cooper, 1993). This uniqueness, note, applies to the uniqueness perceived by the customer (Crawford, 1977; Stevens, Burley & Divine, 1999). On the basis of these findings, normative research has emphasized the involvement of customers in the development of new products and services. Since the customer using a new product or service always ends up as the adjudicator of this product, and thereby its success, the research literature has proposed customer involvement in new product and service innovation (e.g., Prahalad & Ramaswamy, 2000). More specifically, the customer is thought of as a co-producer and idea generator for new products and services (Prahalad & Ramaswamy, 2000; von Hippel, Thomke & Sonnack, 1999; Ramirez, 1999; Wikstro¨ m, 1995). The logic behind this reasoning is that if the customers are the ones who can decide whether a product idea is unique or not, then he or she should be thought of as a valuable source for initiating profitable ideas. This greater focus on the customer is not, perhaps, entirely new. The conception of the customer as a co-producer, however, is another step forward. According to Wikstro¨m (ibid) deepening the interaction between customers and manufacturers improves the level of creativity. Since creativity plays an important role in the front-end innovation phase, co-opting customer competence, and involving them into the process, ought to be extra contributing in product development projects. However, whether or not customers or users have really contributed with more creative ideas has not been thoroughly investigated in previous research. There are indications that users are the real source of many innovations (von Hippel, 1988), but this does not answer the question whether or not users contribute with more creative product or service ideas than the company itself.

Purpose and scope The purpose of this paper is to report the empirical findings from a study on user involvement in service innovation. The focus of the paper is on the users’ contributions to the originality of the generated ideas.

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Thus, the research question is formulated as follows: How does user involvement in service innovation affect the originality of the service ideas produced?

Method A working hypothesis for the study has been that user involvement in the service innovation process does affect the end-result with regard to unique ideas. In other words, it has been assumed that user involvement will make a difference compared to the involvement of only professional service developers in the development process – without the interaction of users. The interest is to pinpoint the actual differences and learn how to utilize them for improving user involvement. A cornerstone of our research has been to simulate a real situation of user involvement as realistically as possible. In other words, the research design itself should constitute a realistic way of organizing user involvement. The context chosen was the development of end-user services based on the GSM (Global System for Mobile Telecommunications) standard SMS. These services can be categorized as technically based self-services (Dabholkar, 1996). The platform used in the study is called Unified Services (US). US is essentially a converter between SMS1 messages (text messages via the mobile phone) in GSM and http-calls on the Internet. From the users’ point of view, US enables access to information on the Internet by sending and receiving SMS-messages. Furthermore, US can also be used for remote control. It is for example possible to create a service that can switch lights on and off in a home or a radiator in a building, or check whether a door is locked by just sending an SMS.

Sample All non-professional participants, i.e. the users, were volunteered students from Karlstad University, recruited during lectures. The reason for choosing students is that they represent one of the most frequent user groups of the GSM/SMS service in focus during the study and, thus making them, realistic users. The professional participants in the control group worked as service developers at the R&D department of a leading telecommunications company in Sweden.

Design In the CuDIT (Customer Driven IT) project an experimental method was chosen. The basic

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idea was to design a study that compared new services generated by professional service developers at a company to services generated by users. In doing so, conclusions could be drawn regarding the actual value of user involvement by way of their contribution in an experimental setting. The design was a Multiple-Group Posttest Design (Spector, 1993, p. 38) using three groups. The first was a control group consisting of 12 professionals in service development, i.e. this group did not have any user involvement. The other two groups consisted of 19 and 17 ordinary users, represented by students in non-technical study programmes, e.g. social science, teacher training, business administration, etc. The difference between the two user groups was that in group three (with 17 participants) the students had been educated in different creativity techniques (henceforth creative users). The independent variable was the user involvement strategy (type of user) and the dependent variable was the originality of service idea (see Table 1 for design).

Limitations From a methodological perspective, the design has two weaknesses. It does not use truly random assignment of the participants, nor does it have full control of the process during the experiment. Random assignment was not practically possible for any of the usergroups. Group one was picked at random; however the two other groups were volunteers. Although groups two and three were not assigned at random, we claim that they are most probably representative of the group of people that would participate in this kind of endeavor. The argument for this is that the whole setting of the experiment was designed in a similar manner to what could be employed in a real situation. The other problem to tackle is the limited amount of control over the experimental process. During the idea generation (12 days), the participants worked with the task on their own, though with the possibility of contacting us if problems arose.

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To deal with this, all participants were equipped with a logbook (diary). After completion of the trial, all participants were interviewed as well; particularly about the incidents that took place around the ideas they had reported. Process data was thus collected from both the diary and the interviews. However, this data is not included in the analysis in this paper.

Procedure The actual experiment consisted of four stages; initiation, idea generation, termination, and evaluation (see Figure 1). Initiation At the initiation meeting, users were gathered and the scope of the study was outlined. Then the application platform, US, was demonstrated to the participants. The purpose was to give them a feeling of the range of possibilities for these kinds of services. The task and instructions were handed out, in both oral and written format. All participants, with the exception of the professional service developers, were given the task of creating service ideas that they perceived as valuable to themselves. The experts, on the other hand, were instructed to design services that they thought would bring added value to the students at Karlstad University. By carrying out these different formulations, all groups were actually trying to satisfy the same target group, namely the students at Karlstad University. Consequently, it was possible to compare the ideas created for new services. The participants were instructed to document the idea creation process in a diary that was handed out to them. The purpose of the diary was twofold, to function as a method for triangulation and to collect process data. The participating users were also equipped with mobile phones containing a special account, since they were to come up with services ideas for this type of equipment. To provide the participants an even better sense of how these services work, they were given

Table 1. The Design of the Experiment Independent variable

Process

Dependent variable

Type of user: – Professional developers – Ordinary users – Creative users

Idea generation of new services for mobile telephony

Creativity: – Originality

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Figure 1. Outline of One Trial in the CuDIT Experiment access to a sample of 10 already implemented services. To be able to test these, and to gain motivation during the experiment, the phones had a credit of approximately 252 and a socalled chat-board. All participants received hands-on training on how to use the phone through testing some of the services. Idea generation The generation of ideas lasted for 12 days. During this period, participants were to create service ideas by themselves and log them in their diary. An estimate of the amount of time spent on idea generation was on average established to half an hour each day. Termination After 12 days, the idea generation period was concluded and a meeting was held. All equipment was returned and the participants submitted their ideas into a service description. These were written descriptions of the service ideas generated in a pre-defined format. Evaluation After all trials had been concluded and the service descriptions were collected, the evaluation phase followed. In the CuDIT project several dimensions of the service ideas have been evaluated, here we will discuss one of them, originality. In order to evaluate them, we used one panel consisting of experts within the given domain (Amabile, 1996), mobile services, and one panel of users consisting of university students (see below for a more detailed description).

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Measures The assessment method was based on the Consensual Assessment Technique (CAT), (Amabile, 1996). CAT uses a panel of independent judges to evaluate different designs presented to them. ‘Design’ is a generic word for the object to be evaluated. The technique builds upon comparing different designs and judging them in relation to each other, as well as ranking them. The type of judge evaluating a certain result can affect the evaluation, and thus also the (research) question of the value of involving users. For example, a company expert might evaluate the perceived user-value very differently to an ordinary user. In the CuDIT project, two different panels of judges were used to evaluate the ideas. These were (Panel 1) experts (professionals) and (Panel 2) customers (here in terms of students from Karlstad University), both groups familiar with mobile telephony services. Before evaluating the originality dimension, the rating system was described both orally and in writing. A scale of one to ten was used for rating the originality of the service ideas generated. In order to ‘calibrate’ the judge’s perception of the dimension to be evaluated, a test round was conducted. Five service descriptions were picked and assessed individually by the judges. After the individual assessments, the results were discussed in the group. The purpose of this round was to ensure that the judges had understood how the dimension was to be evaluated. After this, the judges rated all the service ideas (objects) for the dimension in question.

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The assessments were made individually. Each judge had a paper copy of each service description.

Results Interjudge reliabilities Ahead of analyzing the research question, an interjudge reliability test between Expert and Customer panels was carried out. A Pearson bivariate correlation test showed significant results for the Expert panel as regards their assessments of the originality variable. The strongest correlation (Pearson’s r) obtained was 0.62 ( p < 0.001) and the weakest 0.29 ( p = 0.009). The judges’ evaluations of the originality of the generated ideas was perceived as satisfactory. Therefore, the individual scores were averaged to a mean score for further statistical analysis. Similar to the Expert panel, an interjudge reliability test was carried out for the Customer panel. Overall, the Customer panel showed significant correlation as well, although one pair of ratings turned out non significant. The strongest correlation (Pearson’s r) received were 0.57 ( p < 0.001) and the weakest 0.05 ( p = 0.626). Although two judges showed an unsatisfactory agreement the overall scoring was estimated to be appropriate for further statistical analysis. Consequently, the individual scores were averaged to a mean score. The effect of user involvement on originality The dependent variable, the originality of the generated service ideas, was tested by means of a one-way ANOVA. Table 2 shows the scoring for the various independent variables, according to the two panels. In respect of panel one (Experts) a one-way ANOVA showed significant differences re-

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garding the originality between the groups [F (2, 242) = 7.33, p < 0.001]. A post hoc comparison (Scheffe´) indicated that the creative trained users had more original service ideas as compared to the company experts ( p = 0.011). The difference between the company experts and ordinary users was close, but not, significant ( p = 0.102). In respect of panel two (Customer) a one-way ANOVA also showed significant differences regarding the originality between the groups [F (2, 242) = 4.87, p = 0.008]. A post hoc comparison revealed that the creative users had more original service ideas as compared to the company experts ( p < 0.001). There were no significant difference between the company experts and the ordinary users ( p = 0.413).

Discussion The present study challenges the normative view that organizations need to consider the voice of the customer when developing new innovative products. This was done by empirically investigating company professionals and users involved in the idea generation of service ideas. The assumption that customer involvement in the early stages of product development would result in more original ideas is supported by the present findings. There are primarily two interesting results which can be derived from the study and which will be discussed here: 1. Customers generate ideas that are more original than the ones generated by the company. 2. Customers generally assess innovative ideas different from the company. It is an interesting fact that, in any event, the creativity trained users generate more

Table 2. Mean scores (and SD) for the originality across the three groups Panels

Groups

Panel one (expert judges)

Panel two (customer judges)

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M

SD

1 Company experts 2 Ordinary users 3 Creative users Total

55 123 67 245

2.99 3.55 4.10 3.57

1.07 1.79 1.58 1.64

1 Company experts 2 Ordinary users 3 Creative users Total

55 123 67 245

4.71 5.05 5.58 5.12

1.38 1.59 1.71 1.60

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original ideas than the professional service developers. One plausible explanation for the results is that users have different cognitive styles of solving problems, often referred to as divergent thinking (Guilford, 1967). Convergent thinking, which is characterized by logical reasoning and problem-solving along established principles, is stimulated and sought for in many working situations. Accordingly, professional service developers may have seen technology grow from an initial state to a more mature and advanced platform over the years. Simultaneous to this, creating a very deep understanding of the technology itself might also become a burden against creativity. The knowledge creates a rigidity in thinking style, professional developers do not think outside the current capabilities of the technology. Since the customers do not possess the same technical skills, they are sometimes able to generate ideas that integrate, in a novel fashion, technology with their personal environments (i.e. needs and requirements). Furthermore, it is mostly a fact that professional developers and R&D staff do not live in the same environment as their customers, which is why it seems natural that a customer is able to provide more original service ideas. After all, it is difficult to envisage other people’s (i.e., a customers’) situations and unarticulated needs and requirements. In respect of evaluating the ideas, experts and users made the same group-wise ranking of the originality of the generated service ideas. Overall, however, the expert panel gave the ideas a lower score than the customer panel. The reason for this is probably due to the circumstance that they have more knowledge of the current state of the art. Accordingly, non professionals seem to be unnecessary as judges of the relative originality of a group of service ideas. On the other hand, the customer panel appear to perceive the absolute originality on a higher level than the experts, which is why the user is a valuable instrument in indicating the absolute originality of an idea. The research undertaken can be viewed in the light of the classic market debate concerning the two strategies, or business philosophies, of technology push and market demand. In innovation research, recent findings have proposed a market demand approach, aiming to develop competitive new products by incorporating and listening to the voice of the customer (Griffin & Hauser, 1993). However, most of this research suggests the involvement of customers for the sake of customization, and not for the sake of finding original products (Christensen, 1997). As the empirical

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findings of this study suggest, users are able to create original and unique ideas, inclining toward the business philosophy of market demand. However, before drawing any final conclusions there is a need to reflect on at least two additional aspects. The first concerns how the originality, or other dimensions of the service ideas, will be affected by an interactive exchange of ideas between users and professionals. In the present study, users and professionals did not interact, and further research is needed in order to explore this matter. The other aspect concerns the question of whether the service ideas developed are possible to implement from a producibility point of view. The ideas generated proved to be original, but how do these ideas rate in respect of other dimensions, such as usefulness or, as mentioned, producibility. Taken together, our study indicates that user involvement in service innovation can contribute to the creativity in the service ideas produced. In respect of the development of new services then, one managerial implication of this study suggests that business organizations, attempting to produce innovative and successful products, have a hidden resource in their customers.

Notes 1. SMS is an acronym for short-message-service, and is a technology for sending and receiving text-messages to the mobile phone. SMS is defined within the GSM specification. GSM is a pan-European standard for mobile telephony. The system was introduced in Europe in 1992, and is today spread all over the world. 2. The cost for sending an SMS message was 0.17 or $ 0.15.

References Amabile, T.M. (1996) Creativity in Context. Westview Press, Boulder, Colorado. Amabile, T.M., Conti, R., Coon, H., Lazenby, J. and Herron, M. (1996) Assessing the work environment for creativity. Academy of Management Journal, 39, 5, 1154–1184. Barron, F. (1955) The disposition toward originality. Journal of Abnormal and Social Psychology, 51, 478–485. Besemer, S.P. and O’Quin, K. (1987) Creative product analysis: Testing a model by developing judging instruments. In Isaksen, S.G. (ed.), Frontiers of Creativity Research. Bearly Limited, Buffalo. Booz, Allen & Hamilton. (1982) New Products Management for the 1980s. Booz, Allen & Hamilton, New York.

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Christensen, C.M. (1997) The Innovator’s Dilemma. When New Technologies Cause Great Firms to Fail. Harvard Business School Press, Boston. Cooper, R.G. (1993) Winning at new products: Accelerating the process from idea to launch. Perseus Books. Crawford, C.M. (1977) Marketing research and the new product failure rate. Journal of Marketing, April, 51–61. Dabholkar, P.A. (1996) Consumer evaluations of new technology-based self-service options: An investigation of alternative models of service quality. Research in Marketing, 13, 29–51. Griffin, A. and Hauser, J.R. (1993) The voice of the customer. Marketing Science, 12, 1, 1–27. Guilford, J.P. (1950) Creativity. American Psychologist, 5, 444–454. Guilford, J.P. (1967) The Nature of Human Intelligence. McGraw-Hill, New York. Isaksen, S.G. (1987) Frontiers of Creativity Research. Bearly Limited, Buffalo. Prahalad, C.K. and Ramaswamy, V. (2000) Coopting Customer Competence. Harvard Business Review, January–February, 79–87. Ramirez, R. (1999) Value co-production: Intellectual origins and implication for practice and research. Strategic Management Journal, 20, 49–65. Spector, P.E. (1993) Research Designs. In Lewis-Beck, M.S. (ed.), Experimental Design & Methods. Sage.

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Stein, M.I. (1974) Stimulating Creativity. Academic Press, New York. Stevens, G., Burley, J. and Divine, R. (1999) Creativity + business discipline = Higher profits faster from new product developent. Journal of Product Innovation Management, 16, 455–468. Wikstro¨m, S. (1995) The customer as a co-producer. European Journal of Marketing, 30, 4, 6–19. von Hippel, E. (1988) The Sources of Innovation. Oxford University Press, New York. von Hippel, E., Thomke, S. and Sonnack, M. (1999) Creating breakthroughs at 3M. Harvard Business Review, September–October, 3–9.

Per Kristensson is Philosophy Licentiate at the Service Research Center, Karlstad University, Sweden. Peter Magnusson, is an Executive PhD Candidate at the Fenix program at Stockholm School of Economics and Telia Mobile. Jonas Matthing is a PhD Candidate at the Service Research Center, Karlstad University, Sweden.

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Configurations of NPD – Production Interfaces and Interface Integration Mechanisms Frido E. Smulders, Harry Boer, Poul H.K. Hansen, Ebbe Gubi and Kees Dorst This paper describes and illustrates different configurations of the interface between new product development and production processes, including both intra-firm and inter-firm interfaces. These configurations are partly based on a process view of product innovation and partly on a structural view of product innovation. In addition to this typology of interfaces some integration mechanisms are described. The typology will serve as a basis for further research aimed at identifying consistent configurations of the different types of integration mechanisms that are available for industry to increase the effectiveness and efficiency of product innovation processes.

Introduction

D

uring the last two decades various interconnected trends have emerged, which have had and will continue to have serious implications for the context in which industry operates. The trends that are important for the argument developed in this paper, include: . A (further) move from vertically integrated

companies to core business driven companies (specialists in a limited number of functions) collaborating in supply chains and networks. (e.g. Lewis, 1995; Trent & Monczka, 1998; Quinn, 1999). . From management within one hierarchy (hierarchical control) to increased ’managerial control’ of and by partners in the market place (market control). . From colocated collaboration on-site to dispersed collaboration between sites, other companies or even competitors (e.g. Baldwin & Clark, 1997). . From few to many essentially different partners. In other words, the scene has changed from a relatively simple industrial texture to an increasingly complex one. The implications of these trends are many. The most interesting ones for the research presented here are that it is no longer within

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the hierarchy that the communication on the interface between functions involved in product innovation (e.g. marketing, product development, production development, production, distribution) takes place. Rather, the communication on and the management of the interfaces move to the increasingly complex market of (possible) partners, i.e. suppliers and customers. At the same time, however, the increasing performance demands that follow from increasing demands from the end users of products (functionality, price, speed, variety) require collaboration if not integration of the specialists working together in supply chains and networks. These trends must have serious impact on the process, technologies, organisation and management of the interfaces between partners offering the marketing, product development, process development, production and distribution ‘services’ that, together, are needed to initiate, develop, produce and bring to the market place, new products. This results in a whole new category of management decisions, concerning the ‘design’ of the supply chain that have to be taken by the managers of the outsourcing company and the suppliers. But what would be the grounds for such decisions? What are the alternatives? And what are the pros and cons of these different types of interfaces? # Blackwell Publishers Ltd 2002. 108 Cowley Road, Oxford OX4 1JF and 350 Main St, Malden, MA 02148, USA.

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This paper takes a first step towards building up a body of knowledge that could answer such questions. It does so by providing a framework for different types of interactions between companies, and developing a typology of interfaces. This typology will serve as a basis for further research aimed at identifying consistent configurations of the many different types of integration mechanisms that are available for industry to increase the effectiveness and efficiency of product innovation processes. In order to reduce the complexity of the research, we decided to first focus on the interface between new product development1 (NPD) and production. And in this, we will only focus on new or customised, not standard, parts, components, sub-assemblies or products, which have to go through some sort of development cycle in order to fit the requirements that have been formulated for the new product. The reason for looking at this particular interface is that the quality of the NPDprocess is largely a function of the implementation of the NPD results within the production. Poor implementation means that the product and process descriptions NPD has delivered are not yet finished or too poor for production to actually start producing the new or customised design. Boer and During (2001) have found that companies tend to overlook the organisational adaptations required to successfully develop, produce and launch innovations. This was found in all three different types of innovation processes they included in their research, i.e. product innovation, process innovation and organisational innovation. This point, and the fact that NPD and production are essentially different types of activity, makes the NPDproduction interface a particularly interesting one to study. In order to find our way within this complex environment of interfaces, we need to create an overall picture of these different types of interfaces. In fact, a typology of interfaces that could serve as a more generic umbrella for the research projects in this area, including the ones that we are currently involved in (see Appendix). We will do this by making use of two generic system perspectives, i.e. the process view and structural view of the product innovation process. The structural view of product innovation provides a description of the organisational units involved. The process view provides a description of the set of activities needed to produce a specific output. It implies a strong emphasis on how work is done, in contrast to who is doing the work. To complete the picture we

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additionally need to address the question of what is being done. This could be regarded as a separate, content view. In this paper, however, we will approach this view as an interface combining the structural and process views. In the next two sections we will introduce the process and structural views. Then we shall combine the two views into a comprehensive framework and introduce the notion of task as the interface between the two views. An example will illustrate some of our current thinking. Next, we will provide an overview of integration mechanisms that companies could use to configure the NPD – production interfaces so that they contribute to the success of their product innovation processes. The paper concludes with some implications for further research.

Process view of product innovation The notion of processes has gained significant attention in the past years due to the managerial focus on Business Process Reengineering (Davenport, 1993). To create a process structure for NPD we need to come up with a generic division of activities that together make up the process structure. In the field of product innovation studies the process of innovation is in its broadest conceptualisation believed to embrace ‘periods of design and development, adoption, implementation, and diffusion’ (Slappendel, 1996). These periods of activities more or less cover the product innovation process, however these are too generic. We have found many other process descriptions by different authors. Although most of these models describe quite similar phases around the actual development of the product, many of them include different phases at the beginning and the end of the product innovation process. Some of them include strategic processes like ‘strategic planning’ (Archer, 1971), ‘strategy formulation and policy making’ (Roozenburg & Eekels, 1994), ‘direction setting’ (Buijs & Valkenburg, 2000), and ‘vision building and strategic analysis’ (Smulders et al., 1996) at the beginning of product innovation. At the end of the process authors include phases like ‘launch’ (Cooper, 1993), ‘production and sales’ (Andreasen & Hein, 2000), ‘market introduction’ (Smulders et al., 1996), ‘ramp up and production’ (Ulrich & Eppinger, 1995) and ‘distribution, sales and use’ (Roozenburg & Eekels, 1994). In this paper we will consider the product innovation process as one single process

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initiated by an idea and ending with a specific product ready to be delivered at the market. We will not include the use of the product by the customer, nor the strategic phase often referred to as ‘fuzzy front end’. Following this delimitation the process can be divided into five generic phases: Concept Development, Product Development, Production Preparation, Production, Delivery (see Figure 1). This means that the object of innovation will gradually change over time. Of course, each of these overall phases can be broken down into several sub-processes. In reality, innovation processes are highly unlikely to evolve according to this neat, linear and sequential model. The real process will be a more simultaneous and iterative way of going through the various stages. However, all stages will somehow have to be addressed during the product innovation process.

Structural view on product innovation There is a multitude of relationships between NPD and production. It is not longer the case that companies just have an in-house NPD department that has to collaborate with the in-house production. There are many more configurations at hand in terms of e.g. early involvement of customers within the NPD processes, co-design with first tier suppliers, etc. All these different forms of involvement from external partners create different types of interfaces with different patterns of interactions across the interface. In order to find our way within this complex environment, we need to create an overall picture of the different types of interfaces. Two starting points helped us create an overall picture of the different types of interfaces between NPD and production. First, if we want to create insight into the force field that is present around the interface between the NPD and the production processes we need to identify the legal structure around this interface. The simple fact that more than one legal entity is involved when we have suppliers taking part in the product innova-

tion process may have substantial influence on the interface between NPD and production. Second, the party who is initiating the outsourcing of work to another party will influence the force field and, through that, the interface. This partner will be the one who is responsible for the product innovation process. We will label this party as the lead partner and the party on the other side as the supply partner. The lead partner initiates all the work in the supply chain regarding the customised part(s) of the new product. The positions of the two partners, relative to each other, may affect the specific form of the interface between NPD and production. In the case of an inter-firm partnership, the customer is of course in the lead, at least initially. His formal power may in fact turn out to be much lower than in an intra-firm relationship in which hierarchy, rather than market mechanisms, determines who is actually in the lead. From these two starting points we created our first idea of a typology for interfaces that can exist between NPD and production. In the following section we will categorise these interfaces by two dimensions: . What function(s) has the lead partner in-

house (i.e. within one legal entity). . What function(s) are delivered by the

supply partner(s) regarding new or customised systems, modules, components, and parts.

A typology of NPD – production interfaces If we apply the two dimensions (in-house functions of lead partner, functions of supply partner) to the companies we have seen in previous and ongoing studies in which we have been involved, we get four different types of lead partners (see Table 1) on one axis. On the other axis we identified four possible configurations of supply partners that play a role in the interface between the NPD and the production process. This makes a 464 matrix with 16 possible variants. Only 12 out of these 16 variants are relevant in the paper. The four

Figure 1. Process Structure of the Product Innovation Process

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other variants miss either NPD or production and therefore do not have an NPD-production interface. Although more than one relationship type is possible within one product innovation process, we will discuss and illustrate each of these 12 variants separately.

Lead partner type 1: Lead partner has NPD and production This type of lead partners, with in-house NPD and in-house production, is still much around in business. This does not necessarily mean though that they are fully integrated companies. In fact, we think that very few companies are left that do not do any outsourcing of part of NPD or part of production. This is also the only configuration that has an internal as well as an external interface between NPD and production. In this paper we will not illustrate the internal interface.

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Interface type 1A: o Components/parts that are developed in-house and produced externally o Interface NPD/production within two legal entities The lead partner makes the specifications, drawings and maybe even a prototype of the components. A supply partner will do the full production of these components according those specifications. There are many examples of this variant: metal body parts of cars, injection mould covers for televisions, microprocessors, mechanical subassemblies, etc. Interface type 1B: o Components/parts that are developed externally and produced in-house o Interface NPD/production within two legal entities

Table 1. Supplier Involvement Regarding Components and/or Sub-assemblies

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In this configuration part of the design, e.g. the outer appearances of the new product, is outsourced to a famous designer. Examples of this are the body designs of cars by e.g. Pinifarina, Bertone, or Alessi’s link with Philips. This could also concern other parts of the product like specific engineering calculations or the development of a gearbox. Of course more than one supplier can be involved in the development, each developing different parts. However the lead partner does the integration of all these parts. Interface type 1C: o Components/parts that are developed externally and produced externally o Interface NPD/production within two legal entities This variant occurs when the lead partner orders from the same supply partner the development as well as the production of a specific component. In most cases such a supply partner has specific knowledge that is not present at the lead partner. E.g. the development and production of optical lenses for theatre lighting or the brake system of cars. This interface becomes more complex if the lead partner has two such suppliers that have to collaborate during their respective development processes. E.g. one that supplies the lenses and another one that supplies the reflector of the same lamp. Interface type 1D: o Components/parts that are developed externally (supplier X) and produced externally (supplier Y) o Interface NPD/production within three legal entities The development of specific components is outsourced to supplier X. The production of that same component is outsourced to another supplier, Y. E.g. the design of a television set is done by a famous designer (supplier X) and produced by an injection moulding company (supplier Y).

Lead partner type 2: Lead partner only has production and no NPD The lead companies in this case are very much oriented to production. They cannot develop new products themselves but need design companies to do that for them. It might be so that those companies in earlier days produced their own products. However, the increased complexity of technologies and increased market demands made it necessary to either create a NPD-department, thus

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becoming a lead partner type 1, or outsource the development. It is even possible that more than one supplier is involved in order to develop the complete product. The question then is, who is responsible for the integration of the various parts, since the knowledge for doing so might not be present at the lead partner (there is no NPD). Interface type 2A: Outsourcing of production, misses the interface with NPD and is therefore outside the scope of this paper. Interface type 2B: o Components/parts that are developed externally and produced in-house o Interface NPD-production within two legal entities The development of (part of) the new product is outsourced. As already mentioned, the involvement of more than one supplier in the development of the product raises the question of integration. However, we know of companies that outsource the concept development and after that also outsource to a different supplier the engineering of all components. In such a case there will be two (or more) suppliers involved in the NPD part. We also know of companies in e.g. the biking business, which outsource the development of mudguards, chain guards, lamps etc. Production takes place at the lead partner. These products are sold to the bicycle industry for first fitting on new bikes and to retailers for second fitting. Interface type 2C: o Components/parts that are developed externally and produced in- and externally o Interface NPD-production within two legal entities This interface type is expected to often go together with type 2B. E.g. the product is developed by a design agency. However some components need additional development by another supplier who also produces that component and delivers it to the lead partner. Let us consider again a company that produces lamps for bikes as a lead partner. They demand a design of a new lamp by a design agency, which comes up with a new lamp that has an electronic component. Neither the agency nor the lead partner has enough knowledge on this technology and the lead partner is also not able to produce the component. The lead partner asks a supplier of type 2C to do additional development and

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produce the lamp. The assembly will be in the production line of the lead partner. Interface type 2D: o Components/parts that are developed inand externally and produced externally o Interface NPD/production within three legal entities Here we have the situation that product development is outsourced to company X and part of the production of that newly developed product is again outsourced to company Y. The other part is done by the lead partner. If for example the lead partner is very good at injection moulding, but also needs for a certain product a customised metal component or sub-assembly, then they need to outsource that to another supplier (Y).

Lead partner type 3: Lead partner only has NPD and no production Lead partners like these could be large engineering, design or trading companies that are able to do the development of new products. They do not have any production, other than maybe a prototype shop. All production must be outsourced according to their specifications. Another possibility is that they outsource part of the NPD (e.g. engineering, concept, etc.). They might have a shipping department. Interface type 3A: o Components/parts that are developed in-house and produced externally o Interface NPD/production within two legal entities In this situation the lead partner sends the drawings, bill of materials and other relevant information to the supplier that will produce the component, sub-assembly or product. E.g. a design agency comes up with the design of a computer cable roll-up device that shortens the hanging cables and wires in a simple way. They outsource the production and assembly to the same supplier and let them ship it directly to the retailers. Or a lead partner that develops household appliances and let them produce in China. Interface type 3B: Outsourcing of NPD, misses the interface with production regarding the outsourced component and is therefore outside the scope of this paper. If part of NPD is outsourced, then type 3C and 3D are possible interface types.

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Interface type 3C: o Components/parts that are developed in- and externally and produced externally o Interface NPD/production within two legal entities The lead partner in this situation outsources part of the NPD and the production of a component, sub-assembly or complete product to one and the same supplier. In the above mentioned example of the cable roll-up device, not only production is outsourced to the same supplier but also the engineering. Another example is the combination of this interface with type 3A, in which for example an electronic component and the rest of the production including the assembly, is outsourced to another supplier. Interface type 3D: o Components/parts that are developed in- and externally and produced externally by two (or more) suppliers o Interface NPD/production within three (or more) legal entities Here, the lead partner outsources the NPD of a component or subassembly to supplier X and the production of that same element to supplier Y. Consider the situation that the lead partner is a company that is brand owner of a furniture line. Because they are brand owners, they do the conceptual development of new products. Then they outsource the engineering to a specialised engineering company, while the production of that new product is outsourced to another supplier.

Lead partner type 4: Lead partner has no NPD and no production Type 4 lead partners are typically brand owners and trading companies. They have to outsource both NPD and production and therefore to orchestrate all product innovation activities across company borders. Interface type 4A and 4B are not relevant in this paper because there is no interface between NPD and production. Interface type 4C: o Components/parts that are developed externally and produced externally by the same supplier o Interface NPD-production within one legal entity Here the lead partner outsources the development and production of a component, subassembly or complete product to one supplier.

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If this supplier is the only supplier, then he develops and produces the complete product under the brand name of the lead partner. When there are more suppliers, e.g. interface type 4B, then this supplier might develop and produce a component or sub-assembly to fit in the end product. Interface type 4D: o Components/parts that are developed externally and produced externally by two (or more) different suppliers o Interface NPD-production within three (or more) legal entities This interface type concerns the outsourcing of a component, sub-assembly or product to two different suppliers. One that develops the part and the other one to produce it. An example is a lead partner in the child care business. They bring on the market all kind of products to carry and transport babies. For every product in their portfolio, they select a design agency and a separate supplier for production.

Discussion Although the division in different types of interfaces may seem somehow theoretical, for all of these types mentioned we found one or more real life examples. Of course, some of these types occur quite frequently while other types are much more rare. In future research we want to find out what contingencies influence successful co-ordination of the tasks at hand for each of these interfaces. That will bring us closer to providing answers to the managerial issues (like ‘when to outsource what’) that were mentioned in the introduction. But first we will complete our modeling by combining the process and the structural views on product innovation to support that research.

Combining the structural and the process view By combining the structural and the process view we can further classify the interfaces in a matrix like framework (see Table 2). The relationship between the structure and the process is effectuated via tasks. Tasks define what has to be done, e.g. in terms of external requirements and conditions, internal constraints and specified objectives. Starting with the overall strategic task of the enterprise, i.e. its mission, we may develop a structure of tasks and sub-tasks. A task will be carried out in one structural unit but will depend on other tasks in other structural units. Furthermore, in order to realise a given task, a series of activities is required. Thus, tasks relate activities to structural units. The link between two tasks and a specific relationship with a chain of activities constitutes the interface, see Figure 2. In the particular case the supply partner is involved in the product development process and two interfaces have been identified: 1. Interface 1 describes the portfolio of efforts related to task 1 at the lead partner and task 3 at the supply partner according to the concept development phase. 2. Interface 2 describes the portfolio of efforts related to task 1 at the lead partner and task 3 at the supply partner according to the product design phase.

Example of managing the NPD – production interface with involvement of suppliers Company I develops and manufactures audio and video equipment. For a number of years the company had focused on defining core competencies and outsourcing parts of

Table 2. A Matrix of Generic Phases and Interface Types Phases Concept Interface type development

Product development

Product preparation

Production

Delivery

1A

......

1B

4D

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Figure 2. Schematic Illustration of the Combined Process and Structural View Specifying the Interfaces

traditional production. This led to a significant increase in the efficiency of the whole supply chain. Following the success within production of components the company considered applying similar methods in new product development. This included outsourcing of both the development and the production of components. The final assembly would still be done internally. In the automotive industry, this approach has proven to be successful but the batch sizes in company I were much smaller. For some years, the company had outsourced part of the software development but the experiences were not very satisfactory. Some of the internal software people pointed to the role of ownership as the problematic part. It was felt difficult to create this feeling of ownership with the software suppliers. Considering these experiences the company defined a new approach in the product development process. The initial concept development was done internally. As soon as top management approved the concept the involvement of pre-selected partners were initiated. This phase was named the ‘architectural phase’. During this phase the product specifications are defined only loosely and mainly qualitatively. The focus is on defining the modules and, in particular, the interfaces between them.

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The architectural phase is split into five smaller phases: 1) involvement of partners, 2) development of modules and interfaces – I, 3) evaluation, 4) development of modules and interfaces – II, and 5) evaluation and accept. In each of the development phases at least three alternatives are required. During the evaluation phases the different stakeholders (assembly, service, purchasing, logistics, quality assurance, test, etc.) are confronted with the alternative solutions. The fact that the solutions are physical and that there are alternatives, makes it possible for the stakeholders to comment on and assess the different solutions. After the final acceptance of the architecture the traditional product development process begins. During this process the different partners formulate and negotiate specifications. Each partner is responsible for defining their own specifications regarding their part(s) or component of the final product. By doing so, the amount of ownership of these specifications and amount of responsibility regarding these parts or components is increased substantially. The first attempt to organise the process this way was a product with 10 well-defined modules, three of which were fully developed by external partners. External partners produced seven of the modules. The product

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could be assembled manually with no need to use of any specialised tools. Company I is so convinced about the power and the way of handling the architectural phase that they have launched a training program aiming at training a new category of employees: product architects. A new project has recently been launched within the core products of Company I. This project is to follow the same principles as the one reported above. By doing this, the company can increase the capacity of their product development function and thereby add more features for customisation.

Configurations of interfaces and integration mechanisms The objective of this paper was to propose a typology of interfaces that would provide a basis for further research. This ‘static’ model of the interfaces has been presented above. But in order to develop answers to the managerial issues mentioned in the introduction, we need to look at the goals that people have in dealing with these interfaces. An important issue in the field of NPD that could determine the way people deal with these interfaces is the need to reach integration in development processes (Buijs & Valkenburg, 2000; Andreasen & Hein, 2000). Andreasen and Hein have an explicit motivation for this. ‘Product development cannot be carried out in the best possible way if it is allowed to disintegrate into different areas of specialisation, areas of activity or areas of responsibility’ (p. 2). We will now explore whether the typology of interfaces that we have constructed can be combined with the many different types of integration mechanisms that are available for industry. The case study of company I is just one example of the many different configurations of NPD – NPD and NPD production interfaces that companies may consider to increase the success of their product innovation processes. Furthermore, the case study shows a few of the many mechanisms that are theoretically available to achieve an efficient and effective level of co-ordination or even integration on these interfaces. This section of the paper proposes a typology of integration mechanisms that may be used in research projects aimed at identifying and explaining configurations of interfaces and integration mechanisms that appear to enhance the success of product innovation processes. Some of these projects will be briefly described in the final section of this paper.

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The simplest form of an interface element is based on informal comunication between the partners. However, as process, structures and tasks become more complex, these informal contacts often become insufficient, and consequently they must be supplemented by other integration mechanisms, including more formal ones. Organisation theory offers part of a classification of co-ordination and integration mechanisms. Of particular relevance are publications by Galbraith (1973) and Mintzberg (1979). However, according to Paashuis and Boer (1997) there is also a range of non-organisational mechanisms that may serve to achieve co-ordination and integration across interfaces, both on the intra-firm and the inter-firm levels of product innovation processes. These authors propose four categories of mechanisms namely: integration by strategic, process, technological and organisational integration, which can be understood as follows.

Integration by strategy Goals and strategies serve several purposes. The selection of specific goals and strategies to achieve these goals, has considerable consequences. Two issues ought to have great impact on the design of processes, technologies and organisational arrangements, namely: . The choice of product-market combina-

tions. . The role companies want to play in the

market place, both individually and collaboratively, through the qualifying criteria that govern the market and decisions regarding the intentions to win orders in the market. Furthermore, goals give a sense of direction to employees, motivate them, act as guidelines for decision making, and provide a standard for assessment. If well and unambiguously communicated, goals and strategies have great co-ordinating influence on the behaviour of (groups of) employees. Without at least a common sense of direction, it is essentially impossible to know whether current NPD projects are performed effectively, i.e. contribute to the individual companies’ and indeed the supply chain’s or network’s strategy. And similarly, if no or conflicting NPD goals and strategies have been established, it will be impossible to determine the most suitable configuration of activities, technologies and organisational arrangements, both within and on the interface between firms.

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Integration by process Perhaps the most important and certainly the least understood ‘mechanism’ of improving NPD performance is re-designing the design process itself, so that it is optimised from within. Related to business process re-engineering, this involves eliminating activities that do not add value, and simplifying and, if possible, integrating (also organisationally) or even automating (technologically) remaining activities. Research aimed at understanding the process of NPD is relatively recent and the dynamic, relatively unpredictable and pulse-like (rather than flow-like) character of the process (Verganti 1994) does not make the process easy to understand and (re-)design. The product development process can be validly described in two ways: as a mostly linear Rational Problem Solving activity, and as a circular, iterative process of Reflective Practice and Learning (Dorst, 1997). In the NPD cooperation between companies, both the problem solving activity and the learning have to be supported and coordinated.

Integration by technology Technology consists of the knowledge, experience, skills, methods, techniques, tools, machines and equipment people in organisations use to perform their task. The wide range of technologies used in organisations can be divided into three broad categories, namely: ‘humanware’, software and hardware. Given these categories, there are several ways of achieving technological integration. ‘Humanware’ concerns the knowledge, experience, skills, not only in a technical sense, but also including the social and managerial skills (e.g. communication, leadership, decision making, project management), that people use to do their job. Important ‘humanware’-related aspects that affect integration appear to be associated with people’s: . (Predominantly technical) knowledge of

upstream and downstream activities. . Social and managerial skills. . Attitude towards cross-functional co-

operation collaboration and communication. Important mechanisms contributing to the designers performing their own task more effectively (i.e. first-time-right in less time) are: . Formal training. . Training-on-the-job. . Job rotation (e.g. designers working on the

shop floor, for a while). . Management not only committing itself, but

really involving itself and setting the example.

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Software technologies are the methods, work practices, procedures, either automated, in the form of computer software, or not, that people use to perform their task. Some design technologies, especially the applications of information or communication technology, are integrating in themselves, for example computer-aided design (CAD), computer aided process planning (CAPP) and computeraided design and manufacturing (CAD/ CAM); engineering databases (EDB) and electronic data interchange (EDI). Other applications, such as teleconferencing, support the communication between people working on different locations, but are still very much in their infancy. Yet other not necessarily automated technologies in this category, such as quality function deployment (QFD), force design and marketing to collaborate if the techniques are to be applied to their full potential. Failure mode and effects analysis (FMEA) and the whole range of Design for ‘X’ (DfX) (X stands for assembly, manufacturing, etc.) basically do the same for the interfaces between design, manufacturing and assembly. Hardware technology includes tools, machines, computers, handling devices and many other pieces of equipment. In the case of product design, hardware in the form of computers and communication linkages is the medium that enables the use of some of the software applications mentioned before. In a dispersed NPD environment, hardware and software technologies (Information & Communication Technology, ICT) are likely to play a key role to facilitate communication on the interfaces between partners.

Integration by organisation This refers to the use of suitable organisational arrangements, i.e. the more or less durable, formal and informal, structural and cultural arrangements organisations use to divide and co-ordinate labour. The following, not necessarily exhaustive, list provides a continuum of horizontal linkages, ranging from informal to formal, temporary to permanent, and processoriented (grouping by function) to productoriented (grouping by output), ways of linking (groups of) people (e.g. Galbraith 1973): . Standardisation and formalisation, i.e. in. . . . . .

tegration through e.g. paper work. Direct, face-to-face communication. Liaison roles. Task forces and project teams. A matrix structure. Secondment. Co-location.

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. Self-contained groups. . Role combination.

Whereas these alternatives may all be feasible within the firm, some of them are less likely to contribute much to in dispersed NPD. The most likely candidates worth considering to support communication between companies are standardisation, liaison roles and secondment.

Summary and conclusion The typology of NPD – production interfaces proposed in this paper combines structural and process views on product innovation and uses the concept of task to combine the two. Twelve relevant interfaces between NPD and production were identified. Furthermore, the paper describes a classification of integration mechanisms. We are using this work and will continue to do so, in research aimed at identifying consistent configurations of interfaces and integration mechanisms. That is, different configurations of different types of integration mechanisms that fit to the different NPD – production (and also NPD – NPD) interfaces in such a way that the ’sum-total’ effectively contributes to the success of product innovation processes. This should provide a solid basis for answering the managerial issues that are now arising in this important area of current business reality. An aspect that has so far not been included in our research is the role of contingencies like the newness of the product, the complexity of the parts that are being outsourced, the reason for outsourcing (capacity or capability), former experiences with the supply partner, etc. Future research will be aimed at finding out the relevance of these contingencies regarding their influence on successful coordination of the tasks at hand for each of these interfaces.

Acknowledgements Acknowledgements: The first author wants to thank the Netherlands Organization for Scientific Research (NWO) for their support.

Note 1. In this paper, NPD will be referred to as the process that leads to the creation of product and process descriptions. Production is the process transforming these descriptions into physical products and delivering them to the market.

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References Andreasen, M.M. and Hein, L. (2000) Integrated Product Development. Technological University of Denmark, Copenhagen. Archer, L.B. (1971) Technological innovation: a methodology. Inforlink, Frimley. Baldwin, C. and Clark, K. (1997) Managing in an age of modularity. Havard Business Review, September–October, 84–93. Boer, H. and During, W.E. (2001) Innovation, what innovation? A comparison between product, process and organizational innovation, International Journal of Technology Management, 22, 1–3, 83–107. Buijs, J.A. and Valkenburg, R. (2000) Integrale productontwikkeling. Lemma, Utrecht. Cooper, R.G. (1993) Winning at new products: Accelerating the process from idea to launch. Addison Wesley, Reading, MA. Davenport, Thomas H. (1993) Process innovation – Reengineering Work through Information Technology. Harvard Business School Press, Cambridge, MA. Dorst, C.H. (1997) Describing design – a comparison of paradigms. PhD Thesis, Delft University of Technology. Galbraith, J.R. (1973) Designing complex organizations. Addison-Wesley, Reading, MA. Lewis, J. (1995) The connected corporation. The Free Press, New York. Mintzberg, H. (1979) The structuring of organizations. Prentice-Hall, Englewood Cliffs, NJ. Paashuis, V. and H. Boer (1997) Organizing for concurrent engineering: an integration mechanism framework. Integrated Manufacturing Systems, 8, 2, 79–89. Quinn, J. (1999) Strategic outsourcing: Leveraging knowledge capabilities. Sloan Management Review, Summer, 10–12. Roozenburg, N.F.M. and Eekels, J. (1995) Product Design: Fundamentals and Methods. Wiley, West Sussex. Slappendel, C. (1996) Perspectives on innovation in organizations. Organization Studies, 17, 1, 107– 129. Smulders, F.E.H.M., de Caluwe´ , L. and van Nieuwenhuizen, O. (2001) Last stage of NPDproject: intervention in existing processes?! In Idea Safari, Proceedings of the 7th European Conference on Creativity and Innovation, EACI, Enschede (forthcoming). Smulders, F.E.H.M., van Engelen, J.M.L.M. and Kiers, M. (1996) Handboek voor commercie¨le Ingenieurs, thema Productinnovatie. Samson, Alphen a.d. Rijn. Trent, R. and Monczka, R. (1998) Purchasing and supply management: trends and changes throughout the 1990s. International Journal of Purchasing and Materials Management, Fall, 2–11. Ulrich, K.T. and Eppinger, S.T. (1995) Product Design and Development. McGraw-Hill, New York. Verganti, R. (1994) Re-engineering the new product development process. In De Weerd-Nederhof, P.C., Kerssens-van Drongelen, I.C. and Verganti, R., Managing the R&D process. University of Twente/Politecnico di Milano/Twente Quality Centre Enschede.

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Appendix: Research projects in which the authors are involved At the School for Industrial Design Engineering, Delft University of Technology, The Netherlands, a range of research projects is taking place. The most relevant ones for this paper are: . The interface between design agencies and

their clients (who are the lead partners). Aimed at understanding the interface from the perspective of the supplying NPDpartner. The interfaces studied in this project are 1B-type and 2B-type interfaces. . An explorative study of the actual interventions that facilitate or provoke the necessary changes within the operational processes (Smulders et al. 2001). This project is aimed at developing a better understanding of the ‘soft side’ of the interface between a lead partner and the – in this case – internal supply partner. . A study of the ramp-up or implementation of newly developed products in the production process, aimed at developing a better understanding of what is actually passing the interface between NPD and production and what is being done with that regarding the ramp-up processes. At the Center for Industrial Production at Aalborg University, Denmark, a range of relevant projects is in process. The topics studied include: . Sourcing of new technology. This project is

aimed at the effective implementation and absorption of new technology through collaborative relationships with external partners. . The strategic use of product architecture to combine customer-oriented product inno-

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vation with internal standardisation and cost reduction. . Design for Logistics. The purpose of this single case based research project is to investigate the potential interactions between products and logistics by studying the structure of existing products and their supply chains, and then developing a framework for concurrent product and supply chain development. . Distributed collaboration in NPD. This project is aimed at identifying best practice models for ICT-supported collaborative high speed/right speed NPD.

Frido E. Smulders is assistant professor of Management of Innovation at the faculty of Industrial Design Engineering, Delft University of Technology, The Netherlands. His research focuses on the interface between product development and production. Harry Boer is professor of Organisational Design and Change at the Center for Industrial Production, Aalborg University. His research interests are in the integration of operations, incremental change and learning, and radical innovation. Poul H.K. Hansen is associate professor at the Center for Industrial Production, Aalborg University, Denmark. His research focuses on product development in networks. Ebbe Gubi is a PhD student at the Center for Industrial Production, Aalborg University, Denmark. His research project focuses on Design for Logistics. Kees Dorst is senior researcher in Design Methods at the faculty of Technology Management, Eindhoven University of Technology, The Netherlands.

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The Climate for Creativity and Change in Teams Scott G. Isaksen and Kenneth J. Lauer We must all hang together, or assuredly we shall all hang separately. – Benjamin Franklin, At the signing of the Declaration of Independence, July 4, 1776.

This article reports the results of a study conducted to examine the ability of the Situational Outlook Questionnaire (SOQTM) to effectively discern climates that either encourage or discourage creativity and the ability to initiate change in a team setting. The purpose of the study is to examine the concurrent criterion–related validity of the SOQ. The article explores the characteristics in an organisational climate that promote teamwork and some of the tripwires one needs to be aware of in the formation and management of teams. Nine dimensions of the climate for creativity and change as measured by the Situational Outlook Questionnaire are put forward and defined in relation to teams. The methodology and results of the study are reported. The results show that when subjects (N = 154) complete the SOQ based on their recollection of a best- and worst-case team experience, the measure is able to consistently and significantly discriminate between the two types of experiences. Conclusions, implications, and areas for future research to further examine the validity of the SOQ are explored.

Introduction

T

he need for organisational change stems from two basic sources. Numerous external and internal forces drive the changes that organisations have to anticipate and manage as a means to ensure their survival and success. Changes in government policies and regulations, actions taken by competitors, and changing needs and desires of customers are a few examples of external drivers of change coming from the marketplace. A survey of 506 CEOs from around the world conducted in 2000 and published in 2001 by The Conference Board and Accenture shows what some of the major market challenges are today (see Table 1). All organisations must also face the demands of increased efficiency, flexibility and growth. These internal issues are core challenges for leaders and managers within organisations. Table 2 shows the results obtained on The Conference Board and Accenture survey when CEO’s were asked to rate management issues. The potential role of teams in handling both the marketplace and management challenges

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identified in this survey were apparent to us in a variety of ways. We saw that beyond the formal organisational structure, often depicted in organisational charts, the way most leaders and managers deal with these challenges is through the use of teamwork. Our experience has shown that: . Senior management must work together

as a team to build a shared vision and strategy for the organisation . Middle management must team crossfunctionally to meet most of these challenges . Supervision must demonstrate team competence in organising to get people to accomplish tasks, and . Projects and Initiatives within all parts of the organisation require teamwork to meet the novelty and complexity of obtaining the objectives they are focused on The Conference Board and Accenture survey went on to examine what drivers of change are being focused upon by CEO’s today. These interviews revealed that CEO’s felt the key drivers for the challenges of Increased Flexibility and Speed, and Competing for # Blackwell Publishers Ltd 2002. 108 Cowley Road, Oxford OX4 1JF and 350 Main St, Malden, MA 02148, USA.

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Table 1. Ten Leading Marketplace Challenges Challenge

Percent identifying as a challenge

Changes in type/level of competition Impact of the Internet Industry consolidation Downward pressue on prices Shortages of key skills Changing technology Changes in supply/distribution systems Access to/cost of capital Regulatory issues (labor, market access, etc.) Currency issues

40.7% 38.3% 37.4% 33.4% 31.6% 21.9% 19.2% 16.6% 15.0% 7.7%

Source The CEO Challenge: Top Marketplace and Management Issues 2001 by The Conference Board

Table 2. Ten Leading Management Challenges Challenge

Percent identifying as a challenge

Customer loyalty/retention Increasing flexibility and speed Competing for talent Reducing costs Managing mergers/acquisitions/alliances Increasing innovation Engaging employees in the company’s vision/values Developing and retaining potenial leaders Launching new technology initiatives Improving the stock price multiple

37.2% 33.6% 29.2% 28.9% 23.9% 21.9% 20.8% 20.0% 19.8% 18.0%

Source The CEO Challenge: Top Marketplace and Management Issues 2001 by The Conference Board

Talent include:

years 1946–1962. This accounts for 81 million people in the USA.)

. Keeping pace with new technology and

product innovations . Creating Organisational structures that . . . .

promote flexibility and speed Making faster decisions enabled by increasingly rapid information flow Obtaining the right kind of people for the new market conditions Creating a higher purpose that instils a passion that people now want from work Overcoming the lack of younger workers to replace retiring baby boomers (which consists of individuals born between the

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Conceptual Frame In our practice over the last ten years we have worked with a number of organisations in a number of situations and at a variety of levels. Part of that work often focused on team building and team development as a means to promote and increase problem solving skills in organisational settings. It became apparent to us that the work we were doing with team creativity had a direct

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impact on all the drivers mentioned by CEO’s in the Conference Board and Accenture survey. We felt that an empirical study of team creative climate might be able to shed some light on the nature and nurture of teams as a means to improve organisational climate, flexibility, productivity and profitability. In this paper we will explore the questions of what type of climate facilitates team creativity and inversely, what type of climate hinders team creativity. The literature has been summarised regarding the characteristics that promote teamwork and the dimensions of the creative climate. An exploratory investigation, from the world of professional services, provided initial evidence that the climate for most and least creative teams is clearly distinguishable. Thus, since the climate for successful team creativity and performance is identifiable, it is measurable and more importantly it is manageable. We will explore these manageable aspects found in this study and suggest further avenues of research in this topic. Teams are one of the basic building blocks of every organisation. After individuals, they may be considered the most important resource in any organisation. That so much real day-to-day work within organisations is conducted more and more by teams explains the interest in high-performance work systems, electronic groupware, small-group facilitation skills, and a host of other strategies for improving the way groups work. However, before we continue we think it would be helpful to explore what we mean by a team. According to the Merriam-Webster dictionary the word ‘team’ is derived from the Middle English teme, from the Old English tEam that was used to describe a group of draft animals. Merriam-Webster defines the current use of the word to mean ‘a number of persons associated together in work or activity: as a: a group on one side (as in football or a debate) b: a crew, gang’. For us a team means a combination of individuals who come together or who have been brought together for a common purpose or goal in their organisation. Since teamwork is so important for organisational effectiveness, and climate is emerging as a construct to be assessed, understood and improved, the purpose of this article is to explore the climate for creativity within teams.

Identifying Characteristics That Promote Teamwork Authors, researchers and practitioners have offered many suggestions for productive teamwork. Given how important it is to be

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able to contribute productively as a member of a working group, it is interesting to note the increased interest in developing teamwork skills (Belbin, 1981 a & b; Carnevale, Gainer & Meltzer, 1990; Guzzo & Salas, 1995; Katzenbach & Smith, 1993; Katzenbach, 1998). This section of the article will provide some general characteristics which promote teamwork and some tripwires to watch out for when working with groups. There are a variety of ways to differentiate working groups from teams. One senior executive with whom we have worked described groups as individuals with nothing in common except a zip/postal code. Teams, however, were characterised by a common vision. Smith (1996) described a team as ‘. . . a small number of people with complementary skills who are mutually committed to a common purpose, a common set of performance goals, and a commonly agreed upon working approach.’ The following dozen characteristics of productive teams have been formulated from reviewing the work of McGregor (1967), Bales (1988) and Larson & LaFasto (1989). A clear elevating goal. Having a clear and elevating goal means having understanding, mutual agreement and identification with respect to the primary task a group faces. For instance, one of our client’s R&D teams had the task of revamping how the department developed their products. This team concluded that their current practices did not take into account any customer input and it became their goal to introduce consumer input into the process. Active teamwork toward common goals happens when members of a group share a common vision of the desired future state. Results-driven structure. Individuals within groups feel productive when their efforts take place with a minimum of grief. Open communication, clear co-ordination of tasks, clear roles and accountabilities, monitoring performance, providing feedback, fact-based judgement, efficiency, and strong impartial management combine to create a results-driven structure. Competent team members. Competent teams are comprised of capable and conscientious members. Members must possess essential skills and abilities, a strong desire to contribute, be capable of collaborating effectively, and have a sense of responsible idealism. They must have knowledge in the domain surrounding the task (or some other domain

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which may be relevant) as well as with the process of working together. Unified commitment. Having a shared commitment relates to the way the individual members of the group respond. Effective teams have an organisational unity; members display mutual support, dedication and faithfulness to the shared purpose and vision, and a productive degree of self-sacrifice to reach organisational goals. Collaborative climate. Productive teamwork does not just happen. It requires a climate which supports co-operation and collaboration. This kind of situation is characterised by mutual trust . . . trust in the goodness of others. Organisations desiring to promote teamwork must provide a climate within the larger context which supports co-operation. Standards of excellence. Effective teams establish clear standards of excellence. They embrace individual commitment, motivation, self-esteem, individual performance, and constant improvement. Members of teams develop a clear and explicit understanding of the norms upon which they will rely. External support and recognition. Team members need resources, rewards, recognition, popularity and social success. Being liked and admired as individuals and respected for belonging and contributing to a team is often helpful in maintaining the high level of personal energy required for sustained performance. With the increasing use of crossfunctional and inter-departmental teams within larger complex organisations, teams must be able to obtain approval and encouragement. Principled leadership. Leadership is important for teamwork. Whether it is a formally appointed leader or leadership of the emergent kind, the people who exert influence and encourage the accomplishment of important things usually follow some basic principles. Principled leadership includes the management of human differences, protecting less able members, and providing a level playing field to encourage contributions from everyone. This is the kind of leadership which promotes legitimate compliance to competent authority. Appropriate use of the team. Teamwork is encouraged when the tasks and situations really call for that kind of activity. Sometimes the team itself must set clear boundaries on when and why it should be deployed. One of the easiest ways to

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destroy a productive team is to overuse it or use it when it is not appropriate to do so. Participation in decision making. One of the best ways to encourage teamwork is to engage the members of the team in the process of identifying the challenges and opportunities for improvement, generating ideas, and transforming ideas into action. Participation in the process of problem solving and decision making actually builds teamwork and improves the likelihood of acceptance and implementation. Team spirit. Effective teams know how to have a good time, release tension, and relax their need for control. The focus at times is on developing friendship, engaging in tasks for mutual pleasure and recreation. This internal team climate extends beyond the need for a collaborative climate. Embracing appropriate change. Teams often face the challenges of organising and defining tasks. In order for teams to remain productive, they must learn how to make necessary changes to procedures. When there is a fundamental change in how the team must operate, different values may need to be accommodated. Productive teams learn how to use the full spectrum of their members’ creativity.

Challenges to Watch for with Teams There are many challenges to the effective management of groups. We have all seen groups that have ‘gone wrong.’ As a group develops, there are certain aspects or guidelines that might be helpful to keep them on track. Hackman (1990) has identified a number of themes relevant to those who design, lead, and facilitate groups. In examining a variety of organisational work groups, he found some seemingly small factors that if overlooked in the management of teams will have large implications that tend to destroy the capability of a team to function. These small and often hidden ‘tripwires’ to major problems include: Group versus team. One of the mistakes that is often made when managing groups is to call the group a team, but to actually treat it as nothing more than a collection of individuals. This is similar to making it a team ‘because I said so.’ It is important to be very clear about the underlying goal structure. Organisations

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are often surprised that teams do not function too well in their environment. Of course, they often fail to examine the essential ingredient of competition in their rating or review process. People are often asked to perform tasks as a team, but then have all evaluation of performance based on an individual level. This situation sends conflicting messages, and may negatively effect team performance. Ends versus means. Managing the source of authority for groups is a delicate balance. Just how much authority can you assign to the team to work out its own issues and challenges? The end, direction, or outer limit constraints ought to be specified, but the means to get there ought to be within the authority and responsibility of the group. Teamwork is often under-utilised because the desired ends are unclear and unspecified. As a result, teams are often given too much guidance on the means (the how) rather than sufficient emphasis on the ends (the what and why). Structured freedom. It is a major mistake to assemble a group of people and merely tell them in general terms what needs to be accomplished and then let them work out their own details. At times, the belief is that if groups are to be creative, they ought not be given any structure. It turns out that most groups would find a little structure quite enabling, if it were the right kind. Groups generally need a welldefined task. They need to be composed of an appropriately small number to be manageable but large enough to be diverse. They need clear limits as to the group’s authority and responsibility, and they need sufficient freedom to take initiative and make good use of their diversity. Structures and systems. Often challenging team objectives are set, but the organisation fails to provide adequate support in order to make the objectives a reality. In general, high performing teams need a reward system which recognises and reinforces excellent team performance. They also need access to good quality and adequate information, as well as training and educational support. Good team performance is also dependent on having an adequate level of material and financial resources to get the job done. Assumed competence. Many organisations have a great deal of faith in their selection systems. Facilitators, and others who manage groups, cannot assume that the

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group members have all the competence they need to work effectively as a team, simply because they have been selected to join any particular organisation. Technical skills, domain-relevant expertise, and abilities often explain why someone has been included within a group. These are often not the only competencies individuals need for effective team performance. Members will undoubtedly need explicit coaching on skills they need to work well in a team. Coaching and other supportive interventions are best done during the launch, at a natural break in the task, or at the end of a performance or review period. It appears that the start-up phase is probably the most important time-frame to provide the necessary coaching or training.

Teamwork and Goal Structures There is very clear evidence that if teamwork is desired, then goals that are competitive or individualistic should be avoided ( Johnson, Maruyama, Johnson, Nelson & Skon, 1981). Groups can be structured so that they will co-operate, compete, or act individualistically (Deutsch, 1949; Johnson & Johnson, 2000). Individualistic goal structures are those where there is no relationship among group members’ goal attainments. Group members perceive that obtaining their goals is unrelated to the goal achievement of other members of the same group. An individual’s success in swimming fifty yards, for example, is unrelated to whether anyone else swims fifty yards or not. When working within individualistic goal structures the interaction among group members is likely to be characterised as non-related to work, unnecessary, or even as a distraction to accomplishing the tasks at hand. There is really no perceived need for interaction. Competitive goal structures exist when there is a negative relationship among group members’ goal attainments. Group members perceive that they can obtain their goals only if the other members, with whom they are competitively linked, fail to obtain their goal. When one runner wins a race, for example, all other runners in that race fail to win. When the goal structure is competitive; interaction, communication, and information exchange among group members can often be misleading or threatening. Group members do not utilise each others’ resources. Competitive goal structure also brings increased fear of failure, low trust, evidence of win-lose conflict and high emotional involvement in and commitment to

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productivity by the few members who have a chance ‘to win.’ There is a tendency to avoid risk-taking and divergent thinking. Co-operative goal structures exist when there is a positive relationship among group members’ goal attainments. This happens when group members perceive that they can achieve their goal if and only if the other members with whom they are co-operatively linked obtain their goal. When a team of climbers, for example, reaches the summit of a mountain, the success is experienced by all members of the team. In groups with cooperative goal structures, interaction among members is characterised by effective communication and exchange of information, facilitation of each others’ productivity, helping, and sharing. Group members use each other’s resources. The climate is characterised by high acceptance and support among members, high trust, decreased fear of failure, and a problem-solving orientation to conflict. People working within teams perform better when they are structured for cooperative and collaborative work. In short, productivity increases. Promoting teamwork within groups is not merely a matter of warm-ups, fun and games, or team-building exercises. Seeking co-operative goal structures and organising for effective teamwork is best done upon the foundation of a key philosophy. One of the best writers and thinkers about this area is Greenleaf (1977) on the servant as leader. His basic premise is that a leader seeks first to serve. It is just this attitude that establishes a collaborative environment with which co-operative goal structures are likely to flourish. This philosophy has been recently linked to creative leadership (Freeman, Isaksen & Dorval, 2002).

The Climate that Promotes Creativity Scholars have contributed a great deal to our understanding of climate (Litwin & Springer, 1968; Payne & Pugh, 1976; Schneider, Brief, & Guzzo, 1996; Tagiuri & Litwin, 1968). Some scholars have linked their study of climate to creativity (Amabile, Conti, Coon, Lazenby & Herron, 1996; Talbot, Cooper, & Barrow, 1992; Turnipseed, 1994). Ekvall has also researched the organisational climate conducive to innovation and growth (Ekvall, 1983; Ekvall, Arvonen & Waldenstrom-Lindblad, 1983; Ekvall, 1987; Ekvall, 1991; Ekvall, 1996; Ekvall, 1997), and his work has been translated and validated for use in North America (Cabra, 1996; Isaksen, Lauer & Ekvall, 1999; Lauer, 1994; Sobieck, 1996; Speranzini, 1997).

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Similar to other organisational psychologists (Pettigrew, 1990; Schneider & Gunnarson, 1991), Ekvall has differentiated the concepts of climate and culture. Ekvall (1991) defined climate as the observed and recurring patterns of behaviour, attitudes, and feelings that characterise life in the organisation. Culture reflects the deeper foundations of the organisation. Culture includes values, beliefs, history and traditions. According to this distinction, culture provides the foundation for patterns of behaviour that are more readily observed, described, and changed. These patterns of observed behaviour, along with many other variables (e.g., management, leadership, organisational size and structure, etc.), help to establish the climate within the organisation. The concept of climate may be separated into two distinct, but complementary, constructs commonly referred to as psychological and organisational climate depending on the unit of analysis ( James, James & Ashe, 1990). Psychological climate is the cognitive appraisal by an individual of environmental attributes in terms of their acquired meaning and personal values to the individual. When individual appraisals are aggregated, based on the belief that individuals in an organisation have a sense of shared meaning, the result is referred to as organisational climate. As an attribute of an organisation, organisational climate has been identified as a productive construct to utilise in preliminary and sustained organisational diagnosis for development or improvement efforts. Climate is an intervening variable that influences organisational and psychological processes which, in turn, influence the overall productivity and well-being of an organisation. Climate influences, and is subsequently influenced by, the outcome of organisational operations. Climate affects organisational productivity and well-being by influencing organisational processes such as problem solving, decision making, communicating and coordinating, the individual processes of learning and creating, and levels of motivation and commitment. A number of factors affect climate (e.g., the larger external environment within which the organisation operates, the resources available within the organisation, its strategic positioning and architecture as well as its culture and leadership practices). As such, climate is an important variable in understanding organisational performance and change (Burke & Litwin, 1992; Schneider, Brief & Guzzo, 1996). Ekvall has accumulated a great deal of support for his approach to measuring climate through his own field research with colleagues

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and doctoral students, as well as his consultancy experiences in organisational psychology. As a result of this sustained program of research and practice, Ekvall has demonstrated that his method of assessing climate clearly discriminated ‘stagnated’ from ‘innovative’ organisations (Ekvall, 1996). Ekvall’s colleagues and students were able to make independent assessments of the degree to which each of the 30 international organisations was innovative. The organisations in the studies were assessed on their ability to bring novel products or services to the marketplace. This assessment included both technical and market novelty. Those that were able to put many new products and services through their systems were labeled innovative. Those who had extreme difficulty, or simply could not produce new products or services, were called stagnated. Clear and significant differences on the scores were observable between the stagnated and innovative organisations on the dimensions designed to measure the creative climate. The following nine dimensions have been found to effectively discriminate the degree to which a climate supports creativity. The dimensions have been derived on the basis of Ekvall’s extensive validation with organisations, and our own work to translate, extend, and validate the measure we utilise (Isaksen & Kaufmann, 1990; Isaksen & Lauer, 1999; Isaksen, Lauer, Ekvall & Britz, 2001; Lauer & Isaksen, 2001; Lauer, Isaksen & Dorval, 1996). Challenge and Involvement means the extent to which teams are given opportunities to get involved in the daily operations, long-term goals, and visions of the organisation. When there is a high degree of challenge and involvement team members feel motivated, energised, and committed to making contributions. The climate is dynamic, electric, and inspiring. Team members find their work to be personally fulfilling and meaningful to their team and organisation. In the opposite situation, team members are not engaged and feelings of alienation and apathy are present. The team lacks direction, members lack interest in their work and interpersonal interactions within and without the team are dull and listless. Freedom refers to the degree that teams can take initiatives or are at liberty to act without constantly referring to higher authorities or ‘rule books’ for decisions. The team members exhibit independence in behaviour and the team is given the

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autonomy and resources to define much of their work. Team members are provided the opportunities and take initiatives to acquire and share information about their work. In the opposite climate teams work within strict guidelines and are not allowed to take initiative. Team members carry out their work in prescribed ways with little room to redefine their tasks. Trust and openness refers to the degree of emotional safety in relationships. When there is a high degree of trust, team members trust one another and feel ‘safe’ enough to be open and honest with their colleagues, in the spirit of constructive relationships. Team members are genuinely open and frank with one another. They count on each other for professional and personal support. Team members have a sincere respect for one another and give credit where credit is due. Where trust is missing, team members are suspicious of each other, and therefore, they closely guard themselves, their plans, and their ideas. In these situations team members find it extremely difficult to openly communicate with each other and function as a team. Idea time is the time the team takes off to generate new ideas or consider the merits of existing ideas and opportunities. In the high idea-time situation, possibilities exist to discuss and test suggestions not included in the task assignment. There also are opportunities to take the time to explore and develop new ideas. Flexible timelines permit team members to explore new avenues and alternatives. In the reverse case, every minute is booked and specified. The time pressure makes thinking outside the instructions and planned routines impossible. Playfulness and humour refers to the amount of spontaneity and levity displayed within the team. A professional, yet relaxed atmosphere where goodnatured jokes and laughter occur often is indicative of this dimension. Team members can be seen having fun within the team and at work. The climate is seen as easy-going and light-hearted. The opposite climate is characterised by gravity and seriousness within the team. The atmosphere is stiff, gloomy and cumbrous. Jokes and laughter are regarded as improper and intolerable. Conflict means the presence of personal and emotional tensions within the team and between team members. When the level of conflict is high, team members

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dislike and may even hate each other. The climate can be characterised by ‘interpersonal warfare.’ Plots, traps, power and territory struggles are usual elements of team functioning. Personal differences yield gossip and slander. In the opposite case, team members behave in a more mature manner; they have psychological insight and control of impulses. The team welcomes, accepts and deals effectively with diversity. Conflict is the only negative dimension, for which a lower score is generally better. Idea Support refers to the ways new ideas are considered, taken up or advocated by the team. In the supportive climate, ideas and suggestions are received in an attentive and professional way by teammates. They listen to each other and encourage initiatives. Possibilities for trying out new ideas are created within the team. The team’s atmosphere is constructive and positive when considering new ideas. When idea support is low, the automatic ‘no’ is prevailing within the team. Fault-finding and obstacleraising are the usual styles of responding to ideas. Debate is the occurrence of encounters and disagreements between viewpoints, ideas, and differing experiences and knowledge within the team. Conflict relates to personal tension while debate is related to idea-tension. In the debating team all the voices of team members are heard and they are keen on putting forward their ideas for consideration, and their merits are openly debated and resolutions reached. Where debate is missing, team members follow authoritarian patterns and procedures without questioning them or exploring alternatives. Risk-Taking refers to the degree to which the team can tolerate ambiguity and make decisions with some uncertainty. Team members are prepared to live with the potential negative consequences. In the high risk-taking case, teams take bold initiatives even when the outcomes are unknown. Teams and team members feel as though they can ‘take a gamble’ on ideas. They will often ‘go out on a limb’ to put an idea forward. In a risk-avoiding climate there is a cautious, hesitant mentality within the team. Team members will lack decisiveness, try to be on the ‘safe side’ and often ‘sleep on the matter.’ They may set up committees, defer decisions to other teams, and cover themselves in many ways.

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Previous research with the SOQ used the organisation (Lauer & Isaksen, 2001) as the unit of analysis. All of our previous studies regarding these dimensions have been conducted with individual psychological climate as the unit of analysis (Isaksen & Kaufmann, 1990; Isaksen & Lauer, 1999; Isaksen, Lauer, Ekvall & Britz, 2001). This study represents an initial attempt to use teams as the unit for comparison.

Method The data were collected as a part of a distance learning workshop within a large global professional services firm that was led by the lead author from a site in Baltimore, Maryland USA. This sample was chosen because those providing a variety of professional consulting services to a diverse kind of organisation would provide a broad lens for this initial study. The workshop was called ‘Teamwork for Innovation’ and was one of a series of workshops offered within the program. The participants in the study were all enrolled in this series of workshops as a part of their own interest in developing their leadership and management skills. The 170 participants were all managers in the firm. They had at least three to five years experience and all elected to participate in this module. They came from 23 locations in North America including Boston, New York, Miami, Toronto, Tampa, and Atlanta. A set of nine questions (see Appendix A) was designed to summarise the key behaviours described in the dimensions above. Participants used the same set of nine questions for two different tasks. One asked them to recollect their most creative team experience, and the other asked them to recall their least creative team experience. A tenth openended item was included to ask what factor the respondent thought was most important or detrimental to the success of the team. Before they were given a description of climate, or any of the dimensions outlined above, the participants were invited to respond nominally to the nine closed-ended questions after identifying the most creative team they have experienced. The definition provided to them regarding the most creative team was one that produced something that was: new, unique, or original; valuable, relevant and useful; and accepted, produced results, and made a positive impact. In addition, they were asked to write a narrative response to the question: What do you think was the most important factor accounting for the team’s success? The distance learning

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technology allowed the presenter to know the number and percentage of respondents for every question. After 90% of the participants completed their responses to the above questions, they were requested to respond nominally to nine additional closed-ended questions about their least creative team experience. The least creative team was described for them as one that produced something that was: well within previous practice or standard, where they ‘reinvented the wheel’; useless or valueless; and was rejected or produced very little or no impact. They were also asked to respond to an open-ended question that asked them to identify the most significant barrier hindering the team’s success. Participants could choose a number for each of the sets of nine questions that ranged from zero to three. Assigning the number zero meant that they did not observe the dimension at all. Giving a team the number one signified that they observed a dimension to some extent. Two meant that the dimension was fairly applicable. Three signified that they observed the dimension very often. Each participant was able to read each of the two sets of nine questions on their own personal monitor and select a number indicating their assessment of the frequency of the behaviour described in the dimension. All quantitative responses were electronically conveyed to the distance learning provider and the results were aggregated and recorded. All narrative responses were also electronically communicated and summarised by the provider. The comments were transcribed onto one master list and numbered for future reference. The first list included all the factors of success and the second, all the barriers

identified by the participants. Each list was analysed separately to identify key themes. The themes were identified on a separate list and all comments were placed into a theme. The work on themeing the responses continued until all comments were included. Each list was then given to a second reviewer and were checked by having another reviewer independently place each comment into a theme. There was 97% agreement of fit and the few comments that did not agree provided additional clarity of definition for the theme. Since there were no controls to ensure that all participants completed all questions before proceeding, a different number of responses were collected for each of the two sets of nine questions. As a result, averages were used for comparison purposes. In addition, some participants provided more than one response to the narrative questions, and others chose not to respond at all. All narrative responses were recorded separately as factors for success and barriers. These responses were then themed using content analysis and were validated by two independent raters with a 97% agreement with the themes.

Results The quantitative comparisons between the most and least creative teams are presented in Table 3. Significant differences were observed on all nine mean scores (see Table 4). These results were consistent with results of the Isaksen, Lauer, Ekvall & Britz (2001) SOQ study of individual perceptions of their best and worst case experience in a job. They are also consistent with a SOQ study by Isaksen & Lauer

Table 3. Averages of the Most and Least Creative Team Responses Dimension

Challenge & Involvement Freedom Trust & Openness Idea Time Playfulness/Humor Conflict Idea Support Debate Risk-Taking

Most Creative Team Experience

Least Creative Team Experience

260 202 253 227 235 27 218 231 210

100 110 88 65 77 123 70 83 65

N = 154

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Table 4. Tests of Significance on the Most and Least Creative Team Responses Dimension

t Value

Statistical Significance

Challenge & Involvement Freedom Trust & Openness Idea Time Playfulness/Humor Conflict Idea Support Debate Risk-Taking

11.63 8.98 30.06 15.39 24.54 731.73 12.82 15.16 10.19

p < .01 p < .05 p < .001 p < .01 p < .01 p < .001 p < .01 p < .01 p < .01

N=154

(2001) that explored the individuals perception of perceived support for creativity. These previous studies used the individual level of analysis as the unit for comparison, while this is the first study using teams. These quantitative results are consistent with the previous research with the SOQ using both an individual and organisational unit of analysis. The main themes derived from a qualitative analysis of the 330 narrative comments received by the 160 subjects are summarised as: Interpersonal Dynamics. The more creative teams had the ability to work together without major conflicts in personalities. There was a high degree of respect for the contributions of others. Communication was characterised by ‘The willingness of team members to listen to one another and honour the opinions of all team members.’ Members of these teams reported that they knew their roles and responsibilities and that this provided freedom to develop new ideas. In the least creative teams there was an ‘unwillingness to communicate with one another because people did not make the effort to understand each other.’ There were instances of animosity, jealousy, and political posturing. Energy and Motivation. The more creative teams ‘played hard and worked even harder.’ Team members enjoyed contributing and celebrated their accomplishments. ‘All team members were motivated to do the best job possible in reaching the end goal, so everyone was willing to pitch in to get the job done.’ There was a high degree of enthusiasm and commitment to get the job done. On the least creative

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teams there was a lack of motivation. There was a lack of initiative, ideas, and follow through on suggestions. The least creative teams had a ‘lack of motivation and the inability to recognise the value provided by the end result.’ Openness. The most creative teams had an environment that encouraged new ideas and allowed the development of new ways of working. ‘No matter what the disagreements, we all knew that we had to bring our ideas together to get the job done.’ Everyone felt comfortable discussing ideas, offering suggestions because ‘. . . ideas were received in a professional and attentive manner . . . people felt free to brainstorm to improve others’ ideas without the authors’ feelings getting hurt. In the least creative teams new ideas were not attended to or encouraged because ‘. . . individuals placed their own priorities before the teams’. They were characterised by not being able to discuss multiple solutions to a problem because team members couldn’t listen to any opinion other than their own. In these teams, members were ‘. . . expected to follow what had always been done and finish as quickly as possible.’ Leadership. In the most creative teams the ‘. . . leader led by example, encouraging new ideas and sharing best practices.’ Leaders provided clear guidance, support and encouragement, and kept everyone working together and moving forward. Leaders also worked to obtain support and resources from within and outside the group. In the least creative teams, the leader ‘. . . created a situation where everyone was confused and afraid to ask questions.’ Leaders ‘tore down people’s

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ideas,’ ‘set a tone of distrust,’ and ‘stifled others who had ideas and energy to succeed.’ They ‘. . . kept all control, but took no action.’ Focus, Direction, and Goals. The most creative teams had clear and common goals. ‘The most important factor accounting for my team’s creative success was, undoubtedly, each member’s drive to attain the end goal, knowing the benefits that would be derived from the results.’ The goals were clear and compelling, but also open and challenging. The least creative teams had conflicting agendas, different missions, and no agreement on the end result. ‘Everyone did their own thing without keeping in mind the overall objective that the group was charged to achieve.’ The tasks for the least creative teams were tightly constrained, considered routine, and were overly structured. Trust. The most creative team members trusted each other, promoted open and honest communication and supported each other’s views. ‘The most important factor for the success of the team was the overwhelming trust we had for each other, both personal and work-related.’ In the least creative teams there was ‘. . . Absolutely no trust among team members. Everyone was suspect of someone’s underlying motives.’ Diversity of skills and experience. The most creative teams recognised the diverse strengths and talents and used them accordingly. ‘Each individual brought a cornucopia of experience and insight. All of this, together with the desire to meet the end goal was the key to success.’ The least creative teams had inadequate skill sets and were unable to effectively utilise their diversity. The themes derived through qualitative analysis are consistent with much of the literature regarding effective teamwork and contain characteristics that respond to tripwires and goal structures.

There are many implications for those who lead and manage organisations. One of the most important is that teams requiring creativity in order to pursue their tasks need to attend to the dimensions of the creative climate, as well as the factors derived from the narrative comments. Attending to these ingredients of creative team climate is a function well suited for the leader or facilitator of the group. This facilitation and leadership must be done in such a way that it establishes, nourishes, and maintains a climate that is appropriate for the team to succeed. There is more than sufficient literature to support this facilitative kind of leadership within teams (Isaksen, 2000). The study does have some limitations that need to also be identified. The first is that the results are based on the internal selfperceptions of the respondent and these were not observed or validated by an outside source as being either a creative or noncreative team. The use of a virtual platform for the collection of the responses to the questions is also a concern because there were time limits for the completion of the questions and not every participant completed the questionnaire. Our observations from completing this study suggest many productive areas of further inquiry in this area. First we suggest that future researchers utilise the entire SOQ to ensure that the questionnaire used is reliable and has support for its validity. We would also recommend that intact work teams be used and that external measures of creative productivity be used. A final recommendation that we have focuses on the facilitation and leadership abilities of individuals in the team. Our observations from the field have been that teams containing individuals who have facilitation and leadership skills are more efficient, effective and creative than teams which are lacking these skills (Bradford, 1976; Isaksen, 1986). A study of teams that controls for these variables could lead to some empirical support to our general observations.

References Summary and Conclusions The significant results reported on the basis of well over one hundred different team experiences indicate that there are clear and meaningfully distinct climates for creative team performance. The results of this study were also consistent with previous research on creative climate and the literature on small group effectiveness.

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Amabile, T. M., Conti, R., Coon, H., Lazenby, J. and Herron, M. (1996) Assessing the work environment for creativity. Academy of Management Journal, 39, 1154–1184. Bales, R.F. (1988) Overview of the SYMLOG system: Measuring and changing behavior in groups. SYMLOG Consulting Group, San Diego, CA. Belbin, M. (1981a) Management teams: Why they succeed or fail. Pfieffer & Co, San Diego, CA. Belbin, M. (1981b) Team roles at work. Pfieffer & Co, San Diego, CA.

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Bradford, L.P. (1976) Making meetings work: A guide for leaders and group members. University Associates, San Diego, CA. Burke, W.W. and Litwin, G.H. (1992) A causal model of organizational performance and change. Journal of Management, 18, 523–545. Cabra, J.F. (1996) Examining the reliability and factor structure of the Climate for Innovation Questionnaire. Unpublished master’s thesis, State University College at Buffalo, New York. Carnevale, A.P., Gainer, L.J. and Meltzer, A.S. (1990) Workplace basics: The essential skills employers want. Jossey-Bass, San Francisco. Deutsch, M.A. (1949) A theory of cooperation and competition. Human Relations, 2, 129–152. Ekvall, G. (1997) Organizational conditions and levels of creativity. Creativity and Innovation Management, 6, 195–205. Ekvall, G. (1996) Organizational climate for creativity and innovation. European Journal of Work and Organizational Psychology, 5, 105–123. Ekvall, G. (1991) The organizational culture of ideamanagement: A creative climate for the management of ideas. In Henry, J. and Walker, D. (eds.), Managing innovation. Sage Publications Ltd., London, pp. 177–190. Ekvall, G. (1987) The climate metaphor in organization theory. In Bass, B. & Drenth, P. (eds.), Advances in organizational psychology. Sage, Beverly Hills, CA, pp. 177–190. Ekvall, G. (1983) Climate, structure and innovativeness of organizations: A theoretical framework and an experiment. (Report 1). FAra˚det – The Swedish Council for Management and Work Life Issues, Stockholm, Sweden. Ekvall, G., Arvonen, J. and Waldenstrom-Lindblad, I. (1983) Creative organizational climate: Construction and validation of a measuring instrument. (Report 2). FAra˚det – The Swedish Council for Management and Work Life Issues, Stockholm, Sweden. Freeman, T., Isaksen, S.G. and Dorval, K.B. (2002) Servant leadership and creativity: An opening dialogue. In Spears, L. and Lawrence, M. (eds.), Focus on leadership: Servant-leadership in the 21st century. John Wiley & Sons, New York, pp. 256– 267. Greenleaf, R.K. (1977) Servant leadership: A journey into the nature of legitimate power and greatness. Mahwah, NJ: Paulist Press. Guzzo, R.A. and Salas, E. (eds.) (1995) Team effectiveness and decision making in organizations. Jossey-Bass, San Francisco. Hackman, J.R. (1990) Groups that work (and those that don’t): Creating conditions for effective teamwork. Jossey-Bass, San Francisco. Isaksen, S.G. (1986) Facilitating small group creativity. In Gryskiewicz, S.S. and Burnside, R.M. (eds.), Creativity Week VIII Proceedings. Center for Creative Leadership, Greensboro, NC, pp. 71–84. Isaksen, S.G. (2000) Facilitative leadership: Making a difference with creative problem solving. Kendall/ Hunt, Dubuque, IA. Isaksen, S.G. and Kaufmann, G. (1990) Adaptors and innovators: Different perceptions of the psychological climate for creativity. In Rickards, T., Colemont, P., Grøholt, P., Parker, M. and

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Appendix A: Situational Outlook Questionnaire Sample Questions 1. Most people on this team were highly motivated and committed to making contributions in accomplishing the purposes and goals of the team. 2. People on this team define much of their own work and frequently took independent initiatives to acquire information, make decisions, and plan. 3. People on the team trusted each other, were open and honest, and count on each other for personal support. 4. People on this team took the time to consider and test new ideas and ways of doing things. 5. People on this team had fun doing work. There was a great deal of good-natured joking and laughter. 6. People on this team often set traps for each other and engaged in territory struggles, gossip, and slander. 7. New ideas were received in an attentive and professional way by bosses, peers, and others. People listened, encouraged, and tried new ideas here. 8. People on this team discussed and considered opposing opinions and a diversity of viewpoints. 9. People on this team feel as though they can go out on a limb and be first to put an idea forward. They tolerated uncertainty and ambiguity. 10. What do you think was the most important factor for the team’s success? (Please write your answer)

Scott G. Isaksen is the CEO of The Creative Problem Solving Group, Inc. and Senior Fellow of the Creativity Research Unit. Kenneth J. Lauer is the Director of Research and Operations at The Creative Problem Solving Group, Inc. and Coordinator of the Creativity Research Unit.

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# Blackwell Publishers Ltd 2002