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New product success factors: A comparison of ‘kills’ versus successes and failures
Author(s) -
Cooper R. G.,
Kleinschmidt E. J.
Publication year - 1990
Publication title -
randd management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.253
H-Index - 102
eISSN - 1467-9310
pISSN - 0033-6807
DOI - 10.1111/j.1467-9310.1990.tb00672.x
Subject(s) - attractiveness , product (mathematics) , marketing , new product development , competitive advantage , business , sample (material) , operations management , economics , psychology , mathematics , chemistry , geometry , chromatography , psychoanalysis
The paper reports an analysis of the characteristics of those new projects that are killed, that is, terminated before commercialisation. Such projects constitute the majority of new product projects. The authors' aim was to learn from the differences between ‘kills’ and those that are commercialised. The latter may, of course, turn out to be successes or failures. Their sample consisted of 250 new projects of which 123 were ultimately successful, 80 failed and 47 were kills. Two hypotheses were tested: that kills and failures had similar characteristics and that kills differed from successes in the way that failures differed from successes. Four groups of multidimensional project characteristics were measured: product advantage, market attractiveness, competitive situation, and synergy/familiarity. The results showed that neither hypothesis was generally supported, The patterns of characteristics observed were complex but were unravelled through a computer model simulating how managers perform the evaluation process. It showed that the results could be explained on the basis that errors could be made in evaluation. For example, it is difficult to evaluate product advantage. Surprisingly, competitive situation is not a discriminator between successes, failures and kills but managers treat it as if it were. Some characteristics are perceived by managers to be negative although they are, in fact, favourable to project success. The authors claim that these results should lead to better allocation of R&D resources among proposed projects.