Demand and Supply Analytics II
Expand your knowledge of using data to make better business decisions by learning about price optimization, market segmentation, and supply chain management.
Modules/Weeks
Weekly Effort
Discipline
Format
Cost
Course Description
- Apply tools and concepts to address demand and supply management challenges in various industries.
- Utilize price optimization techniques, including static and dynamic approaches, to maximize revenue.
- Implement market segmentation and non-linear pricing strategies to target different customer segments effectively.
- Analyze consumer choice modeling and customized pricing for improved decision-making in pricing strategies.
Course Prerequisites
- Undergraduate-level knowledge in probability, statistics, linear algebra, and calculus
- Prior experience with basic programming concepts in a procedural programming
What You Will Learn
By the end of this course, learners will be able to:
Identify and evaluate business analytics opportunities that drive business value.
Build models to aid managerial and business decision-making processes.
Analyze case studies of successful organizations that have utilized analytical techniques effectively.
Gain knowledge of fundamental analytical methods and apply them to various real-world scenarios, including price response function, price elasticity, static and dynamic price optimization, price differentiation, quantity-based revenue management, network revenue management, and overbooking.
Course Outline
Module 1: Markdown
Module 2: Multi-product revenue management
Module 3: Customized pricing
Module 4: Introduction to inventory management
Module 5: Decentralized inventory system and supply chain coordination
Module 6: Review
Instructors
Daniel Guetta is an Associate Professor of Professional Practice at Columbia Business School and Director of the Business School's Center for Pricing and Revenue Management. He is also Director of the Business Analytics Initiative at Columbia Business School and Columbia Engineering. Guetta's research concentrates on using data and analytics to create value in businesses. He teaches courses in business analytics, data science, pricing, supply chain management, and technical tools such as Python and cloud computing. Guetta has written award-winning case studies in the area and co-authored "Python for MBAs," which was released in Fall 2020. Before joining Columbia's faculty, Guetta worked as a data scientist and engagement manager at Palantir Technologies. He holds a PhD in Operations Research from Columbia Business School, and completed his undergraduate studies in physics and mathematics at Cambridge and MIT.
Please note that there are no instructors or course assistants actively monitoring this course.