Contingent manpower planning in a high clock speed industry

In this paper we present a framework that balances the significant tradeoffs and helps managers in crafting a strategy for the induction of contingent workers in a complex assembly environment. The key issues we have considered in this paper include distinct manufacturing sub-processes, hierarchical or nested workforce skills, regular and overtime capacity, and impact of learning. We report a real life case study pertaining to the Singapore operations of a global computer manufacturer that served as the backdrop of this research and provided us with several intuitions. A linear programming model is presented to help determine the optimal allocation of permanent and contingent workers to all sub-processes. Our numerical study comprising more than 165 distinct experiments indicates that both the firm's cost performance and the number of contingent workers inducted are significantly affected by key parameters such as cost of induction, overtime premium cost, and overtime capacity. We highlight the impact of demand variability, and emphasize the overall value of the model presented in this research through the managerial insights that can be drawn from it.