Hospitality data is only as good as the ratio used to calculate it. Is it better to be on PAR or on POR? We explain the differences between per-available-room and per-occupied-room bases
Data is king, but futile if you don’t know how to best interpret the numbers. Asking yourself, “What’s the best way to analyze my data?” is too broad and only adds to the confusion. A better approach is to start by setting goals for your analysis. What specific information do you want to extract from your data?
When you have a clear understanding of this, you can choose the most relevant ratios accordingly. The two most popular ways to calculate hospitality ratios are on a per-available-room (PAR) or per-occupied-room (POR) basis.
PAR Ratios
The available rooms at your property are (mostly) fixed. Ratios that are calculated against this basis are independent of property-size differences. Consequently, they ensure that no matter what your competitors’ room counts may be, the results will be comparable. For this reason, it’s an excellent way of benchmarking your operation’s ability to generate revenues, control fixed expenses and maximize flow-through and profitability.
For example, you can use a ratio like gross operating profit per available room (GOPPAR) to benchmark how much profit each of your rooms yields against a competitive set, with the certainty that this number won’t be biased by differences in size. Moreover, you can look at your base annual salaries per available room to understand the fixed component of your payroll vis-à-vis other properties in your market.
The main takeaway when looking at PAR ratios is that they remove the noise in the data caused by different room counts across properties.
POR Ratios
Conversely, the number of occupied rooms in your hotel is variable. Calculating ratios on a per-occupied-room basis isolates the data from these differences in room sales volume. Thus, you can use this calculation to benchmark your property’s variable costs.
To fully understand the difference between PAR and POR ratios, let’s use complimentary breakfast expenses as an example. The table below shows hotel A’s and B’s results on a per-available-room basis:
| Hotel A | Hotel B | |
| Comp Bkfst Exp | $10,000 | $10,500 |
| Available Rooms | 3,000 | 2,400 |
| PAR | $3.33 | $4.38 |
In this scenario, hotel A seems to be doing a better job at controlling costs than hotel B. However, this is a premature conclusion to draw, because complimentary breakfast is an expense that is driven by the volume of business. In other words, by looking at these numbers, it’s impossible to determine whether hotel B sees higher PAR expenses because it’s doing a poor job of controlling costs, or simply because it has more occupied rooms.
In order to have a clearer understanding of this, we need to look at the numbers per occupied room:
| Hotel A | Hotel B | |
| Comp Bkfst Exp | $10,000 | $10,500 |
| Occupied Rooms | 1,850 | 2,350 |
| POR | $5.41 | $4.47 |
Now that both hotels have been analyzed on a fair playing field, we can see that hotel B was actually performing better. The PAR ratios were not reliable when benchmarking complimentary breakfast expenses because they were affected by the differences in occupied rooms across properties.
This same reasoning applies to all other variable costs in the hotel, such as guest supplies, cleaning supplies and hourly payroll.
Conclusion
Ratios are the cornerstone of operational benchmarking because they provide data with context by standardizing it and ensuring its comparability. There is no right or wrong ratio when it comes to analyzing the data, but understanding the strengths and limitations of each type is key to interpreting the numbers and drawing conclusions from them. By consistently tracking their chosen ratios against a relevant competitive set, hoteliers can find opportunities to increase revenue, control costs and, ultimately, optimize the bottom line.
