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A risk analytics model for strategic workforce planning: readiness of enlisted military personnel

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Listed:
  • Leo MacDonald

    (Kennesaw State University)

  • Jomon Aliyas Paul

    (Kennesaw State University)

Abstract

We develop a dynamic stochastic model of military workforce planning that incorporates uncertainties about personnel gains and losses across ranks. We then apply it to determine the probability of not meeting required targets as well as the resulting shortages and overages in the short, medium, and long terms along with the evaluation of policies to mitigate these risks. Our model allows decision makers to adjust recruiting and training practices to minimize the risk of not meeting target personnel levels as well as to value retention and reenlistment policies by calculating the expected marginal value of retaining additional service members. Moreover, it allows us to create a penalty function to optimize recruiting and training levels. The outcome is a tool to evaluate and ensure comprehensive force readiness.

Suggested Citation

  • Leo MacDonald & Jomon Aliyas Paul, 2024. "A risk analytics model for strategic workforce planning: readiness of enlisted military personnel," Annals of Operations Research, Springer, vol. 338(1), pages 513-533, July.
    • Handle: RePEc:spr:annopr:v:338:y:2024:i:1:d:10.1007_s10479-023-05567-0
    DOI: 10.1007/s10479-023-05567-0
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    References listed on IDEAS

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