Mbop6014; module 1; supply chain analytics in scm
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This document outlines the modules for a Supply Chain Analytics course. The first module introduces basic supply chain concepts and models, including serial, distribution, and assembly networks. It also covers how supply chain analytics can enhance performance by improving visibility, managing demand volatility, and reducing cost fluctuations. Key topics include smarter logistics, demand and inventory management, and optimizing sourcing and logistics. The document also outlines the decision phases in a supply chain and different views of supply chain processes.
Mbop6014; module 1; supply chain analytics in scm
- 2. School: School of Business Course Code: MBOP 6014 Course: Supply Chain Analytics Faculty: Dr Aijaz Ahmad Khan Module-1: Supply Chain Analytics applications
- 3. Prerequisite/Recapitulations . • Basic understanding of Operations Management concepts • Basic understanding of Logistics and Supply Chain Management concepts • Basic understanding of Sourcing and Materials Management concepts • Basics of Mathematical and Statistical modelling concepts
- 4. Objectives . • Understand basic concepts of Operations Management • Understand basic concepts of Logistics and Supply Chain Management • Understand basic concepts of Operations Research and Mathematical modelling • Application of Supply Chain concepts into an analytical framework • Application of Materials Management concepts into an analytical framework
- 5. Basic Supply Chain Model .
- 7. Supply Chain Objective . • Maximize overall value created Supply Chain Surplus = Customer Value – Supply Chain Cost
- 8. Serial Supply Chain Serial Supply Chain
- 9. Distribution Supply Chain Distribution Supply Chain
- 11. • Supply Chain Analytics plays a key role in enhancing the performance of supply chain by improving visibility, managing volatility, and reducing fluctuations in cost. • Visibility of global supply chain and logistic processes • Managing Demand Volatility • Cost fluctuations in supply chain Supply Chain Analytics .
- 12. • Moving to Smarter Logistics to improve Supply chain visibility • Managing volatility though demand and inventory management • Reducing cost fluctuations by optimizing sourcing and logistics activities Analytics in Supply Chain .
- 13. Decision Phases of a Supply Chain . • Supply chain strategy or design • How to structure the supply chain over the next several years • Supply chain planning • Decisions over the next quarter or year • Supply chain operation • Daily or weekly operational decisions
- 14. Process View of Supply Chain . • Cycle View: processes in a supply chain are divided into a series of cycles, each performed at the interfaces between two successive supply chain stages • Push/Pull View: processes in a supply chain are divided into two categories depending on whether they are executed in response to a customer order (pull) or in anticipation of a customer order (push)
- 15. Cycle View of a Supply Chain .
- 16. Push-Pull View of Supply Chain – Walmart/LL Bean .
- 17. Push-Pull View of Supply Chain – Dell .
- 18. Supply Chain Macro Processes .
- 19. Framework for structuring drivers in Supply Chain .
- 21. Porter’s Value Chain Analysis of SC .
- 22. Bullwhip effect in SC .
- 23. References . • Sunil Chopra and Peter Meindel. Supply Chain Management: Strategy, Planning, and Operation, Prentice Hall of India, 2018. • Jeremy F. Shapiro. Modeling the Supply Chain. Duxbury Thomson Learning, 2018. • Ecker J.G. and Kupferschmid,M. (1988) Introduction to Operations Research, NY, Wiley • David Simchi Levi, Philip kaminsky, and Edith Simchi Levi. Designing and Managing the Supply Chain: Concepts, Strategies, and Case Studies. Irwin McGrawHill, 2016 • Sridhar Tayur, Ram Ganeshan, Michael Magazine (editors). Quantitative Models for Supply Chain Management. Kluwer Academic Publishers, 1999. • Dantzig G.B. (1949) Programming of interdependent activities, Mathematical model. Econometrica, 17, 3, 200-211. • Thie, P. (1988) An Introduction to Linear Programming and Game Theory, Wiley, NY.