Skip to content
Joshua Hale

Joshua Hale

Joshua Hale

Operation Research Engineer at Intel Corporation

Joshua Hale received his Bachelor of Industrial and Systems Engineering degree with summa cum laude honors from Auburn University. He completed his doctoral studies at Georgia Institute of Technology, where he received a PhD in Industrial and Systems Engineering with a concentration in Supply Chain Engineering. He is currently an operation research engineer in the supply chain intelligence and analytics group at Intel Corporation in Phoenix, Arizona. During his tenure at Intel he has worked on several strategic projects in inventory planning, analytics strategy, and factory operations. His research interests include simulation optimization and inventory planning, with a focus on supply chain applications. He has published papers in engineering journals and conference proceedings on optimization and simulation techniques.

Track: Supply Chain

Monday, April 15, 11:30am–12:20pm

Closing the Gap Between Forecasting and Inventory Management

Although methods for forecasting and inventory optimization are well established, the intersection of the two is less developed. Nevertheless, minimizing forecast error and inventory cost separately may lead to sub-optimal overall performance. When forecasts are employed for inventory decisions, it is advantageous to consider the resulting inventory performance instead of more commonly used forecast error metrics. Forecasting methods are typically evaluated based on statistical properties without taking into account lead times, inventory cost, or service levels. Similarly, inventory methods are optimized independently of the forecasting process and treat the forecast as simply an input. In this talk, we discuss methods developed to improve the integration between forecasting and inventory management. The goal of this work is to move beyond sequential optimization of forecast and inventory models to a framework in which forecasting and inventory management are treated as an integrated cycle where each one influences the other.