Due to significant overlap in course content, students cannot take both this course and the spring term full-semester Supply Chain Management course.

Career Focus

This course is appropriate for students interested in pursuing careers in any management function (e.g., operations, marketing, finance) in firms that make, sell and/or distribute physical products, or in organizations (e.g., consulting firms, investment banks, private equity firms, software providers, transportation providers) that analyze, invest in, and/or offer products and services to those firms.

Given this course’s analytical focus, it is also appropriate for any students broadly interested in the deployment of analytics capabilities in businesses. Although primary applications will be centered on supply chain and operations, most classes will have equally important takeaways related much more broadly to human-algorithm (or human-AI) collaboration, i.e., how human employees can work together with AI and algorithms to improve business outcomes. No analytics experience is necessary – students of all backgrounds are welcome!

Educational Objectives

Supply Chain Analytics (SCA) builds on aspects of the first-year Technology and Operations Management (RC TOM) course. However, whereas RC TOM focuses primarily on producing and developing products and services, SCA emphasizes managing product availability, especially in a context of rapid product proliferation, short product life cycles, and global networks of suppliers and customers. Hence, topics not examined in RC TOM such as inventory management, distribution economics, and demand forecasting are explored in SCA. SCA also differs from RC TOM in that RC TOM concentrates primarily on material and information flows within an organization, whereas SCA focuses on managing material and information flows across functional and organizational boundaries, and thus has ties to the first-year courses in marketing and leadership.

Supply Chain Analytics also builds on aspects of the first-year Data Science for Managers (RC DSM) course. However, whereas RC DSM focuses primarily on mechanics and applications of particular data science techniques, SCA emphasizes how to deploy data science (analytics) capabilities in business operations and how employees can best leverage their own expertise and data science tools to improve business outcomes.

Please note that the full-semester Supply Chain Management course will include a majority of the material in Supply Chain Analytics plus a broader, more “general management” view of supply chain management, including additional non-analytics cases with case protagonist guests joining to share their broader management perspectives. Due to significant overlap in course content, students cannot take both courses.

Grading

Grading will be based on class participation, engagement, and a capstone project consisting of playing a week-long “Supply Chain Game” simulation and writing a corresponding report.

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