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Solving a Staffing Model Using an Overbooking Simulation

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  • Kingsley Gnanendran

    (University of Scranton, PA, USA)

Abstract

This paper adapts a Monte Carlo overbooking simulation approach to determine appropriate levels of staffing when there is a clear trade-off between assigning too many versus too few workers. In the scenario considered, if a scheduled staff member fails to show up, one or more other employees will need to be assigned to additional (overtime) hours to “cover” the absent employee’s workload, leading to increased payroll costs. But even this can only be done up to a point since overtime hours are limited, by company policy, to a fraction of the regular time hours available during the shift. Therefore, if too few employees were scheduled to begin with, some demand may be left unmet, resulting in potential loss of revenue. This paper shows how the question of how many employees should be scheduled to each shift can be modeled similar to the well-known airline overbooking problem. We solve this staffing model using Oracle Crystal Ball, an Excel add-in for conducting Monte Carlo simulation, thereby demonstrating its easy applicability in practice.

Suggested Citation

  • Kingsley Gnanendran, 2025. "Solving a Staffing Model Using an Overbooking Simulation," European Journal of Business and Management Research, European Open Science, vol. 10(2), pages 1-5, March.
  • Handle: RePEc:epw:ejbmr0:v:10:y:2025:i:2:id:52598
    DOI: 10.24018/ejbmr.2025.10.2.2598
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