A Dynamic Model of Resource Allocation in Multi-Project Research and Development Systems

Nelson R. Repenning
MIT Sloan School of Management, E53-339
Cambridge, MA USA 02142
Phone 617-258-6889
Fax: 617-258-7579

Second Version: September 1999

Support has been provided by the National Science Foundation, grant SBR-9422228, The Center for Innovative Product Development at MIT, the Harley-Davidson Motor Company and the Ford Motor Company. Thanks to Drew Jones for providing useful comment on early versions of the model. The associate editor and two anonymous referees provided very helpful comments. Special thanks to Don Kieffer of Harley-Davidson for providing the catalyst to this study. An earlier version of this paper was titled 'Resource Dependence in Product Development Improvement Efforts.'


Managers and scholars have increasingly come to recognize the central role that design and engineering play in the overall process of delivering products to the final customer. Although significant progress has been made in the design of effective product development processes, many firms still struggle with the execution of their desired development process. In this paper I develop a model to study one hypothesis to explain why firms experience such difficulties. The analysis of the model leads to a number of new insights not present in the existing literature. First, I show that under a plausible set of assumptions product development systems have multiple steady-state modes of execution (or equilibria). This insight suggests that it is possible for product development systems to get Œtrappedı in a state of low performance. Second, the analysis highlights that, for multiple equilibria to exist, a positive loop must dominate the system. I also provide the conditions required for such dominance. Third, the analysis demonstrates that the sensitivity of the system to the undesirable self-reinforcing dynamics is determined by the utilization of resources. Fourth, simulation experiments show that testing delays also play a critical role in determining the system's dynamics. I also consider one extension to the model, the introduction of new development tools, and discuss policies for performance improvement.

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