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International Journal of Operations &Production Management,Vol. 21 No. 4, 2001, pp. 490-503.# MCB University Press, 0144-3577

Knowledge and continuousinnovation

The CIMA methodologyHarry Boer

Aalborg University, Denmark

Sarah CaffynCENTRIM University of Brighton, UK

Mariano CorsoUniversity of Pisa, Italy

Paul CoughlanTrinity College, Dublin, Ireland

Jose GieskesTwente University, Enschede, The Netherlands

Mats MagnussonChalmers University, GoÈ teborg, Sweden

Sara Pavesi and Stefano RonchiPolitecnico di Milano, Italy

Keywords New product development, Innovation, Kaizen, Learning

Abstract Competition today is forcing companies to increase their effectiveness throughexploiting synergy and learning in product innovation. Literature, however, is still mainly focusedon how product development projects, seen largely as isolated efforts, should be organised andmanaged. This article proposes a model to describe and explain how companies can gain asubstantive competitive advantage by extending their innovation efforts to other phases of theproduct life cycle and by facilitating knowledge transfer and learning both within the company andwith other partner organisations. The model is based on collaborative research by the authors,based on their involvement in the Euro-Australian co-operation project CIMA (Euro-Australianco-operation centre for Continuous Improvement and innovation MAnagement).

IntroductionTo survive in a demanding and turbulent competitive environment companiesare investing a growing amount of resources and managerial attention inproduct innovation. With pressures to reduce product development intervalsand to increase the frequency of new product introductions, this attention ismore and more continuous and the efforts involve partners outside the

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Many people contributed to this article through their involvement in the CIMA-project, bytriggering and challenging the authors' thinking in previous discussions, or in the form ofuseful comments on draft versions of the article. All these contributions are gratefullyacknowledged and in particular those from Roberto Verganti and Emilio Bartezzaghi(Politecnico di Milano); Niklas Sundgren (CORE-Chalmers University, GoÈteborg), RossChapman and Paul Hyland (University of Western Sydney at Macarthur).

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organisational boundaries, often on a global basis. Yet, with few exceptions, forexample, Meyer and Utterback (1993) and Sundgren (1998), the literatureremains focused on the management and organisation of new productdevelopment (NPD) projects as isolated efforts. An alternative perspectivedeveloped by Bartezzaghi et al. (1997a, b) proposes NPD projects as discretesteps within a more comprehensive process of continuous product innovation(CPI). As well as focusing on products in a family context, CPI includes all thephases of the product life cycle that follow the launch in the market place.Evidence from best practice companies, for instance, shows howmanufacturing, maintenance and service, though not integral parts of thedevelopment phase, can still provide valuable feedback and additionalopportunities to innovate future related products. From this perspective then,product innovation is a continuous and cross-functional process involving andintegrating a broad range of different competencies inside and outside theorganisational boundaries. Mastering the sharing and transfer of knowledgewithin this process requires new managerial skills, but can become a powerfulcompetitive weapon. This article proposes a methodology, based on abehavioural model, to help companies facilitate knowledge transfer and fosterlearning in the process of CPI.

In the next section, the research setting will be defined, introducing theconcept of continuous product innovation and focusing on how knowledge canbe generated and transferred within the process of CPI. Subsequently, theCIMA methodology will be introduced, and in particular the underlyingbehavioural model which explains how management can foster continuousimprovement and learning in CPI. Then, three cases will be reported to showhow the methodology was used in companies to prompt managerial actions toimprove continuous improvement and learning in their product innovationactivities. The paper will conclude with the main managerial implicationsarising from the work so far, as well as suggestions for further development.

The research reported here started as part of the Euro-Australian co-operation project CIMA (Euro-Australian co-operation centre for ContinuousImprovement and innovation Management ESPRIT 26056). The objective ofCIMA was to facilitate co-operation and knowledge/technology transferbetween European and Australian organisations, through:

(1) The establishment of a Co-operation Centre, with sites in Europe andAustralia, which were to promote and support bilateral activitiesbetween the two continents involving mutual learning and technologyand knowledge transfer.

(2) The development of a first Euro-Australian `̀ trial'' project, involvingconsortium of five European and three Australian research centres,aimed at developing a methodology to support companies in managinglearning and continuous improvement in product innovation.

This article describes some of the results of the CIMA trial project, focusing inparticular on the development of the methodology of learning in productinnovation (PI), and reporting on its first applications in companies in Italy,Sweden and The Netherlands.

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Knowledge management in PIA model of CPISince the early 1970s, managerial and scientific interest in (product) innovationhas increased rapidly, with publications focusing, initially, on aspects such asfactors of success and failure, the diffusion of innovations, innovation roles,and organisational characteristics beneficial (or detrimental) to different stagesof the innovation process. During the 1980s, various researchers started to callfor more process-oriented research, believing that the successful managementof innovation also depends on a thorough understanding of what is reallyhappening during innovation processes. As a consequence, a plethora ofprocess models of product innovation was proposed which, however, mostlyfocussed on the management of the NPD process (see e.g. Saren, 1984).Towards the end of the 1980s, quality and speed, in addition to price, emergedas order winners or even qualifiers in many markets (e.g. Smith and Reinertsen,1991). In response, concurrent engineering was thought to represent a longlasting paradigm for product innovation management. Integration amongdifferent phases of a project, heavy-weight project management and projectteam autonomy were considered as synonymous with best practices. By themid 1990s, a new stream of studies emerged which enlarged this perspective,proposing that a focus on single projects is not enough to stay competitive.Rather, success depends even more on exploiting synergy among projects, forexample by fostering commonality and reusing design solutions over time(Wheelwright and Sasser, 1989; Wheelwright and Clark, 1992; De Maio et al.,1994; Cusumano and Nobeoka, 1992). Correspondingly, attention progressivelyshifted from single projects to families of projects (Meyer and Utterback, 1993;Sanderson and Uzumeri, 1995) and to the process of learning and knowledgetransfer and reuse (Imai et al., 1988; Bartezzagi et al., 1997a; Sundgren, 1998).

These streams of literature, however, consider PI as occurring only withinthe boundaries of the product development process. Downstream phases in theproduct life cycle are still important for innovation but only as long as theyrepresent valuable sources of information or constraints that should beanticipated and considered during development (Clark and Fujimoto, 1991).However, evidence is emerging that other phases in the product life cycle (suchas for instance manufacturing, consumption and maintenance) are not onlysources of information. They may actually present additional opportunities toinnovate products. This is a direct consequence of rapid product developmentand time to market reduction where companies, especially in rapidly shiftingenvironments, deliberately release products that are not fully optimised. Forexample, in the software industry, platform package releases are followedfrequently by a rapid, almost continuous, stream of enhanced releases, whichhave major bugs fixed and features optimised.

The concept and the boundaries of PI are therefore changing dramatically.Feedbacks and opportunities coming in from the later field phases are storednot only for feeding next generation product development projects, but also asvaluable opportunities for PI within a product life cycle. These two dimensionsare combined in the model of CPI proposed by Bartezzaghi et al. (1997b) (seeFigure 1). In their view, first, CPI embraces not only NPD (concept, product and

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process design, and product launch), but also subsequent phases in product lifecycle (improvement in manufacturing, customisation in sales and installation,and enhancements and upgrading during product use). Second, they suggest amove from the traditional perspective of single products to that of productfamilies. Consequently, at the level of the product family, the CPI processincludes all the interactions among products in the family. Hence, innovationmay concern a product that is in its development phase, a product that has beenalready released to market, or a transfer of solutions between products. In thenext section, we will focus on the last of these concerns, knowledge transfer.

Knowledge transfer in CPIThe emerging literature on knowledge management includes five dimensionsthat should be taken into account when analysing knowledge transfer in CPI:

(1) The setting of knowledge transfer.

(2) Level of dissemination.

(3) The scope of knowledge.

(4) The degree of abstraction and generalisation.

(5) The degree of articulation or embodiment.

These five dimensions can help in interpreting the process of acquiring,transferring, consolidating and applying knowledge in order to design appropriateenablers to foster and sustain it. We will discuss each dimension in turn.

The first dimension concerns the setting (routes, directions) of knowledgetransfer. In the CPI model, nine main directions or routes of improvement and

Figure 1.Main directions for

knowledge transfer inthe CPI process

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learning are distinguished (arrows 1 to 9 in Figure 1). Categorically, thefirst three routes concern knowledge transfer within the same product lifecycle. The remaining six routes concern transfer between different products inthe same family. See Corso (forthcoming) for further details on the nine routes.In brief:

(1) Intra-product transfer in development: knowledge is transferred fromone phase of the development project to another.

(2) Intra-product transfer from development to field: knowledge istransferred from the development project to the operations of theorganisation.

(3) Intra-product transfer in field: knowledge is transferred betweendifferent in-field activities, e.g. from maintenance to production(improvement).

(4) Intra-phase transfer in development: knowledge is transferred from thedevelopment phase of one PI project to that of another.

(5) Inter-phase transfer in development: knowledge is transferred from onephase of a PI project to another phase of another, usually subsequent,project, e.g. early experience with one product to the development phaseof the next product.

(6) Intra-phase transfer in field: transfer of knowledge on the same kind ofin-field activities related to different products.

(7) Inter-phase transfer in field: knowledge on different in-field phases isexchanged between products/projects.

(8) Inter-product transfer from field to development: knowledge acquiredfrom field activities is transferred to the development of new products.

(9) Inter-product transfer from development to field: transfer of knowledgegenerated during the development of new products to improve productsalready launched.

All these routes present a potential for learning and innovation which,however, can be exploited only by actively designing, implementing andmanaging adequate mechanisms to enable this transfer of knowledge. Eachknowledge transfer route can be fostered by particular enablers whosesuccessful implementation strongly depends on the actors involved, the waythey influence the process, and on the type of knowledge involved.

The second dimension of knowledge is its level of dissemination. Dependingon the specific culture of the organisation, emphasis can be placed on sharingknowledge and fostering learning at different levels: from individuals, togroups, to the organisation as a whole or even the inter-organisational system.

The third dimension, is the scope of knowledge. This scope can range fromcomponent knowledge, which refers to the mastering of specialist skills andtechnologies and their embodiment into components, to architecturalknowledge, which refers to how components and skills are integrated andlinked together into a coherent whole (Henderson and Clark, 1990).

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A fourth dimension of knowledge concerns the degree of abstraction andgeneralisation (scope of applicability to different situations) (Arora andGambardella, 1994).

The fifth and final dimension is the degree of articulation or embodiment. Inorder to facilitate knowledge transfer and to prevent its drain, organisationscan embody knowledge in vehicles such as design solutions (e.g. componentsand architectures), standard methodologies and procedures, or organisationalstructure and routines (Nelson and Winter, 1982). Such embodied knowledge ismore easily transferable (Barney, 1991; Itami, 1987). In contrast, tacitknowledge is more effective but difficult to imitate (Collis and Montgomery,1995). Companies, therefore, need to be able to effectively manage both theprocesses of embodiment of tacit knowledge into articulated forms as well asinternalisation of articulated knowledge into tacit forms (Hedlund, 1994;Nonaka, 1991). Awareness and explicitation, moreover, are fundamental inorder to enable knowledge to be questioned and, if necessary, changed (Bohn,1994).

In the next section, the CIMA methodology to support the management andimprovement of learning in CPI will be introduced.

Supporting knowledge management in PI: the CIMA methodologyThe CIMA methodology is designed to be used by researchers acting asfacilitators to help companies in fostering and sustaining the process oflearning and knowledge management in CPI. The methodology comprises fourclosely related elements:

(1) The CIMA process, aimed at mapping the current level of learning andknowledge management within product innovation, identifyingstrengths and weaknesses and then suggesting enabling mechanismswhich can be implemented by the company to stimulate continuousimprovement and learning, depending on specific contingencies. Theprocess has been applied in three different modes (and several variants):action research, single-company or multi-company workshops (witheither a paper-based or electronic questionnaire), and remote setting(also either with paper-based or electronic questionnaire). See Coughlanet al. (2000) for further details.

(2) The CIMA model, a behavioural model of learning in CPI, the mainconceptual underpinning of the methodology.

(3) The self-administered CIMA questionnaire, which is essentially anoperationalisation of the CIMA model, to collect data on user companies.The questionnaire is available in two formats, on paper and on diskette.

(4) The CIMA knowledge base in which all the data are stored. Theknowledge base provides the basis for intra-firm and inter-firmcomparison leading to company-specific suggestions for improvement.

The next subsection will focus on the CIMA model as an explanatory model forlearning in CPI.

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The CIMA behavioural model of learning in CPIThe first version of the CIMA model was developed to reflect a wide range oftheoretical perspectives on innovation, NPD, learning, continuousimprovement, organisation theory and performance measurement. The modelwas then piloted in a couple of exploratory in-depth case studies. Subsequently,the model was refined and then applied again in over 80 companies in Europeand Australia using the CIMA process and questionnaire referred to above.Along the way, the CIMA knowledge base was gradually filled, which allowedfor ever-better feedback and suggestions to the user companies. The refinedCIMA model is presented briefly in the remainder of this section.

The CIMA behavioural model helps to describe and analyse the learning andknowledge generation processes within PI in terms of a number of interrelatedvariables. From the analysis, company-specific guidelines for improvinglearning and knowledge generation processes can be developed to assistmanagers in sharing and learning from experiences of improvement practiceswith a view, ultimately, to improving PI performance. The variablesdistinguished are:

. continuous Innovation performance;

. behaviours underpinning continuous innovation and learning within PI;

. levers that can foster these behaviours;

. continuous learning/innovation capabilities;

. company-specific contingencies.

The relationships between these variables are illustrated in Figure 2.

Operationalisation of the CIMA modelBased on the literature and the first set of case studies, the variables in the modelwere operationalised as follows. See Corso and Pavesi (2000) for further details.

Performance is the result of improvement activities carried out in the PIprocess. This variable was operationalised and measured in terms of:

P1 Improvement generation.

P2 Improvement coherence with corporate goals.

Figure 2.Elements in the CIMAbehavioural model oflearning in CPI

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P3 Improvement diffusion within the same PI process, both within andacross organisational boundaries.

P4 Improvement diffusion between different PI processes, both within andacross organisational boundaries.

P5 Improvement consolidation.

Improvement performance is achieved through a set of eight discretebehaviours enacted by individuals:

B1 Individuals and groups use the organisation's strategic goals andobjectives to focus and prioritise their improvement and learningactivities.

B2 Individuals and groups use innovation processes as opportunities todevelop knowledge.

B3 Individuals use part of available time/resources to experiment newsolutions.

B4 Individuals integrate knowledge between all different phases of productinnovation.

B5 Individuals transfer knowledge between different PI processes.

B6 Individuals abstract knowledge from experience and generalise it forapplication to new processes.

B7 Individuals embed knowledge into vehicles.

B8 Individuals assimilate and internalise knowledge from external sources.

These behaviours can be influenced by the implementation and application oflevers, or mechanisms that managers can use when managing the PI process.These levers may be in evidence even though managers may not be tryingconsciously to stimulate learning. If appropriately oriented, however, theselevers can have a substantial influence on the attitudes and practices ofindividuals in creating, storing and transferring knowledge. Eight categories oflevers have been identified:

L1 Product family strategies.

L2 Innovation process definition.

L3 Organisational integration mechanisms.

L4 Human resource management policies.

L5 Project planning and control.

L6 Performance measurement.

L7 Design tools and methods.

L8 Computer-based technologies.

The capabilities can be described as integrated stocks of resources that areaccumulated over time through learning, or established through deliberatedecisions. These stocks of resources include internalised behaviours, technical

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skills, organisational routines, and corporate assets such as informationsystems, databases, libraries, tools, and handbooks. The level of a company'sCI capabilities determines the efforts that are needed to stimulate thecorresponding behaviours. In the model the following classes weredistinguished:

C1 Knowledge generation capability.

C2 Learning alignment capability.

C3 Capability to integrate knowledge within PI process.

C4 Capability to transfer and diffuse knowledge between PI processes.

C5 Knowledge consolidation capability.

Finally, contingencies are factors that influence the choice of levers to fosterbehaviours. Among the contingent factors distinguished in the model areexogenous variables such as the market situation of the company, andendogenous factors such as company size, and product and process complexity.

In addition to the operationalised variables, the model proposes a theory inthe form of hypothesised or tested relationships between the variables. Thefirst version of the model was based entirely on the literature and on theexperience of the researchers. The pilot studies added variables, removedothers, and confirmed, rejected or changed the originally-hypothesisedrelationships between them. The subsequent series of more than 80 casestudies has improved and enriched the model. In the next section, threeexamples of the application of the CIMA model are reported.

Interpreting cases through the CIMA modelTo date, the CIMA methodology (including the process, model, questionnaireand knowledge base) described in the previous section has been applied inmore than 80 companies in order to suggest specific mechanisms that can beimplemented to foster behaviours and, through that, achieve higher levels ofCPI performance. In this section, results from three applications of the CIMAmethodology are reported: company X in Italy, company Y in Sweden, andcompany Z in The Netherlands. In each case, data were gathered during semi-structured interviews with the main actors in each company's CPI process,using a common questionnaire. For the Italian case, company X, a PC-disketteversion of the questionnaire was used allowing for immediate feedback to thecompany. The case summary below will include one of the diagrams used inthe methodology. We will outline the observations in each case in turn.

Company X (Italy)Company X competed in the tractor industry which was characterised byincreasing concentration and globalisation. A strong emphasis on the renewaland enlargement of the product range, and a recognised excellence in productdesign allowed company X to survive and grow in an industry dominated bylarger competitors with correspondingly greater technical and financial resources.Once a country-based company with strong roots in its local environment,

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company X had recently taken over a number of its traditional competitorsbecoming one of the world leaders in its segment, with a broad portfolio of famoustractor marks. The resulting increased size and complexity and the competitivepressure both for reduced time-to-market and for improved use of criticalresources, required a quantum leap in the effectiveness of knowledge sharing andcapitalisation over time across different sites and product families.

The CIMA methodology highlighted integration and improvement diffusionwithin the PI process (P3) as the key performance area to be addressed and,correspondingly, behaviour B4 (Individuals integrate knowledge between alldifferent phases of PI) as the key behaviour to enhance. This finding isillustrated in Figure 3. A joint diagnosis with the company's managers outlinedhow weaknesses in this behaviour were responsible for rework, design changesduring the production phase and other critical effects that were hardlyconsidered by the R&D department.

Drawing examples of management practices in similar cases from the CIMAknowledge base, alternative interventions were discussed and finally anintegrated plan of actions on four different levers was decided. Through L3,organisational integration mechanisms, the project manager's role and that ofthe project work team were redesigned. Through L1, a product platformstrategy was introduced. Furthermore, a structured database to store andretrieve project knowledge throughout the company was implemented, whichwas a combination of levers L7 and L8.

Figure 3.Company X synoptic

diagram

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Company Y (Sweden)At company Y, a leading global company in the telecommunications industry,an R&D centre located in Sweden was studied. This centre, which specialisedin a particular technological field, organisationally was part of a larger unit, butwas geographically isolated from the rest of the company. The R&D centre hadbeen established a few years previously in an attempt to retain skilledengineers by providing interesting jobs in an attractive environment. Thecentre performed R&D tasks on projects spanning several organisational units.Time was the main performance parameter in this extremely dynamic industryand, correspondingly, the requirements for effective and timely co-ordinationwere substantial.

Using the CIMA methodology to map the CPI process, it was seen that, ingeneral, the R&D centre performed well with respect to knowledge transfer andlearning. The area that emerged as the most important to attend to wascoherence of improvements with corporate goals (P2). This shortcomingpointed to the importance of enhancing the frequency and diffusion ofbehaviour B1, individuals and groups use the organisation's strategic goalsand objectives to focus and prioritise their improvement and learning activitiesin the innovation process. The relatively limited evidence of this behaviour wasdiscussed with the site manager, who thought that it was most likely a result oftheir way of working. Performing rather clearly demarcated tasks within largeprojects made it difficult for the employees involved to have a clear picture ofstrategies and goals at a company level. Two factors were seen to contribute tothis problem. First, a clearly communicated product family strategy (L1) waslacking. To some extent this was explained by the unit's short history, aconstant lack of time, and an outspoken opportunistic orientation. Furthermore,there was a limited focus on process improvements (C4). The latter was furthercomplicated by integration problems between the units involved in R&D,which were due to geographical distances and different interpretations ofcompany-wide models and processes.

The mapping and the subsequent analysis revealed clearly a need for anincreased use of a product platform strategy (L1). In addition, the introductionof new performance measurements (L6) that could take knowledge transfer andlearning into account in a more explicit way was recommended.

Company Z (The Netherlands)Company Z was a large Dutch company, specialised in designing andproducing integrated defence systems for command and control, sensor andcommunications purposes. Some of the most important contingencies were:

(1) Product and market complexity, articulated in:

. high internal complexity due to size, dimension, lead-time and life;expectancy of the systems, which were developed by differentpartners and (sub) contractors, and then integrated;

. high external complexity, due to different goals of partners, whichwere related, amongst others, to political constraints.

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(2) High technology innovation: defence-industry was highly innovative,combining IT, radar-technology with naval systems expertise.

(3) High political complexity, due to decision-making process and nationalgovernment and industrial interests.

The CIMA methodology was used for mapping and analysing three relatedprojects. This exercise led to the conclusion that process improvement washeavily emphasised at the expense of B3 (individuals use part of available time/resources to experiment with new solutions) and B4 (individuals integrateknowledge among all different phases of product innovation). It was alsoconcluded that there was neither an explicitly articulated product familystrategy (L4) nor, more generally, a PI strategy. However, when looking at dailypractice, the conclusion was that there was a more or less clear emergentstrategy with implicit goals.

Drawing examples of levers from the other CIMA cases of companies withsimilar contingencies, possible interventions based on various levers wereidentified. Human resource management activities (L4) such as thedevelopment of specialist skills, departmental assessment and developmentplans, could contribute to intensifying B3 (individuals use part of availabletime/resources to experiment with new solutions). Furthermore, it was felt thatL5 (project planning and control systems directed at improvement projects) andL6, performance measurement (feedback systems, benchmarking activities,measures for creativity e.g. number of improvements proposed) could impactalso on B3.

In order to improve B4, (individuals integrate knowledge among all differentphases of PI), three levers were discussed. L2 (innovation process definition)could diffuse the activities involved in developing and implementing a newinnovation process quicker and to a wider part of the company. Through L3,organisational integration mechanisms, temporary teams and/or liaison rolesand cross-disciplinary meetings could be established. Finally, through L4,human resource management concepts, job rotation could spread the results ofthe new PI process and, through that, stimulate, diffuse and increase thefrequency of favourable behaviours.

The conclusion was that explicit use of levers that related to the transfer ofknowledge within the PI process and between PI projects/processes couldsupport improvement of the PI process.

Conclusions: managerial implications and future development of theCIMA methodologyThis article has presented some interim results of the application of the CIMAmethodology. In its current form, the methodology provides a structured, step-by-step approach to mapping the user company's current level of learningwithin PI, identifying strengths and weaknesses and then suggesting enablingmechanisms which can be implemented by the company to stimulatecontinuous improvement and learning, depending on specific contingencies.This process is supported by a behavioural model, explaining relationshipsbetween learning behaviours and outcomes, capacities enabling these

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behaviours, levers that managers can use to change existing or promote newbehaviours, and contingencies affecting this whole set of relationships.Furthermore, this model is operationalised and available as a questionnaire invarious different modes. Finally there is a knowledge base comprising the dataof over 80 companies.

Experience with its application thus far shows that the methodology is notonly usable by companies, even in a remote setting, but also yields usefulresults for them in the form of an increased understanding of the strengths andweaknesses of their PI `̀ system'' and suggestions for improvement. In thisarticle three case studies were used to demonstrate the usefulness of themethodology. As the number of cases analysed grows over time, the richnessand robustness of the analysis of and recommendations to subsequentcompanies will improve.

In the future, application of the tool will be complemented with anautomated data collection and report generation system, linked to theknowledge base in which also the actions undertaken by every company will beincluded. Using feedback from companies and facilitators assisting theimplementation, the methodology will be refined and consolidated. Moreoverthe enlargement of the user network and of the CIMA knowledge base willprovide the opportunity to analyse and study the application of levers in verydifferent (contingent) situations. Exchange of knowledge and experiences isthus facilitated, as well as allowing for essential benchmarking.

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