Demand and Supply Analytics
Harness data analytics to optimize pricing strategies and streamline operations, empowering smarter business decisions that drive growth and efficiency.
Harness data analytics to optimize pricing strategies and streamline operations, empowering smarter business decisions that drive growth and efficiency.
Master the art of leveraging data for strategic business decisions in this comprehensive course on Demand and Supply Analytics. Delve into the intricate world of pricing strategies, inventory management, and operational challenges faced by businesses across industries. From airline ticket pricing to retail inventory optimization, you'll explore real-world scenarios and develop analytical skills to address complex business problems. Learn to build predictive models, apply basic analytical methods, and analyze case studies of successful analytics deployments. By the end of this course, you'll be equipped to identify, evaluate, and capitalize on business analytic opportunities that drive value and improve decision-making processes.
Instructors:
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What you'll learn
Identify and evaluate business analytic opportunities that create value
Develop models to support managerial and business decisions
Apply basic analytical methods to real-world business problems
Analyze case studies of successful analytics deployments
Understand static and dynamic price optimization techniques
Learn strategies for price differentiation and customized pricing
Skills you'll gain
This course includes:
Live video
Graded assignments, exams
Access on Mobile, Tablet, Desktop
Limited Access access
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There are 12 modules in this course
This course provides a comprehensive exploration of demand and supply analytics, focusing on how businesses can use data to make better operational and pricing decisions. Key topics include static and dynamic price optimization, price differentiation, revenue management, overbooking strategies, customized pricing, consumer choice models, and inventory management. The course covers both theoretical concepts and practical applications, using case studies to illustrate successful analytics implementations in various industries. Students will learn to build models that support managerial and business decisions, apply basic analytical methods, and identify opportunities for creating business value through analytics. The curriculum is designed to equip learners with the skills to address complex business challenges in areas such as airline pricing, hotel booking strategies, retail inventory management, and product bundling.
Introduction
Module 1
Static price optimization
Module 2
Dynamic price optimization
Module 3
Price differentiation
Module 4
Quantity based revenue management
Module 5
Network revenue management & overbooking
Module 6
Customized pricing and consumer choice models
Module 7
Markdown management and behavioral issues in pricing
Module 8
Introduction to inventory management
Module 9
Stochastic inventory management
Module 10
Miscellaneous topics in inventory management
Module 11
Final review
Module 12
Fee Structure
Instructor
Data Science and Business Analytics Expert
Daniel Guetta serves as Associate Professor of Professional Practice at Columbia Business School and holds dual directorship roles, leading both the Center for Pricing and Revenue Management and the Business Analytics Initiative at Columbia Business School and Columbia Engineering. His expertise bridges the gap between academic theory and practical business applications in data science, with a focus on supply chain management, machine learning, and convex optimization. After completing his undergraduate studies in physics and mathematics at Cambridge and MIT, he earned his PhD in Operations Research from Columbia Business School. Before joining Columbia's faculty in 2017, he worked as a data scientist and engagement manager at Palantir Technologies, where he tackled complex data challenges across various industries from finance to pharmaceuticals
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