Improving The Analytical Mechanism for Inventory Management

Abstract

The article discusses strategies for enhancing the analytical mechanisms used in inventory management. It emphasizes the integration of data from various sources to provide a unified view of inventory levels, enabling more accurate decision-making. The use of advanced analytics and forecasting with machine learning algorithms is highlighted to predict demand more effectively. The importance of real-time tracking for immediate inventory updates and the application of optimization algorithms to balance inventory levels are discussed. The article also stresses the need for clear performance metrics and KPIs to assess inventory management efficiency, the role of collaborative planning across departments, the benefits of automating routine tasks, and the value of training for staff to improve inventory management analytics