Encyclopedia Thursday, July 29, 2021 224 hits

Revenue management in hotel industry and innovation

Mladen Mitrović, PhD student at Faculty of Tourism Studies - Turistica, University of Primorska

 

HOW TO CITE:
 
Mitrović, M. (2021). Revenue management in hotel industry and innovation. In AIRTH Encyclopedia of Innovation in Tourism and Hospitality. Retrieved: <insert-date>, from http://www.airth.global

 

Revenue management is an area experiencing progressive popularity in the world of the hotel industry. Large hotels and hotel chains around the world have been practicing demand forecasting, market segmentation, performance measurement, dynamic pricing, benchmarking, as well as other processes that together constitute revenue management, with great success for many years. A commonly accepted definition of revenue management is to sell the right product to the right customer, at the right time, for the right price, through the right channel (HOSPA, p. 4). 

Although for a long time hoteliers have been considered slow innovators and acceptors of new technologies, it seems that AI-based RM solutions have completely "fascinated" them. 

Photo by Amiel D Hechanova on Unsplash (The Royal Hotel
Revenue management is an area experiencing progressive popularity in the world of the hotel industry. Large hotels and hotel chains around the world have been practicing demand forecasting, market segmentation, performance measurement, dynamic pricing, benchmarking, as well as other processes that together constitute revenue management, with great success for many years. A commonly accepted definition of revenue management is to sell the right product to the right customer, at the right time, for the right price, through the right channel (HOSPA, p. 4). 
 
From the historical point of view, back in 1970s, airline industry encountered a problem of filling all empty seats and improving the profitability of their business which led airline companies to introduce revenue management (RM) concept for the first time. After being developed by the airline industry, the RM began its extension in the form of a very successful common business practice within a wide range of industries, for example, in restaurants, telephone operators, hotels, conference centers, golf courses, car rental companies, cruise lines, etc.. A few years later, in 1980s, thanks to Marriot International, this concept was implemented in the hotel industry which resulted in generating around $150 million more than before, only by applying RM techniques.
 
Three essential conditions for RM to be applied:  fixed amount of available resources, the resources sold are perishable and different customers are willing to pay various prices for the same product.
 
In the last few years, concept of RM expanded to total revenue management (TRM). The concept of Total RM could be observed from the point of view that hotels should take into consideration all revenue streams (rooms, food and beverage, parking, spa, golf, retail, meeting space) instead only a room revenue, as a factors of the total profit contribution.
 
Today, a hotel RM is based on dynamic pricing, and traditional approaches in setting prices are no longer enough. Revenue managers need help in order for their work to be efficient on one hand, and on the other to enable them personal satisfaction. Software that relies on artificial intelligence (AI) and machine learning is playing an increasingly important role in this. Hoteliers are able to analyze a large number of data and implement them in such a way as to apply an optimal strategy in their business.
 
Although for a long time hoteliers have been considered slow acceptors of new technologies, it seems that AI-based RM solutions have completely "fascinated" them. By using it, large hotel chains and smaller hoteliers have significantly increased their profitability. Here, in addition to the inevitable historical, other data are used, such as market trends, booking trends, competition prices, inventory control, etc. With all the data, the so-called big data, only the RM jurisdiction is exceeded, and the information obtained is important for other departments in the hotel as well.
 
Certainly, when there is a possibility to obtain a large amount of data, one should be careful. First of all, there is a need to complete the processing of a smaller amount of data first in order to move to a larger number. Also, it is very important not to get lost in all this information that comes from different sides, which means that it should be learned to separate important information from those that are irrelevant. Mastering the so-called big data is definitely not an easy task.  
 
Of course, with the emergence of new quality and functional technological solutions in business practice, there is almost inevitably a debate whether it will completely replace the human factor. When it comes to RM software based on AI, the situation seems pretty clear at this point. They are advanced and helping in making the right tactical decisions, but definitely cannot replace a revenue manager or RM team. They cannot predict everything even when the circumstances are favorable, not to mention extreme situations such as terrorist attacks, natural disasters, or epidemics (one of which we are witnessing – the Covid 19 pandemic). Because of all this, it can be concluded that man is still in charge, and that AI RM software is a significant tool that makes it easier for those responsible to make final decisions.
 
References:
 
Ivanov, S. and Zhechev, V. (2012). Hotel revenue management – a critical literature review, TOURISM Review , Vol. 60, No. 2, 2012, 175 -197.
 
Marriott, J. Willard, Jr. and Cross, R. G. (2000). Room at the Revenue Inn. The book of management wisdom: Classic writings by legendary managers, ed. Peter Krass, 199-208. New York: Wiley.
 
Noone, B., Enz, C. and Glassmire, J. (2017). Total Hotel Revenue Management: A Strategic Profit Perspective, Cornell Hospitality Report, Vol. 17, No. 8, 1-15.
 
HOSPA e-book Revenue management, PRACTITIONER SERIES
 
https://www.hotelnewsresource.com/article104903.html
 
https://www.hospitalitynet.org/opinion/4095276.html
 
https://lodgingmagazine.com/data-and-ai-are-simplifying-hotel-revenue-management/
 
https://triometric.net/caught-in-the-big-data-deluge-what-about-mastering-little-data-first/
 
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