From Project to Process Management: An Empirically-Based Framework for Analyzing Product Development Time

TLDR

Product development projects often share similar activity flows, yet most planning tools treat them as independent, ignoring the resource competition that arises when multiple projects run concurrently. The study proposes an empirically grounded framework to analyze development time in organizations managing concurrent projects. By modeling the organization as a stochastic processing network where engineering resources are workstations and projects are jobs, the authors use spreadsheets to quantify time allocation and run simulations to explore factors affecting cycle time. The resulting model offers a managerial tool for formal performance analysis, identifies key data to collect for cycle‑time improvement, and provides a conceptual basis for comparing engineering and manufacturing operations.

Abstract

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.