Solving a Staffing Model Using an Overbooking Simulation
Year: 2025
Type: article
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.
Author: Kingsley Gnanendran
Institution: University of Scranton
Language: English
Subfield: Emergency Medical Services
Field: Health Professions
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4408740300