1997_verganti_leveraging on systemic learning to manage the early phase of product innovation...

A number of studies have pointed out theimportance of the early phases of new pro-duct development projects. In fact, thesephases (addressed in the literature withdifferent names, such as pre-project activi-ties, concept generation, product planning,idea generation, investigation, productdefinition) are concerned with a number ofcritical decisions that have great impact onthe performance of product development.Any fault occurring in these early phases inunderstanding the market needs, in choos-ing the product architecture and technologyand in defining the product specificationswould eventually deteriorate the innovationprocess, since adjustments in later stagesimply reworks that are costly and timeconsuming. Although the relevance of earlyproject phases has been empirically verifiedin the literature, the mechanisms that allowthese phases to be properly managed arestill largely unexplored. This paper investi-gates the articulated and coherent set ofmethods, organizational mechanisms andbehavioural patterns that successful com-panies adopt to manage concept generationand product planning. Inferences are basedon a field research concerning 19 in-depthcase studies of Italian and Swedish com-panies in the vehicles, helicopters and whitegoods industries. The paper supportsfindings of other studies concerning theimportance of teamworking and communi-cation. However, teamworking emerges as anecessary, but not a sufficient mechanism.Systemic learning from past experiences isthe real keystone toward an effectivemanagement of the early phases of productdevelopment processes.

R&D Management 27, 4, 1997. © Blackwell Publishers Ltd, 1997. Published by Blackwell Publishers Ltd,108 Cowley Road, Oxford OX4 1JF, UK and 350 Main Street, Malden, MA 02148,USA.

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Leveraging on systemic learning to managethe early phases of product innovationprojects

Roberto Verganti

Dipartimento di Economia e Produzione, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133Milano, Italy

1. Introduction

Most authors maintain that the success ofproduct innovation is rooted in the earlyphases of the product life cycle (Hayes et al.,1988; Gupta and Wilemon, 1990; Rosenthal,1992; Wheelwright and Clark 1992a; Clarkand Wheelwright, 1993; Brown and Eisen-hardt, 1995). These are the phases where theproduct concept is generated, the productspecifications are defined and the basic projectdecisions are taken, concerning the productarchitecture, the major components, the pro-cess technology and the project organization.These phases are generally denoted withdifferent names, such as pre-project activities,concept generation, product planning, ideageneration, investigation, product definition(these terms will be used interchangeably assynonymous in the paper). The importance ofpre-project activities has been empiricallyvalidated in well-known research studiesbased on extensive surveys (de Brentani,1991; Cooper, 1994; Cooper and Kleinsch-midt, 1994, 1995). Also, the new organiz-ational paradigms of product development thathave emerged in the last few years, giveprominence to the early development phases.One of the basic principles of these paradigmsis that the impact of design choices on marketrequirements, design feasibility, ease ofmanufacture, usability, reliability, maintain-ability, recyclability, and so on, should beanalysed as early as possible in the productdevelopment process; this will prevent theneed for late reworks that are costly and timeconsuming (Trygg, 1991). Authors assert thatthe anticipated analysis of the implications dueto a new product concept and specification

may be successful only if carried out at across-functional level, i.e. through multi-functional and multi-disciplinary teams (e.g.,Hauser and Clausing, 1988; Gupta andWilemon, 1990; Clark and Fujimoto, 1991;Fujimoto, 1993; Bacon et al., 1994). Clarkand Fujimoto, for example, in their study ofproduct innovation in the world auto industry,describe the preliminary exchange of informa-tion with downstream phases as the morecomplete, albeit complex, coordinatingmechanism adopted by successful Japanesecompanies. Teamworking and early involve-ment of key development roles are thereforesuggested as the main organizational princi-ples in concept generation and productplanning. In particular, studies focused on thebenefits provided by early involvement ofmanufacturing (Trygg, 1991; J×urgens, 1995;Ettlie, 1996; Haddad, 1997) and of majorsuppliers (Clark, 1989; Dyer and Ouchi 1993;Kamath and Liker, 1994; Liker et al., 1996).New managerial techniques have been alsoproposed to support teamworking in the earlyphases of product development, such as Qual-ity Function Deployment (Hauser andClausing, 1988) and Life Cycle Costing(Blanchard, 1979). However, although com-panies are increasingly adopting multi-functional teams in concept generation and

product planning and dedicate great efforts toanticipate downstream information, they stillface substantial problems. This means thatreasons for failures in managing early phasescannot be simply traced back to a lack ofcommunication between different departmentsor to time pressure that induces to skipproduct-planning activities. Hence, the needemerges to further understand the complex,articulated and coherent set of managerialcriteria, organizational mechanisms andbehavioural patterns that allow downstreaminformation to be properly anticipated and thattransform early involvement in a successfulpractice.

The purpose of this paper is to identify theprinciples and mechanisms that appear to beeffective when managing the early phases ofproduct development projects. It reports theresults of a field research based on nineteenin-depth case studies of companies operatingin three different industries: vehicles (7companies), white-goods (10 companies),and helicopters (2 companies). Companiesare located in Italy (13 cases) and in Sweden(6 cases). Table 1 concisely illustrates thecompanies’ business area, their size and thecontent of innovation in their product range.The research method entailed to collect bothqualitative and quantitative information at

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378� R&D Management 27, 4, 1997 © Blackwell Publishers Ltd 1997

Table 1. Outline of the 19 companies involved in the case studies.

Revenues New product lines Percentage of(1994 – launched on the 1994 revenues

Employees million market between due to newMain products Country (1994) dollars) 1992 and 1994 product lines

1. Cars Italy 125 000 30 000 10 752. Cars Sweden 7000 2475 1 603. Trucks Italy 32 000 6875 3 404. Trucks Sweden 500 122 4 605. Trucks Sweden 20 000 5250 4 406. Buses Sweden 500 130 4 207. Tractors Italy 2500 938 3 808. Large cooking devices Italy 1800 250 1 909. Cooling, washing and cooking dev. Italy 530 113 3 10

10. Washing devices Italy 350 82 3 1511. Cooling, washing and cooking dev. Italy 1630 325 16 3012. Cooling, washing and cooking dev. Italy 12 000 2373 11 5013. Large vacuum cleaners Italy 62 13 2 5014. Vacuum cleaners Italy 110 28 2 2015. Vacuum cleaners Sweden 700 112 1 3016. Large sewing machines Italy 596 64 1 3017. Sewing machines Sweden 400 63 3 6018. Small helicopters Italy 100 16 2 10019. Helicopters Italy 5500 562 3 30

the company level and at a single projectlevel (consisting of the most recent andfinished innovation project of a product lineor platform). Qualitative data allowed anunderstanding of the managerial approachand organizational mechanisms implementedin concept generation and product planningby each company. They have been gatheredby interviewing four managers in each com-pany (marketing, research and developmentor product engineering, process engineeringor manufacturing, project manager or plat-form manager). Quantitative data supportedcomparison of different approaches andinvestigation of their effectiveness. Thesedata have been collected through a question-naire with more than 200 variables andstructured managers’ subjective information.

In the next sections, first the reason for theimportance of pre-project activities is main-tained and the major problems and difficultiesencountered when managing these activitiesare introduced. Next, section 3 discusses

successful approaches and mechanisms tomanage pre-project activities, on the basis ofthe lessons drawn from observations of the 19case studies. Finally, section 4 focuses onwhat appears as the most interesting andeffective driver for managing the early phasesof product development: the exploitation ofpast experiences and systemic learning. Thislatter detailed discussion will benefit by thequantitative and structured information col-lected through the questionnaire.

2. The early phases of productdevelopment projects: significanceand management issues

The reason for the importance generallyascribed to early product development phasesmay be traced back to the structural nature ofthe product life cycle. As Figure 1 shows, thelife cycle of a product may be seen as a pro-cess with different stages and several internal

Systemic learning in the early phases of product innovation

© Blackwell Publishers Ltd 1997 R&D Management 27, 4, 1997 �379

Figure 1. The information structure of the product life cycle.

and external interactions (see also Clark andFujimoto, 1990; Fujimoto, 1993). The mainstages are product development (which articu-lates in concept generation and productplanning — i.e., what we consider as earlyphases — product design and processdesign), production, consumption, disposal,and enhancement or evolution into a nextgeneration product. These stages and phasesare linked by reciprocal interdependencies(Thompson, 1967; de Weerd-Nederhof et al.,1994). First, reciprocal interdependenciescharacterize the internal activities of the pro-duct development process. For example: anew product concept must fit with availableand prospected product technologies; a designsolution must be feasible and should accountfor the constraints coming from processdesign; the different parts and components ofthe product must fit each other consistently. Inother words, the new product concept, thenew product package and the new productionprocess mutually interact and should be con-tinuously integrated each other (Slack et al.,1995). For this reason, most authors look atproduct development as a series of problemsolving cycles occurring among its internalactivities (see for example Clark and Fujimoto1991; Souder and Monaert, 1992). Second,reciprocal interdependencies occur betweenthe product development process and thesubsequent production and consumptionprocesses. In fact, in order to develop a newproduct and to launch it into the market,customer expectations have to be anticipatedand constraints due to manufacturability haveto be accounted for; in this respect, Clark andFujimoto (1991) represent the productdevelopment process as a simulation of con-sumption and production: developing a newsolution means forecasting the future con-straints and opportunities that will arise duringthe life cycle of the product. Finally, recipro-cal interdependencies occur also with nextgeneration products. In fact, new ideas andsolutions may be carried over, especiallywhen the current project develops a newplatform to be re-used in other derivativeproducts (Wheelwright and Sasser, 1989;Wheelwright and Clark, 1992b; De Maio etal., 1994; Corso et al., 1996). Constraints andopportunities coming from future productionand consumption of the latter should thereforebe anticipated in the former.

Managing product innovation entails toeffectively handle these reciprocal interde-pendencies between new solutions designedin the early phases and constraints/oppor-tunities arising in the later phases of theproduct life cycle. This is a complex task,since downstream information is not com-pletely known when developing a newsolution. In fact, on the one hand novelty ofthe product and on the other hand the con-tinuous changes in the market, technological,competitive, and regulatory environments,together with the company’s strategy, createnew constraints and new opportunities thatare unlikely to be predicted at the outset of aproject. Uncertainty about downstream infor-mation therefore creates severe problems andeventually compromises the product develop-ment performance, since:

solutions have to be changed later to dealwith unexpected events. This is typical ofengineering changes due to unfeasibility orpoor manufacturability emerging duringpilot production. These late changes entailcostly reworks and increase the time tomarket of the product;downstream phases have to put additionalwork in the project in order to handleincompatible solutions (e.g., specialfixtures have to be developed in the pro-cess design phase, since product drawingsdid not contemplate constraints due toproduction technologies). This againimplies higher development costs anddelays;quality of the new product (defined as itsfit with the production and consumptionprocesses) is impaired, e.g. the actualmarket needs are not satisfied or new tech-nological opportunities are not incorpor-ated into the product.

In order to deal with reciprocal interdepen-dencies in the product life cycle companieshave two different alternatives (see Figure 2):

Feed-back planning (or reactive appro-ach). The product is developed withoutintensively anticipating information in theearly phases. Reasons behind this approachlay on the high uncertainty of downstreaminformation when examined in theupstream phases of product development.Since this uncertainty decreases as the

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production and consumption processesbecome closer (see the dotted line inFigure 2), changes to design solutions dueto unexpected constraints or opportunitiesare introduced later in the project, whendownstream information is available. Thisapproach is effective provided late correc-tive actions (i.e. engineering changes oradditional work in downstream phases)have a minor impact on the productdevelopment performance. However, thisis seldom true: as studies on Project Man-agement and Product Developmentunanimously assert (e.g., Meredith andMantel, 1989; Hayes et al., 1988; Trygg,1991), the later the downstream con-straints emerge, the higher the time andcost due to reworks and engineeringchanges (see the continuous line in Figure2). In fact, late changes entail a greaternumber of already developed solutions tobe re-designed, including also those mostcostly and time consuming such as detailedproduct design and process design. Insome cases, unexpected technologicalopportunities or flaws in interpreting themarket needs arise when the product isalready on the market, and it is thereforetoo late to introduce any change;Feed-forward planning (or proactive

approach or front loading, Fujimoto,1997). Information is anticipated as earlyas possible in the product developmentprocess, so that new solutions generated inthe early phases already account for futureconstraints and opportunities. The manage-ment focus and attention is thereforeconcentrated in concept generation andproduct planning where, as Figure 2shows, there is the highest ability toinfluence the outcome of the project.Hence, great efforts are devoted to prop-erly define the product concept andspecifications in order to reduce possibleproblems and reworks in later phases. Thedrawback of feed-forward planning is theuncertainty that affects the early phases.This approach is effective provided a com-pany has great capabilities to anticipatehighly uncertain information, otherwiseearly analysis of future constraints is asterile exercise: time at the beginning ofthe project is wasted while reworks in laterstages are not avoided.

Both reactive and proactive capabilitiesare necessary. However, studies previouslyreported in the introductory section, whichdemonstrate a strong relation between deci-sions taken in pre-project phases and success



Figure 2. Uncertainty and detrimental impacts of reciprocal interdependencies in the different stagesof the product life cycle.

of innovation, support the superiority offeed-forward planning. Indeed, this approachis also advocated by the new organizationalparadigms of product development. In thisperspective, feed-back planning is consid-ered as a compensation to feed-forward. Itentails that any initially unforeseen eventshould be handled later by reacting at lowcost and time. Anyway, since later changeshave dramatic impacts on product develop-ment performance, this should be avoided asmuch as possible through a strong proactiveorientation.

Nevertheless, although there is a wideagreement on the effectiveness of feed-for-ward planning, this approach is quitecomplex. In fact, uncertainty about down-stream information is remarkable in the earlyphases of product development. This is amajor problem especially in highly innova-tive projects or in fairly mutable environ-ments in terms of customer needs,competition, technologies and regulations.Implementing successfully the feed-forwardapproach therefore implies a need to under-stand which mechanisms allow the handlingof uncertainty at the outset of a project andsimultaneously boost innovation.

3. The principles of feed-forwardplanning

Managing the early phases of productdevelopment in a proactive perspective callsfor an articulated and coherent set of organiz-ational mechanisms, managerial principlesand methods. In particular, lessons learnedfrom the, 19 case studies showed that 6principles make feed-forward planningeffective: teamworking and communication,harmonized objectives, encouraged andsupported proactive thinking, integrationwith detailed design, planned flexibility,systemic learning. They are examined in thefollowing sections.

3.1. Teamworking and communication

Anticipation of downstream constraints andopportunities entails the collection of a largeamount of information. Bacon et al. (1994),for example, consider as information to beanticipated the customer and user needs, the

competitive product offerings, the tech-nological risks and opportunities and theregulatory environment into which the pro-duct will be delivered. In some companiesthis information is collected and analysed bya specialized department (e.g., the productplanning department). In other cases, theproduct manager or platform manager areresponsible for specifying the productconcept; sometimes, a single function isinvolved in the early phases of productdevelopment, such as marketing (in market-driven companies) or research and develop-ment (in high-technology industries).However, a number of studies demonstratethat the most successful criterion for collect-ing and analysing such an articulated set ofinformation is the early involvement of allthe major departments which have directcontact with future constraints and oppor-tunities: marketing (and in some cases leadcustomers), research, product engineering,process engineering, manufacturing, pur-chasing (and/or major suppliers). Theeffectiveness of teamworking and earlyinvolvement also emerges in this study (seesection 4 for quantitative evidence). Indeed,all companies except one allocate conceptgeneration and product planning to a multi-functional team. This preliminary cross-functional exchange of information amongthe main actors of product developmentprovides four major benefits: first, it enlargesthe knowledge base available in the earlyphases of product development and thereforereduces the uncertainty on future constraintsand opportunities; second, it assures align-ment of product concept with companystrategy and functional strategies (i.e., thetechnology, marketing and manufacturingstrategies); third, it allows downstreamphases (e.g., Process Engineering) to startearlier with some preliminary activities, thusencouraging parallel design phases; fourth,since the owners of downstream constraintsare involved in concept generation, then theircommitment to upstream decisions isfostered.

3.2. Harmonized objectives

In most case studies we noted that, althoughdifferent departments were gathered in a pre-project cross-functional team, this did not

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assure communication and anticipation ofinformation from the product life cycle. Oneof the reasons for this ineffectiveness of feed-forward planning was that team members didnot share common objectives while involvedin concept generation. Hence, they implicitlyor even explicitly paid prevailing attention totheir own functional performance. In thesecases, for example, the Product Engineeringrepresentative often hindered any early deci-sion that could place additional constraints toproduct design and increase the time neededto provide detailed drawings. In this situa-tion, with a lack of a shared system ofobjectives, integration in the pre-project teamis unlikely to occur and early involvementmay result in a fruitless exercise. Upstreamdepartments, exposed to time pressure, donot see any advantage in anticipating andcommunicating their likely product design todownstream phases, while Process Engineer-ing and Manufacturing bring to pre-projectonly their constraints and feasibility prob-lems, restraining the creativity andinnovation typical of concept development.Of course, a new culture and distinctivecapabilities are necessary when applying thefeed-forward approach. Upstream phaseshave to master the development of newsolutions in the presence of a higher numberof constraints, while downstream phasesshould learn to be creative. However, such aculture and capabilities are ineffective (andmoreover are unlikely to be nourished) ifpre-project team members do not have com-mon objectives. This means, for example, allmembers being measured on the overall timeto market of the project, or on the break-even-time of the product (House and Price,1991). A harmonized performance measure-ment system fosters early sharing ofinformation, since all pre-project team mem-bers are measured both on the newness andintegrity of product concept and on theirability to avoid the detrimental impacts oflate, unexpected events.

3.3. Encouraged and supported proactivethinking

Anticipating information in the early phasesof a product development project is a difficulttask, since plenty of uncertain and unstruc-tured information should be analysed.

Without proper guidance and support, mostpre-project teams eventually only anticipatesuperficially. Then, given the uncertainty onfuture implications of an early decision, theyquickly proceed straight into detailed design,where the necessary information eventuallyemerges. Proactive thinking should on thecontrary be stimulated, nurtured and sup-ported as much as possible in the earlyphases. The problem is how to encourageuncertain information to be gathered in theearly phases, without entering into detaileddesign. The most successful companies inour sample apply three methods to this end.

Formal pre-project stage. Most companiesuse a formal procedure that regulates theactivities and documents to be completed inthe concept generation and product planningphases, which usually end with top manage-ment’s formal approval. Some of them alsouse check-lists to screen the product conceptin the light of typical downstream constraintsand opportunities (in this respect, see alsothe study of de Brentani, 1986). This doesnot mean that these companies definedetailed specifications, nor that they restricttheir feed-forward effort only in the earlyphases of product development (indeed,proactive thinking is necessary during all theproduct development process). They simplytry to focus the initial phases of the projecton the sole effort of anticipating information.They clearly define the objectives, the basicconcept, the architecture and parts of theproduct and of the production process, anddevelop a plan for the following downstreamphases. Detailed analyses are only performedon a few critical issues, with the aim ofanticipating possible constraints and oppor-tunities rather than providing thorough andcomplete drawings. Any other detaileddesign is instead pushed further in subse-quent phases in order not to divert the pre-project team from its feed-forward effort.The only focus is proactively thinking on theconsequences and opportunities that willemerge in the product life cycle.

Managerial techniques and tools. In recentyears several methods have been proposed tosupport the feed-forward effort of thepreproject team. Examples are Quality Func-tion Deployment, Target Costing, Failure



Mode/Failure Effect Analysis, Value Analy-sis, Life Cycle Costing and Analysis. TargetCosting (Sakuray, 1989) was the mostapplied technique in our sample while QFDwas used only partially successfully in 6cases. Indeed, as also other studies demon-strate (Akao, 1990; Govers, 1996), QFDstimulates cross-functional proactive think-ing, but it also bounds the pre-project team tothorough and long early analyses, which inturbulent environments may be useless andcounterproductive.

Early prototyping. One of the most effectivemechanisms to foster early discussion andenhancing the feed-forward exercise is tosimulate as early as possible the physicalcharacteristics of the new product. To thispurpose a useful method is early prototyping,i.e. the early and rapid development of aprototype that reflects the expected features,functions, and characteristics of the productin a rough and approximated manner. Again,early prototyping should only aim at stimu-lating proactive thinking and not at testingdetailed solutions; hence, it may be easilyand quickly realized by the pre-project team.A white-goods company, for instance, sim-ply modifies a product of the previousgeneration in order to simulate the functionsand characteristics of the new product. A carmanufacturer has decided to anticipate thedevelopment of prototypes in the first phaseof product development, although theseprototypes may not be an accurate anddetailed reproduction of the new car. Acompany in the helicopters industry usesElectronic Mock-Up Systems to detect anygeometric interference of parts duringconcept generation. For further insights onadvanced technologies that are currentlyaccelerating the fabrication of early proto-types see Bullinger et al., 1995.

3.4. Integration with detailed design

Efforts of anticipating information in pre-project activities are fruitless if this informa-tion is not transferred and exploited in thefollowing phases of product development(Fujimoto, 1989). A white-goods company,for example, designated its R&D, marketingand manufacturing directors as responsible fordeveloping the concept and specifications of a

new refrigerator. These highly experiencedpeople were able to identify and anticipateinformation on a number of critical areas ofthe new product. However the refrigeratorfaced several problems and modificationsduring production ramp-up since product andprocess engineers had only a minor knowl-edge of the criticalities that were identified bythis high-level pre-project team.

We observed several ways of integratingpre-project with downstream detailed design.Most companies rely on reports that describeproduct specifications. Albeit necessary,these reports in themselves are rarely able totransfer the richness of the unstructuredinformation discussed in the pre-projectteam. The most effective solution appears toprovide continuity between people involvedin the early phases and the design teams: firstof all, by assuring that the project manageralso belongs to the pre-project team andparticipates in concept generation and pro-duct planning; second, by keeping the pre-project team in action during product andprocess design (e.g., as a product planningcouncil); third, by involving working-levelmembers early in product planning, at leastin some meetings or in the preliminary col-lection of downstream information.

3.5. Planned flexibility

As seen in section 3.3, encouraging proactivethinking does not necessarily mean that thepre-project team must anticipate and analysein detail any possible constraint and opportun-ity of the product life cycle. In some cases,too much information is more detrimentalthan effective. Consider the followingexample. A white-goods company of oursample adopts a stage-gate structure for theproduct development process. This means thatproduct development is split into sequentialphases, separated by check points (see Coo-per, 1990). In particular, after investigationand product planning, a strategic committeehas to certify the coherence and completenessof product specifications before proceedingany further. Product specifications thereafterare not allowed to change. An extreme andtoo strict application of this approach createdsevere problems in a project for developing anew washing-machine. The concept develop-ment team was forced to define in detail the

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product specifications before starting productdesign. The consequence was that conceptgeneration and product planning took twicethe time of product and process design. More-over, the quality of the product wascompromised, since the pre-project phaseconsumed such a large amount of time thatcustomer’s needs had already changed whenthe product reached the market.

Indeed, complete and detailed productspecifications are seldom necessary,especially when the environment faced bythe company is turbulent and variable, or inhighly innovative trials (see Iansiti, 1995).Here, initial uncertainty is considerable.Downstream information therefore is notcompletely available during product planningand risks of implementing late correctiveactions cannot be unconditionally avoided. Inthe helicopters industry, for example,defining detailed specifications for avionicssystems is useless, since technology is con-tinuously changing and new unpredictableopportunities often emerge. In a white goodscompany, the pre-project team was unable tocertify the reliability of a device for controll-ing the temperature of a new oven. In fact,this device was radically innovative and itsinclusion in the new product was only poss-ible by completing its refinement simul-taneously with oven development.

In these cases, where the informationneeded for defining product specificationsdoes not become available until the team getsinto design, detailed feed-forward planningdoes not provide significant insights on futureconstraints/opportunities and eventuallyresults in a waste of precious time. A feed-back approach therefore seems to be the onlyviable alternative (Smith and Reinertsen,1991; Von Hippel and Tyre, 1995; Ward etal., 1995; Thomke, 1996). However, feed-forward planning again plays a central role incontrolling the detrimental impacts of areactive policy. In fact, the cost and time oflate corrective actions may be greatly reducedif preventive measures are taken from theearly development phases. For example, theproduct may be conceived with a modularstructure so that any change in a single partwill not affect the overall system. Protectiveand alternative solutions may also be pre-viously arranged to overcome any infeasibil-ity problem due to a new technology. Finally,

additional resources may be allocated to themost uncertain activities. These preventivemeasures confer flexibility to the productdevelopment process (on the concept ofdevelopment flexibility see Thomke, 1996).Without this flexibility the feed-back appro-ach would provide poor performance. Notethat preventive measures are effective pro-vided they are arranged in the early phases ofthe project. For this reason, we call this prin-ciple planned flexibility. It entails that theflexibility of the product development processis planned early so that late adjustments andinnovations may be accepted with marginalconsequences. In other words, referring backto Figure 2, it means that feed-forward plan-ning should aim both at: (1) reducinguncertainty about constraints and opportuni-ties by anticipating downstream information,thus decreasing the probability of implement-ing late corrective actions; and (2) reducingthe cost and time of these corrective actions,thanks to planned flexibility.

The principle of planned flexibility alsoshows that feed-forward and feed-back plan-ning are not reciprocally incompatible. Onthe contrary, they may be jointly appliedwith outstanding results and mutual support.This synergy is evident in those companies inthe sample that use an overlapped structurein product development. ‘Overlapping’means to carry on simultaneously differentphases of the product development process(Imai et al., 1988). It may provide superiorperformance, as demonstrated in severalstudies. Clark and Fujimoto (1991), forexample, analysed the benefits of overlap-ping product design and process design in cardevelopment, while Iansiti (1995) investi-gated the practice of overlapping conceptgeneration and detailed design in the main-frame and multimedia industries. Overlap-ping is a feed-back approach. In fact, itimplies that upstream phases progressivelyrefine a new solution on the basis of the rapiddownstream feed-backs ensuing from theactual attempts to implement the innovativesolution (Fujimoto, 1989; Ward et al., 1995).In addition, overlapping entails that, withtwo or more phases simultaneously in pro-gress, late changes may be accepted with lowimpact on cost and time. For example,insofar as product specifications are notfrozen, the product concept may be adjusted



to deal with sudden changes in market needsor in the competitive environment and pro-duct design may be updated according tonew technological developments, especiallythose concerning the manufacturing process.In other words, overlapping enlarges thewindow for reacting to late constraints andopportunities.

Being a reactive approach, overlappingimplies the embedding of substantialflexibility into the product developmentprocess. This leads again to the pre-projectpolicy of a company and to the plannedflexibility principle. Indeed, several com-panies in the sample followed an overlappedpath for developing their new product. How-ever, successful implementations wereobserved only in those cases where overlap-ping was an explicit approach, i.e. where theflexibility it needs (e.g., cross-functionalteams and enhanced communications means)was properly planned and activated since theearly phases of the project. A car manufac-turer, for example, noted that overlappingproduct design and process design waseffective only when product designers, pro-cess designers and suppliers had frequentand direct interactions, avoiding endorse-ment from project manager and functionalmanagers. This increased level of delegationto working-level teams was achieved byfostering the proactive orientation of mana-gers during concept generation and productplanning. Top managers and leaders devotedgreat attention in the early phases to analysethe coherence between product concept andfuture constraints (including functionalconstraints due to a lack of resources andfunctional strategies). Apart from a fewcritical issues that were specified in details,their major purpose was to agree upon allow-ances within which designers could havemargins for decision. Detailed design teamswere then able to interact directly and had ahigher degree of freedom to seize quicklyany unexpected opportunity.

This example shows that overlapping andfeed-forward planning may provide superiorperformance when jointly applied. In fact, onthe one hand overlapping becomes effectiveespecially when supported by proactivethinking and planned flexibility. On the otherhand, overlapping, with its increased reactivecapabilities, may provide a useful support to

feed-forward planning, since the proactiveeffort may focus only on few critical ele-ments, avoiding detailed and time consuminganalyses of every downstream constraint andopportunity.

4. Systemic learning: the keystone offeed-forward planning

As emerged in the above discussion, theproactive capability of a company does notdepend on the time and effort spent inconcept generation and product planning.What actually makes the difference in feed-forward planning is the capability of the pre-project team to identify early on any criticalareas and to forecast their influence on pro-ject performance. Critical areas have twomajor characteristics: (1) they are the mostuncertain as well as relevant elements in theproduct life cycle, and (2) they call for costlyand time consuming corrective actions ifdetected and handled late in the project.Critical areas may concern the market needs,the competitive environment, the product andprocess technologies, the regulations or theproject resources. They should receive pri-mary attention and anticipation effort in thepre-project team. For example, in helicopterdevelopment, the distribution of weights hasto be defined and thoroughly specified asearly as possible, since any subsequentchange could generate a number ofmodifications in several components and inthe architecture of the product. A white-goods company recognized as a critical areain a new refrigerator project the high variabil-ity in the characteristics of the polyurethaneinsulation provided by its prospective sup-plier; a detailed analysis in product planningwas devoted to define the proper thickness ofinsulation material and, therefore, of the bodyof the refrigerator. The product design teamswere therefore able to provide solutionswhich already accounted for constraints inraw materials and in the supply process.

The basic issue in feed-forward planning istherefore how to identify critical areas inadvance and how to understand theirimpacts, given the initial project uncertainty.In this respect, the previous section emphas-ized the benefits of teamworking, communi-cation, common objectives, and tools, such

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as Quality Function Deployment and earlyprototyping. However, our case studiesdemonstrated that feed-forward capabilitiesalso depend on ‘soft’ rules and behaviouralpatterns. Consider the following example. Awhite goods company should develop a new,very small refrigerator. New technologicalsolutions are proposed and, from a technicalpoint of view, the new product is feasible.However, the concept development teamwants to detect early any problem that couldemerge in the assembly line that could makethe product unmanufacturable (unless at veryhigh costs). To deal with this issue, a feed-back or a feed-forward approach could beimplemented. A purely reactive approachwould entail that Product Engineering startsdeveloping the new refrigerator and providesinformation and drawings to Process Engin-eering as soon as possible; then ProcessEngineering begins to develop dies, tools andfixtures and verifies any assembly problems.Any feed-back concerning manufacturingconstraints would reflect the actual practiceof Process Engineering in attempting toimplement the upstream design. In otherwords, feed-back is based on a learning bydeveloping mechanism. Feed-forward plan-ning, on the contrary, is based on acompletely different and far more complexprocedure. This entails that in the conceptgeneration phase Product Engineering andProcess Engineering, both belonging to thepre-project team, exchange uncertain infor-mation on future constraints and opportuni-ties. In particular, about every possibleinformation need that could be anticipated,Product Engineering selects only those partsof the new technological solution that couldgenerate problems during process design andmanufacturing. Note that these critical areasare not necessarily concerned with the mostcomplex parts of the product; in other words,the product engineer has not to anticipatecriticalities on his own future tasks (usuallythese criticalities are easily known by askilled designer). The difficult thing is thatProduct Engineering should identify, withoutentering into detailed design, any criticalareas that could create problems in otherphases. Process Engineering would thenanalyse this preliminary information in orderto detect possible manufacturing constraintsand opportunities. Hence, the capability of

Process Engineering to anticipate down-stream constraints strongly depends on theinformation provided by the product engineerand, therefore, on his understanding of theprocess technologies.

This example shows that feed-forwardplanning is made effective by the systemicknowledge held by each member of the pre-project team, i.e. by his capability to detectearly which elements in his own decisionsmay have significant consequences on theother phases of the product life cycle. Thissystemic knowledge is not built through alearning by developing mechanism, such asin feed-back planning. Being in the initialphases, systemic knowledge may only bedrawn from previous projects, i.e. throughlearning from experience mechanisms.Hence, the capability of a company to learnfrom past projects and to incorporate thissystemic experience in the pre-project teamappears as the keystone of feed-forwardplanning. We call this principle systemiclearning.

The importance of systemic learningmechanisms clearly emerges from our casestudies. In particular, Figures 3–5 comparethe contributions of systemic learning andteamworking to feed-forward planning.Measures are drawn by data in the structuredquestionnaires, which are aggregated bymeans of fuzzy functions and fuzzy opera-tors. Details on metrics are provided in theappendix. Here, two major points are high-lighted. First, all measures are relative, thusmaking it possible to compare companiesoperating in different industries. Second, wedo not analyse the impacts of the aboveprinciples on the overall performance of theproduct development project (e.g., productsuccess in terms of sales), since overallperformance is affected by several parametersand phenomena (company A for example,ranks third in terms of product functionalfeatures; however, because of a lack of feed-forward capabilities, it achieved this perfor-mance to the detriment of extremely highproduct costs and time to market). On thecontrary, we restrict the analysis on the soleparameters that reveal the capability to antici-pate uncertain downstream information in theearly phases of product development. Thisfeed-forward effectiveness was measuredthrough a fuzzy function depending on the



occurrence of the typical drawbacks of inef-fective pre-project phase (such as reworks,engineering changes, unexpected events thatcall for additional work in later stages ofproduct development, higher product costsand time to market than foreseen).

Figure 3 shows the relation between feed-forward effectiveness and the degree ofteamworking and communication in earlyphases (a fuzzy function that accounts forinvolvement in the pre-project team of themajor actors of the product life cycle, fortheir teamworking attitude, and for theircommunication patterns). Company A, thatappoints concept generation to its ProductEngineering Manager, has poor proactivecapabilities compared to other companies, allusing a team approach to pre-project. Thishighlights how communication in the earlyphases is necessary in order to anticipatedownstream information. It also confirmsresults of other studies on early involvement,with the note that teamworking in earlyphases is becoming a diffuse practice. How-ever, if we focus the analysis on 18companies excepting A, teamworking doesnot appear as a sufficient condition for suc-cessful feed-forward planning. Somecompanies (see for example company B)have considerable degrees of teamworkingand communication. However, this does notdirectly reflect in high feed-forward effec-

tiveness, especially if compared to companyC that is remarkably proactive.

The above results were therefore furtherexamined in the light of the systemic knowl-edge embodied in pre-project teams. As saidabove, systemic knowledge is the under-standing of each pre-project team memberabout the impacts of his specific decisions onthe product life cycle as a whole. Directmeasures of systemic knowledge were notavailable, because of the intangible nature ofthis variable. We therefore investigated themechanisms that each company uses tocreate this knowledge, i.e. the systemiclearning mechanisms. In particular, systemiclearning only occurs if people that developedthe product concept and specifications alsoreceive and conceptualize the feed-backsrelated to their original choices. Projecttermination meetings and project audit at thebreak-even time of the product appear asextremely useful in this regard (for studiesspecifically investigating learning mechan-isms in new product development, seeMaidique and Zirger, 1985; McKee, 1992;Clark and Wheelwright, 1993; Caffyn, 1996;Hughes and Chafin, 1996; Bartezzaghi et al.,1997). Indeed, the most proactive companieshave a common policy in introducingsystemic knowledge to the early projectphases. Their pre-project team members havea major role also during project terminationand audit in order to learn from variationsbetween their prospected early solutions andactual final outcomes. In companies D and E,for example, the pre-project team is alsoappointed to the project termination phase; inthese project termination meetings priority isgiven to discussion of unexpected problemsand to understanding reasons for variations inproject results. Job rotation of team mem-bers, on the contrary, seems to be lesscapable of generating systemic learning,since it usually implies upstream solutionsand downstream constraints being experi-enced in different development projects. Thelearning cycle is therefore interrupted and, inaddition, specialized knowledge is likely tobe compromised. In other words, the pre-project phase does not necessarily needgeneralists, but specialists with knowledge ofthe systemic impacts of their choices.

These considerations are supported by thestructured data collected in the questionnaires.

Roberto Verganti


Figure 3. Relation between teamworking/communication and proactive capabilities.

Systemic learning was measured through afuzzy function depending on: existence of aformal project termination or project auditphase; relative importance, in that phase, ofthe analysis of mismatching between initialsolutions and resulting constraints/oppor-tunities; presence in the project terminationteam of the same members that belonged tothe pre-project team. One company has beenskipped in this analysis since it has been usingproject termination procedures only recently(less than 4 projects). Its learning path istherefore not identifiable.

Figure 4 demonstrates how systemic learn-ing emerges as a keystone for feed-forwardplanning (the correlation coefficient betweendegree of systemic learning and feed-forwardplanning is 0.76, with a significance level ofmore than 99%). In addition, Figure 5 pointsout the superior performance provided byteamworking when supported by systemiclearning. In particular, the two most effectivecompanies (D and E) are characterized byhigh teamworking and systemic learning,while the unsuccessful project in company Alacks both these principles. Companies withlow and intermediate performance mainlylocate in the lower-right area of the matrix:this confirms that teamworking is not asufficient condition for effective anticipationof information, unless it is sustained bysystemic learning. Most interesting, company

C shows considerable proactive capabilitieswith only a moderate orientation towardteamworking (its pre-project team consists ofthe Marketing, Product Engineering andProcess Engineering functional managers).This means that systemic knowledge andunderstanding of the impacts of early choiceson the entire product life cycle is often moreimportant than enlarging the number ofpeople involved in early phases.



Figure 4. Relation between systemic learning frompast development projects and proactive capabilities.

Figure 5. Joint analysis of teamworking/communication and systemic learning.

5. Conclusions

Managing the product development processimplies handling reciprocal interdependenciesbetween upstream solutions and downstreamconstraints/opportunities in the product lifecycle. The early phases of a developmentproject play a central role in this regard. Infact, by anticipating as early as possible theanalysis of implications due to a new productconcept, or to a new product and processtechnology, late corrective actions may beavoided and high levels of quality and inno-vation may be achieved. However, proactivepolicies are extremely complex, because of thehigh uncertainty inherently induced by inno-vation and environmental turbulence. In thispaper the basic mechanisms that make earlyproject activities and feed-forward planningsuccessful have been investigated. In particu-lar the following principles have been drawnby observing successes and failures in 19 casestudies: teamworking and communication,harmonized objectives, encouraged and sup-ported proactive thinking, integration withdetailed design, planned flexibility, systemiclearning. All these principles are necessary andare effective only if jointly applied. The majorchallenge is that they are only partiallyencoded in managerial techniques and tools.Instruments, such as checklists, mappingtools, structured data-bases or early prototyp-ing may be useful. However, ‘soft rules’,behavioural patterns and, most of all, the skillsof pre-project team members emerge as essen-tial. In particular, the crucial capability is whatwe call systemic knowledge, i.e. the capabilityto detect the impacts of specific early decisionson the downstream phases of the product lifecycle. A lack of this capability makes workingin teams fruitless and causes sterile feed-for-ward efforts.

The paper shows how systemic knowledgeand proactive skills are nurtured by continu-ously striving to learn from experience inproduct development. Companies in the sam-ple that involved pre-project team membersalso in project termination and that stimulatedthe analysis of variances between early solu-tions and actual final outcomes demonstratedthe highest proactive capabilities. Systemiclearning is therefore the driving force behindfeed-forward planning. It is the keystone thatmakes the other proactive principles effective.

Systemic learning entails that there is a subtlelink between the current proactive effort andprevious similar projects. This shows thatlearning from experience is not marginal,even for managing innovation processeswhere previous and established assumptionsmust be overcome. Radical developments ofnew products and continuous improvementsof capabilities can co-exist and, indeed, arethe self-supporting leverages of the samesuccessful mechanism.

Appendix

In order to compare the proactive capabilitiesof the nineteen companies, structural datawhere collected by means of a questionnairewith more than 200 parameters. By aggregat-ing some of these parameters we obtainmeasures for the 3 synthetic variables reportedin Figures 3–5 (feed-forward effectiveness,teamworking and communication, systemiclearning). Aggregation is implemented thanksto fuzzy set theory (Zimmermann, 1993).This is necessary since each synthetic variablehas two major characteristics: (1) it ismultidimensional, being dependent on severalconstituting parameters through a hierarchicalstructure (for example, systemic learningdepends on the main focus of project termina-tion, on the main roles involved in projecttermination and on the main roles involved inpre-project); (2) its constituting parametersare measured in the questionnaire byheterogeneous indexes (for example the focusof Project Termination is a Likert’s-like scale,while the involvement in pre-project ofspecific roles such as Manufacturing or Pro-duct Engineering is a logical variable). In thiscase, the ‘crisp’ fuzzy logic is adopted, that is:heterogeneous parameters are transformedinto homogeneous fuzzy functions whosevalue varies between 0 and 1; then, theseconstituting fuzzy functions are aggregatedthrough fuzzy operators. In particular, twocompensatory operators are used in the study:

X.Fuzzyand.Y = α min(X, Y)+ (1 − α)(X + Y)/2,

X.Fuzzyor.Y = α max(X, Y)+ (1 − α)(X + Y)/2 , where α = 0.2.

Table 2 reports the aggregation operators

Roberto Verganti


for the 3 synthetic variables analysed in thestudy. A brief explanation of the constitut-ing parameters from which syntheticmeasures have been derived is also pro-vided. It is important to point out that allmeasures are relative, thus making it poss-ible to compare companies operating indifferent industries.

References

Akao, Y. (ed.) (1990) Quality Function Deployment. IntegratingCustomer Requirements into Product Design. Cambridge MA:Productivity Press.

Bacon, G., Beckman, S., Mowery, D. and Wilson, E. (1994)Managing product definition in high-technology industries: a pilotstudy. California Management Review, Spring, 32–57.

Bartezzaghi, E., Corso, M. and Verganti, R. (1997) Continuousimprovement and inter-project learning in new product development.International Journal of Technology Management, 14, 116–138.



Table 2. Measures for the synthetic variables analysed in Figures 3–5.

Syntheticvariable Aggregation operator Notes on constituting parameters

Feed-forwardeffectiveness

Teamworking andcommunication

Systemic learning

1 – [(Reworks .Fuzzyor. Unexpectedevents).Fuzzyor.(Costvariance.Fuzzyor.Timevariance)]

Departments .Fuzzyand.Attitude .Fuzzyand.Communication

Team .Fuzzyand. Focus

Reworks = occurrence of reworks duringdetailed design, relative to other flaws inthe project not depending on feed-forward capabilities (e.g., lack of topmanagement support);

Unexpectedevents = occurrence of eventsinitially unforeseen, relative to otherflaws in the project;

Costvariance = variance of final productcosts with respect to the target costestablished in the early phases. Thisvariance is considered to be extremelycritical if product cost is a competitivepriority for the company;

Timevariance = variance of the actual timeto market with respect to the expectedtime to market established in the initialplan. This variance is considered to beextremely critical if time is a competitivepriority for the company.

Departments = number of major rolesinvolved in the pre-project team(Platform Manager or Product Planning,Marketing, Research or ProductEngineering, Process Engineering,Manufacturing, Purchasing, leadcustomers, major suppliers);

Attitude = importance of attitude towardsintegration when selecting pre-projectteam members relative to other skillparameters (e.g., technicalcompetencies);

Communication = % of co-located teammembers.

Team = percentage of pre-project teammembers involved in project terminationof previous similar projects;

Focus = importance of analysis of variancesduring project termination of pastprojects, relative to other purposes ofproject termination (execution ofproduction rump-up, late problemfighting, resource evaluation).

Blanchard, B.S. (1979) Design and Manage to Life Cycle Cost.Portland: M/A Press.

Brentani, U. de (1986) Do firms need a custom-designed newproduct screening model? Journal of Product Innovation Man-agement, 3, 108–119.

Brentani, U. de (1991) Success factors in developing new businessservices. European Journal of Marketing, 15, 2, 33–59.

Brown, S.L. and Eisenhardt, K.M. (1995) Product development:past research, present findings, and future directions. Academy ofManagement Review, 20, 2, 343–378.

Bullinger, H.J., Fischer, D. and Worner, K. (1995) Rapid prototyp-ing — a method for the development of innovative products. The13th International Conference on Production Research, Jer-usalem, 6–10 August, pp. 426–429.

Caffyn, S. (1996) Extending continuous improvement to the newproduct development process. R&D Management, 27, 3,253–267.

Clark, K.B. (1989) Project scope and project performance: theeffect of parts strategy and supplier involvement on productdevelopment. Management Science, 35, 1247–263.

Clark, K.B. and Fujimoto, T. (1990) The power of productintegrity. Harvard Business Review, November–December,107–118.

Clark, K.B. and Fujimoto, T. (1991) Product DevelopmentPerformance. Cambridge MA: Harvard Business School Press.

Clark, K.B. and Wheelwright, S.C. (1993) Managing New Productand Process Development. New York, NY: The Free Press.

Cooper, R.G. (1990) Stage-gate systems: a new tool for managingnew products. Business Horizons, 33, 3, May–June.

Cooper, R.G. (1994) Third-generation new product process.Journal of Product Innovation Management, 11, 3–14.

Cooper, R.G. and Kleinschmidt, E.J. (1994) Determinants oftimeliness in product development. Journal of Product InnovationManagement, 11, 381–396.

Cooper, R.G. and Kleinschmidt, E.J. (1995) Benchmarking thefirm’s critical success factors in new product development.Journal of Product Innovation Management, 12, 374–391.

Corso, M., Muffatto, M. and Verganti, R. (1996) Multi-productinnovation: emerging policies in automotive, motorcycle, andearthmoving machinery industries. 3rd International ProductDevelopment Management Conference, EIASM, Fontainebleau,April.

De Maio, A., Verganti, R. and Corso, M. (1994) A multi-projectmanagement framework for new product development. EuropeanJournal of Operational Research, 78, 178–191.

Dyer, J.H. and Ouchi, W.G. (1993) Japanese-style partnerships:giving companies the competitive edge. Sloan ManagementReview, Fall, 51–63.

Ettlie, J. E. (1996) Global comparisons of early manufacturinginvolvement (EMI) in new product development. EIASM 3rdInternational Product Development Conference, Fontainebleau,France, 15–16 April, pp. 275–298.

Fujimoto, T. (1989) Organization for Effective Product Develop-ment: the Case of the Global Automobile Industry. PhDDissertation, Harvard University, Graduate School of BusinessAdministration, Boston MA.

Fujimoto, T. (1993) Information asset map and cumulative concepttranslation in product development. Design Management Journal,Fall, 34–42.

Fujimoto, T., (1997) Shortening lead time through early problemsolving — a new round of capability building competition in theauto industry. International Conference on New Product Develop-ment and Production Networks, WZB, Berlin, 20–22 March.

Govers, C.P.M. (1996) QFD as a way of management. R&DManagement Conference on Quality and R&D, Enschede, TheNetherlands, 6–8 March, pp. 144–153.

Gupta, A.K. and Wilemon, D.L (1990) Accelerating the develop-ment of technology-based new products. California ManagementReview, 32, 2, Winter, 24–44.

Haddad, C. (1997) Involving manufacturing in the early stages ofproduct development: a case study from the North Americanautomotive industry. International Conference on New ProductDevelopment and Production Networks, WZB, Berlin, 20–22March.

Hayes, R., Wheelwright, S.C. and Clark, K.B. (1988) Dynamic

Manufacturing. Creating the Learning Organization. New YorkNY: Free.

Hippel, E. von and Tyre, M.J. (1995) How learning by doing isdone: problem identification in novel process equipment.Research Policy, 24, 1–12.

House, C.H. and Price, R.L. (1991) The return map: tracking productteams. Harvard Business Review, January–February, 92–101.

Houser, D.E. and Clausing, D. (1988) The house of quality.Harvard Business Review, May–June, 63–73.

Hughes, G.D. and Chafin, D.C. (1996) Turning new productdevelopment into a continuous learning process. Journal ofProduct Innovation Management, 13, 89–104.

Iansiti, M. (1995) Shooting the rapids: system focused productdevelopment in the computer and multimedia environment.Working Paper 95-026, Boston: Harvard Business School.

Imai, K., Nonaka, I. and Takeuchi, H. (1988) Managing the newproduct development process: how Japanese companies learn andunlearn. In Clark, K.B., Hayes, R.H. and Lorenz, C. (eds.), TheUneasy Alliance: Managing the Productivity-TechnologyDilemma. Boston MA: Harvard Business School Press, pp.337–375.

J×urgens, U. (1995) Anticipating problems with assembly in theearly stages of product development. Third International Work-shop on Assembly Automation, Venice, October 12–14.

Kamath, R.R. and Liker, J.K. (1994) A second look at Japaneseproduct development. Harvard Business Review,November–December, 154–173.

Liker, J.K., Kamath, R.R., Wasti, S.N. and Nagamachi, M. (1996)Supplier involvement in automotive component design: are therereally large US Japan differences?’ Research Policy, 25, 59–89.

Maidique, M.A. and Zirger, B.J. (1985) The new product learningcycle. Research Policy, December, 299–313.

McKee, D. (1992) An organizational learning approach to productinnovation. Journal of Product Innovation Management, 9,232–245.

Meredith, J. R. and Mantel, S. J. (1989) Project Management. AManagerial Approach, New York NY: John Wiley.

Rosenthal, S.R. (1992) Effective Product Design and Development:How to Cut the Lead-Time and Increase Customer Satisfaction,Homewood IL: Business One Irwin.

Sakuray, M. (1989) Target costing and how to use it. Journal ofCost Management, Summer.

Slack, N., Chambers, S., Harland, C., Harrison, A. and Johnston,R. (1995) Operations Management. London: Pitman Publishing.

Smith, P.G. and Reinertsen, D.G. (1991) Developing Products inHalf the Time, New York NY: Van Nostrand Reinhold.

Souder, W.E. and Monaert, R.K. (1992) Integrating marketing andR&D project personnel within innovation projects: an informationuncertainty model. Journal of Management Studies, 29, 4, July,485–512.

Trygg, L. (1991) The need for simultaneous engineering in time-based competition. In Ranta, J. and H×orte, S. ÈA. (eds.), Tech-nology Management: Technology Strategies and IntegratedInformation Systems in Manufacturing. Helsinki: VTT.

Thomke, S.H. (1996) The role of flexibility in the development ofnew products: an empirical study. Working paper 96-066, Boston:Harvard Business School.

Thompson, J.D. (1967) Organizations in Action, New York NY:McGraw-Hill.

Ward, A., Liker, J.K., Cristiano, J.J. and Durward, K.S.II (1995)The second Toyota paradox: how delaying decisions can makebetter cars faster. Sloan Management Review, Spring, 43–61.

Weerd-Nederhof, P.C. de, Kerssens-Van Drongelen, I.C. andVerganti, R. (eds.) (1994) Managing the R&D Process.Enschede, The Netherlands: TQC.

Wheelwright, S.C. and Clark, K.B. (1992a) RevolutionizingProduct Development: Quantum Leaps in Speed, Efficiency andQuality. New York NY: Free.

Wheelwright, S.C. and Clark, K.B. (1992b) Creating project plansto focus product development. Harvard Business Review,March–April, 70–92.

Wheelwright, S.C. and Sasser, W.E. (1989) The new productdevelopment map. Harvard Business Review, May–July, 112–123.

Zimmermann, H.J. (1993) Fuzzy Set Theory and its Application,6th ed. London: Kluwer Academic.

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