Foundations of Supply Chain Analytics and Decision-Making

In today's global market, successful logistics operations rely on data rather than intuition to keep goods moving efficiently. Understanding how to analyze and model supply chain data is essential for minimizing costs and preventing costly disruptions. This course guides you through the essential analytical methodologies used to solve complex supply chain problems. You will transition from understanding basic logistics concepts to applying mathematical models, forecasting techniques, and statistical tools to real-world operational decisions. What you'll learn: - Understand core supply chain terminology, key performance indicators, and foundational analytical frameworks. - Apply probability and statistical methods to analyze demand uncertainty and inventory levels. - Formulate optimization models to streamline transportation networks and reduce logistical costs. - Analyze supply chain data using regression techniques to identify trends and forecast future demand. - Evaluate supply chain resilience and mitigate operational risks using modern predictive modeling strategies. The curriculum begins with fundamental definitions of supply chain metrics before moving into practical applications of statistics, regression, and optimization. Through written explanations and practical scenarios, you will learn how to translate raw operational data into actionable business strategies. This course is designed for beginners, aspiring supply chain analysts, and logistics professionals looking to build their analytical toolkit, with no advanced mathematical background required. Start building the analytical skills needed to optimize modern supply chains today.