Faculty & Research
Revenue Management Forecasting Aggregation Analysis Tool
By: Gary M. Thompson Ph.D.
Executive Summary:
The RMFAA tool is designed to help hoteliers identify the best level of aggregation to use in their revenue management forecasts of room demand. Hotel revenue managers (or revenue management systems) typically forecast the number of arriving guests (i.e., demand), for each day of arrival, for each length of stay, and each rate class.
In making these forecasts, you have four options. First, you can forecast the total number of arrivals for a day and then break that number into length-of-stay and rate classes using historical proportions (i.e., full aggregation). Second, you can forecast the total number of arrivals for a particular day in each rate class and then break that number into lengths-of-stay using historical proportions (i.e., aggregation by rate class only). Third, you can forecast the total number of arrivals for a given day in each length of stay and then break that number into rate classes using historical proportions (i.e., aggregation by length of stay only). Finally, you can develop independent forecasts of the total number of arrivals for a day for each length-of-stay and rate class (i.e., no aggregation).
Based on the data you provide, the RMFAA tool determines which of these forecasting approaches works best for your property. To use the tool with something other than the sample data it contains, you’ll need to provide the historical numbers of arrivals, by day, by length of stay, and rate class. Ideally, you should use unconstrained demand information (i.e., requests) and have two or more years of data.
The tool requires the following three documents:
For an explanation to the tool click on the link below
Tool Introduction (pdf 803kb)
To download the tool spreadsheet click on the link below
RMFAA Tool
To download the tool application which is necessary for your analysis, click on the link below
RMFAA Tool Application
Your Comments Please
If this CHR Report made a positive impact on your management approach or business operations, we welcome your commentary. We would like to post your comments on our website. Please submit your comments to js372@sha.cornell.edu and rohit.verma@cornell.edu.
Other Reports or Articles You May Find of Interest
- Hotel Revenue Management in an Economic Downturn: Results of an International Study, by Sheryl E. Kimes
- Setting Room Rates on Priceline: How to Optimize Expected Hotel Revenue, by Chris Anderson
- Hotel Revenue Management: Today and Tomorrow, by Sheryl E. Kimes
About Gary M. Thompson Ph.D.
Gary M. Thompson is a professor of operations management in the School of Hotel Administration, where he teaches graduate and undergraduate courses in operations management. Previously he spent eight years on the faculty of the David Eccles School of Business at the University of Utah. He holds a BS with first class honors from the University of New Brunswick, an MBA from the University of Western Ontario, and a PhD in operations management from The Florida State University. His current research focuses on optimizing restaurant table mixes, on optimizing conference schedules to improve attendee satisfaction, on course scheduling in post-secondary and corporate training environments, and on the effects on customer service of labor staffing and scheduling decisions. His research has appeared in the Cornell Hospitality Quarterly, Decision Sciences, the Journal of Operations Management, Management Science, Naval Research Logistics, Operations Research and other journals. He has consulted for several prominent hospitality companies and is the founder and president of Thoughtimus, Inc., a small software development firm focusing on scheduling products.
For more information visit http://www.hotelschool.cornell.edu/research/facultybios/faculty.html?id=84