How Distributors Use Demand Sensing to Predict Orders

In this episode of Wholesale & Distribution with Fexingo, Lucas and Luna explore how distributors are using demand sensing—a data-driven approach that goes beyond historical averages to predict short-term order patterns. They break down a real-world example from a mid-sized industrial parts distributor that used point-of-sale data, weather feeds, and machine learning to reduce forecast error by 40 percent and cut safety stock by 25 percent. The conversation covers how demand sensing differs from traditional forecasting, the role of granular data like SKU-level sell-through, and practical steps for distributors just starting out. Lucas explains the difference between sensing and forecasting, while Luna questions whether smaller distributors can afford the tech—and finds that even basic tools can deliver quick wins. This episode ties directly to channel partners, inventory efficiency, and margin protection without repeating prior topics like just-in-time or predictive analytics. #DemandSensing #Distribution #Wholesale #SupplyChain #InventoryManagement #Forecasting #MachineLearning #DataAnalytics #B2B #ChannelPartners #SellThroughData #POSData #SafetyStock #ForecastError #IndustrialParts #Business #FexingoBusiness #BusinessPodcast Keep every episode free: buymeacoffee.com/fexingo