Staffing a Multiskilled Workforce with Varying Levels of Productivity: An Analysis of Cross‐training Policies*

Service operations that utilize cross‐trained employees face complex workforce staffing decisions that have important implications for both cost and productivity. These decisions are further complicated when cross‐trained employees have different productivity levels in multiple work activity categories. A method for policy analysis in such environments can be beneficial in determining low‐cost staffing plans with appropriate cross‐training configurations. In this paper, we present an integer linear programming model for evaluating cross‐training configurations at the policy level. The objective of the model is to minimize workforce staffing costs subject to the satisfaction of minimum labor requirements across a planning horizon of a single work shift. The model was used to evaluate eight cross‐training structures (consisting of 36 unique cross‐training configurations) across 512 labor requirement patterns. These structures, as well as the labor requirement patterns, were established based on data collected from maintenance operations at a large paper mill in the United States. The results indicate that asymmetric cross‐training structures that permit chaining of employee skill classes across work activity categories are particularly useful.