Performance Opportunity for Workforce Agility in Collaborative and Noncollaborative Work Systems

To gain insight into the potential logistical beneets of worker cross-training and agile workforce policies, we study simple models of exible workers in serial production systems. The primary control issue is how to assign workers to jobs/stations over time. Under assumptions of complete worker exibility and collaborative work, we prove that a simple expedite policy minimizes along each sample path the cycle time (delay) for each job. Therefore, the expedite policy also minimizes work in process and maximizes throughput along every sample path. We also compute the performance improvement opportunity achievable using exible workers as opposed to the optimal static allocation of workers. This enables us to examine the factors that make workforce agility a potentially attractive strategy. We also consider the intuitive analogy to the expedite policy for the noncollaborative work environment which we call the pick-and-run policy, but demonstrate by counterexample that it is not always optimal. Finally, we extend some of our insights from the demand-constrained environment to a capacity-constrained environment operating under a constant-WIP (CONWIP) protocol.