Ever craved your favorite dish, only to find its key ingredient missing from the store? You're not alone - stock outs can have significant consequences for businesses, resulting in frustrated customers and lost sales. On the other hand, overstocking can lead to wasted storage costs and potential write-offs. The replenishment system is responsible for striking the right balance between these opposing risks.
The key to successful replenishment is making accurate predictions about future demand.

This presentation takes a deep dive into the intricate world of demand forecasting, at Europe's largest retailer. We will demonstrate how enhancing simple machine learning methods with domain knowledge allows to generate hundreds of millions of high-quality forecasts every day.