Marriott Rooms Forecasting

6 Pages Posted: 21 Oct 2008 Last revised: 25 May 2018

See all articles by Samuel E. Bodily

Samuel E. Bodily

University of Virginia - Darden School of Business

Larry Weatherford

University of Wyoming - College of Business

Multiple version iconThere are 2 versions of this paper

Abstract

The manager of a large downtown hotel has to decide whether to accept 60 additional reservations or not. If she accepts, she will be overbooked and face certain costs if all the people holding reservations show up. The manager must forecast, based on historical data, how many of the people holding reservations will show up and then decide, after taking into account the cost involved, whether to take the additional bookings. The case can be used in a class on seasonality and exponential smoothing in time-series forecasting.

Excerpt

UVA-QA-0389

Rev. May 16, 2018

Marriott Rooms Forecasting

β€œA hotel room is a perishable good. If it is vacant for one night, the revenue is lost forever.” Linda Snow was commenting on the issue of capacity utilization in the hotel business. β€œOn the other hand, the customer is king with us. We go to great pains to avoid telling a customer with a reservation at the front desk that we don't have a room for him in the hotel.”

As reservation manager of one of Marriott's hotels, Snow faced this tradeoff constantly. To complicate the matter, customers often booked reservations and then failed to show, or cancelled reservations just before their expected arrival. In addition, some guests stayed over in the hotel extra days beyond their original reservation and others checked out early. A key aspect of dealing with the capacity-management problem was having a good forecast of how many rooms would be needed on any future date. It was Snow's responsibility to prepare a forecast on Tuesday afternoon of the number of rooms that would be occupied each day of the next week (Saturday through Friday). This forecast was used by almost every department within the hotel for a variety of purposes; now she needed the forecast for a decision in her own department.

Hamilton Hotel

. . .

Keywords: decision theory, forecasting, female protagonist, diversity case, management of service industries, time series

Suggested Citation

Bodily, Samuel E. and Weatherford, Larry, Marriott Rooms Forecasting. Darden Case No. UVA-QA-0389. Available at SSRN: https://ssrn.com/abstract=911858

Samuel E. Bodily (Contact Author)

University of Virginia - Darden School of Business ( email )

P.O. Box 6550
Charlottesville, VA 22906-6550
United States
434-924-4813 (Phone)
434-293-7677 (Fax)

HOME PAGE: http://www.darden.virginia.edu/faculty/bodily.htm

Larry Weatherford

University of Wyoming - College of Business

1000 E. University Avenue
Laramie, WY 82071
United States

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
696
Abstract Views
3,129
rank
23,293
PlumX Metrics