The Easy Ride Is Over for Many Revenue Managers

Let me say it upfront, because hiding the idea behind ten polite paragraphs would take away much of its meaning: many Revenue Managers are about to see the good times come to an end.

Not Revenue Management.

Not good professionals.

Nor the need to manage price, inventory and demand.

What is coming to an end is a particular way of practising the profession: looking at pickup, reviewing pace, comparing rates, updating a forecast, opening or closing discounts, changing BAR and then arriving at a meeting to explain what has just happened.

For years, this had enormous value because there was scarcity. Few people could bring together all that information, interpret it quickly enough and turn it into commercial decisions. Those who mastered that data enjoyed a clear advantage within the hotel.

Artificial Intelligence is rapidly reducing that scarcity.

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And when a capability is no longer scarce, its value changes.

A machine can analyse historical demand, OTB, pickup, booking curves, cancellations, elasticity, channels, competitors, events, length of stay, guest behaviour and hundreds of additional signals simultaneously. It can recalculate a decision whenever any of them changes. It can do so every hour. Every minute, if necessary.

It does not have bad Mondays.

It does not need to wait for the weekly Revenue meeting.

It does not get tired after reviewing the fifth Excel spreadsheet.

And it does not need to prove that the decision it made yesterday was correct.

That is why the question I find truly interesting is no longer whether Artificial Intelligence is going to enter Revenue Management.

It already has.

The question is another one:

What will the Revenue Manager do when the machine does much of the work we have paid them to do until now better than they can?

For many years, the Revenue Manager has held a peculiar position within the hotel. It was a specialist role, with privileged access to information that much of the organisation did not handle. They understood patterns, anticipated demand and decided when to raise, lower, open, close or restrict.

In many meetings, they also appeared with spreadsheets that, to the rest of us mortals, seemed to be written in Sanskrit.

That reinforced a certain authority.

But I am afraid Sanskrit is starting to translate itself.

I do not write this to belittle a profession I consider essential. Quite the opposite. I have worked with Revenue for years and have seen the enormous value it brings when it is properly understood.

That is precisely why I believe we need to separate two things:

the importance of Revenue Management and the need for certain tasks to be performed manually by a person.

They are not the same thing.

And we have probably confused them for far too long.

The most automatable part of Revenue is precisely what takes up too many hours

Let us do a simple exercise.

Let us consider what still consumes a considerable part of many Revenue Managers’ working day:

• reviewing occupancy and OTB;
• analysing pickup;
• comparing pace;
• studying booking curves;
• monitoring competitors’ rates;
• identifying hot dates;
• reviewing cancellations;
• opening or closing discounts;
• changing BAR;
• introducing restrictions;
• controlling minimum stays;
• updating forecasts;
• reviewing segments and channels;
• preparing reports;
• comparing ADR and RevPAR;
• explaining variances in meetings.

I am not saying it is simple work.

I am saying something far more uncomfortable:

a huge part of it is automatable.

Current systems can already identify patterns, process information from multiple sources and continuously recommend or execute pricing decisions. And the evolution of the sector is progressively shifting the Revenue Manager’s role from manual execution towards commercial strategy.

We can debate whether it will happen in three, five or seven years.

What truly matters is not getting the date right.

It is understanding the direction.

Because a profession does not need to disappear to undergo radical transformation.

It is enough that we can do with one person what we previously needed three people to do.

That is called productivity.

And it has consequences.

Clusters will become larger.

One person will be able to oversee more properties.

Certain tasks will disappear.

Some positions will not be replaced.

And those who remain will have to justify their value elsewhere.

There is no need to dramatise it.

But pretending it will not happen does not help either.

For years, we have repeated a reassuring phrase:

“Technology will allow Revenue Managers to leave repetitive tasks behind and devote more time to strategy.”

Perfect.

Now comes the uncomfortable question:

are they really devoting that time to strategy?

Because if we automate four hours of work only to spend the next four manually checking that the machine has done what we expected, we have not transformed very much.

We have merely created a new way of supervising the old.

AI should not enable the Revenue Manager to do the same work faster.

It should force us to ask which part of that work still deserves to be done by a person.

This is where one of the profession’s greatest risks emerges.

The Revenue Manager whose value depended on having information is losing their advantage.

The one who stood out primarily for calculating is as well.

The one who added value by detecting patterns now faces a machine capable of detecting many more.

And the one who mainly changes rates is working directly in one of the areas most exposed to automation.

That does not mean experience will cease to matter.

It means we will have to use it differently.

For years, we have elevated the Revenue Manager’s intuition to almost mystical status.

“That weekend will come in.”

“This market books late.”

“We will not sell at this price.”

“We have to take the group.”

“We are too expensive.”

“The competition has just dropped.”

We have all heard those phrases.

And many times, whoever says them is right.

Experience develops extraordinarily valuable mental patterns.

But we also have biases.

We remember our correct predictions particularly well.

The wrong ones tend to have a much shorter corporate life.

We cling to a forecast because it was ours.

We seek information that confirms our hypothesis.

Empty rooms make us uncomfortable.

We react emotionally to certain competitive movements.

And we can end up confusing judgement with habit.

AI is not infallible either.

It can work with poor data.

It can use the wrong model.

It can misinterpret an anomaly.

And, above all, it can brilliantly optimise the wrong objective.

But it has one important advantage:

it can learn from a volume of decisions that no professional can store mentally.

That is where the conversation changes.

The Revenue Manager of the future will not have to prove they can calculate better than a machine.

They will have to prove that they know what we should calculate and why.

The Revenue Manager who only knows Revenue has a problem

This, for me, is the real transformation.

The future is not about becoming an even faster Revenue Manager.

It is about ceasing to be only a Revenue Manager.

For too long, we have treated Revenue, marketing, sales, distribution, operations and finance as related but separate territories.

Each has its data.

Its meetings.

Its tools.

Its KPIs.

And sometimes its own priorities.

The guest, naturally, knows nothing about any of this.

Neither does the P&L.

A hotel operates as a system.

And the Revenue Manager of the future will have to understand it that way.

For years, the fundamental question was:

What price should we sell this room for?

That question is starting to become too narrow.

Now we need to answer:

What business should the hotel accept?

That means understanding much more than price.

It means knowing how much it costs to acquire a booking.

Which channel generates it.

What demand it displaces.

What length of stay it blocks.

What operational costs it creates.

What ancillary spend it may generate.

What impact it has on positioning.

What value that guest has throughout their entire relationship with the hotel.

And, ultimately, what contribution it leaves.

That is why the evolution seems quite clear to me:

Yield Management → Revenue Management → Total Revenue Management → Profit Management → Commercial Intelligence

The final stage is especially important.

Because a guest is not a room.

They sleep, of course.

But they may also have breakfast.

Dinner.

A drink.

Park.

Use the spa.

Buy an experience.

Host an event.

Return.

Book direct next time.

Recommend us.

Or become a corporate client.

If we continue to view them exclusively as Room Revenue, we are analysing only part of their value.

The Revenue Manager of the future will have to understand that whole picture.

And they will also have to understand something we have treated too distantly for years:

profit.

We can improve RevPAR and worsen profitability.

We can sell more rooms and generate less margin.

We can accept an apparently fantastic booking whose acquisition cost makes it mediocre.

We can fill the hotel and create operational pressure that ends up generating overtime, incidents and a poorer reputation.

That shift in perspective changes the questions asked in a meeting.

From:

“What price should we set?”

to:

“What mix of demand generates the greatest contribution?”

From:

“How do we achieve higher occupancy?”

to:

“What occupancy level produces the best result?”

From:

“Do we accept the group?”

to:

“What demand does it displace and what is its net contribution?”

From:

“What is the competition doing?”

to:

“Why should our strategy automatically depend on it?”

From:

“How much revenue are we generating?”

to:

“How much of that revenue are we converting into profit?”

This is where a different kind of professional begins to emerge.

A professional who needs to understand finance.

Marketing.

Distribution.

Sales.

Operations.

Customer Experience.

Costs.

Segmentation.

Product.

Positioning.

And strategy.

They do not need to become the greatest specialist in every discipline.

But they must stop replying:

“That is not Revenue.”

Because the future of Revenue probably lies precisely beyond the boundaries we have used to define it for years.

They will also have to learn something even more difficult:

to work with an Artificial Intelligence that, in certain areas, will know more than they do.

Not use it occasionally.

Work with it.

Understand what information it processes.

What signals it uses.

What objective it pursues.

What constraints it has.

When we should introduce an exception.

When we should let it work.

And when a decision needs human context that is still not properly represented in the data.

The latter will be especially interesting.

Imagine that the system recommends €247 and our intuition says €229.

What do we do?

Until now, we could change the rate and move on.

In the future, the question will be more uncomfortable:

why do we believe we know better?

We may have an excellent reason.

An event the system does not know about.

A refurbishment.

A product issue.

A commercial circumstance.

An inventory change.

Perfect.

We intervene.

But it may also be that our only explanation is:

“It seems too expensive to me.”

That will no longer be enough.

The Revenue Manager of the future will have to distinguish between professional judgement and emotional interference.

And we may be able to measure it.

We will be able to compare:

what happened when the person intervened,

against what would have happened had we kept the automated decision.

That will turn much of our intuition into something it has not always been until now:

auditable.

It may be uncomfortable.

But it will also be extraordinarily healthy.

Because we will discover where human knowledge truly adds value.

And where we were simply used to intervening.

AI will not end Revenue Management; it will end part of its ritual

There is something about this transformation that I find especially interesting.

For years, there was a fairly recognisable ritual.

The Revenue Manager arrived at the meeting.

Shared their screen.

Opened the report.

Commented on pickup.

Compared it with the previous year.

Explained pace.

Pointed out several dates.

Showed the competition.

Proposed a few moves.

And we all nodded solemnly.

I am not saying that meeting had no value.

I am saying that part of the knowledge that justified that ritual can now be available before anyone enters the room.

If we all already know what changed, why it changed, what scenarios exist and what the system recommends, spending forty minutes describing the data will make less and less sense.

The meeting can begin where it used to end.

With:

“What do we do?”

That is fantastic.

But it also raises the professional bar enormously.

Because describing data is much easier than making strategic decisions.

The professional who navigates this evolution successfully will not be the one who knows the most reports.

It will be the one who can connect the consequences of a decision.

A price reduction can increase conversion.

But it can also alter positioning.

Change the guest mix.

Modify acquisition cost.

Increase operational pressure.

Cannibalise future sales.

Impact profitability.

And teach the market to expect the same discount next time.

The machine can analyse many of those variables.

But strategy still requires a much broader view of the business.

That is where the opportunity lies.

Because while certain tasks lose value, others gain it.

I would distinguish four profiles:

• Revenue Manager 1.0 — The operator. Reviews reports, changes rates, opens and closes inventory, and updates forecasts. This is the profile most exposed to automation.
• Revenue Manager 2.0 — The analyst. Understands distribution, segments, demand patterns and booking behaviour. They add more value, although many of their analytical capabilities will be amplified by AI.
• Revenue Manager 3.0 — The commercial strategist. Integrates Revenue, distribution, marketing, sales, product and positioning.
• Revenue Manager 4.0 — The profitability strategist. Does not optimise rooms. Optimises the business. Understands acquisition cost, contribution, TRevPAR, GOPPAR, operational capacity and total guest value.

Perhaps in a few years we will still call this person a Revenue Manager.

Perhaps not.

It may end up being Commercial Strategist, Profit Manager, Director of Commercial Strategy or any other name we invent.

That matters very little to me.

What matters is that the content of the role will be different.

There will also be another consequence that I consider positive.

AI can democratise Revenue Management.

A small independent hotel cannot always afford to bring in a highly specialised professional.

Automation can give it access to pricing, forecasting and analytical capabilities that, a few years ago, were reserved for companies with far larger structures.

That will make it possible to do better Revenue in a great many properties.

But it will inevitably also reduce the value of certain professional tasks.

Both things are true at the same time.

And we should not be afraid to say so.

The claim that “AI will not eliminate jobs; it will only help people” seems far too comfortable to me.

AI will help many people.

It will transform many jobs.

It will create some new ones.

And it will make others unnecessary.

That is exactly what happens when productivity increases significantly.

A global h2c study found that many hoteliers see AI as an opportunity to free teams from repetitive tasks and devote more time to strategic functions.

I agree.

But that contains a condition we sometimes forget.

You have to be able to provide strategic value when the repetitive task disappears.

That is the real test.

That is why I deliberately use the expression “the good times are ending”.

Not because Revenue Managers work little.

I know many who work extremely hard.

The good times were something else:

being able to keep performing exactly the same tasks for years and assume they would continue to hold the same value because they had always been necessary.

That privilege is ending.

And not only for Revenue.

Also for those of us who run hotels.

For marketing.

Reservations.

Administration.

Consulting.

And virtually any information-intensive function.

AI is reducing the value of having answers.

And increasing the value of asking good questions.

That change strikes me as profoundly relevant to Revenue Management.

Because a machine can find the price that maximises a mathematical function.

But first, someone has to decide:

what is worth maximising.

If we ask it for occupancy, it will optimise occupancy.

Perhaps too cheaply.

If we ask it for ADR, it may protect price by sacrificing profitable demand.

If we ask it for RevPAR, it may ignore certain costs.

If we ask it for GOP, it may find economically efficient solutions that damage long-term positioning.

That is why the great challenge of the next stage will not simply be having better algorithms.

It will be defining better objectives.

That is management.

That is strategy.

And that can make the new Revenue Manager an even more important figure than the current one.

But different.

Much more demanding.

And probably fewer in number.

If you work in Revenue, my first piece of advice would be to do something quite simple and perhaps unpleasant: analyse for one week where you actually spend your hours. Separate every task into those that require genuine professional judgement and those that gather, reorganise, compare or process information. If a large part of your day belongs to the second group, do not wait for someone else to automate your work. Automate it yourself and use the time freed up to occupy the strategic ground that will come next.

The second would be to deliberately expand your territory. Learn finance, marketing, sales, distribution, operations and strategy. Understand a P&L. Understand acquisition cost. Learn why a decision that looks excellent for RevPAR can be mediocre for GOPPAR. And understand how a pricing decision made today can become a guest experience problem thirty days later. The Revenue Manager who only knows how to talk about Revenue will have fewer and fewer relevant conversations within the hotel.

And the third may be the most important: do not compete against Artificial Intelligence by doing what it can do better. Do not try to process more data, control more rates or work longer hours than an algorithm. It is an absurd competition. Use it. Govern its decisions. Challenge its objectives. Provide context. Connect departments. Think in scenarios. Turn information into strategy and strategy into profitability. Because the Revenue Manager will not become an endangered species because AI knows how to set prices. They will become an endangered species if, when AI learns to do it better, they still believe that setting prices was their job.