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R and D Planning Techniques
Author(s) -
Lovelace Robert F.
Publication year - 1987
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.1467-9310.1987.tb00058.x
Subject(s) - interdependence , plan (archaeology) , normative , management science , process management , value (mathematics) , computer science , knowledge management , business , political science , engineering , geography , archaeology , machine learning , law
The R and D manager who seeks to improve his ability to plan for R and D has available a plethora of descriptive and normative guidance offered by practitioners and theorists respectively. Nevertheless, while R and D planning models frequently are reported, the value of such to the practising manager merits further study inasmuch as issues of effectiveness generally are unexplored. This paper reviews the R and D planning models appearing in the literature, organizes them into a taxonomy constructed along two dimensions, considers three commonly reported planning model types, and offers suggestions to the manager regarding preferred planning model characteristics. A classification of R and D planning models is presented which organizes planning models by planning direction: top down, bottom up, mixed; and level of analysis: individual project, research program, corporate research agenda, and national/international research goals. Classified R and D planning models are explored using paradigms gleaned from the R and D and the planning literatures. The quantifiability of assumptions, the extent of internal environmental variables considered, and the recognition of external environmental interdependencies provided standards against which three commonly occurring R and D planning models are evaluated. The value of available planning models to the manager of R and D is hypothesized as is his ability to improve planning efforts through model evaluation and selection. An agenda for future research on R and D planning is proposed, based on insights gleaned from the application of the evaluation criteria to the taxonomy.