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Why Revenue Management?
* Segmented Market
Hotels typically segment their market (customer base) into a set of categories based on the price each category is willing to pay. Typical categories include the business traveler and the vacation traveler. Because demand patterns for each of these categories may vary significantly, hotels find it difficult to satisfy all of the demand simultaneously. A good example is the comparison between the time-conscious business executive and the pricesensitive vacation customer. The former is willing to pay a higher price in exchange for flexibility of being able to book a room at the last minute while the latter is willing to give up some flexibility for the sake of a more inexpensive room. RM tries to maximize revenues by managing the tradeoff between a low occupancy and higher room rate scenario (business customers) versus a high occupancy and lower room rate (vacation customers). Such a strategy allows hotels to fill rooms that would otherwise have been empty.
* Fixed Capacity
A hotel’s capacity is relatively fixed - it is nearly impossible to add or remove rooms based on fluctuations in demand. If at all hotel capacity were flexible, there would be no need to manage capacity.
* Perishable Inventory
In the hotel industry, hotel rooms are the inventory. A hotel room that remains unoccupied for a night loses all its value for that night. This inventory cannot be stored and is lost forever. Because RM tries to manage demand instead of supply, it proves to be good business sense for the hotel.
* Low Marginal Cost
The fixed cost of adding a room in a hotel is heavily capital intensive. However, once the hotel manages to cover its initial fixed costs, the cost of serving an additional customer is low enough that the hotel can sell the room at a lower margin if it wishes. Such a strategy will obviously need to be balanced by one that also seeks to sell the room(s) at higher margins. Thus, the high fixed cost/low marginal cost nature of the business makes price differentiation a necessity – something that is made possible by application of RM.
* Advanced Sales
More often than not, requests for bookings start early. Therefore, hotels have enough leeway to adjust room prices based on the variation between realized bookings and expected demand. If all hotel rooms are sold at the same time, the hotel does not have the flexibility to adjust prices upward if demand picks up later. The tradeoff occurs when a manager is faced with the option of accepting an early reservation from a customer who wants a low price, or waiting to see if a higher paying customer will eventually show up.
* Demand Fluctuations
Demand for hotel rooms is characterized by crests and troughs, which the hotel factors in during the room pricing process. In peak season, the hotel can increase its revenues by raising room prices, while during lean seasons it can increase its utilization rate by lowering prices. Past data will offer the manager a way to forecast when these periods of high and low demand may occur. Unfortunately, it is very difficult to predict the actual demand with a high degree of certainty.
Therefore, the most critical challenge facing the hotel industry is predicting potential capacity, and developing a pricing strategy that will encourage maximum capacity and revenue. Revenue Management is the most effective technique to solve this challenge, similar to aggregate and hierarchical production planning techniques often employed in the manufacturing industry.
Revenue Management is based on complex optimization methodologies developed from advanced statistical and analytical models. In order to arrive at a solution, managers need to evaluate several millions of decisions, which requires a significant investment of skills, hardware and time. Many RM practitioners prefer to breakdown the actual business scenario into four sub-problems, and then identify an individual solution to some or all of these sub-problems.
This would significantly reduce the number of potential non-optimal decisions thereby providing fewer choices, leading to quicker results.
These four sub-problems are:
a) Market segment identification,
b) Forecasting and Pricing,
c) Inventory allocation, and
Next > How does it all work?
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