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While product development efforts are often viewed a unique configurations of idiosyncratic tasks, in reality different projects within an organization often exhibit substantial similarity in the flow of their constituent activities. Moreover, while most of the planning tools available to managers assume that projects are independent clusters of activities, in reality many organizations must manage concurrent projects that place competing demands on shared human and technical resources. This study develops an empirically-based framework for analyzing development time in such contexts. We model the product development organization as a stochastic processing network in which engineering resources are “workstations” and projects are “jobs” that flow between the workstations. At any given time, a job is either receiving service or queueing for access to a resource. Our model’s spreadsheets quantify this division of time, and our simulation experiments investigate the determinants of development cycle time. This class of models provides a useful managerial framework for studying product development because it enables formal performance analysis, and it points to data that should be collected by organizations seeking to improve development cycle times. Such models also provide a conceptual framework for characterizing commonalities and differences between engineering and manufacturing operations.
Adler et al. (Wed,) studied this question.