Revenue management was probably the brainchild of the aviation industry, as airlines sought a means of maximizing their profitability by charging high prices on popular routes at peak times when seats were in demand, while offering low fares during quieter periods to drum up additional demand. The goal was to achieve the optimal combination of seat, passenger, time and price, and as the distribution model developed, also came to encompass factors such as the best channel at the most efficient commission.
As airline passengers became familiar with the idea of peak and off-peak travel, and the idea that advance reservations could be cheaper than last-minute bookings, the hotel industry also began to take notice. Of the major players, Marriott was one of the first to attempt to implement revenue management during the 1990s – and given the characteristics of the hotel product, it is easy to see why the concept quickly gained traction.
Hotels are ideal candidates for revenue management because the number of rooms available is fixed, and the product is perishable; a room which is unsold on Saturday cannot be saved and sold as stored inventory on Sunday. The fixed costs of a hotel are relatively high, while the marginal costs are low. Furthermore, the product can readily be sold at different rates, and the demand will respond to price accordingly. Customers can treated separately and allocated to different segments, and the rooms can all be sold in advance of the time they will be used.
To run an affective revenue management system a hotel requires data detailing the property’s past performance. Occupancy rates for previous years must be available, with information covering the prices at which rooms were sold along with the times that the rooms were sold. It is important to know for any given date the proportion of rooms already sold by any specified earlier date in order to establish the booking rate.
Customer segmentation is also essential. Previous customers can be categorized in many ways, although the most basic segments are group v individual, and business v leisure. Booking habits and occupancy rates for each customer type must be established through analysis of the data. It is then also important to consider factors such as weather conditions in the past, the level of competition in the past, and whether or not any special events took place in previous years which might have shifted demand patterns or customer demographics. All of these factors may have influenced the occupancy rates and revenues obtained, and if a hotel looks at the data without taking such factors into consideration, managers will be unprepared for potentially different outcomes.
Revenue managers must also look forward with regard to external factors. One principal of revenue management is to use price to regulate demand, but when external shock occur unexpectedly, it may be impossible for hotels to react swiftly enough to take advantage. For example, if an airline suddenly announces a flash sale to a particular city for a particular date window, a hotel’s inventory can be sold out before managers have had a chance to raise the prices. In other cases, the knowledge that a city is about to host a major sporting event can see managers put prices up, only to find that demand is suppressed by the high prices, leaving unsold inventory and a bonanza for late bookers.
It is also important to avoid cannibalization. This is where discounts are offered to stimulate demand during low periods, but the outcome is merely to sell rooms at lower prices to people who would have booked anyway at the regular rate, while failing to attract any additional business. This is a particular challenge for revenue managers, who must aim to squeeze the maximum possible revenue out of each room. A high degree of sophistication is needed in order to extract high prices from people who are willing to pay, while simultaneously and selectively dropping prices to a level low enough to ensure all the rooms are filled, with the final room taken by a cheapskate who is still paying at the upper limit of his personal budget.
The software companies have certainly made the process easier, by proving access to data, and allowing the price-demand relationship to be closely monitored. However, automation can only ever be a part of the answer, as a professional revenue manager will be able to add experience and personal observation to the information generated by the software in order to achieve the perfect balance of prices, rooms, guests, channels, and dates.