MIT SCM Symposium 2024

In the dynamic landscape of the fast moving consumer goods industry, companies must effectively manage production capacity and inventory to respond to fluctuations in demand. To mitigate the risk of lost sales, companies can adjust two levers to handle such volatility: increase inventory levels or production capacity. In this context, the planning team of our sponsor company, a large company in the snack food industry, aims to address this problem cost-efficiently, ensuring profitability amid uncertainty. They seek a tactical capacity-planning model that strikes the correct balance between inventory levels and capacity utilization. This paper takes a holistic approach to capacity and inventory management. We present a mixed integer linear programming model that handles the trade-off and balances holding inventory and increasing capacity on the tactical horizon. We model that trade-off using data from one of the sponsor company's production lines, the relevant stock-keeping units, and the associated inventory and capacity increase costs. While increasing capacity may seem counterintuitive because it entails lower utilization, our model shows that even a slight increase above the sponsor company's current baseline capacity can lead to lower inventory levels in specific periods, resulting in improved financial performance. Based on data from one year, our model recommends a 2.70% increase in production capacity, resulting in a reduction of 5.99% in inventory holding expenses and achieving an overall annual financial improvement of 0.53%.