Workforce modeling: Difference between revisions

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'''Workforce modeling''' '''is the process of aligning the demand for skilled labor with the availability and preferences of workers. It utilizes mathematical models to perform tasks such as sensitivity analysis, scheduling, and workload forecasting.'''

{{Use mdy dates|date=October 2024}}{{peacock|date=January 2014}}

'''This approach iscan widelybe used in industries with complex labor regulations, certified professionals, and fluctuating demand — such as healthcare, public safety, and retail. Workforce modeling tools oftencan include software that helps determine staffing needs based on workload variations across times of day, days of the week, or seasonal cycles.'''

'''Workforce modeling''' '''is the process of aligning the demand for skilled labor with the availability and preferences of workers. It utilizes mathematical models to perform tasks such as sensitivity analysis, scheduling, and workload forecasting.'''

'''This approach is widely used in industries with complex labor regulations, certified professionals, and fluctuating demand — such as healthcare, public safety, and retail. Workforce modeling tools often include software that helps determine staffing needs based on workload variations across times of day, days of the week, or seasonal cycles.'''

==Definition==

The term can be differentiated from traditional staff [[Schedule (workplace)|scheduling]].<ref>{{Cite journal |last=Ernst |first=A. T |last2=Jiang |first2=H |last3=Krishnamoorthy |first3=M |last4=Sier |first4=D |date=2004-02-16 |title=Staff scheduling and rostering: A review of applications, methods and models |url=https://www.sciencedirect.com/science/article/pii/S037722170300095X |journal=European Journal of Operational Research |series=Timetabling and Rostering |volume=153 |issue=1 |pages=3–27 |doi=10.1016/S0377-2217(03)00095-X |issn=0377-2217|url-access=subscription }}</ref> Research indicates that traditional static planning models result in 60% of operating hours being either understaffed, or overstaffed, while modern workforce modeling implementations have achieved substantial cost reductions.<ref name=":1">{{Cite web |title=AI workforce planning for travel and logistics {{!}} McKinsey |url=https://www.mckinsey.com/industries/travel/our-insights/ai-can-transform-workforce-planning-for-travel-and-logistics-companies |access-date=2025-06-24 |website=www.mckinsey.com}}</ref> Staff scheduling is rooted in [[time management]].<ref>{{Cite journal |last=Pinedo |first=Michael L. |date=2022 |title=Scheduling |url=https://link.springer.com/book/10.1007/978-3-031-05921-6 |journal=SpringerLink |language=en |doi=10.1007/978-3-031-05921-6|url-access=subscription }}</ref> Besides demand orientation, workforce modeling also incorporates the forecast of the workload and the required staff, the integration of workers into the scheduling process through interactivity, and analysis of the entire process.<ref>{{Cite journal |last=Algethami |first=Haneen |last2=Martínez-Gavara |first2=Anna |last3=Landa-Silva |first3=Dario |date=2019-10-01 |title=Adaptive multiple crossover genetic algorithm to solve workforce scheduling and routing problem |url=https://doi.org/10.1007/s10732-018-9385-x |journal=Journal of Heuristics |language=en |volume=25 |issue=4 |pages=753–792 |doi=10.1007/s10732-018-9385-x |issn=1572-9397}}</ref> The evolution from traditional scheduling to workforce modeling demonstrated quantitative benefits and reflects broader technological advancement in organizational management.<ref name=":1" />

{{Unreferenced section|date=May 2025|small=y}}

The term can be differentiated from traditional staff [[Schedule (workplace)|scheduling]]. Staff scheduling is rooted in [[time management]]. Besides demand orientation, workforce modeling also incorporates the forecast of the workload and the required staff, the integration of workers into the scheduling process through interactivity, and analysis of the entire process.{{citation needed|date=June 2025}}

==Complexity of the model==

Many applications providing workforce modeling solutions might use the [[linear programming]] approach. Linear methods of achieving a schedule generally assume that demand is based on a series of independent events, each with a consistent, predictable outcome. Modeling the uncertainty and dependability of such events is a well-researched area.<ref name="Clancy, Thomas R. 2008">Clancy, Thomas R. ''Managing Organizational Complexity in Healthcare Operations.'' [[The Journal of Nursing Administration 38.9 (2008): 367–370. Print.]]</ref> Modeling approaches such as [[system dynamics]] have been employed in workforce modeling to address interdependencies and feedback loops within large organizations, such as [[NASA]].<ref name=":0">{{Cite journal |last=Marin |first=Mario |last2=Zhu |first2=Yanshen |last3=Meade |first3=Phillip |last4=Sargent |first4=Melissa |last5=Warren |first5=Jullie |date=2007 |title=Workforce Enterprise Modeling |url=https://www.jstor.org/stable/44719519 |journal=SAE Transactions |volume=116 |pages=873–876 |issn=0096-736X}}</ref> [[Heuristic|Heuristics]] have also been applied to the problem, and [[metaheuristics]] have been identified as effective methods for generating complex scheduling solutions.<ref name="Clancy, Thomas R. 2008" /><ref>{{Cite journal |last1=Burke |first1=Edmund |last2=Causmaecker |first2=Patrick De |last3=Berghe |first3=Greet Vanden |last4=Landeghem |first4=Hendrik Van |date=2004 |title=The State of the Art of Nurse Rostering |url=https://lirias.kuleuven.be/bitstream/123456789/123829/1/JOS_ |url-status=dead |journal=Journal of Scheduling |volume=7 |issue=441–499 |pages=441–499 |doi=10.1023/B:JOSH.0000046076.75950.0b |archive-url=https://web.archive.org/web/20160304113501/https://lirias.kuleuven.be/bitstream/123456789/123829/1/JOS_ |archive-date=March 4, 2016|url-access=subscription }}</ref>

==References==