SELF DRIVING REVENUE MANAGEMT FACT OR FICTION?

There is a lot of talk and write about the degree of automation in Hotel Revenue Management. In this article we try to look at it holistically in order to come up with an answer that fits for everyone. The result is surprisingly simple. Please let us know your thoughts.

We at Hotelwise will be happy to advise you. Contact me on [email protected] +37255992425 or visit https://hotelwise.eu/

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SELF DRIVING REVENUE MANAGEMT- FACT OR FICTION?

TASKS OF REVENUE MANAGEMENT

What exactly does Revenue Management in a hotel include? The tasks and responsibilities of a Revenue Manager go far beyond determining the right price at the right time (which in itself requires a great deal of knowledge and experience.) The entirety of tasks of a Revenue Manager can roughly be categorized as follows:

1.???Yielding/Pricing

2.???Forecasting

3.???Optimize Distribution-Mix

4.???Optimize technology

5.???Keep data updated and coherent

6.???Rate recommendations for contracting

7.???Recommendations for geo-marketing

8.???Budgeting

9.???Communication with all stakeholders

If the question were “can Revenue Management be fully automized” I could actually stop right here without any further comment. Everyone who has been anywhere near Revenue Management will come to the conclusion, that it is impossible to have all of the above done by a machine. And I mean ever!

However…

AI-AUGMENTED REVENUE MANAGEMENT

As always it is the right mix that leads to success. AI-augmented Revenue Management, in which the human Revenue Manager uses the right tools for the right task, has become indispensable. Data has now become impossible to handle manually. The massive amount of data available -internal and external-, complex patterns, quickly changing market conditions and human error in anything done manually make automation not a nice to have but an absolute must.

That means for 2 of the above 9 mentioned tasks, machines of some kind or other are vital. (1+5). They can either be done fully automated (5) or partially (1). Some might argue that pricing can also be fully automated which is probably true if the hotel sells its entire inventory online.

As soon as contracted business comes into play and the hotel has to deal with LRAs, allotments, materialization, cancellations, wash, group requests, short release periods etc. a human brain is required to make sense of it. To state just a few examples, just because a certain tour operator had an 80% materialization of its allotment in the last year(s) does not mean it is the same this year and the machine will not be able to pick up the phone and ask the TO about the booking situation way before the release period is up (and decide on the number of overbookings accordingly) and it is notoriously difficult to determine with what certainty a business group will actually materialize and if so with how many guests and strict prepayment terms and release periods are ever more difficult to enforce and lead to a disadvantage in the bidding process.

Another pricing difficulty that systems cannot ideally solve is to determine and implement the right segmentation mix for each day of the year with corresponding stop sale recommendations to the sales team and closing of low prize rates in the system.

HUMAN OVER MACHINE

It is the remaining 7 tasks of Revenue Management where the human intelligence is irreplaceable with no AI input (or marginal in some cases at best).

The forecasting and budgeting process, if done properly, requires the input of month to month or even day to day variables into the segmentation (for room revenue). It is impossible to “feed” all these into the even most sophisticated RMS.

Technology & Distribution Mix evolve so fast that it takes a dedicated person within a large Revenue Team to stay up to date. To be aware of all the latest changes and additions in the market is a job that has to be done by a human. 100%.

For Geo Marketing & contracted rate recommendations the help of systemised data analysis is certainly helpful. However, there are so many possible interpretations to these that AI assistance can at best be called marginal.

Communication. Even in a small hotel there is a number of people who take a keen interest in the state and development of the most important KPI (revenue). When it comes to a large hotel or even a chain this number can increase to well above a dozen. The hotel team, the hotel management, the owners, asset managers, all need to be kept in the loop and given the possibility for input. AI will provide the data. The process of communication however varies from stakeholder to stakeholder and so do their questions and input. That makes it an exclusively human task.

CONCLUSION

For a small hotel that sells all of its inventory over the internet, own website or OTAs, an RMS-only solution is the best way to go. As all the necessary information is very easily available a well set up system can do the job. For any bigger hotel with a more varied business mix a human lead approach is still the only way to go. In many cases, to subscribe to an RMS can be a waste of money or even harmful. Particularly then, when the owner becomes aware that his/her new toy not only costs money to subscribe to but also results in an increase in payroll as a dedicated and qualified person is needed to attend to it. In many cases, in order to save money, that mandatory next step is not taken and the Front Office- or Reservation Manager is tasked to “handle it on the side”.