Impact of lead time variability in supply chain risk management

Abstract

In this article, we study the impact of lead time variability on the performance of supply chain risk management in the beer industry. The stakeholders considered are the empty aluminum can supplier, the brewery and the distributor. The stochastic lead time model developed is an extension of the previously developed base model (with deterministic lead time) under which commodity price risk and demand uncertainty are managed via an integrated risk management approach using operational methods and financial derivatives. Simulation-based optimization is used to model and analyze such a complex system. We find that lead time variability does not always deteriorate the supply chain performance. Only high levels of lead time variability are found to justify more the need for a coordinated supply chain. The findings also reveal the need for using different hedging strategies to manage products flows across the supply chain under stochastic lead time versus the deterministic case. Managerial insights for the supply chain studied are argued based on experimental design findings.