Hierarchical Demand Forecasting: From Cream Cheese to Blood Thinners

Overview
Whether you’re predicting grocery store shelves or hospital inventories, forecasting demand for thousands of individual items presents a unique set of challenges. In this talk, we’ll explore the world of hierarchical demand forecasting through real-world examples spanning everything from cream cheese to blood thinners. Along the way, we’ll cover the practical challenges of building forecasts at scale, the trade-offs involved, and the techniques that make these systems accurate, robust, and production-ready.

Agenda
6:00pm - 6:30pm: Networking - food & drinks
6:30pm - 8:00pm: Presentation & discussion
8:00pm: Networking at Lake Monster Brewing

Meet Our Featured Speaker
David Bradley is a Data Scientist III at Cencora, where he develops large-scale demand forecasting systems supporting over a large array of products across the pharmaceutical supply chain. Previously, he held data science roles at Kraft Heinz, CH Robinson, and Analysis Group, applying forecasting and machine learning to challenges ranging from consumer goods and logistics to healthcare. David holds a Ph.D. in Economics from the University of Minnesota, specializing in time series econometrics and forecasting. His work focuses on building production-ready forecasting systems that bridge cutting-edge machine learning with practical business decision-making.

Sponsors
This event is sponsored by Lab651 & Recursive Awesome