Careful comp set selection key to performance
 
Careful comp set selection key to performance
14 FEBRUARY 2012 6:59 AM

The selection of a competitive set can have implications on the actual performance of a hotel—for better or for worse.

The standard key metric used to measure an individual hotel’s room revenue performance achievement is revenue per available room, which is calculated by dividing an individual hotel’s room revenue by the hotel’s available rooms.

 

Gary Isenberg

Taking this one step further, one of the most widely utilized benchmarks in the hotel industry is the metric known as RevPAR Index, also referred to as Revenue Growth Index. RevPAR Index measures an individual hotel’s performance compared to market-wide RevPAR and is calculated by dividing an individual hotel’s RevPAR by the market-wide RevPAR. The RGI of a hotel reflects a measurement of the property’s ability to obtain its fair share of RevPAR for its specific market. An Index above 100% indicates a hotel achieving more than its fair share of the market-wide RevPAR, while an Index below 100% represents a property not attaining its fair share of the market-wide RevPAR.

 

The most commonly defined “market” to measure an individual hotel’s performance is the property’s competitive set. A competitive set is typically defined by hotel ownership and/or management and in some cases with guidance provided by the subject’s brand affiliation. Properties included in a competitive set should represent direct competitors of a specific property. Factors in determining the selection of direct competitive properties might include: location, number of rooms, type of property, brand affiliation (if any), amenities, available meeting space, etc.

Competitive set selections should be reviewed on a continuous basis to ensure their relevance, as markets are continuously in flux due to, but not limited to: the addition of new hotels, reduction of supply, vagaries in brand affiliations and changes in requirements of surrounding hotel demand generators. Fundamentally, a comp set with the most accurate depiction of a subject property’s competitiveness can drive and impact actual results.

Grading performance
For a moment consider the elementary school report card as an STR Trend Report, the hotel’s RevPAR as the student’s performance, the market as the criteria to measure the performance of the student, and RevPAR Index as the actual grade.

Back in my elementary school days the grading system did not consist of letter grades but rather a simple three tier ranking system; Unsatisfactory (“-“), Satisfactory (“S”) and Better than Satisfactory (“+”).  Therefore, if the report card is considered to be the STR report, then an “S” equates to a RevPAR Index of 100% while a “-“ is likened to a RevPAR Index below fair share or less than 100%, and so on.

School report cards are segmented into subcategories referred to as course subject, just as an STR report can be divided into submarkets such as market class, tract, comp set, etc. Each course subject contains criteria by which the performance of a student is measured, similar to individual properties within each sub market and/or competitive set. The measurement criteria for the course subject of Physical Education might include items such as: participates in class, works well with others, positive attitude or follows instructions. These criteria seem adequate for gym class but would not be suitable for the sole measurement of English class, where the expected criteria should include topics such as spelling, grammar and reading comprehension. Therefore, it would not be relevant to measure a student’s performance in English class by the criteria for gym class. This might result in a skewed evaluation. 

The same can be said for a competitive set. Including hotels that are not truly direct competitors is comparable to measuring a student’s performance in one subject using the criteria from another.
 
Measuring the correct items on report cards allows students to identify their individual strengths and weaknesses, which enable them to grow, learn and improve. The same can be said about a properly selected competitive set, which allows management to focus and improve performance against the hotel’s direct competitors. Hotel management performance is typically determined and judged by its ability to maximize a competitive set’s RevPAR index. Individual managers’ goals and objectives are frequently designed around improving these statistics so as to underscore the notion “what gets measured gets done.”

A case study
The following is an example of a recent assignment executed by LWHA Asset and Property Management Services. This case study validates my thesis of how the selection of a competitive set can have implications on the actual performance of a subject property.

LWHA reviewed a 200-plus room, limited-service midscale property located in a major airport market. When the property originally opened, it was the only limited-service facility in the immediate market. The immediate market, excluding the subject, consisted of four full-service properties and one upscale limited-service property. Management and ownership of the property included all five properties in the competitive set, which was a clear representation of the entire local market at the time the subject entered the marketplace. 

Over time, an additional five limited-service hotels opened. In addition, during this time period two of the competitive set properties underwent a change in brand affiliation. 

Management/ownership of the subject property did not adjust the existing set to reflect the changes in the marketplace, as the full-service properties were closer in proximity to the subject. The subject’s RevPAR Index averaged a RevPAR Index of 110% compared to the competitive set described above. Based on these results, it was concluded by ownership and management that the property led the market in RevPAR. 

During our engagement, an additional STR report had been analyzed to reflect the actual changes in the competitive marketplace. This revised competitive set included the sub-market’s limited-service midscale and upscale properties, and excluded the full-service properties. The performance of the subject went from an RGI ranking of 110% to 90%.  Obviously, the actual RevPAR of the property remained the same; however, the performance of the RevPAR Index as compared to the new set fell below its fair share. Therefore, management and ownership’s conclusion that the property led the market in RevPAR was a misnomer.

After a thorough analysis, we determined the original competitive set no longer represented the direct competition of the subject property, as these full-service properties relied heavily on airline crew and group rooms for the majority of their business, while the subject property marketed to and depended on transient rooms for a preponderance of its business. The full-service competitors sold a significant number of rooms at lower base rates to group and crew customers, leaving a smaller amount of rooms available for transient guests. With fewer rooms available for transient business, the full-service properties sold the remaining rooms at higher room rates than the limited-service properties in the local market. The subject property, a limited-service hotel, mirrored the pricing strategy of the original comp set and out-priced itself as compared to its true competitors, the limited-service properties, which resulted in a RevPAR Index of 90%, achieving a level below fair share. 

As a result of this performance, we recommended the property alter its selling strategy to be more competitive with the revised and more accurate competitive set. The subject property quickly improved its RevPAR Index to more than 100%. The conceptualization and implementation of the revised sell strategy of the subject hotel came about as a result of the competitive set modification.

The STR report is a valuable tool and is considered the hotel industry’s report card. However, if a selected competitive set is not an appropriate representation of a subject’s competitive landscape, the outcome can be misconstrued by producing inaccurate and sometimes detrimental results.

Gary Isenberg has more than 28 years of diversified hospitality experience. He joined LWHA Asset and Property Management Services as president in May of 2011. He leads the firm’s practice of providing third-party asset management, property management and an array of advisory services specializing in hotel operational and financial functions. Mr. Isenberg can be reached at 212-300-6684 x 108 or gary.isenberg@lwhadvisors.com.

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