And the Numbers Are...

As CFO at Sugarbush, Vt., in the mid-’90s, I looked forward to receiving the “Economic Analysis of United Sates Ski Areas” (EA), put out by NSAA and RRC each summer. I looked at the EA as a valuable tool, and for some years I put a lot of effort into my resort’s input. Sharing financial information in a way that gives ski areas an idea how they are competing against their peers is very valuable.

As time marched on, I became less excited about the study’s arrival. Partly, that was because publication was moved back to August, after planning for the next year had been done, and I began to find that it wasn’t as helpful as I had expected. Perhaps I was also expecting too much from it—no economic study can raise EBITDA for you.

More recently, as I began to use the EA in my consulting business, I find that it has significant usefulness. The stratification of the data is significant. With some work on the part of the end user, the information can be used to make a meaningful comparison of your ski area against a competitive set by region, size (VTFH), and level of profitability (although this last set of data is only listed in the Appendix, and is used rarely in the discussion).

The ski area characteristics data (see chart, below) are fairly detailed and help you understand your place within that matrix. Unfortunately, not all areas can easily correlate the characteristics to the financial matrix they fit in most closely.

I don’t mean that as criticism, just as an observation. The authors are very aware of the limits and challenges they have in presenting the information in a manner that is useful to the readers. If more resorts participated, the larger data set would improve the quality of the analysis dramatically. Granted, the survey may be asking for information in a different format or categories than a resort’s financial system provides, but it’s worth the effort.


Whatever the publication date, the prior year’s report has the framework to be of value in the current year. The most obvious use is to measure yourself against the norm in your region and at your size level. But understand it has its limitations, too. If you put together a table by line item, showing your performance against the comparable norm, and present that to your management team, everyone will find reasons that the norm is not a valid comparison. And they are probably right. However, the EA may be used by financial institutions for lending or funding purposes. It is important to know where you stand in relation to the norm if you are seeking outside resources.

There are several challenges to using the EA as a measurement tool:
  • It’s heavily weighted to larger resorts—43 percent of respondents in 2012 were over 10,000 VTFH. On an overall basis, that skews the numbers and percentages. That makes the by-size and by-region information more useful for most areas. However, the study only reflects input from 116 ski areas; there are 325 ski areas in NSAA. Greater participation would improve the report’s ease of use.
  • In the detail of the profit and loss statement, which presents the findings by operational category, there is room for misinterpretation in some categories. For example, do you report a spa or health center under Lodging or Miscellaneous/Other/Property Operation? The devil is in the details.
  • Size comparisons. VTFH would be an excellent measure in a perfect world, where utilization were not a factor. A significant number of areas have long lifts, and thus more VTFH than their visit totals might suggest are needed. And size, as measured by VTFH, has costs associated with it, which may not relate to revenue. The VTFH/revenue ratio may seem negative for one resort (and imply underutilization), and positive to another, and overstate the case in each instance.
So how should size be measured? In my opinion, skier/snowboarder visits would be a better measure than VTFH. Measuring by visits would provide a better comparison for revenues by department, total revenue/visit, etc. True, some costs are associated with infrastructure such as lifts—if VTFH is higher, lift maintenance will be higher, too, and so will other lift-related costs such as insurance. But visits seem to be the standard measure in most discussion circles; very rarely does anybody refer to VTFH when talking about an area’s performance.

It would be interesting to see the EA data sorted by visits and compared to the VTFH sorting. There would be no difference in the overall data, of course, but the by-size comparisons might be more useful.

Personally, coming from the Northeast, “region” is the most meaningful breakdown for comparison purposes. In the Northeast and especially in New England, we tend to consider all areas to be within our competitive set.

Using the regional grouping, especially in the revenue section, and really knowing your market, you can get a very clear understanding as to how the competitive set is doing. As long as you are comfortable with the categories of revenue and expense, and can accurately put your financial information in alignment, you can clearly establish how you stack up.


For me, the “Average Ski Area Financial Data—Income Statement” charts (below) have always been the most useful. They allow you to better understand your sources of income and your expenses, by size and region, in one look.

They would be even more useful if these data were broken down by region and size. That would pretty much get you as close as possible to a peer comparison. But the data sets might get too small and thus threaten the idea of confidentiality.

Still, these charts are the most useful for comparison purposes. I prefer the tables with percentages rather than whole numbers, because percentages are easier to use than dollar figures.

For example, consider the case of a smaller mid-sized area (7,501 -10,000 VTFH) in the Northeast. Operating profit in 2012 for Northeastern areas was 16.8 percent. The operating profit for all areas with 7,501 – 10,000 VTFH was 25.3 percent. That’s a spread of 8.5 basis points. Given that differential, you might want to average the two, or you could weight the percentages from each column based on how many resorts are in that size range in your region.

The key is to use the data. If you have to do some additional manipulation as above, do it. The important thing is to create a benchmark. Peer comparisons are important as a metric to understand how you are performing.

I have found Balance Sheet information less useful than the Income Statement. Variations in accounting methods can distort asset and liability accounts more than the operational accounts, due to such things as inventory valuation, LIFO vs. FIFO, reserves and depreciation schedules, and more importantly, acquisitions and divestitures. Case in point: the Executive Summary reports an increase in gross fixed assets of 19.6 percent. However, there is no explanation in the report for that significant increase. It may simply be that some reporting resorts had made large acquisitions that were not in their balance sheet in the prior year. This does not invalidate the balance sheet data that is presented, but merely demonstrates the various kinds of activity that can take place within the asset and liability accounts.

I have found the balance sheet ratios helpful, and this is one area we all know the lending gurus pay close attention to. Using these ratios as monthly or quarterly benchmarks will do a lot to help avoid end of year stress.


Ultimately, the NSAA Economic Analysis is a very useful tool that all ski areas should have on the shelf and use throughout the year as a metric of their current performance. This tool can get better if you encourage your peers to participate. I am sure many who do not would cite the effort required, or concerns about confidentiality. It takes some effort, yes, but is well worth it. And my conversations with the authors have reassured me they zealously protect the confidentiality of the data.

Last but not least, all in the winter resort business should suggest improvements to RRC. They are very willing to take input and seek to continually improve the report. They work very hard on it, and that makes them especially keen to make it a benefit to all.
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