Chris Anderson is a professor at the Cornell School of Hotel Administration. Prior to his appointment in 2006, he was on faculty at the Ivey School of Business in London, Ontario, Canada. His main research focus is on revenue management (RM) and service pricing. He actively works with industry, across numerous industry types, in the application and development of RM, having worked with a variety of hotels, airlines, rental car and tour companies, as well as numerous consumer packaged goods and financial services firms. 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 School of Hotel Administration, he teaches courses in revenue management and service operations management.
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.
WHAT YOU'LL LEARN
- 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
3-5 hours per week
100% online, instructor-led
Who Should Enroll
- Functional Managers
- Any professional that uses data to make business decisions
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