T his article develops a model of a project as a payoff function that depends on the state of the world and the choice of a sequence of actions. A causal mapping, which may be incompletely known by the project team, represents the impact of possible actions on the states of the world. An underlying probability space represents available information about the state of the world. Interactions among actions and states of the world determine the complexity of the payoff function. Activities are endogenous, in that they are the result of a policy that maximizes the expected project payoff.A key concept is the adequacy of the available information about states of the world and action effects. We express uncertainty, ambiguity, and complexity in terms of information adequacy. We identify three fundamental project management strategies: instructionism, learning, and selectionism. We show that classic project management methods emphasize adequate information and instructionism, and demonstrate how modern methods fit into the three fundamental strategies. The appropriate strategy is contingent on the type of uncertainty present and the complexity of the project payoff function. Our model establishes a rigorous language that allows the project manager to judge the adequacy of the available project information at the outset, choose an appropriate combination of strategies, and set a supporting project infrastructure-that is, systems for planning, coordination and incentives, and monitoring.

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Abstract-Understanding the communication process in product development organizations has been recognized as a key element to improve product development performance. It is particularly interesting to study information exchanges in geographically distributed product development teams because of the highly interdependent nature of design organizations. Additionally, the use of electronic-based communication media has changed how development teams communicate. By studying the way product development teams use various communication media (face-to-face, telephone, and e-mail), we assess how the process of exchanging technical information is influenced by factors such as geographic dispersion, organizational bonds, and degree of team interdependence. We present a model that allows us to formulate several hypotheses about how these factors influence both communication frequency and media choice. We use empirical evidence from the telecommunications industry to test our hypotheses. We confirm previous results about the obstructive influence of distance on technical communication. However, we found that such negative effects may be mitigated by other factors such as the recognizing of highly interdependent team members, the existence of strong organizational bonds, and the use of electronic communication media.

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Research and development (R&D) project selection is a critical interface between the product development strategy of an organization and the process of managing projects day-to-day. This article describes the project selection problem faced by an R&D group of BMW (Munich, Germany). The problem was structured as minimizing the gap between target performance of the technology to be developed and actual performance of the current technology along chosen criteria. A mathematical programming model helped this organization to increase the transparency of their selection process, which previously had been based on experience coupled with evaluation of individual projects in isolation Implementation was a success in that the predevelopment group continues to use the model to make better decisions. However, the organization did not use the model for its intended purpose: constrained optimization. The traditional explanation for this partial implementation is that the analytical model did not capture all considerations relevant to optimization (e.g., uncertainty or strategic fit), and that further model refinements are required to achieve further implementation. We offer an alternative explanation, one based on the technology transfer literature. The diffusion of the analytical model from academia to industry faced the same problems as any technology transfer: Significant tacit knowledge had to be transferred along with the codified knowledge of the analytical model. This required iterated problem solving, which required the limited time and resources of the diffusing agents (academia) as well as the adopting agents (industry). Thus, the organization adopted only those elements of the modeling method that could be transferred within the resource constraints, focusing on those elements offering the highest benefit per effort invested. Disciplines MathematicsThis journal article is available at ScholarlyCommons: http://repository.upenn.edu/oid_papers/228 Selecting R&D Projects at BMW: A Case Study of Adopting Mathematical Programming ModelsChristoph H. Loch*, Michael T. Pich*, Christian Tetwiesch**, Michael Urbschat*** September 1999Abstract R&D project selection is a critical interface between the product development strategy of an organization and the process of managing projects day-to-day. This article describes the project selection problem faced by the transmission pre-development group of BMW. The group had to choose a portfolio of projects to set the foundation for the "best powertrain 2000." This problem of project selection was structured as minimizing the gap between target perfom1ance and actual perfom1ance along chosen criteria. A mathematical progranm1ing model helped this organization to increase the transparency of their selection process, which previously had been based on experience coupled with evaluation of individual projects in isolation. The model was used to structure data collection, to apply to consistent criteria to the selection of pre-development projects, and to compare weighted project...