Performance Variability and Project Dynamics

Abstract

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.

Hierarchical Structure and Search in Complex Organizations

“…Simulation work on the NK model complemented by other models has shown that the decentralized search of interdependent subproblems tends to slow and get bogged down as the problem's complexity (the number of subproblems) increases (Ethiraj and Levinthal 2004, Huberman and Wilkinson 2005, Mihm et al 2003: ongoing choices in some groups make the requirements for other groups inherently unstable (Thomke 1997, Van Zandt 1999. Although these studies have identified managerial actions to mitigate the problem, they have not addressed the question of whether and how hierarchical organizational structures can improve search time and quality.…”

Process models in design and development

“…In one such model, Loch et al (2003) apply an eigenstructure analysis to show that convergence of an iterative process becomes less probable and more time-consuming as the number of coupled tasks increases. In two others, Huberman and Wilkinson (2005) and Schlick et al (2013) create spectral models incorporating fluctuations in task performance, both showing that variance in overall process time can increase dramatically if the fluctuations exceed a certain threshold.…”

Study of iterations in the design process of a product for automotive industry

“… is needed to solve complex problems [9];  may help to deal with a changing context [9];  may be reduced by a focus on central information-consuming/generating nodes [2];  is strongly influenced by small changes in task time if close to capacity [10].…”