Michael T. Pich

On Uncertainty, Ambiguity, and Complexity in Project Management

This 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 theadequacy 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.

Managing project uncertainty: from variation to chaos

This publication contains reprint articles for which IEEE does not hold copyright. Full text is not available on IEEE Xplore for these articles.

Factors that influence technical communication in distributed product development: an empirical study in the telecommunications industry

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), the authors assess how the process of exchanging technical information is influenced by factors such as geographic dispersion, organizational bonds, and degree of team interdependence. They present a model that allows us to formulate several hypotheses about how these factors influence both communication frequency and media choice. They use empirical evidence from the telecommunications industry to test their hypotheses. They confirm previous results about the obstructive influence of distance on technical communication. However, they 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.

Selecting R&D projects at BMW: a case study of adopting mathematical programming models

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.

Two-Moment Analysis of Open Queueing Networks with General Workstation Capabilities

The QNET method for two-moment analysis of multiclass open networks is extended to allow complex workstations of various types. For example, the extension described here allows one to treat stations where several unreliable machines are tended by a small number of repair technicians, or stations where several machines that require setups are tended by a small number of operators. To illustrate the general concepts, a four-station manufacturing example is discussed in detail. In the QNET method, one first replaces the original queueing network by an approximating Brownian system model. The Brownian approximation is motivated by heavy traffic theory, and to achieve a unified treatment of complex workstations within the QNET framework we apply the following principle: For purposes of heavy traffic analysis, a workstation can be characterized by just two parameters, the asymptotic mean and asymptotic variance of its cumulative potential output process. This heavy traffic principle has long been known to researchers in the field, but we show that it has power and utility even in circumstances where the mean and variance parameters cannot be determined analytically. We explain how the heavy traffic principle can be applied successfully under certain conditions, and show by example that those conditions are not always met.

How Do Entrepreneurial Founding Teams Allocate Task Positions

How do founding team members allocate task positions when launching new ventures? Answering this question is important because prior work shows both that founding team members often have correlated expertise, thus making task position allocation problematic; and initial occupants of task positions exert a lingering effect on venture outcomes. We draw on status characteristics theory to derive predictions on how co-founders’ specific expertise cues and diffuse status cues drive initial task position allocation. We also examine the performance consequences of mismatches between the task position and position occupant. Qualitative fieldwork combined with a quasi-experimental simulation game and an experiment provides causal tests of the conceptual framework. We find that co-founders whose diffuse status cues of gender (male), ethnicity (white) or achievement (occupational prestige or academic honors) indicated general ability were typical occupants of higher ranked positions, such as CEO role, within the founding team. In addition, specific expertise cues that indicated relevant ability predicted task position allocation. Founding teams created more financially valuable ventures when task position occupants’ diffuse status cues were typical for the position; nonetheless position occupants with high diffuse status cues also appropriated more of the created value. Our results inform both entrepreneurship and status characteristics literature.