Attractions industry leaders have access to more data than ever: attendance by the hour, per cap by category, queue heat maps, sentiment tracking, conversion funnels, and the list goes on. However, the ability to make decisions seems to be getting harder.
The conflict is not data versus intuition. The conflict is how to effectively use both.
Testing the Numbers
In my experience, many projects have not succeeded because the data was never properly stress tested. There was a famous park that opened with attendance projections based on tourism growth statistics and optimistic capture rates. The reality was that within the first year of operation, the attendance was a fraction of what was forecast. The reason for the discrepancy was not the execution of the project. The reason was a flawed understanding of the market and a cost base that was designed to a reality that never existed.
Experience has shown the most common mistakes in forecasting are the simplest.
Tourism growth statistics are based on the number of visits, not the number of unique visitors. Market studies can be based on optimistic bias. The reality of the market can be misunderstood by failing to segment the data. The growth in the data can be linear, with no consideration of what happens in a downward trend.
I consider intuition a data point, but not the data itself. If the data suggests that a forecast is too optimistic or too conservative, then intuition says to test it. The art is to test the intuition to validate or invalidate the data.
Testing Different Markets
One interesting calibration exercise is to compare the same attraction concept in two different markets, one of which is a mega city of tens of millions within a one-hour trip with a large target demographic. In such a market, an attraction concept can be pushed to its limits in terms of capacity. In a mid-size metropolitan area, the ceiling will be much lower in terms of the target demographic. While the attraction concept itself may be identical in each of these markets, the markets themselves are not. While it’s tempting to borrow performance assumptions from one market to the other, it’s not ambition; it’s inaccuracy.
After establishing the market reality, performance is a result of three interrelated disciplines.
Financial Forecasting
Investment planning needs to be thorough. A feasibility study should consider downside scenarios just as much as upside scenarios. Investment needs to be properly aligned to realistic demands, including planning for reinvestment from day one.
Expense management requires a structural approach. Payroll costs, marketing, maintenance, and utilities are usually predictable in terms of industry standards. A pro forma that significantly diverges from these standards should be understood by management precisely for what reason.
Overruns in costs during the development phase are a permanent increase in the hurdle rate. Maintenance costs rapidly erode guest perception.
The best operators I have observed are neither purely analytical in their approach to running a business nor purely intuitive. This balance requires discipline, and they are those who can use data to establish a range of performance and experience to interpret what the data alone cannot tell them.
