Hospitality Revenue Analytics

Tackling the Tall Tale of Total Revenue Management

Early last year, Dan Ariely, a professor and director of the Center for Advanced Hindsight at Duke University, compared Big Data to teenage sex for several funny reasons. I took his quote and modified it for the hotel business by replacing ‘Big Data’ with ‘Total Revenue Management.’

Total Revenue Management is like teenage sex:
everyone talks about it,
nobody really knows how to do it,
everyone thinks everyone else is doing it,
so everyone claims they are doing it…

Why is there such a disconnect between the volume of conversation(articles/blogs) about Total Revenue Management(TRM) and the actual use of it? The answer is in the math.

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First, let’s define what TRM is and what it is not.  There is a common misconception that Total Revenue Management is the application of revenue management concepts to revenue streams other than rooms, such as F&B, Spa, Golf, etc that make up the total hotel revenue. Based on this definition you could conceivably have the Revenue Manager set prices and discount tiers for each outlet or service.  Better yet, in larger hotel companies you could have a separate RM for each line of business.  Imagine a Rooms Revenue Manager and an F&B Revenue Manager, like you now have a Rooms Controller and and F&B Controller at many properties.  Each manager would look for opportunities to manipulate pricing in order to find the most profitable balance between demand and capacity utilization (i.e. occupancy).  Each line of business could also have their own Revenue Management System and they could have competitor’s price shopping tools or even their own “STAR” report. Furthermore, instead of having a Rooms Comp Set, you could also have a Restaurant and Spa comp set.  Imagine comparing Revenue Per Available Seat to benchmark your hotel’s main restaurant versus your competition.  Sounds brilliant, except for one thing – that is not Total Revenue Management.

True Total Revenue Management IS about unleashing the power of RM on all revenue streams, but it is also about designing pricing strategies that optimize the total performance of the hotel even if that means that some of the revenue streams are not optimized. Let me say that again, EVEN IF THAT MEANS THAT SOME OF THE REVENUE STREAMS ARE NOT OPTIMIZED. Let’s take the easiest example to explain – the casino guest. Smart casinos care about each guests total spend, and thus they regularly comp room nights to hotel guests that spend heavily on gaming and outlets.  These casinos sacrifice rooms profit for total profit.  This is Total Revenue Management, when the interconnected relationships across revenue streams is considered simultaneously in order to create a bundle of prices that optimizes the hotel’s total bottom line.  In other words, Total Revenue Management is not about looking at each line of business individually, but as a collective package of experiences to forecast and optimally price.

This is Total Revenue Management, when the interconnected relationships across revenue streams is considered simultaneously in order to create a bundle of prices that optimizes the hotel’s total bottom line. 

This vision of Total Revenue Management  is a lot more challenging to achieve than the first, which is part of the reason why we have not seen it widely deployed yet.  For one thing, most revenue center managers are conditioned to think about the performance of their “silo” rather than think about the entire hotel performance.  You can’t blame them, hotel performance bonuses are based  on the individual performance of each department.  Imagine asking the Spa Director at your property to accept a 10% price decrease on all services because the numbers prove that it would increase total guest profit.  I have been part of those conversations and they are not pretty.

The second definition of TRM also requires more complex math, it can not be done with simple arithmetic.  Analyzing supply and demand for rooms is considerably less complex than analyzing multiple revenue streams simultaneously. To achieve true Total Revenue Management, you need to follow and value your guests footsteps throughout their stay. This type of analysis begins by digging into the behavior of past guests and this is where things get complicated. Modelling Total Revenue Management  requires advanced data mining algorithms with a layer of optimization mathematics on top. At a minimum, you will need to use Market Basket analysis and Decision Trees allow you to paint a 360 degree picture of every footstep your guests are likely to take. Learn more about these techniques here.

Upgrading the mathematical approach to Total Revenue Management allows hotel managers to shift from Per Available Room measures to Per Available Customer measures.  Only by moving to a customer-centered set of measures, where the overall guest spend is more important than the spend in any single outlet can you begin to embark of the path to Total Revenue Management.

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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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