How One Buyer Used AI Demand Forecasting to Cut Safety Stock 40 Percent

In this episode of The Buyer's Side, Lucas and Luna explore how a mid-sized electronics buyer used machine learning demand forecasting to reduce safety stock by 40 percent, freeing up $8 million in working capital. They walk through the specific model—a gradient-boosted tree trained on three years of point-of-sale data—and the procurement manager's step-by-step implementation, from IT integration to supplier negotiation. The episode also covers pitfalls like overfitting and demand signal latency, and why the buyer chose not to fully automate replenishment. A concrete look at how AI is reshaping inventory strategy, not through hype but through daily procurement decisions. #DemandForecasting #SafetyStock #MachineLearning #Procurement #SupplyChain #InventoryOptimization #WorkingCapital #ElectronicsBuyer #GradientBoosting #PointOfSaleData #AIinProcurement #SupplierNegotiation #Business #FexingoBusiness #BusinessPodcast #TheBuyersSide #InventoryManagement #DataDrivenProcurement Keep every episode free: buymeacoffee.com/fexingo