Cross-training performance in flexible labor scheduling environments

Abstract

Cross-training effectively pools multiple demand streams, improving service levels and, when demand streams are negatively correlated, boosting productivity. When services operate for extended hours, however, those benefits are intermittent because employees take their skills home with them at the end of their shift. This study explores how cross-training and workforce management decisions interact to affect labor costs and service levels in extended hour service operations with uncertain demand and employee attendance. Using a two-stage stochastic model, we first optimally staff, cross-train, schedule, and allocate workers across departments. We then simulate demand and attendance and, as needed, re-allocate available cross-trained workers to best satisfy realized demand. Comparing the performance of full- and partial cross-training policies with that of dedicated specialists, we found that cross-training often, but not always, dominated the performance of a specialized workforce. When cross-trained workers are less proficient than specialists, however, increased cross-training forced tradeoffs between workforce size and capacity shortages. However, both workforce size and service levels often improved with increased scheduling flexibility. Further, increased scheduling flexibility appears to be an efficient strategy for mitigating the effects of absenteeism. Thus, scheduling flexibility may be an important cofactor for exploiting the benefits of cross-training in labor scheduling environments.