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Strategic Workforce Planning Under Uncertainty

Author(s)
Jaillet, Patrick; Loke, Gar Goei; Sim, Melvyn
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Abstract
<jats:p> A new study in the INFORMS journal Operations Research proposes a data-driven model for conducting strategic workforce planning in organizations. The model optimizes for recruitment and promotions by balancing the risks of not meeting headcount, budget, and productivity constraints, while keeping within a prescribed organizational structure. Analysis using the model indicates that there are increased workforce risks faced by organizations that are not in a state of growth or organizations that face limitations to organizational renewal (such as bureaucracies). </jats:p>
Date issued
2022
URI
https://hdl.handle.net/1721.1/143705
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science; Massachusetts Institute of Technology. Operations Research Center
Journal
Operations Research
Publisher
Institute for Operations Research and the Management Sciences (INFORMS)
Citation
Jaillet, Patrick, Loke, Gar Goei and Sim, Melvyn. 2022. "Strategic Workforce Planning Under Uncertainty." Operations Research, 70 (2).
Version: Author's final manuscript

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