Publication Type

Journal Article

Publication Date

8-2002

Abstract

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 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.

Keywords

Project Management, Uncertainty, Complexity, Instructionalism, Project Selection, Ambiguity

Discipline

Business | Management Sciences and Quantitative Methods | Operations and Supply Chain Management

Research Areas

Operations Management

Publication

Management Science

Volume

48

Issue

8

First Page

1008

Last Page

1023

ISSN

0025-1909

Identifier

10.1287/mnsc.48.8.1008.163

Publisher

INFORMS