Behavior Aware Service Staffing
David D. Cho, Kurt M. Bretthauer, Kyle D. Cattani, Alex F. Mills
Production and Operations Management · 2019 · Volume 28 · Issue 5
Abstract
Empirical studies of service systems have shown that workers exhibit different service rates depending on their assigned workload. In contrast, staffing models typically assume a constant service rate. To address this issue, we model two commonly observed behavioral effects, speedup and slowdown, in a general way that allows us to study their joint impact on service staffing. We fit our behavioral model to a hospital dataset and show that both effects are present across a variety of departments. Given these findings, we incorporate speedup and slowdown behavior into a multiperiod workforce staffing model and show that a workload (defined as the number of jobs assigned to each worker) that maximizes the service rate is typically not optimal. As expected, the effectiveness of the widely practiced single-ratio workload staffing policy depends on the strength of the speedup and slowdown effects. Interestingly, we find that in the presence of slowdown, weak behavioral effects (where workers work at a relatively constant rate) are the cases where the single-ratio policy performs the worst; the optimal workload instead varies the most as system demand changes. This result differs from practice in many services such as healthcare, where fixed patient-to-nurse ratio workloads are commonly used. We show that the strength of behavioral effects modulates the trade-off between a steady workload and the number of schedule adjustments.
Keywords
behavioral operations management, service operations management, workforce staffing, speedup and slowdown
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