Supply Chain Analytics

Modern supply chains generate massive amounts of data, but turning that data into insights requires the right analytical tools and capabilities. This course equips you with the core quantitative methods used by supply chain professionals to model uncertainty, analyze data patterns, and optimize critical decisions under real-world constraints. Through realistic case studies, hands-on spreadsheet modeling, and practical applications, you’ll master essential analytical techniques: probability and statistics for modelling variability, hypothesis testing and regression analysis for data-driven decisions, mathematical optimization for planning and network design, and simulation for evaluating policies under uncertainty. By the end of this course, you'll be equipped to apply rigorous analytical methods to solve supply chain challenges and drive measurable performance improvements. Supply Chain Analytics is a self-paced course with a scheduled final exam. All materials are released at the start of the course so you can progress at your own pace. This Supply Chain Analytics course is part of the MITx MicroMasters Credential in Supply Chain Management , offered by #1 ranked SCM Master's program at the Massachusetts Institute of Technology. This is an open enrollment course, making it accessible for almost anyone, anywhere in the world to enroll and learn for free. 3b

• Model uncertainty in supply chains using probability and statistical analysis
• Conduct hypothesis testing and regression analysis to support data-driven decisions
• Formulate and solve mathematical optimization models for supply chain planning and network design
• Use simulation techniques to evaluate policies, test scenarios, and assess decisions under uncertainty
• Apply algorithmic and approximation methods to solve complex problems when exact solutions are computationally infeasible

• Secondary school algebra and basic mathematics concepts
• Passing knowledge of statistics and probability