a model of npd

8/7/2019 A model of NPD

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A Model of New Product Development: An Empirical Test

Author(s): Billie Jo Zirger and Modesto A. MaidiqueSource: Management Science, Vol. 36, No. 7 (Jul., 1990), pp. 867-883Published by: INFORMSStable URL: http://www.jstor.org/stable/2632324 .

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MANAGEMENT SCIENCEVol. 36, No. 7, July 1990

Printed in U.S.A.

A MODEL OF NEW PRODUCT DEVELOPMENT:AN EMPIRICAL TEST*BILLIE JO ZIRGER AND MODESTO A. MAIDIQUEDepartment of Industrial Engineering and Engineering Management, Stanford University,Stanford, California 94305Florida International-University, University Park, Miami, Florida 33199

This paper reportson the culminationof a four year study of high technologyproduct nnovation.During the course of this research,we examined over 330 new products in the electronics industryin order to better understand the factors that differentiated successful from unsuccessful productdevelopment efforts.This paper presents the conclusions from the final phase of the research. In this study weempirically test a model of product development that incorporates our findings from the earlierexploratory survey and case study phases of our research.The model identifies the critical orga-nizational subunits, development activities and communication channels that influence productoutcome, as well as, external factors such as characteristics of the product and the competitiveenvironment.Our findings suggest the following key factors affect product outcome: ( 1) the quality of theR&D organization, (2) the technical performance of the product, (3) the product's value to thecustomer, (4) the synergy of the new product with the firm's existing competences, and (5)management support during the product development and introduction processes.Also importantbut less significantwere the (6) competence of the marketing and manufacturing organizationsand market factors, such as the (7) competitiveness and the (8) size and rate of growth of thetarget market.(PRODUCT DEVELOPMENT PROCESS; PRODUCT SUCCESSES; INNOVATION PRO-CESS; PRODUCT INTRODUCTIONS)

1. IntroductionSuccess in product development is a critical management issue for the modern firm,especially those in technology driven industries.Clearerunderstandingof the factors thatdrive product outcome can help a firm focus valuable R&D resources, better utilizeresources dedicated to the product delivery process and increase the market demand fora firm's new products.Research has shown that new product introductions are vital to most manufacturing

firms' growth and prosperity. A Booz, Allen and Hamilton study of over 700 Fortune1000 companies estimated that new products would provide over 30 percent of thesefirm's profits during a five-year period from 1981-1986. Fortechnology driven industriessuch as the information processing and instruments and controls industries, the contri-bution to profits of new products was over 40 percent. The same study suggested thatthe number of new productsintroduced by these firms wereexpected to double comparedto the previous five-year period (Booz Allen & Hamilton 1982).This paper reportson the culmination of a four-year study of high technolQgyproductinnovation. During the course of this research,we examined over 330 new products inthe electronics industry in order to understand the factors that differentiatedsuccessfulfrom unsuccessful product development efforts. In this final phase of the research, weempirically test a model of product development that incorporatesour findings from theearlier exploratory survey and case study phases of our research (Maidique and Zirger1984). The model identifies the critical organizational subunits, development activities

* Accepted by Alok K. Chakrabarti;received November 30, 1988. This paper has been with the authors 2months for 2 revisions.867 0025- 1 909/90/3607/867$0 1.25

Copyright?3 1990, The Institute of Management Sciences


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868 BILLIE JO ZIRGER AND MODESTO A. MAIDIQUEand communication channels that influence product outcome, as well as, such externalfactors as characteristics of the product and the competitive environment. In the firstsection of the paper, we briefly review prior researchon new product development em-phasizing those studies that have compared product successes and failures.

2. R&D in New Product DevelopmentNew product development has been studied using several methodologies. Case studiesof the development of specific new products constitute the earliest research (Morison1966, Sorenson 1971, Baruch and Kiser 1973, Baruch and Barbour 1971, 1972, Rosen-bloom 1976). This early research provided detailed descriptions of each phase of thedevelopment process, but lacked the statistical validity of a large, systematic samplestudy. Thus, researchersbegan to study larger samples, usually focusing on groups of

either successful or alternatively unsuccessful products.One of the earliest studies of new product successes was Myers' and Marquis's (1969)(Marquis 1969) landmark study of 567 product and process innovations. These inno-vations had been developed by 121 firms representing five manufacturing industries.Their most important finding, the importance of identifying and understandingthe user'sneeds, has been confirmed by numerous researchers in the subsequent studies. Newproducts were more successful if they were designed to satisfy a perceived need than ifthey were developed to simply take advantage of a new technology.Another key finding of the Myers and Marquis study was the importance of organi-zational communication, both internal and external.According to theirstudy, informationgeneratedand diffusedinternally representeda major portion of the information requiredto develop the innovations. This finding suggests the need for strong interfaces betweenthe functional groups particularlybetween R&D and marketing.Other researchers have focused on product failure as the unit of analysis. Explainingthe failureof new products has been the focus of several studies including the ConferenceBoard study of new U.S. products (Hopkins 1980) and Cooper's (1975) examination of114 Canadian industrial product failures from 66 industrial firms. These two studiesidentifiedthe principalcausesfor failure as ineffective productmarketing and poor marketresearch. They also identified other marketing problems such as inadequate assessmentof market potential, poor understanding of competitor's strengthsand weaknesses, andinaccurate product pricing. Apart from these studies' focus on failure, a common de-nominator for success also emerged from this stream of research. Successful innovationwas found to be stronglyinfluenced by the firm's understandingof its "customers' needs"and its effectiveness in marketing.Notwithstandingthe important insights generated by these studies,conclusions reachedby the isolated study of successes or failure must be viewed as tentative. A study thatfocuses on only successful or only unsuccessful new products will provide a list of influ-encing factorscharacteristicof the type of products in the sample. Nonetheless, if severalof the influencing factors are common to both the success and failure samples, thisapproach will not provide a means to differentiate successful from unsuccessful productdevelopmient.Therefore, studies of either successes or failuresmay not provide a full understandingof the differencesin the product development processes,internalorganizational structure,firm strategies,external environments, or other factors that may influence a product'soutcome. For example, if a factor is present in a success group and not in a failuregroupwhile all other study variables are constant, we can then suggest that this factor differ-entiates successfulproduct development from an unsuccessful effort. Such concerns aboutmethodology led researchers o use an approach that directly compared product successesand product failures.


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MODEL OF NEW PRODUCT DEVELOPMENT 869The Scientific Activity Predictor from Patterns of Heuristic Origins (SAPPHO) study,the first comparative study of product success and failure, was conducted during theearly seventies in the United Kingdom (Rothwell et al. 1974, Rothwell 1972). The SAP-PHO investigators identified 43 product success and failure pairs in the chemical and

scientific instruments industries.The productswereselectedfrom two unrelated industriesin order to identify possible industry effects. The SAPPHO study concluded that productsuccess was primarily related to the following five factors:(1) understanding of user needs,(2) attention to marketing and publicity,(3) efficiency of development,(4) effective use of outside technology and external scientific communication, and(5) seniority and authority of the managers' responsible for the development of theproduct (Rothwell et al. 1974, Rothwell 1972).The SAPPHO findings confirmed three of prior researchers'findings, and introducedtwo new success factors both of which were related to characteristics of the organizationand the team that developed the successful products. First, R&D teams must be efficientand effective in their development efforts. R&D efficiency and effectiveness was definedas the ability to (1) identify product defects prior to the product launch, (2) assess thefeasibility of projects and select the most promising ones, (3) appropriatelyallocate bothcapital and labor resources,and (4) efficientlyutilize the available resources.The secondnew factor, one that was also confirmed in several subsequent studies, was the need foran executive champion, a senior member of the firm with power and authority whofought for the product. Researchers have suggestedthat product champions facilitate the

allocation of resources to the development effort, and stimulate cooperation and com-munication between the functional groups, other important factors in product success.Other studies of success and failure products in European and Japanese markets fol-lowed SAPPHO. A studyof Hungarianelectronicsproducts by Szakasits 1974) confirmedthe SAPPHO findings and emphasized communication, technical competence and pro-ficiency market understandingand synergy, product planning and management support.Kulvik's (1977) study in Finland also had similar results to the SAPPHO conclusions.A study of West German products by Gerstenfeld(1976) found that market pull productswere more successfulthan technology push, and that monitoringthe product developmentprocess was essential to ensureminimal resourceswere allocated to project failures.Finally,Utterback et al. (1976) in his study of European and Japanese products emphasized theimportance of a competitive advantage, patent protection, regulatory constraints andproject urgency.A studyof 103projects developed by U.S. industrial firms was conductedby Rubensteinet al. (1976). This researchfocused on the innovation process at the project level. Theyconcluded internal management factors were primaryinfluences on product success andthat government policies, actions and regulations were secondary. They suggested or-ganizationsconcentrate on improving communication, particularlybetween the functionalgroups, and upgradedata collection, analysis and decision making processes forprojects.

More recently, a major study of 200 product innovations, Project NewProd, was con-ducted in Canada by Robert Cooper (Summer 1979) (Cooper 1979). In his researchCooper studied pairs of product successes and failures that had been developed by thesame firm and for the same industry. The SAPPHO study, by comparison, kept theindustry constant, but not the firmfor each product pair. Cooper's methodology allowedhim to identify differences relating to characteristics of the organization and the proj-ect team.The NewProd data were collected using a mailed survey sent to a senior person in thefirm, usually the general manager. The respondent was asked to rate the successful andfailed products along 77 dimensions that described the environment, the organization,


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870 BILLIE JO ZIRGER AND MODESTO A. MAIDIQUEand characteristics of the development process. Cooper found that the most critical de-terminants of new product success were:(1) having a product unique or superior in the eyes of the customer,(2) having marketing knowledge and proficiency,

(3) having technical and production synergy and proficiency,(4) avoiding markets in which many new products are introduced,(5) being in a high need, high growth, large market,(6) avoiding pricing the product higher than competitive alternatives,(7) having marketing and managerial synergy,(8) avoiding markets which are very competitive and where customers are very sat-isfied.(9) avoiding products, markets, customers, and technologies which are new to thefirm (Cooper 1979).Cooper and Kleinschmidt (1987) later followed NewProd with another study of 203Canadianproductwinners and losers.He concluded that the threemost importantsuccessfactors were:(1) Product superioritywhich included featuressuchas unique benefitsto the customer,product quality, reduced customers' costs, product innovativeness, and providing a so-lution to a customer's problems.(2) Project definition and "up front" activities.(3) Marketing and technological synergy.Cooper's results suggesttwo new dimensions of successful product development. Thefirst is that market conditions such as a market segment's potential size and growth are

positively related to successful product development programs. Cooper's market factorcombines marketneed with market attributessuch as growthand size. The role of marketneed or pull has also been identified by several other researchers(Marquis 1969, Rub-enstein et al. 1976, Globe et al. 1973). Nonetheless, market attributes had not beenpreviously found to be as significant. The second new dimension suggested by Cooper'sstudy was the importance of developing a product that is technically superior and in-novative. Technical superiorityand uniqueness in his study is definedas a producthavinghigher quality, unique benefits and features and one that allows the customer to reducehis costs. In addition, Cooper suggested that to succeed new products should capitalizenot only on market expertises but also on R&D and production capabilities.Cooper did not, however, test two factors that have been identified as significant byother researchers: he importance of interfaces between functional groups such as mar-keting and R&D, and the influence of key sponsors such as senior managersand productchampions. Interfaces between the functional groups are important (Rubenstein et al.1976, Souder and Chakrabarti1978, Gupta et al. 1985) because they provide the mech-anisms for transferring nformation such as customer needs and wants, product pricingpoints,and markettiming and positioning. Myers'and Marquis's 1969) and the SAPPHOresults(Rothwell 1972) referred o the need forstrong nternalcommunication. Numerousstudies, including the work previously mentioned and other studies such as Rubensteinet al.'s (1976), Globe et al.'s (1973), and the Hungarian SAPPHO type study (Rothwell1974), have confirmed the importance of sponsorship.Remarkably, despite this considerable research foundation, the literature on new prod-uct success does not include a major comparative study of U.S. industrialproducts. Yet,industrial product development, especially in the research intensive industries, is of fun-damental importance to the U.S. economy for several reasons. Technological innovationhas been a potent factor in U.S. productivity growth during the last 50 years (Mueser1985, Avard et al. 1982). Product life cycles are shorter in high technology firms, andfor most of these firms a significant portion of their revenues are derived from newproduct introductions. High development costs are a third reason managers and re-


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MODEL OF NEW PRODUCT DEVELOPMENT 871searchers alike should study technological innovation. R&D investment for technologyfirms average 4%-6% of sales and may range as high as 10%-15%.Lastly, in part due tothe rapidly changing nature of product and process technology, it is critical to the com-petitiveness of U.S. electronics firms that managers better understand the factors thatinfluence new product success. All of these considerations provided the impetus for thisresearch project.

3. A Model of Product Development & Hypotheses DevelopmentThis research project began in 1982, and includes field data on over 330 electronicsproduct successes and failures. The research is divided into three parts: two exploratorysurveys (158 products), a case study validation (21 cases), and an empirical testing ofour model of the factors that influence product outcome. The findings from our two

exploratory surveys and the case studies were reported in two earlier articles (Maidiqueand Zirger 1984, 1985). The conclusions from the earlierphases of this studyareimportantbecause they provide the basis for our model of the factors that influence productoutcome. We found from these studies that new product success was likely to be greaterunder the following circumstances.(1) The firm has an in-depth understanding of its customers and the marketplace.(2) The firm markets proficiently and commits a significant amount of its resourcesto selling and promoting its successful products.(3) The firm's R&D is efficiently planned and well executed.(4) The firm's R&D, production and marketing functions are well coordinated.(5) The firm provides a high level of management support for the product from thedevelopment stage through its launch to the marketplace.(6) The product has a high performance to cost ratio.(7) The product benefits significantlyfrom the firm's existing market and technologystrengths.(8) The product provides a high contribution margin to the firm.(9) The market has few competing products (Maidique and Zirger 1984).A simple listing of the critical factors necessaryto develop successful new products isuseful, but not a strong guide for managerialaction. For this reason, we sought to move

beyond this stage and create a model of the critical influences on a new product's de-velopment that could then be tested. Developing quantifiable constructs of this modeland empirically testing it is the subject of this paper.Using the findings from the earlier phases of the study (Maidique and Zirger 1984,1985) and the research iteratureas a guide, we refined our model of the criticalinfluenceson the product development process.This model (Figure 1) is based on our interpretationof the process of new product development in a technology-based industry as a change-producing ctivity hat is usuallyblockedat key transfer oints by thetendencyat eachstage of the process to resist change (Lawrence 1969, Schon 1967). In the followingsection we explain the significantattributes of the model followed by the hypotheses wedeveloped to test the influence of each of these attributes on product outcome.The model describes the development process in terms of the organizational and ex-ternal entities that influence product outcome. Internal to the organizational are threeprimary groups involved in a new product's development: R&D, manufacturing andmarketing. Prior research indicated that three factors relatingto these functional groupsinfluenced product outcome. First, the competence of the functional groups. Productsuccess was more likely if development was conducted by a competent and skilled R&D,manufacturing (Cooper 1987) and marketing team. Second, it was important that thedevelopment process was well-planned and capably executed (Cooper 1987). Often thisincluded the assistance of a product champion (Rothwell et al. 1974, Rubenstein et al.


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872 BILLIE JO ZIRGER AND MODESTO A. MAIDIQUE

MARKETVALUE

LEADCUSTOMERS

R&D/ENG MARKETINGMANAGEMENT

MANUFACTURINGFIGURE 1. Critical Elements of the New Product Development Process.

1976) who promoted the product to senior management, to other functional groups andto customers throughout the development and introduction cycle. Finally, successfuldevelopment relies on strong communication links and cooperation between the func-tional groups (Rubenstein et al. 1976, Souderand Chakrabarti1978, Souder 1981, Gupta1985) in order to effectively manage the transition of the product through the variousdesign and development stages. The implicit barrier between the functional groups isrepresentedin the model by physical separationsbetween the entities. Without consciouseffortsby the organizationto bridgethese gaps, information critical to the product's formand function are likely to be lost, particularly as an organization grows in complexityand diversity.These findings led to the followinghypothesesthat represent he importanceof competent functional groups and strong internal and external communication.

Hypothesis 1. R&D competence and management is positively related to productsuccess and negatively related to product failure.Hypothesis 2. Marketing and manufacturing competence and coordination is posi-tively related to product success and negatively related to failures.Another important attribute and one that plays an important role in overcoming theseinternal organizationalbarriers s management support (Rothwell et al. 1972, Utterbacket al. 1976, Souder and Chakrabarti1979). Management support is shown in the modelas a force that pulls the functional groups together. Management impetus provides or-ganizational support for change and assures sufficientallocation of resources.This is notto say that product champions, the focus of much prior research, are not important,especially for radical innovations (Booz Allen & Hamilton 1968, Schon 1963). But, forour sample, which was largely composed of incremental and significant enhancements,their role was secondary compared to managerial sponsorship.Hypothesis 3. General management support of the product development effort ispositively related to product success and negatively related to failure.


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MODEL OF NEW PRODUCT DEVELOPMENT 873Understanding customers' needs was also critical to developing a product success.With indepth knowledge of their customer's problems, a firm can develop solutions thatprovide a significant value (Utterback et al. 1976, Cooper et al. 1987). Value can bemanifested in terms of the product's cost savings, quality (Buzzell and Gale 1987),

performance advantages or a combination of features.For example, one product successin our sample was priced 20%less than competitive products, and provided a three-foldperformance advantage. Since value in high technology markets is often measured interms of product performance, we also tested whether product success was more likelyto occur when products were technically superior in some aspect of their performance.Hypothesis 4. A product providing a significant value (performance to cost) to thecustomer is positively related to successful products and negatively related to failures.Hypothesis 5. A technically superior product is positively related to successful out-

comes and negatively relatedto failures.Another one of our principal findings and that of other researchers (Cooper 1979,Souder and Chakrabarti 1979, Kulvik 1977) was that products are more likely to besuccessful if they build upon existing technological and market strengths. Entry into newmarkets or technologies generally requiresthe establishment of new customer/ companyconnections (i.e., new lead customers), and if new personnel arebrought in, new patternsof coordination duringthe product's development. Thus, the established communicationnetworks and the coordination required in the new product development loop can besignificantly disrupted by the organizational restructuringthat entry into new marketsand technologies generallyrequires(Tushman and Romanelli 1985). In addition, enteringnew markets or using new technologies requires that the firm develop new competences,a process that can be riskierand more time consuming than building upon an existingbase. It is for these reasons that establishedteams enteringmarkets that areclosely relatedto their organization's current businesses have the best change of succeeding with a newventure (Cooper 1979).

Hypothesis 6. Products that build upon the firm's existing market, technology andproduct competences are positively related to successes and negativelyrelatedto failures.Finally, two market characteristics were found to influence product outcome. First,firms who enter markets where competition is weak have a better chance of providing asignificant value to the customer. For example, in a newly created market, new entrantscan pursue niche strategies by developing product enhancements that extend the appli-cations of a product in ways no previous competitor has conceived. Also, in the earlystages of a new product's development, competitors are struggling against each other toestablish their product as the industrystandard.Alternatively,new entrantsin establishedmarkets with innovative technologies or creative approaches to solving the customer'sproblems often have a good chance at shaking up the market positions of existing com-petitorsif these firms are insecure. Ourearlierwork(Maidique and Zirger 1984) suggested

that the competitiveness of the market influenced product outcome in contrast to Cooperand Kleinschmidt's ( 1987) results that indicated no relationship between outcome andmarket competitiveness.Hypothesis 7. Weak competitive environments are positively relatedto product suc-cesses and negatively related to failures.Also products entering large and growing markets are also more likely to be winners.As the market rapidly expands, existing competitors may have difficulty ramping up tosupply market needs at the quality and reliabilitylevels the customer demands. In thesesituations, the strongest competitors usually focus on the market with the largest market


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874 BILLIE JO ZIRGER AND MODESTO A. MAIDIQUEshare and/or profit potential. This leaves lucrative market niches available for others.Market expansion could also be triggered by new applications for the product or newcapabilities, in many cases these innovative approachesare offeredby new entrantstryingto establish a foothold in the market. In contrast, Cooper and Kleinschmidt ( 1987) testedfor market attractiveness and potential and determined it was not related to productoutcome.

Hypothesis 8. Markets that are largeand growing are positively related to successfuloutcomes and negatively related to failures.Using our model of new product development as a guide, we have presented eighthypotheses that we believe represent the key influences on new product outcome. Ournext step was to test these hypotheses in a large sample study of product successes andfailures. The objective of this final test and analysis was to confirm the significance of

these hypotheses in influencing product outcome and determine the relative importanceof each of the factors. The researchmethodology and the results of the test of our hy-potheses follows.4. Research Methodology

The unit of analysis for the study was a product pair, one success and one failure,andthe sample consisted of 172 electronics products. Only products that were technicallyfeasible and for which at least one unit has been manufactured were included in thedatabase. Two products were selected by each company that participated in the study,one product considered to be success and one a failure. Respondents were asked tochoose a pair of products that were financial extremes. The degreeof a product's successand failure was measured on a ten-point scale ranging from a major financial loss to amajor profitability contributorwith financial breakeven at its midpoint. The success andfailureratingsweregraphedand the results areshown in Figure2. In the aggregatesuccessand failureratingsdid overlap, but for any pair of products in the sample, successes werealways more financially lucrative than failures. Also, the correlation between a successand a failureoutcome was low, 0.05, and a t-test of the successand failure means indicateda significant difference (p < 0.001). The product success and failure pair within eachcompany were developed within five years of each other and were introduced into thesame or similar market. The sample distribution by market is as follows: (1) computerhardware, peripherals, software and related equipment (30%), (2) test, measurementand process control instruments (22%), (3) telecommunications and communicationsystems and equipment (16%), (4) electronic components, materials and equipment(16%), and (5) other (16%).The data were collected using a survey of senior managers participating in a generalmanagement program for senior executives in electronics companies. The respondentswere either general managers, presidents, or chief executive officers of their firms orfunctional vice-presidents of a division of a Fortune 1000 company. All the data werecollected prior to the participants' participation in the program to minimize programbias. Respondent bias due to functional and educational background differences wastested, and found to be insignificant for those subgroups that were large enough to bestatisticallytested.The same questionnairewas administeredtwice, the firsttime in 1983 to 33 respondentsand a second in 1984 to 53 different managers resulting in 86 different product pairs.Due to the small sample size for each individual year, it was desirable to combine thetwo years of data into one sample. To test the likeness of the two data sets, a MANOVAtest was conducted that compared the statistical similarity of the mean value for eachitem in the 1983 survey with the corresponding item mean value in the 1984 survey.


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MODEL OF NEW PRODUCT DEVELOPMENT 875Percent Success/Failure

40%Innovation Type

Failuresr 7Successes30%

20%

10% .. .. .

0% -5 -4 -3 -2 -1 0 1 2 3 4 5Failures 7% 21% 17% 16% 17% 15% 3% 3% 1%Successes I 1% I 4% I 6% I 19% I 36% |29% | 6% |

Financial PerformanceBreakeven - 0

FIGURE2. Innovation Financial Success (Percent of Total).

The F significance using the Hotelling and Wilks test was 0. 348 indicating no significanceitem difference in the two years of data. Twenty-four of the original 172 products waslater excluded because of incomplete data. The final analysis included 77 successfulinnovations and 71 failures.The questionnaire used for data collection was divided into three parts. The first partof the survey instrument asked for background data on the respondent and his firm ordivision. In the second section of the survey, we asked the respondent to select anddescribetwo innovations, one success and one failure.Any supplementaryliterature suchas product brochures, technical bulletins or advertisements relating to the product werecollected for background purposes. The respondentwas also asked to evaluate the degreeof each product's success on a ten-point scale.The third and final section of the survey consisted of 23 items (see Appendix 1) thatwe had determined from our previous survey (Maidique and Zirger 1984) and case studywork (Maidique and Zirger 1985) and the research of others, influenced new productoutcome. These items describe the basic elements of our model of the product devel-opment process as shown in Figure 1. Each respondent in the sample group was askedto determine to what degree both the success's and the failure's development was influ-enced by each item. The 23 items were each rated on a seven-point Likert-type scalewith endpoints labelled strong agreement (7) and strong disagreement (1).While the 23 items provided the foundation for our empirical test of the productdevelopment process, we felt these items could be reduced to a smaller set of underlyingconstructs. In order to reduce the data set, we conducted numerous SPSS exploratoryfactor analyses varying the extraction technique, the number of factors and the rotationmethods. The factor analysis resultedin an eight-factorsolution (principal components,varimax rotation). We believe the eight-factor solution provides a good description ofthe underlying constructsfor the following reasons:(1) the factor loadings of the variablesaveraged more than 0.69, (2) the amount of common factor variance explained by the


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876 BILLIE JO ZIRGER AND MODESTO A. MAIDIQUEeight factors was 70%, (3) different factoringand rotation techniques gave us largely thesame variable groupings for each factor, and (4) the variable groupings matched ourintuitive conceptualization of the hypothesized constructs. All except one factor had aeigenvalue greater than one, a common rule of thumb used by practitioners. Since thereis no one correct method to determine the number of factors in the data set (Kim andMueller 1978), one factor with an eigenvalue less than one was included because ofits contribution to our intuitive model. The factors and their loadings are shown inTable 1.Constructs were developed from the factors. These constructs are shown in Table 1and their names correspond to the factor labels determined for each factor group. Theitems measuring each construct are also shown in Table 1. For example, R&D Excellenceconsisted of seven measures and Product Value was measuredby three items. The valuefor each construct was determined by calculating the numeric averageof the scale valuesfor the items in each construct.Table 2 shows the intercorrelationsbetween the constructs,the reliabilities, the means and standard deviations for the constructs. One factor, man-agement support, was described by only one variable, therefore, its construct has noreliability measure.The first construct, R&D Excellence, consisted of seven items with a scale mean forsuccessful products of 5.74 and a failure mean of 4.11 (Table 2). The Cronbach's alphaof the R&D Excellence scale was 0.83. The Marketingand Manufacturing Competencescale had a 4.85 and 4.13 mean value for successes and failures respectively, and aninternal consistency measure of 0.70. The Product Value and Product Synergy scaleseach had three measures and had reliability values of 0.52 and 0.73. Product Value hada success mean of 4.87 and a failure of 3.72. The Product Synergy scale had a 0.98difference between the mean value of the success ratingfor the scale, 5.91, and the failurerating of 4.93. Technical performance was measured by a two-item scale with a reliabilityof 0.67, and the mean value of successfulproducts, 5.61, was greater han the unsuccessfulproducts mean by 1.7. Finally, the market descriptor scales, market size and growth andweak competitive environment, had reliability indexes of 0.59 and 0.53 respectively, andwere each measured by two items. The mean value for successful products using themarketsize and growthscalewas 5.64 and the failure mean was 4.87. The competitivenessof the environment scale was similar with a success averageof 5.21 and failure of 4.30.

5. Analysis and ResultsA linear discriminantanalysiswas conducted, a technique that producesa discriminantfunction that distinguishes statistically between two groups of cases (i.e. successes andfailures). It is an empirically robust technique (Efron 1975, Lachenbruch 1975, Lee andBayus 1985) and is well suited to our study's centralquestion, whatdistinguishesbetweensuccessful and unsuccessful product development. Discriminant analysis has finite sta-tistical properties, therefore, produces coefficients and R-square values that are readilyinterpretable.The cases were grouped by product outcome, success or failure, and the discriminantfunction included eight variables.Wilks method was used for selecting variables for themodel and their order of inclusion. The structure coefficients are shown in Table 3 andindicate the correlation between the discriminant function and each variable.They areused forinterpreting he model becausein cases where the correlationbetween the variablesis significant (see Table 2), the magnitude and sign of the standardizedcoefficients maybe misleading. The F values for all of the variable constructs were high, and they wereall highly significant (p < 0.01). The canonical correlation is high (0.70) indicating astrong relationship between the groups and the function, and Wilks' lambda is significantsuggesting strong discrimination among the two groups (Klecka 1984).


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MODEL OF NEW PRODUCT DEVELOPMENT 877TABLE 1

Factor Analysis ResuiltsFactor

Factor & Variable Description LoadingsR&D Excellence- Product had superior quality and reliability. 0.76- Product was developed by a highly competent engineering organization. 0.75- Product development process was well planned. 0.70- Product was strongly supported by project management. 0.65- Coordination between engineering and manufacturing was good. 0.63- A clearly identified individual was an activist in promoting the product's developmentthroughout the product development and the introduction cycle. 0.52- Product was a good match with the customer's needs. 0.41

Eigenvalue: 6.5 Percent of variance: 28.3Marketing and Manufacturing Competence- Coordination between marketing and manufacturing was good. 0.74- Product was manufactured by a highly competent manufacturing organization. 0.73- Product was introduced by a highly competent sales and marketing organization. 0.72

Eigenvalue: 1.9 Percent of variance: 8.2Synergy with Existing Competences- Product benefitted from its closeness to the company's existing products. 0.86- Product benefitted from its closeness to the company's existing markets. 0.77- Product benefitted from its closeness to the company's technologies. 0.63

Eigenvalue: 1.7 Percent of variance:7.3Superior Technical Performance- Coordination between marketingand engineering was good. 0.60- Product had superiortechnical performance. 0.63

Eigenvalue: 1.5 Percent of variance:6.7Large and Growing Market- Product was developed for a largemarket. 0.84- Product was developed for a rapidly growing market. 0.77

Eigenvalue: 1.3 Percent of variance:5.8General Management Support- Product was strongly supported by general management. 0.81

Eigenvalue: 1.3 Percent of variance: 5.6Weak Competitive Environment- Product was firstto the market. 0.80- Product was developed for a market with few strong competitors. 0.77

Eigenvalue: 1.0 Percent of variance: 4.5Product Value- Product was priced lower than competitive alternatives. 0.84- Product provided superiorbenefit to cost. 0.50- Product concept developed from frequent interactions between the productdevelopment team, introduction team, and the customers. 0.41

Bigenvalue: .87 Percent of variance:3.8


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878 BILLIE JO ZIRGER AND MODESTO A. MAIDIQUETABLE 2

Intercorrelations,Reliabilities, Means and Standard DeviationsIntercorrelationsand Reliabilities

1 2 3 4 5 6 7 81 R&D Excellence 1.002 Mkt & Mfg Competence 0.50***3 Product Value 0.43*** 0.194 Technical Performance 0.64*** 0.50*** 0.41**5 Management Support 0.30*** 0.18 0.16 0.36***6 Product Synergy 0.36*** 0.29*** 0.26** 0.34*** 0.207 Weak Competitive Env. 0.18 0.11 0.20 0.22** 0.06 0.138 Large& Growing Market 0.25** 0.20 0.13 0.20 0.22 0.16 -0.08

Reliabilities 0.83 0.70 0.52 0.67 a 0.73 0.53 0.59** p _ 001.*** p 0.001.a Only one variable used in this scale.

Successes Failures Total SampleVariable Mean Std Dev Mean Std Dev Mean Std Dev

R&D Excellence 5.74 0.81 4.11 1.23 4.96 1.31Mkt & Mfg Competence 4.85 1.30 4.13 1.37 4.50 1.38Product Value 4.87 1.13 3.72 1.30 4.32 1.34Technical Performance 5.61 1.09 3.91 1.59 4.79 1.60Management Support 6.20 1.18 5.20 1.76 5.70 1.57Product Synergy 5.91 1.12 4.93 1.48 5.44 1.39Weak Competitive Env. 5.21 1.62 4.30 1.67 4.77 1.70Large & Growing Market 5.64 1.15 4.87 1.71 5.27 1.49

A split sample analysis was also done to assess the extent of bias induced by using thesame cases for both determiningthe function and the predictive accuracyfor the function(Green 1978, Klecka 1984). As shown in Table 3, the split half sample had very similarcoefficient magnitudes and rankings compared to the full sample model.As a predictor of a success and failure outcome, the discriminant model was quitegood, and correctly predicted success or failure in 88% of the original samples (Table4). The classification accuracywas very significantbased on a z statistic of 9.01 (Joy andTollefson 1975). Similarly, the split sample predicted outcome well.All of Our Individual Hypotheses Were Supported. R&D competence (Hypothesis1) was positively related to product success. When the R&D group was competent andthe product development was well planned, coordinated and executed, the product wasmore likely to be financially successful. Marketingand manufacturing competence (Hy-pothesis 2) and Management support (Hypothesis 3) were also predictors of success.Product characteristics, Product Value (Hypothesis 4) and Technical Superiority (Hy-pothesis 5) were positively related to product success. Products that did not provide asignificant value to the customer and were "me-too" products were more likely to befailuresin this sample. Product and market choices were also important. Firms that builtupon their existing market, product and technology strengths (Hypothesis 6) were morelikely to have a product success. Finally, market characteristics also predicted productoutcome. Failureswere more likely for products introduced into highly competitive (vHy-pothesis 7 ), and small, stagnant markets (Hypothesis 8).


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MODEL OF NEW PRODUCT DEVELOPMENT 879TABLE 3

Resuiltsof Hypotheses Tests Based on Multiple Discriminant AnalysisSplit SamplebStructure StructureVariable Description Coefficients Coefficients

Excellent R&D Organization 0.80*** 0.77***SuperiorTechnical Performance 0.64*** 0.60***Product Value 0.48*** 0.44***Synergywith Existing Competences 0.38*** 0.48***Management Support 0.35*** 0.34**Competent Marketing& Manufacturing 0.28** 0.27**Weak Competitive Environment 0.28** 0.22*Large & Growing Market 0.27** 0.16Group Centroids: Failure -1.023 -1.106Success 0.943 0.968Canonical Correlation 0.70 0.72Eigenvalue: 0.978 1.100Wilks' Lambda: 0.5 1* 0.48**

* p_? 0.05.** p _ 0.01.*** p -' 0.001.b Since the percentcorrectpredictionis overestimated due to the use of the same casesin derivingthe classificationfunction, the analysiswas rerunusing half the data to derivethe function and the remainder to test the function's classification accuracy. (Klecka

1984, pp. 51-52.)

6. DiscussionFive major points arise from this study. The first key finding is that managerial ex-cellence is critical to product success. Products are more likely to be successful if theyare planned and implemented well. Project planning should include all phases of thedevelopment process; research, development, engineering, manufacturing and marketintroduction. The functional groups should interact and coordinate activities during the

development process. Particularly important are the links between R&D and the otherfunctional groups, marketing and manufacturing. One critical reason for a strong linkwith marketing is to ensure the firm understands user needs and effectively translatesthese needs into solutions for the customer. The connection with manufacturing is em-phasized because of the increasing importance of efficientand effective operations, a goalTABLE 4

DiscrimninantAnalysis Classification Tables(Predicted Group) PercentActual CorrectlyGroup # of Cases Successes Failures Classifiedc

Total SampleSuccesses 77 93.5% 6.5% 87.8%dFailures 71 18.3% 81.7%Split SampleSuccesses 37 86.5% 13.5% 83.6%Failures 36 19.4% 80.6%c Classification accuracy, z: 9.01 (p -' 0.001).d Classification accuracy was computed using a z statistic (Joy and Tollefson 1985).


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880 BILLIE JO ZIRGER AND MODESTO A. MAIDIQUEthat cannot be reached unless design for manufacturing is part of the product's devel-opment objectives. To ensure goals are clearly set a prioriand agreed upon between thefunctional groups, Crawford 1984) suggested hat firmsnegotiate a new product protocol.Development does not have to be a linear process (Takeuchi and Nonaka 1986).Many phases of the process can overlap and personnel can move with the product tosmooth the transition and communicate learnings. The process should also be regularlyand formally monitored throughout the life of the project (Cooper and Kleinschmidt1987). Cooper et al. (1985) found that productsuccess was linked to consistent adherenceto a new product process; one that included market studies, initial screeningand prelim-inary market assessment. Note that two of the three activities they flagged were relatedto understanding the market. An essential part of effective product development is un-derstandingcustomer needs and embodying solutions to those needs in the product.Finally, many have found the use of product champions as important enablers of theprocess. Productchampions are one or more individuals who build technical and financialsponsorship throughout the organization and nurture the project through developmentand introduction.Our second majorconclusion is that newproductsmustprovidesignificant value to thecustomer. Value can be measured in several ways. It can be superior technical perfor-mance, a characteristic of many of the successes in our sample. Value can be providedby a lower cost design, one that allows pricing the product lower than competitive alter-natives or, it can also be provided by a product that provides a set of unique features.Superiorproduct quality and reliabilitywas another form of value for the customer. Allof these measuresof value, either singly or in combination, translate into a product thatprovides a superior benefit to cost for the customer. In order to understand the value ofparticular features to customers, the developing firm must have close contact betweenthe development team and the end user. Often developing firms had frequentinteractionswith lead customers (Von Hippel 1986), particularlywith customers who were trendsetters in their industry and could provide insightful and innovative suggestions duringproduct development.The thirdprimary contributor oproductsuccess is strategicfocus. Firms should chooseprojects that build upon the firm's existing technological, marketing, and organizationalcompetences. Related products allow firms to use and further develop existing techno-logical competences, and take advantage of communication sources and networks bothinternal and external to the firm. "Sticking to your knitting" (Peters and Waterman1982) has been a common theme in the popular general management literature.Not-withstanding this synergybenefit, we do not suggest that a firm never venture into newtechnical or market arenas. Without occasional ventures in new directions, the firm willsoon exhaust the technical potential of current product lines particularly in rapidlychanging high technology markets. It is, however, important that when new ventures areundertaken, the firm consider and perhaps minimize where possible one or more di-mensions of newness.

Management commitment is also essential to product success. Without managementsupport, the scarce staffing and capital resources necessary to develop the product arenot likely to be approved. Securing the support of management is materially aided if,early in the development process, the development team can demonstrate significantmarket demand for their product.A fifth and final, albeit weaker, contributor to new product success is the market en-vironment. Products that are first to the market and experience little competition aremore successful. This is consistent with our finding that technically superior, first to themarketproductswerewinners. Also, introducingproducts into relatively argeand growingmarkets is more likely to result in product success. Technological leadership, however,


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MODEL OF NEW PRODUCT DEVELOPMENT 881is very risky. Innovators must have indepth customer communication and customerunderstanding. Technology leaders generally find that they must educate potential cus-tomers about the uses and applications of a new product. As the customer uses the newproduct, the developing firm must understand how customer needs change and mature,and then redesign the product accordingly. Additionally, leaders must try to establishindustry standards,if they plan to be a major playerin the market and lead the processiondown the learning curve. Ripe, untouched markets are enticing for product developers,but entry must be carefully planned and well-executed to avoid a product failure.

7. ConclusionDuring the five years of this project we have investigated over 330 new electronicsproducts. We have conducted two exploratorysurveys, numerous case studies at company

sites, and successfully developed and tested a model of new product development. Thefindings in this paper represent our understanding of the critical components affectingthe successful launch of a new high technology product. It is hoped that these findingscan be a guide to further research,as well as, useful to practitioners who are managingproduct development programsin the ever increasingly competitive electronics market.Religious adherence to these success factors-managerial excellence, superior benefit tocost, strategic focus, managerial commitment and early entry into large and growingmarkets-cannot, unfortunately, ensure a firm of a new product winner. On the otherhand, we are convinced that careful attention to the areas that our extensive researchhas identified will lead to enhanced probabilities of success for new product developersand will assist subsequent researchers in their own contributions to our field.1

'This research was funded by the Department of IndustrialEngineeringand Engineering Management whileboth authors were at StanfordUniversity. The authors wish to thank WarrenHausman, IndustrialEngineeringand EngineeringManagement,StanfordUniversity, for his encouragementand support duringthis investigation.Appendix 1. List of Study Items

1. The product development process was well planned.2. Coordination between engineeringand manufacturingwas good.3. The product was developed by a highly competent engineering organization.4. The product was developed for a rapidly growing market.5. The product was strongly supported by project management.6. The product had superiortechnical performance.7. The product was a good match with the customer needs.8. The product benefitted from its closeness to the company's technologies.9. The product was manufactured by a highly competent manufacturing organization.10. The product was developed for a market with a few strong competitors.11. The product was strongly supported by general management.12. The product was priced lower than competitive alternatives.13. The product concept developed from frequent interactions between the product development and intro-duction team and customers.14. Coordination between marketingand engineering was good.15. The product was introduced by a highly competent sales and marketing organization.16. The product benefitted from its closeness to the company's existing markets.17. A clearly identified individual was an activist in promoting the product's development throughout theproduct development and the introduction cycle.18. Coordination between marketingand manufacturingwas good.19. The product was developed for a large market.20. The product benefitted from its closeness to the company's existing products.21. The product had superior quality and reliability.22. The product provided superiorbenefit to cost ratio.23. The product was first to the market.


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a model of npd

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