Chris Anderson is a professor at the Cornell Nolan School of Hotel Administration. Prior to his appointment in 2006, he was on the faculty at the Ivey School of Business in London, Ontario, Canada. Professor Anderson’s main research focus is on revenue management and service pricing. He actively works in the application and development of revenue management across numerous industry types, including hotels, airlines, and rental car and tour companies, as well as numerous consumer packaged goods and financial services firms. Professor Anderson’s research has been funded by numerous governmental agencies and industrial partners. He serves on the editorial board of the Journal of Revenue and Pricing Management and is the regional editor for the International Journal of Revenue Management. At the Nolan School of Hotel Administration, Professor Anderson teaches courses in revenue management and service operations management.
Course Overview
Decision making is never as simple as we would like it to be, since rarely does a single factor alone predict an outcome. In a competitive business environment, not taking this uncertainty into account has serious costs. In this course, you'll use foundations in probability to describe risk mathematically and incorporate those calculations into your decisions so you can take them to the next level. Working through increasingly complex modeling situations, you will learn to use estimates of probable future outcomes for Go/No-Go decisions and to run a Monte Carlo simulation allowing you to examine outcomes that vary based on multiple, interdependent decisions.
You are required to have completed the following courses or have equivalent experience before taking this course:
- Understanding and Visualizing Data
- Implementing Scientific Decision Making
- Using Predictive Data Analysis
Key Course Takeaways
- Calculate marginal value for a binary decision
- Determine optimal values for a repeating, sequential decision
- Build risk aversion into your model
- Calculate utility for a given decision
- Develop and use a Monte Carlo simulation
- Perform sensitivity analysis Use expected utility to accommodate risk
How It Works
Course Author
- Restaurant Distribution Strategy
- Hospitality Professional Development Program
- General Managers Program
- Data Analytics in R
- Management 360
- Data Analytics 360
- Revenue Management 360
- Data Analytics
- Hospitality Management
- Advanced Hospitality Revenue Management: Pricing and Demand Strategies
- Hospitality Digital Marketing
Who Should Enroll
- Analysts
- Functional Managers
- Executives
- Consultants
- Any professional that uses data to make business decisions
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