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?
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