Performance Variability and Project Dynamics

We present a dynamical model of complex cooperative projects such as large engineering design or software development efforts, comprised of concurrent and interrelated tasks. The model contains a stochastic component to account for temporal fluctuations both in task performance and in the interactions between related tasks. We show that as the system size increases, so does the average completion time. Also, for fixed system size, the dynamics of individual project realizations can exhibit large deviations from the average when fluctuations increase past a threshold, causing long delays in completion times. These effects are in agreement with empirical observation. We also show that the negative effects of both large groups and long delays caused by fluctuations may be mitigated by arranging projects in a hierarchical or modular structure. Our model is applicable to any arrangement of interdependent tasks, providing an analytical prediction for the average completion time as well as a numerical threshold for the fluctuation strength beyond which long delays are likely. In conjunction with previous modeling techniques, it thus provides managers with a predictive tool to be used in the design of a project's architecture. Bernardo A. Huberman is a Senior HP Fellow and Director of the Information Dynamics Laboratory. He is also a Consulting Professor of Physics at Stanford University. For the past ten years he has concentrated on understanding distributed processes and on the design of mechanisms for information aggregation and the protection of privacy as well as market-based distributed resource allocation systems. Dennis Wilkinson is a recent graduate of Stanford University with a doctorate in Physics, and has accepted a position in the Department of Defense. His research interests include dynamics of social networks and other stochastic systems, information extraction from large, complex networks, and techniques in distributed computing.