From Instinct to Insights: Data-Driven Inventory Forecasting in Logistics
Too Long; Didn't ReadInventory forecasting heavily relies on accurate data and advanced analytics. AI-driven forecasting can reduce errors by 20-50%, but limited useful data impedes AI adoption. Data quality and analytics optimization are essential. AI and drones aid data collection, aiding real-time decision-making. AI tools predict sales at SKU level, aligning inventory with demand, enhancing operational efficiency. Implementing successful forecasting involves defining critical parameters, data smoothing, and training what-if simulations with augmented data. Data-driven inventory forecasting is crucial for supply chain success, enabling on-time product availability, customer satisfaction, and strategic decision-making.