The Ultimate Revenue Management Report
By Howard Hammerman, Ph.D.
Revenue managers have a number of tools at their disposal: They can raise or lower rates, impose or relax minimum stay restrictions, offer more or fewer room nights to OTAs for example. Most managers base their decisions on the room nights currently on the books and their best guess as to the number of room nights that will be sold between the current date and the near future.
During the past decade I have had the privilege of working with some of the best revenue and reservation managers in the North American hospitality business. Listening to their requests and responding to the best of my ability I quickly determined that accurate on the books forecasts could not be done using the raw HOST data alone. I had to combine current reservations with historical ones, correct for suites and shares and disaggregate reservation data into a table with one record per occupied unit per day. I could then compare current pace to the same date a year prior and pace to actual results. I created a FoxPro program called OccTrack and have tested it successfully in more than a dozen SMS-HOST properties.
is an example of what can be done with the resulting data. I have included the row and column tags in order to explain the data that it contains. The data are fictitious. Please remember that this is an example of the program results as of
June 7, 2003. The fictitious revenue manager is trying to understand his pace for September,2013. Columns B through E show what is on the books as of the current date (June 7, 2013 in this example) for a target month (September 2013 in this example). Columns G through J show what was
on the books as of one year prior (June 7, 2012) for the same target month a year prior. The differences between the two annual snapshots are shown in columns L through O.
Rows 6 through 15 shows the revenue and rooms breakdown by market for the current year, the prior year (as of the same date) and the differences. Row 17 in columns B through E show the revenue and room nights budgets set for the property for the current year. Row 18 columns G through J show the actual performance for the target month last year.
Looking at Line 24 we see that the property is 76 units and $10,709 below its budget for September. However line 15 columns L and M shows that it is 156 units and $3,266 overits pace when compared to the same day last year.
The big question is: How much additional business will be booked during the remaining days of June and during September? One approach to answering this is to look at last year. Last year the property gained 217 room nights and $28,295 from June 7 to September 31. By taking the final results last year and dividing them by the “as of” results for last year we get a ratio that can be used for predicting performance this year. I call this the rent up ratio. The room night ratio of 1.2364 is the result of dividing 1,135 by 918. The ADR ratio is 1.0820 ($98.74/91.26). The revenue ratio is 1.3377 ($112,070/83,775). This is shown on line 20, columns G through J.
The forecasted revenue and room nights are shown on line 21, columns B through E. First room nights were forecasted by multiplying the actual room nights on the books as of June 7 by the ratio of 1.2364 described above yielding 1,327, an increase of 253. Forecasted ADR was calculated by taking multiplying the ADR ratio times this year’s ADR ($81.04) and rounding down to the nearest dollar to yield $85.00. This was multiplied by the forecasted number of room nights to yield the forecasted revenue of $115,449 well over budget for this year and $3,379 over last year’s performance.
The variance of actual to budget, actual to forecast and forecast to last year’s actual numbers are shown in lines 24 to 26. The current forecast shows a modest gain in revenue as a result of the 17 percent increase in room nights despite a decline in ADR versus the property’s September 2012 performance. Some managers would interpret these statistics as a mandate to increase rates for the remaining unsold rooms even if it resulted in a decline in occupancy.
Lines 28 and 29 look backwards in both time periods to get a feeling for the pace of bookings in the recent past. We see that 45 percent of the current room nights were booked in the past month implying that 55 percent were booked earlier. Last year only 48 percent were booked within the past month. The same pattern holds true for bookings in the past week. This suggests that the property has been increasingly successful in getting guests to book early.
The remaining lines in the report show the statistics leading to REVPAR all based on the
current on the books numbers. Note a $3.91 increase in REVPAR versus the same date last year.
There are countless ways this report can be enhanced and customized. Instead of basing the forecast on all units, we can calculate the rent up ratio separately for each market and then apply it to the performance in each market for the current year. We can show booking gains for more or different time periods. Graphs can be introduced as well.
This example shows the numbers for one target month. Most properties organize the report so that it shows the same numbers, month by month, for the next four to six months. The properties that use the OccTrack program have come to rely on it as the best guide for judging how to allocate marketing resources and manage rates.