Building a Scalable, Explainable Demand Forecasting System for Enterprise Retail

This article explores the challenges of large-scale retail demand forecasting, where millions of store-product combinations must be predicted weekly. It argues that success depends not just on model accuracy, but on system design—covering scalability, explainability, monitoring, and fault tolerance. The key takeaway is that combining GAMMs with distributed, piece-by-piece estimation and robust monitoring creates a forecasting system that is both reliable and operationally viable.