One of the most successful areas for the application of system dynamics has been project management. Measured in terms of new system dynamics theory, new and improved model structures, number of applications, number of practitioners, value of consulting revenues, and value to clients, "project dynamics" stands as an example of success in the field. This paper reviews the history of project management applications in the context of the underlying structures that create adverse dynamics and their application to specific areas of project management, synthesizes the policy messages, and provides directions for future research and writing. Copyright © 2007 John Wiley & Sons, Ltd. Syst. Dyn. Rev. 23, 157-189, (2007 ContextProjects abound in industry, public service, and many other endeavors. As a series of activities or tasks that (1) have a specific objective (scope) to be completed within certain specifications (requirements); (2) have defined start and end dates; (3) have funding limits; and (4) consume and/or utilize resources (Project Management Institute, 2000), projects have proven challenging to plan and manage. This is largely because project conditions and performance evolve over time as a result of feedback responses, many involving nonlinear relationships, and to accumulations of project progress and resources. This has made the application of system dynamics to project management a fertile and productive field of study. This paper surveys the large body of system dynamics work on projects, evaluates its progress, and suggests directions for future development.Many different types of models have been developed to improve project management. These models include some of the system features and characteristics addressed by system dynamics. For example, basic project models such as the critical path method explicitly model causally linked development activities and phases and cost control models use forecasted performance gaps (e.g., budget deficits) to allocate funds. More advanced models, such as the computational models developed by Levitt et al. (1999) and others, are quite system dynamics-like, as they include linked development activities as well as feedback. Another body of work models multiple projects, using system dynamics as well as other approaches. Surveying all of these works is beyond the scope of a single article. Therefore, we focus here on models of single projects built using the system dynamics methodology. But even models of single projects are too numerous to describe their structures or applications in detail. Therefore, in this article we focus on the most important and general model structures in conceptual form, and provide references to additional details. Our work is based primarily on the published literature and our experience using system dynamics to model projects. In particular, we describe contributions resulting from work we have done that has not, and very likely never will be, published or otherwise made available.The literature on system dynamics models of pro...

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The authors thank the Organizational Learning Center and the System Dynamics Group at the Sloan School of Management, and the "Python" organization for financial support. Special thanks to the members of the Python project for their interest, commitment and time. :7/97

Feedback loop dominance is a critical tool in explaining how structure drives behavior. Current analytic tools for loop dominance analysis are tacit, not codified, unable to accurately identify dominant loops or inapplicable to most models. Most loop dominance analysis tools focus on model structure to link structure and behavior. We use a behavioral perspective to define dominance, improve descriptions of behavior patterns and identify two important and incompletely developed areas of feedback analysis: simultaneous dominance by multiple loops and shadow loop structures. An analytic procedure is presented, illustrated and compared to an alternative analysis method. An evaluation of the behavioral approach is the basis for identifying new issues and future research opportunities. Copyright © 1999 John Wiley & Sons, Ltd.

Tipping point feedback structures can push a series of product development projects into firefighting mode in which rework overwhelms progress. Similar dynamics also threaten the performance of individual development projects. The current work extends previous tipping point dynamics research to single projects and demonstrates how a simple, common feedback structure can cause complex tipping point dynamics, trap projects in deteriorating modes of behavior, and cause projects to fail. Basic tipping point dynamics in single projects are described, demonstrated, and analyzed with a model. The concept of applying robustness to project design is preliminarily tested and system robustness to tipping point-induced failure is quantified for a simple project and analyzed with sensitivity analysis. Impacts of tipping points on project performance and future research opportunities concerning tipping point and robustness in project management are discussed.

Successfully implementing concurrent development has proven difficult for many organizations. However, many theories addressing concurrent development treat either technical aspects of the development process (e.g., precedence relationships) or behavioral issues (e.g., creating effective cross-functional teams), but not their linkages. We argue that much of the complexity of concurrent development—and the implementation failures that plague many organizations—arises from interactions between the technical and behavioral dimensions. We use a dynamic project model that explicitly represents these interactions to investigate how a “Liar's Club”—concealing known rework requirements from managers and colleagues—can aggravate the “90% syndrome,” a common form of schedule failure, and disproportionately degrade schedule performance and project quality. We discuss the role of the incentives on and behavior of engineers and managers in concurrent development failure and explore policies to improve project performance.

Successful development projects are critical to success in many industries. To improve project performance managers must understand the dynamic concurrence relationships that constrain the sequencing of tasks as well as the eects of and interactions with resources (such as labor), project scope and targets (such as delivery dates). This article describes a multiple-phase project model which explicitly models process, resources, scope, and targets. The model explicitly portrays iteration, four distinct development activities and available work constraints to describe development processes. The model is calibrated to a semiconductor chip development project. Impacts of the dynamics of development process structures on research and practice are discussed. *