The most popular senator in Congress is John Thune, a Republican from South Dakota whose approval rating is 57 percent. While not very high praise for your job, in a Senate with a general approval rating of 15 percent, it is not hard to be the most popular. Meanwhile, Cris Huet, the (current) back-up goaltender for the National Hockey League’s Chicago Blackhawks, had one of the worst save percentages in the NHL at .895. That means he stopped about 9 of every 10 pucks shot at him during the season. But for a profession where the top performer stops 9.3 of 10, 89.5 percent ranks Mr. Huet among the league’s worst.
The unfair reality is that rating performance is often less about your performance and more about whom or what you are being measured against.
The more competitive sets we examine at STR Analytics the more often this seems to be the case with hotels as well. But who determines the comp sets? Comp sets often seem obvious, but it’s surprising how often a more relevant property is subjectively excluded or a less relevant hotel is included. In some cases, hotels are chosen strictly based on location or product type, but that too can be restrictive or overly inclusive.
There are more scientific ways to select a competitive set based on performance rather than perception or opinion.
Some comp sets were determined years ago, before more direct competitors were built. Therefore, a hotel continues to benchmark itself against standards from a previous decade. Many comp sets are agreed upon as part of a negotiation between the owner and the operator, so that performance can be measured to the satisfaction or more often compromise of both parties. Comp sets often can be hand-picked by the general manager and/or director of sales, and can thereafter be doubted by ownership, who might question the set’s legitimacy whenever bonuses are paid. And last, some sets are forced on the operator by ownership, which can lead to dissatisfaction and frustration from property-level management.
Traditionally, subjective criteria is employed by whoever determined a comp set. Individual opinions regarding location, quality, brand and amenities were typically the primary considerations in the selection. But often these attributes suggest the hotels are comparable, but not necessarily competitive. In fact, the phrase “comp set” may have been derived more from appraisal terminology wherein commercial properties were selected as market rental “comps” to establish market income for a particular subject. When hotels became a more defined vertical within commercial real estate, comp(arable) sets became comp(etitive) sets. Sometimes they are one and the same, but what differentiates a competitor from a comparable? By definition, a comparable is a property that shares similar traits with another whereas a competitor needs to be a viable substitute in the consumers’ mind. The most comparable hotels are those that operate similarly, but the most competitive properties are those that share the largest consumer base who will most readily substitute your hotel for another. The more guests of a property that perceive another as a viable substitute the more competitive the two properties are.
It would be great if we could ask every guest visiting a market which hotels they considered in their booking decision and why they chose the one they did. While efforts are under way to gather as much relevant consumer data as possible, the ability to poll everyone in a market or even a statistically significant sample of guests, traveling in from their hometowns to a specific market on a specific night for every hotel is virtually impossible. At least until an all-powerful “big brother” portal offers operator’s information on cookies (not the Doubletree kind) left behind when guests conduct an Internet search becomes available.
What is available is the opportunity to observe and measure where guests are staying, on what nights and in what patterns. By examining the statistical correlation patterns of demand between two or more hotels in a market and calculating whether they are correlated (both rise and fall in similar patterns of demand) or inversely correlated (one hotel consistently increases occupancy on nights when the competitive hotel increases average daily rate), achieve comparable rates each night and ideally cater similarly to both group and transient mix, they are considered more competitive than hotels that follow different performance patterns.
That is not to say hotels cannot be competitive on certain nights or with certain guest segments and far less so on or with others. In these cases, an examination of different comp sets for varying periods or segments may be warranted. But in the end, your most competitive properties are those that offer a substitute product to the same or similar pool of demand. In the lodging industry that product comes down to a box called a guestroom. Although each box can offer greater or lesser amenities and service levels housed in higher or lower quality facilities and locations, ultimately each guestroom can be a substitute for another when it comes to a night’s sleep, a bathroom and shower. You can be the best group house in the market but, if in the end, the same size transient hotel next door achieves higher revenues tonight and greater profit over the long term, they are the top performer.
Therefore, the ultimate measurement of success is what the hotel achieved in revenue and more importantly profitability in total and as a means of gauging performance on a per available room basis. It is nice to know that one hotel achieved greater revenue success among social, military, educational, religious and fraternal (SMERF) travelers than its primary competitors. But that success actually is a black eye for the hotel if that caused them to miss higher revenue and/or more profitable use of their facility by other segments and thus achieve a lower ADR or revenue per available room on a nightly basis, gross operating profit per available room at the end of the month and/or profitability on a quarterly and annual basis.
The statistical examination of nightly performance of hotels in alternative competitive sets can determine which properties’ demand patterns most closely correlate and the relative competitive dynamics of comparable properties. The figure below represents a basic visual representation of some of the results of these comp set studies.
Click image to enlarge.
In the chart above, the subject property’s original competitive set (on the left) indicates a diverse range of ADR in the market with the subject property representing roughly the comp set average. The alternative comp set (on the right) shows a more succinct ADR range with the subject property representing above average ADR and thus benchmarking ADR performance off of similarly positioned competitive properties and a less volatile benchmark.
Once you understand your true competitors you can better evaluate your performance and, more importantly, better anticipate market actions toward traveling on certain days, within certain seasons and among certain segments as well as market reactions to rate levels and fluctuation. This will allow you to use your performance ranking to not only know where you stand, but more importantly to improve revenue and profitability every day.