Hotel Profit Discovery

50 Questions for the Hotel Revenue Manager of 2027

Since 2004, the Hotel Revenue Management function has exploded into a mainstream profession.  In just over a decade, however, the “honeymoon” phase with Hotel Revenue Management has ended.  As channel management technology has improved and become more standardized, the Revenue Manager’s time has been freed from some of the clerical demands of rate distribution and the focus of their jobs has shifted to the justifying the incremental value added by the RM department. As a result, more pressure will be placed on RMs to “deliver the goods” in generating more Revenue.  We are already seeing the impact of this new expectation in the increasing turnover of RMs in some highly competitive markets.

In the next decade, this RM transition from “Revenue Management” to “Profit Engineering” will mean that Marketing, Sales, Finance and RM will synthesize into one function that is responsible for helping hotel companies grow continuously, even within highly uncertain market conditions.  The Revenue Manager in 2026 will need to have a breadth and scope that is far reaching.  Whereas today the vast majority of RM professionals have a reservations or front desk background, in a decade they will have to be results-driven professionals with strong math and analytical acumen who understand the hotel business and also have the ability to effectively communicate their knowledge to other departments and senior leaders.  Many “black-box” software vendors will come and go in the attempt to fill this coming  RM “talent” crisis, while the truly prepared RM, who can develop customized approaches to addressing property-specific challenges will only see their value skyrocket.

Here is just a sample of the types of questions that The Revenue Manager of 2027 will be expected to answer.

Analytics Strategy

Which Analytics tool is most applicable to solve a particular RM problem?

Can a problem which affects profit be solved mathematically or predictively?

How can I formulate a specific challenge into a research question?

Data and Granularity

Can I access all the data that is needed for good decision making?

How reliable and complete is the data used to solve RM challenges?

Can I extract the data at the most granular level?

Do I have the tools necessary to summarize and aggregate the data?

How much real-time data do I need?

Are we looking at a “Big” Data or “Small” Data problem?

Choice and Demand

What are the variables that truly affect demand?

What are the hidden demand patterns that affect profit?

What are the managerial decisions that can impact demand?

What changes can be implemented that will impact demand?


What are the most relevant measures of performance?

How many metrics do I need to accurately assess performance?

How has the business changed over time?

Can we conduct a controlled experiment before we commit resources to this revenue challenge?

Probability and Uncertainty

How predictive is our demand?

What are the most likely outcomes of an RM decision?

How can I analyze seemingly random events e.g. no shows?

Total Revenue Drivers

How do RM decisions impact revenue and profit throughout the hotel e.g. F&B, Spa, Golf and Ancillary?

What are the marketing actions that affect demand?


Have the demand patterns changed significantly?

What is the likely demand given a certain rate offering?

What ADR and RevPAR can I expect?

What is the demand pattern by market, source, room type, rate type, guest type and event?

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What is the combination of rate changes that will give us the most Total Profit?

What is the best rate strategy to re-position my hotel(s)?

What rate should I offer a specific group?

What channel should I close? When and what type of marketing offers are needed to drive demand?

Customized Modeling

How can I leverage technology and math to make the thousands of RM decisions I have to make every day?

How do I automate recurring decisions that are specific to my hotel’s unique RM strategy, e.g. free upgrades?

Which data mining algorithm is best suited to address a particular challenge?

Market Forces

How do my competitors’ decisions affect my demand?  

What uncontrollable forces have a significant impact on demand, e.g. weather, exchange rate?

What is the RM strategy for catastrophic events?

Guest Segmentation

What are the most significant guest behavioral segments?

What rates, offers and rewards should I extend to my loyal guests?

How do I score a guest who is not part of my loyalty program?

What are the promotions that appeal to the most desired guest?

Decision Biases

What are the myths that drive RM decisions in my hotel?

What gut decisions should be replaced with modeling?

What are the blind spots in our RM intelligence?

What business knowledge is no longer applicable or true?

Rhythm of Business

Is this a more a Pricing problem or a Marketing problem?

When is applying the ‘art’ of business more appropriate than number crunching?

What do I know about my hotel(s) that the model doesn’t know?

Communications and RM Culture

What is the most effective way to spread RM Thinking throughout the hotel?

How do I push RM techniques through other departments?

How do I communicate RM strategies and initiatives to my senior executives so as to instill an authentic RM culture and further drive profitability?

The more of these questions that you are trying to answer today, the higher the chance that you will be positioned for RM success in the coming decade.

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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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