Data-Driven Inventory Management with Excel

Balancing customer demand with holding costs is one of the greatest challenges in modern supply chain operations. Keeping too much stock ties up valuable capital, while keeping too little leads to lost sales and unsatisfied customers. This course equips you with the analytical tools to make smart, data-driven inventory decisions. You will transition from basic guesswork to designing robust inventory models that account for demand uncertainty and lead-time variability, utilizing powerful spreadsheet techniques to streamline your workflow. What you'll learn: - Understand core inventory terminology, cost structures, and the fundamental trade-offs in supply chain management. - Calculate optimal safety stock levels and reorder points using probability distributions and service-level targets. - Apply the Economic Order Quantity (EOQ) model to minimize total ordering and carrying costs. - Utilize modern Excel features like dynamic arrays and Power Query to clean, organize, and analyze inventory datasets. - Analyze demand variability and forecast future stock requirements to prevent costly stockouts. The course begins with foundational definitions of inventory types and cost structures, then progresses step-by-step through mathematical modeling, uncertainty analysis, and practical spreadsheet implementation. You will read clear explanations, study formulas, and practice building your own optimization models through written exercises. This course is designed for aspiring operations managers, supply chain analysts, small business owners, and beginners looking to build analytical inventory skills without any prior experience in supply chain modeling. Start reading today to transform raw data into actionable inventory strategies.