Strategic Workforce Planning Under Uncertainty
<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, w...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
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Institute for Operations Research and the Management Sciences (INFORMS)
2022
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| Online Access: | https://hdl.handle.net/1721.1/143705 |
| _version_ | 1826212596566458368 |
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| author | Jaillet, Patrick Loke, Gar Goei Sim, Melvyn |
| author2 | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science |
| author_facet | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Jaillet, Patrick Loke, Gar Goei Sim, Melvyn |
| author_sort | Jaillet, Patrick |
| collection | MIT |
| description | <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> |
| first_indexed | 2024-09-23T15:28:35Z |
| format | Article |
| id | mit-1721.1/143705 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T15:28:35Z |
| publishDate | 2022 |
| publisher | Institute for Operations Research and the Management Sciences (INFORMS) |
| record_format | dspace |
| spelling | mit-1721.1/1437052023-06-26T20:57:59Z Strategic Workforce Planning Under Uncertainty Jaillet, Patrick Loke, Gar Goei Sim, Melvyn Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology. Operations Research Center <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> 2022-07-13T15:24:00Z 2022-07-13T15:24:00Z 2022 2022-07-13T15:17:36Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/143705 Jaillet, Patrick, Loke, Gar Goei and Sim, Melvyn. 2022. "Strategic Workforce Planning Under Uncertainty." Operations Research, 70 (2). en 10.1287/OPRE.2021.2183 Operations Research Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Institute for Operations Research and the Management Sciences (INFORMS) MIT web domain |
| spellingShingle | Jaillet, Patrick Loke, Gar Goei Sim, Melvyn Strategic Workforce Planning Under Uncertainty |
| title | Strategic Workforce Planning Under Uncertainty |
| title_full | Strategic Workforce Planning Under Uncertainty |
| title_fullStr | Strategic Workforce Planning Under Uncertainty |
| title_full_unstemmed | Strategic Workforce Planning Under Uncertainty |
| title_short | Strategic Workforce Planning Under Uncertainty |
| title_sort | strategic workforce planning under uncertainty |
| url | https://hdl.handle.net/1721.1/143705 |
| work_keys_str_mv | AT jailletpatrick strategicworkforceplanningunderuncertainty AT lokegargoei strategicworkforceplanningunderuncertainty AT simmelvyn strategicworkforceplanningunderuncertainty |