Revenue per available room has allowed hotel operators to more efficiently gauge the performance of a property and its pricing and distribution strategies, and helps hotels fine tune yield management and segmentation strategies. Because this metric does such a concise job of helping hotels link occupancy and average daily rate, it is beneficial to translate the RevPAR metric into an industry with similar challenges and data. With a few minor tweaks to the numerator and denominator, ski lift ticket operators can better understand their relative success and pave the way for more intelligent decisions regarding dynamic pricing and which distribution strategies are effective.
Quick comparison of RevPAR and RevPASS:
- RevPAR = total room revenue/available rooms
- RevPASS = total lift ticket revenue/resort capacity (defined by CCC or SAOT, see below for definitions)
In order to calculate RevPASS, we need to determine the data points ski resorts can input into the equation. First, however, it is important to identify a few metrics that resorts currently focus on to determine success.
Historically, ski resort operators have focused on two primary success metrics: skier visits (visitation) and ticket yield. Skier visits is a simple understanding of the total number of individuals using a ski resort’s lift system within a given time period. A ski resort’s ticket yield is analogous to a hotel’s ADR. Ticket yield is a simple average dollar rate of tickets sold within a given time period, frequently looked at on a daily basis.
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Dave Belin |
Capacity is slightly more difficult for a ski area to determine because while resorts focus heavily on a metric defined as “visitation” (simply the number of customers using their ski lifts within a given time period), they rarely view visitation as a percentage of a fixed capacity (as occupancy is a percentage of capacity). This highlights an important difference between the industries: Hotels can and sometimes do hit capacity (a hotel with 100 rooms cannot occupy more than 100 percent), while most ski resorts rarely operate at their full capacity. This difference can be resolved with regards to RevPASS, however, because a fixed denominator is the key within the metric to judging one time period’s relative success against another. Most ski resorts do have capacity estimates, even if they are somewhat subjective (in comparison to the objective number of rooms available at a hotel). Metrics like comfortable carrying capacity (CCC) or skiers at one time (SAOT) are typically functions of the load capacity of a ski resort’s lift system, in combination with other infrastructure like base lodges. This capacity figure becomes the denominator in the RevPASS calculation. Like hotels, sophisticated ski areas reduce capacity during slower times by selectively closing certain chairlifts or sections of the mountain, which helps to reduce their operating costs (particularly labor and power) during those times. Thus, the RevPASS denominator can fluctuate on a daily basis at some ski areas.
As ski resorts start catching up to hotels in pricing and distribution sophistication, the RevPASS metric will be key in measuring past pricing and available capacity decisions (because it can be calculated retroactively), and in gaining a better understanding of the true success of a given time period. In addition, it should help resorts better understand and utilize the revenue-management strategies that help hotels more efficiently sell their rooms.
Though ski resorts are quite different from hotels (they have been slower to adopt advance booking strategies, historically have used fixed pricing and have season passes that hotels don’t offer), they do benefit from a variable cost structure that is essentially zero, have generally high capacity and generate high ancillary revenue (52 percent of total revenue from non-lift ticket sources, on average). This means that understanding RevPASS and using it to implement active revenue management/advance sales strategies could have a real impact on resort profitability.