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Project Management Decisions with Uncertain Targets

Author

Listed:
  • Jeffrey M. Keisler

    (University of Massachusetts Boston, Boston, Massachusetts 02125)

  • Robert F. Bordley

    (Booz Allen Hamilton, Troy, Michigan 48084)

Abstract

Project management decision rules presume that fixed and inflexible targets have been defined for the project. If a project’s slack is defined as the difference between actual project performance and these targets, then these decision rules can be characterized as maximizing the probability that slack is nonnegative (i.e., maximizing the probability of meeting the targets). These rules rely on z -scores to compare uncertain performance to target levels. Following these decision rules will not always suffice for the project manager to act consistently with customer preferences. In particular, actual requirements may be uncertain or subject to change, and customers may have some flexibility. A decision-analytic approach accounting for these factors can allow the project manager to maximize the customer’s expected utility. We redefine project slack to reflect the difference between performance and a random target that reflects both the customer’s risk tolerance and uncertainty about the actual requirement. The z -score associated with this slack is shown to be proportional to the certainty equivalent for a project. Thus utility-maximizing decision rules in the language of decision analysis can be readily translated into z -score-maximizing decision rules in the language of project management. From this, we discuss how related decision-analytic concepts such as value of information might be applied to families of problems in project management.

Suggested Citation

  • Jeffrey M. Keisler & Robert F. Bordley, 2015. "Project Management Decisions with Uncertain Targets," Decision Analysis, INFORMS, vol. 12(1), pages 15-28, March.
  • Handle: RePEc:inm:ordeca:v:12:y:2015:i:1:p:15-28
    DOI: 10.1287/deca.2014.0305
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    References listed on IDEAS

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    Cited by:

    1. Bordley, Robert F. & Keisler, Jeffrey M. & Logan, Tom M., 2019. "Managing projects with uncertain deadlines," European Journal of Operational Research, Elsevier, vol. 274(1), pages 291-302.
    2. Andrea C. Hupman, 2022. "Cutoff Threshold Decisions for Classification Algorithms with Risk Aversion," Decision Analysis, INFORMS, vol. 19(1), pages 63-78, March.

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