Partners: JSI and Addis Ababa University School of Pharmacy
Massachusetts Institute of Technology’s Center of Transportation and Logistics (MIT CTL) Humanitarian Supply Chain Lab is dedicated to improving supply chain performance in low-resource settings. We engage in research, outreach, and education activities.
John Snow Inc. (JSI) asked MIT CTL’s Humanitarian Supply Chain Lab to develop a Supply Chain Analytics course for the School of Pharmacy at Addis Ababa University (AAU) in Addis Ababa, Ethiopia. MIT CTL developed the course, delivered it to a cohort of 50 students, and transferred knowledge to Addis Ababa University faculty members with the intent that they can deliver the course themselves in the future.
Course: Introduction to Analytics in Global Health Supply Chains
Description: This course provided an introduction to applying analytics to solve supply chain problems in Global Health using real-world applications and case studies. The use of models and data was shown. The course introduced important methods to provide a Supply Chain Analytics Toolkit. Methods included linear and mixed-integer programming, algorithms, linear regression, probability distributions, hypothesis testing, and simulation. Advanced methods focused in-depth on forecasting and inventory management.
Course Delivery: This was a blended course comprised of online video lectures and in-person labs. The course was partitioned into 4 modules and each module contains 3 lessons and 3 labs. Videos were provided through an online platform (and USB sticks). Students watched the videos at any time prior to the labs (online or downloaded) and revisited them afterward. An online forum was provided for students to ask questions and discuss the lectures.
Labs: The labs focused on applying the methods presented in the lectures and gaining a deeper understanding of using the methods, working with data, and gaining insights from the analysis. Students were exposed to different software tools to solve problems and gain practice using computers to solve data-driven problems. All software tools used in this course were open source.