Before you start
Students should have familiarity with basic programming concepts in some procedural programming language.
What you will learn
- To identify, evaluate, and capture business analytic opportunities that create business value
- Build models to support and help make managerial and business decisions
- Basic analytical methods and their applications
- Analyze case studies on organizations that successfully deployed analytical techniques
Week 1 – Introduction
Week 2 – Static price optimization
Week 3 – Dynamic price optimization
Week 4 – Price differentiation
Week 5 – Quantity based revenue management
Week 6 – Network revenue management & overbooking
Week 7 – Customized pricing and consumer choice models
Week 8 – Markdown management and behavioral issues in pricing
Week 9 – Introduction to inventory management
Week 10 – Stochastic inventory management
Week 11 – Miscellaneous topics in inventory management
Week 12 – Final review
How do airlines decide when to increase ticket prices? Should a hotel charge less per night for a long stay than a short one? Why do some software companies bundle very different products together? How should a fashion retailer decide when do start discounting clothes? Why do so many discounted rates end in ".99"? How should a company balance the risk of holding too much inventory on hand and the risk of turning away customers? Does it ever make sense for retailers to lie to suppliers about how much they will need to order? Should retailers with multiple locations hold most of their inventory in a central warehouse or at the individual locations?
These are only a small sample of the operational and pricing challenges all businesses regularly face. These challenges are often addressed individually and in isolation but, in reality, all of these decisions interact with each other. This class looks at the demand and supply management challenges faced by companies in various industries and provides an introduction to the tools that can be used to address these challenges.