Course Description

This innovative course, "Supply Chain Analytics (SC0x)," offered by MITx, is a comprehensive introduction to the analytical methods and tools essential for understanding and managing complex supply chain systems. The course is designed to equip students with practical skills in supply chain management, focusing on the application of various analytical techniques rather than theoretical concepts.

What Students Will Learn

• Basic analytical methods for supply chain management
• Application of probability models in supply chain scenarios
• Statistical analysis techniques for supply chains
• Formulation and solving of optimization models
• Use of spreadsheets for real-world supply chain case studies
• Decision-making under uncertainty in supply chain contexts

Pre-requisites

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

Course Coverage

• Introduction to probability and decision analysis for modeling uncertainty
• Basic statistics and regression techniques
• Optimization modeling, including:
  • Unconstrained optimization
  • Linear programming
  • Non-linear programming
  • Mixed integer linear programming
• Hands-on application of analytical methods using spreadsheets
• Case studies drawn from actual supply chains

Who This Course Is For

• Business and management students interested in supply chain operations
• Professionals working in or aspiring to work in supply chain management roles
• Anyone looking to enhance their analytical skills in a business context
• Individuals seeking a practical, hands-on approach to supply chain optimization

Real-World Applications

Graduates will be able to:

• Make data-driven decisions in complex supply chain scenarios
• Optimize inventory management and logistics operations
• Improve forecasting accuracy for demand and supply
• Enhance overall supply chain efficiency and performance
• Conduct quantitative analysis to support strategic supply chain decisions
• Use spreadsheets effectively for supply chain modeling and analysis

Syllabus Overview

1. Probability and decision analysis
2. Statistics and regression
3. Optimization modeling
   • Unconstrained optimization
   • Linear programming
   • Non-linear programming
   • Mixed integer linear programming
4. Case studies and practical applications

This self-paced course offers flexibility for learners, with all materials made available during the second week. Students can begin with any topic at their convenience, allowing for personalized learning paths. The course culminates in a scheduled final exam, providing a structured endpoint for learners to demonstrate their acquired knowledge and skills.