Course Objective

To equip students with an understanding of the “importance and role of supply chain analytics” in the modern business enterprises and how business firms can take advantage with the help of supply chain analytics. Further, for students who wish to specialize in analytics, the course provides a strong foundation for the application of supply chain analytics with analytical platforms.

Learning Outcomes:

At the end of the course the student should be able to

  1. Explain the importance of supply analytics and applications.
  2. Handle the available business information/data more efficiently.
  3. Use analytical tools like R,SAS and MS excel efficiently in order to take managerial decisions more effectively

Detailed Syllabus

1. Introduction to Supply Chain Analytics: Definition, relevance and scope Supply Chain Analytics, recent trends in Supply Chain Analytics

2. Overview of Supply Chain Models and Modelling Systems: Descriptive models, Optimization modes, Off-the shelf modelling system (SLIM), Supply chain operations reference model (SCOR), The network KEIRETSU, Nature-Inspired Intelligence in Supply Chain Management

3. Application of Supply Chain Models: A Calibration Model Establishes Position and Performance Gap, Models for Purchasing, Procurement, and Strategic Sourcing, Logistics Models, from Manufacturing to Accepted Delivery, Models for Forecasting, Demand Management, and Capacity Planning, Models for Order Management and Inventory Management’ Models for Sales and Operations Planning, Advanced Planning and Scheduling Models, Models for Supplier Relationship Management, Models for Customer Relationship Management, Models for Collaborative Design and Manufacturing, Collaborative Planning, Forecasting, and Replenishment Models

4. A Look at Future State of Supply Chain Modelling: Recent developments in theory technology and practices. Future developments and expected improvement in efficiency levels and operational simplicity