Modelling inherent worker differences for workforce planning

TLDR

Workforce planning literature typically assumes workers are identical, but this study uses General Cognitive Ability (GCA) to capture individual differences. This paper investigates workforce management decisions under the assumption that workers are inherently different. The authors develop a mixed‑integer programming model that optimizes hiring, firing, and cross‑training across GCA levels to minimize total costs, and evaluate it in two experiments—one on realistic manufacturing systems with many machine groups and another on parameter effects. The results show that accounting for worker differences improves workforce planning and management.

Abstract

Most of the literature in the area of workforce planning assumes that workers are identical. This paper considers fundamental decisions in workforce management assuming that workers are inherently different. General Cognitive Ability (GCA) is used as the measure for individual differences. A mixed integer programming model is developed to determine the amount of hiring, firing, and cross-training for each GCA level to minimize total costs, which include training costs, salary costs, firing costs and missed production costs over multiple time periods. Two sets of experiments were developed: (1) to show that the model can be applied to realistic manufacturing systems with large numbers of machine groups, and (2) to study the parameters that affect workforce decisions. Our results indicate that worker differences should be considered when planning and managing the workforce.