Hotel Profit Discovery

A Simple and Powerful Metric that few Hotels Use

Sometimes the simplest math can deliver the most powerful analytics. When analyzing variances for revenue performance, there is one powerful metric that is easy to calculate and so easy to explain that everyone will be impressed when you use it. The Variance Analysis Components metric will let you show what portion of a variance in sales or expense is attributed to changes in occupancy and what portion is attributed to changes in price. Let’s look at an example of a variance analysis for Hotel OWL’s Q1 over last year.

Download this Excel file to follow along.


The Total Revenue for January increased by 204,145(D14) which is an increase of 11.5%(D21). The Variance Components section, however, shows that the number of rooms sold added 391,745(D18) to the increase while the decrease in ADR actually decreased revenue by 187,600(D19). Now we can tell that the strategy to lower prices has has a massive 22%(D18) impact on the revenue created by higher occupancy.


This month had the highest increase in revenue, 13.2%(E21). Here again, the Variance Components shows that most of the Revenue increase was created by the higher occupancy(E22).


In March revenue increased over the previous year by almost 10%(F21). Yet the Variance Component breakdown shows that the drop was all ADR led(F23), while the occupancy actually held steady(F22).

Q1 Total

The Variance Components section has helped to prove that while overall travel revenue increased by 3.8%(H21), all of the increase was driven by the occupancy created by sacrificing the rate.

How to Calculate Variance Components

The calculation is very simple. The idea is to hold on variable steady while calculating the change in the other. For rooms sold Component for January the formula is D7*(D6-D10). This means that we are multiplying this year’s ADR by the change in the occupancy. For the ADR Component we essentially do the opposite. The formula is D10*(D7-D11). Here we hold the occupancy steady while we get the difference in the ADR.

The beauty of this simple metric is that you can now clearly see the root cause of a variance when there are multiple contributors. By the way this calculation can be done for more than two components, but I’ll leave that for another blog.

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Robert Hernandez, Statistical Analysis and Data Mining for Revenue Growth Robert is an expert in the field of mathematical Hotel Optimization and Analytics. He has spent the last 17 years building data-driven forecasting and optimization models for companies in over 20 different industries, from tech to tourism. Robert possesses a very unique skill set including cross-disciplinary experience, advanced mathematical and analytics skills, data transformation, industry-specific knowledge and business-process improvement expertise. Robert began his career at the Walt Disney Company in Revenue Planning. Read More+


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