Course Description

This course is the fourth in the 4-course Supply Chain Analytics Professional certificate program. It incorporates learning advanced analytics and mathematical optimization to find solutions for supply chain problems. You’ll learn how to use linear programming, mixed integer programming, and heuristics to conduct prescriptive analytics related to production processes, distribution networks, and routing. The course serves as a capstone for the program by culminating in a hackathon where you’ll design networks, inventory policies, and scenarios and then evaluate the outcomes via simulations.

The online version of the course is comprised of (4) half-day online instructor-led LIVE group webinars (May 16, 17, 18, 19 | 1-5pm ET) and pre-work (e.g. installing and testing software on your computer, testing connectivity with LMS and meeting software, etc.) to be completed before the first day of the course.

Who Should Attend

Experienced business professionals who perform or want to perform analytics to improve their supply chain management processes. They want to tackle strategic goals and to perform leading edge analytics projects that address the full complexity of supply chains.

How You Will Benefit

  • Use mathematical optimization to transform Supply Chain Management (SCM) processes.
  • Apply LP, MIP, and heuristics to SCM, particularly in production planning, routing, and network design.
  • Utilize PowerBI and Python in optimization projects.
  • Participate in a hackathon that pulls together everything learned throughout the certificate program.

What Is Covered

  • Role of mathematical optimization in addressing complex SCM challenges  
  • Appropriate application of linear programming (LP), mixed integer programming (MIP), and heuristics
  • Evaluation of production processes, distribution networks, and routes using optimization
  • Ability to pull together all content of the certificate program into a prescriptive analytics project
  • Hands-on practice with these skills using data from the (fictional) Cardboard Company (CBC)