The hospitality industry has long used typical information sources to create as accurate a demand forecast as possible. However, with more sophisticated technology and software now available hotels would do well to consider that the data points that they have been using may not be telling the whole story.
For years revenue managers and hoteliers have typically forecast demand by looking at historical booking information, and then the pickup or pace of online reservations leading up to an actual stay date. By charting past and present, hoteliers have been able to get an idea of how much future demand there will be for any given date. This is important to not only establish room rates to maximize revenue, but also for operations teams to set staffing levels.
However, while those sources of data are critical they are also limiting. By using only historical and current bookings, hoteliers may get a decent view of future demand for the next month or maybe two, but when very few reservations are on the books, it becomes harder to predict much further out.
What then is missing? For one, unconstrained demand should be studied more closely. Unconstrained demand is often defined as the forecast or number of rooms a hotel could sell if it had an unlimited supply of rooms. And to measure that, most hotels will look only at the world of people actually purchasing rooms at their property.
However, I would suggest that true unconstrained demand should include not just those buying but everyone potentially shopping. This is more measurable and predictable today with the wealth of new consumer-centric data available.
The key to unconstrained demand: web shopping data
To improve algorithms and forecasts, hotels should look at web-shopping data. Two of the most useful information sets can be found on hotels’ online booking engine to give any property a better view of its lost potential business and unconstrained demand.
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