Machine Learning (ML) is a branch of artificial intelligence that enables systems to learn from data and improve their performance over time without being explicitly programmed. In the supply chain context, ML is used to analyze vast amounts of data and uncover patterns that enhance forecasting, demand planning, and inventory optimization. ML algorithms help businesses predict demand spikes, identify anomalies, and optimize reorder points. These systems improve over time as more data becomes available, making supply chain decisions more accurate and dynamic. For inventory optimization, ML enables adaptive safety stock calculations, real-time replenishment triggers, and SKU rationalization. ML-powered platforms can respond to rapidly changing market conditions and supplier performance variations, significantly reducing stockouts and overstocks.
