Ms. Christodoulidou

Revenue Management

Pros and Cons of RevPAR vs GOPPAR

By Natasa Christodoulidou, Assistant Professor, California State University

Co-authored by G. Keong Leong, Ph.D,Associate Dean in the College of Business Administration and Public Policy at California State University Dominguez Hills

Revenue Management

Revenue Management, also known as yield management, may be defined as the process of analyzing, anticipating, and impacting consumer behavior to maximize the profits from a fixed perishable resource, primarily hotel guest rooms and airline passenger seats (Christodoulidou, Berezina, Cobanoglu, 2012). Revenue management, including overbooking and dynamic pricing, has been an enormously important innovation in the service industry (Netessine & Shumsky, 2002). For example, a number of airlines overbook their reservations for a particular flight by 14% since on average they expect a 10% to 20% no shows on flights. The Marriott hotel chain credits its revenue management system for generating additional revenue of about $100 million per fiscal year. These are serious considerations that need to be constantly evaluated and revisited in establishing performance metrics.

Shoemaker and Shaw (2008), established the rules for the revenue management process in the hospitality industry as follows:

  1. Set the most effective pricing based on current conditions and knowledge.
  2. Limit the number of reservations accepted for any given night or room type based on profit potential.
  3. Negotiate volume discounts with groups (bearing in mind that one should not displace a higher rated individual business, but keep a few guest rooms at bay for a particular night).
  4. Match market segments with the right room type, price, and packing needs based on demographic information and data available.
  5. Enable reservation agents to be effective sales agents rather than merely order takers; they can market the property and upsell based on the information provided.

Hence, inventory control and revenue management, may appear to be similar in methodology, as executing one, may lead to the other one. The idea behind this is that with inventory control, at least in theory, one can better manage guest room inventory. In order for this to occur, guest room prices may need to increase or decrease, depending on many variables such as holidays, food and beverage minimum spent during conference and event weeks, and ancillary revenue generated by facilities in the hotel. Historically, in manual oriented systems, whenever a change in price happens, hotel operators had to update all channels manually.

This rarely exists anymore as the use of property management systems (PMS), works interchangeably with the Central Reservation Systems (CRS) of the hotel. In this way, for a particular hotel property, only one central database exists. For example when a reservation is made by a potential guest from a third-party website like Kayak, it will interface with the hotel CRS, access the current price of the particular hotel room, and therefore ensure rate parity. This is one way hotels can control their revenue management process. This method is quite popular and has worked well in the past for many hotel properties.

As part of the Revenue Management methodology, we have two models that have evolved in the last decade, the Revenue per Available Room (RevPAR) and the Gross Operating Profit per Available Room (GOPPAR).

Revenue Per Available Room (RevPAR)

Revenue per Available Room (RevPAR) may be defined as the potential total guest sleeping room revenue divided by the total number of physically available rooms.

Formula for Revenue per Available Room (RevPAR) RevPAR = Occupancy X Average Daily Rate

RevPAR is different from the Average Daily Rate (ADR). While ADR is calculated by the total sleeping rooms revenue divided by total number of sleeping rooms sold, RevPAR is quite different. RevPAR takes into consideration the amount of unoccupied available rooms, while ADR shows only the average rate of rooms actually sold. RevPAR has gained a lot of traction in the hospitality industry the last few years and we have seen an increase in its popularity.

The Gross Operating Profit Per Available Room (GOPPAR)

Gross Operating Profit Per Available Room (GOPPAR) may be defined as the total gross operating profit for a property divided by the number of available rooms.

Formula for Total Gross Operating Profit for a Property (GOPPAR) GOPPAR= (Gross Operating Profit Per Available Room/Number of Available Rooms)

It is arguably one of the most effective ways to look at a hotel's performance and make any necessary adjustments that impact the best interests to achieve the hotel's financial and monetary goals. GOPPAR is a key performance indicator that allows the hotel operator to see the value of the asset in any given time. One can argue that a hotel has a double personality role to play in the sense that it is a real estate asset and an operating business at the same time. GOPPAR may be considered as a more all inclusive approach as it takes into consideration the costs and revenues associated with the hotels ancillary activities instead of just looking at the guest room rate.

Main Differences Between REVPAR and GOPPAR

There are a number of differences that we can look at when determining whether to use RevPar or GOPPAR as a measurement tool in determining ratios and success measures for room inventory and hotel stability. Overall, we need to keep in mind that while RevPAR looks at the revenue on the profit and loss statement, GOPPAR looks at the gross operating profit; these are two completely different elements even though they are financially related.

A hotel property can theoretically have both a high Average Daily Rate (ADR) and RevPAR and still operate at a loss; however, if a hotel has a strong GOPPAR, it will always be profitable. Because of the complexities that go into calculating GOPPAR - it takes into consideration costs rather than just revenue - RevPar is still the most popular standard by which hotels measure the performance of their rooms division based on its simplicity in calculating and overall understanding of metrics in the hotel industry. In addition, REVPAR can be used as a benchmark to compare the hotel with its competitors on a daily, weekly, monthly, and annual basis.

GOPPAR takes into account sales growth and management effectiveness in managing operating costs/expenses. Since the property owners know the value of their assets at any point in time, they can make the right decisions on renovations, capital investments, closures and others. Since GOPPAR factors in cost, housekeeping services must better understand the effect of their duties on this figure and financial controller should be able provide the best input on what affects the value of the property.

It can be argued that in the case of low-end properties and hotels that cater to meeting and conference operations, the room revenue contributes no more than 50-55% of total revenue (Younes and Kett, 2003). This is because a large part of their revenue is derived from items other than guest rooms (for example, food and beverage). For these hotels, RevPAR will consider only a portion of the revenue performance. Consequently we will not have an accurate analysis when comparing hotel performances using RevPAR. In this type of scenario, GOPPAR may be a better measure than REVPAR. Even though this may not reflect the majority of hotels in the United States, worldwide, there are thousands of properties that generate more revenue from items such as food and beverage instead of just the guest sleeping rooms (Shwartz, Altin, and Singal, 2016).

A high RevPAR can act as an indicator for volatility in a hotel investment, yet there may be a greater profit to be made due to the presence of volatility (Ismail, Dalbor, and Mills, 2002). In addition, a high RevPAR may fail to include revenue from food and beverage and other de¬partments, which may alter the financial landscape when taking financial related executive decisions.

Another issue that comes to mind when we use RevPAR is the size of the property. Larger hotels tend to be penalized more than hotels with fewer rooms. We would expect that it is easier to fill a smaller hotel than one twice that size, especially when experiencing market conditions such as seasonality or varying occupancy rates between weekdays and weekends (Younes and Kett, 2003).

RevPAR does not take into account any other ancillary costs that may be necessary to provide the service level and standard expected such as spa facilities, concierge desk, etc. (Brown and Dev, 1999). On the other hand, GOPPAR is a great way to reflect on business performance in the hospitality industry and make any necessary adjustments accordingly since GOPPAR takes a number of cost items into consideration in operating a hotel such as personnel, utilities, insurance, and mortgage (Parker, 2016). Since GOPPAR considers all revenue streams, comparison between properties of different sizes and revenue mixes can be compared, without penalizing those with a bigger percentage of non-room revenue.

The question that one should ask when deciding whether to use RevPAR or GOPPAR is what we are measuring and what should we be measuring. Are we measuring revenues or profits? Overall, GOPPAR cannot exist without RevPAR. Even though GOPPAR may be presenting a more holistic view of the performance of a property, it does not realistically assess a hotel's overall revenue management strategy. Overall, pro¬ductivity measures that include cus¬tomers' actual purchasing habits over time might prove more valuable than those calculations that merely consider a hotel's physical assets (Brown and Dev, 1999).

References

Brown, J. R., & Dev, C. (1999). Looking beyond RevPAR: productivity consequences of hotel strategies.

Christodoulidou, N., Cobanoglu, C., and Berezina, K. (2012), Managing Hotel Electronic Distribution Channels. American Hotel Lodging Association (AHLA).

Ismail, J. A., Dalbor, M. C., & Mills, J. E. (2002). Using RevPAR to analyze lodging-segment variability. Cornell Hospitality Quarterly, 43(6), 73.

Netessine, S., & Shumsky, R. (2002). Introduction to the theory and practice of yield management. INFORMS Transactions on Education, 3(1), 34-44.

Schwartz, Z., Altin, M., & Singal, M. (2016). Performance measures for strategic revenue management: RevPAR versus GOPPAR. Journal of Revenue and Pricing Management.

Shoemaker, S., & Shaw, M. (2008). Marketing essentials in hospitality and tourism. Upper Saddle River, NJ: Pearson/Prentice Hall.

Parker, J. (2016). GOPPAR (Gross Operating Profit Per Available Room) - Best Measurement of Success. HotelExecutive.com

Younes, E. and Kett, R. (2003). GOPPAR a derivative of RevPAR!, HVS International, http://www.hvs.com/content/913.pdf

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This article was co-authored by G.Keong Leong, Ph.D. Dr. Leong is Associate Dean in the College of Business Administration and Public Policy at California State University Dominguez Hills. He received his MBA and Ph.D. from the University of South Carolina. He served previously as MBA Director and Chair of the Management Department at the Lee Business School, University of Nevada Las Vegas (UNLV). Prior to UNLV, Dr. Leong worked in the Fisher College of Business at Ohio State University. His research is in the areas of supply chain management and international operations. He has published in high quality journals such as the Journal of Operations Management, Decision Sciences Journal, Interfaces, Journal of Management, European Journal of Operational Research, International Journal of Logistics Management, and International Journal of Production Research. He has co-authored three books: Principles of Supply Chain Management: A Balanced Approach (Southwestern-Cengage), Operations Strategy: Focusing Competitive Excellence (Allyn & Bacon) and Cases in International Management: A Focus on Emerging Markets (West Publishing Company). He has received research, teaching, and service awards including an Educator of the Year award from the Asian Chamber of Commerce in Las Vegas, Dennis E. Grawoig Distinguished Service award from Decision Sciences Institute, and OM Distinguished Scholar award from the Operations Management Division, Academy of Management. Dr. Leong has served as President of the Decision Sciences Institute, Editor of Decision Line, President of the Western Decision Sciences Institute, and Chair of the Operations Management Division, Academy of Management. Dr. Leong can be reached at gkleong@csudh.edu.

Dr. Christodoulidou is the Director of the Hospitality Technology Research Institute at California State University Dominguez Hills (CSUDH). She is an Associate Professor in the Management and Marketing Department at CSUDH where she teaches for the undergraduate and the MBA programs. She holds a Ph.D. from the University of Nevada Las Vegas (UNLV), an MBA from the University of Wisconsin-Milwaukee (UWM), and a Master’s of Accounting and a B.Sc. from Arizona State University (ASU). Her research interests are in the areas of Hospitality Technology, Electronic Commerce, Electronic Distribution, and E-Marketing. Her research has appeared in numerous academic and professional journals. Ms. Christodoulidou can be contacted at 310-243-3502 or Nchristodoulidou@yahoo.com Extended Bio...

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