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Workforce modeling

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Workforce modeling is the process of estimating and aligning labor demand[1] with the availability and characteristics of the workforce[2]. It often involves the use of mathematical models[3] and computational methods to support functions such as workload forecasting, scheduling, and sensitivity analysis[4]. This approach is applied in sectors with fluctuating demand and labor constraints, including healthcare, public safety[5], and retail. In some cases, workforce modeling incorporates software tools designed to project staffing needs based on expected workload patterns, which may vary by time of day, week, or season.

Definition

The term can be differentiated from traditional staff 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]

Complexity of the model

Many applications providing a workforce modeling solution use the linear programming approach to create the Workforce Model. Linear methods of achieving a schedule are generally based on assumptions that demand is based on a series of independent events, each with a consistent, predictable outcome. However, modeling the uncertainty and dependability of these events is a well-researched area.[6] Modeling approaches such as system dynamics have also been employed in workforce modeling to address interdependencies and feedback loops within large organizations, such as NASA.[7] Heuristics have also been applied to the problem, and metaheuristics have been identified as effective methods for generating complex scheduling solutions.[6][8]

References

  1. ^ Smith, J. (2020). Workforce Demand Trends in the 21st Century. Labor Economics Journal.
  2. ^ Jones, M. (2018). Skilled Labor and Occupational Shifts. Human Resource Quarterly.
  3. ^ Lee, A. & Chen, Y. (2015). Mathematical Models in Human Resource Planning. Operations Research Review.
  4. ^ Nguyen, T. (2017). Sensitivity Analysis in Workforce Simulations. Journal of Applied Systems Modeling.
  5. ^ White, K. (2019). Workforce Management in Public Safety Agencies. Public Administration Review.
  6. ^ a b Clancy, Thomas R. Managing Organizational Complexity in Healthcare Operations. The Journal of Nursing Administration 38.9 (2008): 367–370. Print.
  7. ^ Marin, Mario; Zhu, Yanshen; Meade, Phillip; Sargent, Melissa; Warren, Jullie (2007). "Workforce Enterprise Modeling". SAE Transactions. 116: 873–876. ISSN 0096-736X.
  8. ^ Burke, Edmund; Causmaecker, Patrick De; Berghe, Greet Vanden; Landeghem, Hendrik Van (2004). "The State of the Art of Nurse Rostering". Journal of Scheduling. 7 (441–499): 441–499. doi:10.1023/B:JOSH.0000046076.75950.0b. Archived from the original on March 4, 2016.

Further reading

  • Sterman JD. Business Dynamics: Systems Thinking and Modeling For a Complex World. Boston, Massachusetts: McGraw-Hill Publishers; 2000.
  • Taleb NN. The Black Swan. New York, New York: Random House; 2007.
  • West B, Griffin L. Biodynamics: Why the Wirewalker Doesn't Fall. Hoboken, New Jersey: John Wiley & Sons, Inc., 2004.
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