Course details
Supply Chain Analytics
OPER 60500A
This course focuses on concepts and developments of analytics tools for the supply chain. The topics of this course consist in descriptive, predictive and prescriptive analytics for the supply chain, i.e., retail analytics, transportation and network analytics, and disruption management.
It is aimed to provide students with analytics skills necessary to tackle supply chain problems in the contexts of manufacturing, retail, omnichannel, transportation and public sectors. This course makes use of the Python Programming Language to demonstrate how such analytics tools can be built. Within a team project, students will also develop a proof of concept of an analytics tool for a supply chain application.
Themes covered
- Overview of analytics (definitions; potential; risks and responsabilities)
- Descriptive analytics in the supply chain (metrics and key performance indicators; visualization)
- Retail logistics analytics (demand forecasting using external data; store inventory replenishment; price optimization)
- Transportation and network analytics (distribution in online and omnichanel retailing)
- Disruption management (stochastic optimization of pre-event mitigation and post-event restoration plans)
- Python coding workshops (introduction to programming and Python libraries; program elementary analytics pipelines; understand complex analytics pipelines)
Important notes
Course in French : OPER 60500
Course code
OPER 60500A
Subject
Operations and logistics
Program
Master of Science (MSc)
Location
Côte-des-Neiges
Instruction mode
On-site learning
Credits
3