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LOG 4100

Digital Procurement & Inventory Analytics

National University 3.0 credits

Course Description

This course examines procurement and inventory management through an integrated management and analytics lens. Emphasis is placed on category strategy development, e-sourcing, and supplier performance evaluation using Python-based spend analytics, including price variance analysis, should-cost models, and total cost of ownership. Students analyze inventory decisions across single- and multi-echelon systems, applying news-vendor logic, service-level optimization, intermittent-demand modeling, and (s, S) policy design to support managerial decision-making. Applied labs use pandas and statistical models for ABC-XYZ segmentation and risk-adjusted safety stock calculations, alongside Pyomo optimization modeling to determine reorder parameters. The course also introduces supplier risk scoring using basic machine learning techniques and includes a focused module on ESG considerations and Scope 3 supply chain data to support responsible and resilient sourcing strategies.

Code
LOG 4100
Credits
3.0
Subject
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