Managing occupancy
Managing occupancy is a practice carried out by revenue managers, after they have grasped a complete comprehension of how to use room types and trailing codes, to assists their managerial functions, towards effective management of room occupancies and ADRs. A hotel’s director of sales and management is most times, seen as responsible for maximizing the sales efforts of the hotel, while the revenue manager is responsible for the maximization of hotel occupancy (Zakhary & El-Shishiny, 2009, pp. 1-5).
The options available to them include tactfulness, which will allow them to reach decisions that increase hotel occupancy levels, by adjusting to the unique demand variations of the hotel.
This is done, by employing two different occupancy restraints, which include a minimum length of stay (MLOS), where a hotel offers a restraint that a customer boarding a room on a given day, identified with high demand, should continue stay or occupancy for a number of days, for example, two. Those requesting to occupy the room for a single night are rejected, while those requiring stay for two nights are accepted (Andrew, Cranage, & Lee, 1990, pp. 173-174).
The second strategy is closed to arrival (CTA), which is simply, the restraint by the revenue management, that customers seeking to occupy the hotel on certain days, associated with high demand for rooms are rejected, offering preference to those seeking to occupy the room the day before, so they can stay on the day with CTA or longer than the two days.
An example here is Veema hotel, which has identified, from its occupancy patterns, that its rooms are flocked on Saturday, due to a given event happening on that day. In employing these strategies, they will identify the weak demand, before the ‘high demand’ day, and the weak one after the day, in this case, Friday and Saturday respectively.
The revenue manager at Veema Hotel, can, in this case, impose an occupancy restriction (CTA), that a customer requesting to stay on Saturday, can only be allowed to book the rooms a day before, so they can stay on Friday and the target day, Saturday. The second strategy may be used, by identifying Saturday as the day of high demand, then imposing an occupancy restraint (MLOS), that any customer seeking stay for Saturday, should book the room for more than a night (Wilson, 2001, pp. 45-48; Hayes & Ninemeier, 2006, pp. 187-188).
Managing ADR
Managing average daily rate (ADR) is the strategy used to adjust the rates offered per room, with reference to anticipated demand levels. In employing this strategy, the hotel takes a number of variables into account, which includes anticipated occupancy, revenue forecasts and the anticipated demand. For instance, hotels, during high-demand times, for example when there are games or graduation events to be hosted at neighboring schools or colleges, may require higher room rates from customers seeking reservations for the high-demand times (Vallen & Vallen, 1996; Hayes & Ninemeier, 2006, pp. 190, 191).
In line with these strategies, the lowering of prices below the rack rates may not always affect the hotel’s revenue positively but are often used during extraordinary times, when the rate is apparently the most imperative consideration when choosing a room type or hotel. Ordinarily, price adjustment is affected with reference to other demand determinants; including hotel location, frequent guest programs, brand loyalty, and brand quality (Oh, 1999, pp. 67-82; Dube, Enz, Renaghan, & Siguaw, 1999; Hayes & Ninemeier, 2006, p. 192).
An example here is the example of Oak Tree hotel, which is located near a local university. The hotels’ rack rate is USD 125, and the discounted rates can come down to USD 100 per night. The number of rooms at the hotel is 300, and the requests for reservations during the graduation time may go up to 350 requests, and during sporting events, can go to 330 requests for reservation.
During ordinary times, the number of rooms occupied a day may come down to 100 or 150, which is increased by offsetting their rivals through the discounting exercise. During the 2011 graduation event, the hotel reserved all the rooms (300) at the rack rate of USD 125. The case was the same during the national sports event, when the hotel received close to 345 reservation requests, to which it was only able to honor 300 of the total requests, at the rack rate of USD 125.
However, the management of the hotel noted that securing full occupancy presented a disadvantage, that the likelihood of customer relations not remaining at the expected standard, especially amongst service workers, was higher (Pugh, 2001, pp. 335-344).
Business segmentation
Market segmentation is very vital, in allocating limited resources, for instance, hotel rooms, to both leisure and business travelers, which is a vital yield management tool, through which a hotel can realize optimal revenues. Towards realizing effective marketing and distribution of services to the diverse customer segments, there are a number of tools, which are manipulated to favor the goal.
These include pricing, inventory management and forecasting, which fall under the bracketed field of yield management, which is housed under revenue management (Netessine & Shumsky, 1998, p. 34; Bitran & Mondschein, 1995). In the hotel business, revenue managers base their segmentation on certain characteristics, which guide the process of reserving rooms for business travelers (Schwartz & Hiemstra, 1997).
The problem with customer segmentation usually, is that the number of business customers can not be determined; therefore, the reservation should be based on booking limits and protection protocols. In this case, a booking limit is established, for instance, 240 out of 300 rooms. After the leisure customers have taken the 240 rooms, the rest (60) are sold at the rack rate/ full price.
The protection level is the number of rooms to keep aside for the business customer. The hotel should be able to differentiate between the different segments, who present varied demand behaviors and curve, as the business customer population is more indifferent to prices. For instance, the business traveler is likely to leave the hotel during the weekend, while the leisure customer will often, prefer to stay at the hotel over the weekend.
The rooms sold to the different segments are basically the same, whether preserved for the business customer or left for occupancy by the leisure travelers. The hotel business allows for withholding of rooms for future clientele, as it is not immortal or illegal, like the case is for hospital services (Netessine & Shumsky, 1998, p. 34).
An example here is that of Veema hotel, which has 300 hotels rooms, and has started taking reservations for business workshop customers, expected to attend a workshop program to be held on the 28th of June 2012. The hotel has decided upon a booking limit of 250 for leisure customers, at the discounted rate of 120, awaiting the business customers to take the remaining 50 rooms at the rack rate of USD 125. The disadvantage of placing the limit is that, in case the reserved number is high; the business customers may not fill the reserved rooms. Also, in case few rooms are reserved, then the hotel will forego the revenues to be drawn from the business customers (Vinod, 2004, pp. 178-180).
References
Andrew, W., Cranage, D., & Lee, C. (1990). Forecasting hotel occupancy rates with time series models: an empirical analysis. Hospitality Research Journal, 14, 173– 174.
Bitran, G., & Mondschein, S. (1995). An application of yield management to the hotel industry considering multiple day stays. Operations Research, 43, 23-25.
Dube, L., Enz, C. A., Renaghan, L. M., & Siguaw, J. A. (1999). American lodging excellence: The key to best practices in the U.S. lodging industry. Washington, DC: American Hotel Foundation.
Hayes, D., and Ninemeier, J. (2006). Hotel Operations Management. Upper Saddle River, N J: Prentice Hall.
Netessine, S., & Shumsky, R. (1998). Introduction to the Theory and Practice of Yield Management. INFORMS Transactions on Education, 3 (1), 34-44.
Oh, H. (1999). Service quality, customer satisfaction, and customer value: A holistic perspective. International Journal of Hospitality Management, 18, 67-82.
Pugh, S. (2001). Service with a smile: Emotional contagion in the service encounter. Academy of Management Journal, 43 (3), 335-344.
Schwartz, Z., & Hiemstra, S. (1997). Improving the accuracy of hotel reservations forecasting: curves similarity approach. Journal of Travel Research, 36, 34-45.
Vallen, G. K., & Vallen, J. J. (1996). Check-in check-out. Chicago: Irwin.
Vinod, B. (2004). Unlocking the value of revenue management in the hotel Industry. Journal of Revenue and Pricing Management, 3 (4), 178–180.
Wilson, R. H. (2001). Minimum Length-of-Stay Requirements as Part of Hotel Revenue Management Systems: Are They Legal? Journal of Hospitality Financial Management, 9 (1), 45-48.
Zakhary, A., Atiya, A., & El-Shishiny, H. (2009). Forecasting Hotel Arrivals and Occupancy using the Montecarlo simulation. Journal of Revenue & Pricing Management, 4 (3), 1-5.