Machine Learning for Real-Time Inventory Management in SAP
Betty Heleen · 2025
Real-time inventory management is a crucial aspect of modern supply chain and enterprise resource planning (ERP) systems, particularly in the context of SAP. This paper explores the integration of machine learning (ML) techniques with SAP for enhancing real-time inventory management. By leveraging ML algorithms, businesses can optimize inventory levels, predict demand fluctuations, and automate replenishment processes, leading to reduced stockouts, minimized excess inventory, and improved operational efficiency. The paper delves into the application of predictive models for demand forecasting, anomaly detection for inventory discrepancies, and reinforcement learning for dynamic supply chain decision-making. The integration of these advanced technologies within SAP’s framework provides businesses with a robust solution for achieving greater agility, accuracy, and cost-effectiveness in their inventory management processes.