Revenue management in hotel industry teams: what strong ones do

Many hotels that struggle with pricing assume the fix is better software. Yet the gap between a strong and a weak team in revenue management in hotel industry practice usually sits somewhere else: in how many systems people check each morning, who actually makes the decisions, what leadership rewards, and whether a price is a deliberate bet or a copy of last year.

Roz Hunter and Charles Pinard, pricing consultants at Simon-Kucher, work with hotel chains and brands as well as holiday parks and cottage and villa rentals. Their experience shows any hotel how to read its own revenue team and where AI fits in.

Count the screens before you change the strategy

Before changing prices or systems, look at how the team spends its morning. When Charles starts a project, he spends one to three days on the floor with the revenue managers and counts how many systems each person opens to understand what happened overnight.

Warning signs of a team that spends its energy on data instead of decisions:

• People open eight to ten systems to see what happened to their hotels overnight.
• Revenue, management BI and finance reports tell leadership different things about the same period.
• Revenue managers keep side forecasts and spreadsheets that nobody else sees, including good ideas that are never shared.
• Building reports by hand takes so long that little time is left for pricing.

Charles sees two screens as a workable setup: one for monitoring the booking curve, revenue curve and mix, and one for the actions you take in the system. Roz adds that the real cost is headspace: reconciling reports takes the time that should go into reading trends.

Who should do the thinking in a revenue team

Revenue management is about insight, decisions and calculated risk, and it needs granular knowledge of each property and each market. The setup breaks when one person at the top takes over.

Charles describes companies where a former revenue manager rises to head of commercial or even CEO, reads the pace reports and orders prices up one week and down the next. The team on the floor then carries out instructions it already expects to reverse.

“You cannot have a company that's doing up and down like that with only one brain.”

Charles Pinard, 11:53

According to Charles, nobody enjoys this: analysts lose the meaning of their work, and the leader feels nobody else is thinking. Roz adds that it is easy to see afterwards what the price should have been, so judge decisions on the information people had at the time.

Why revenue teams play it too safe on price

What leadership comments on shapes how a team prices. Roz calls it a classic that no one gets reprimanded for selling out too soon. Good work on ADR and RevPAR rarely gets a call, while a dip in occupancy triggers questions straight away. So the team becomes safe and conservative: pushing rate brings risk and no recognition.

Charles frames the answer as trust: the team has to show that its bets are calculated and reasonable, and that a failed bet will not crash the company. Leaders also need to agree among themselves: asked whether they want revenue, margin or volume, Roz finds, they tend to answer all three.

Central or local: does the revenue manager need to know the hotel?

Both central and local models can fail. Charles has seen companies so central that one brain works for everyone, and others where two hotels in the same region never talk although both would benefit.

A distant revenue manager can miss what the data does not show. Charles recalls a hotel in Germany, managed from France, that filled up fast during an event week the team noticed too late, and a property in France, managed from the Netherlands, that missed the many bank holidays in May. Roz has also seen central teams that know every property in detail. In her view, missed events mean broken processes: alerts and reporting should catch them.

Pricing as a bet: revenue management in hotel industry practice

Smaller hotels often know their beds and facilities in detail but think less about time as part of the product. The same goes for the guest mix, which is where hotel market segmentation comes in.

“It's sometimes a bit difficult for a hotelier to understand that what you're selling is not just a room.”

Charles Pinard, 25:09

Charles mentions Caribbean hotels that hesitate to charge three times as much at Christmas as in the first week of January. Most resistance, he says, comes from operations, where the desk has to explain the price to the guest. A well trained hotel call center faces the same task on the phone.

He also observes that revenue management in hotel industry teams often means replicating last year's booking curve, or following the competition, because nobody asks questions as long as you stay aligned. The hotels that perform best, in his experience, look closely at the competition and then decide when to bet against it. Useful checks from the conversation:

• Compare like with like. A small family hotel and a hotel of 500 to 1,000 rooms are not a fair reference for each other.
• Set clear bands, for example a premium of 10% over a defined set of brands.
• Ignore public prices that nobody pays, such as rates set high so loyalty members feel their points are worth more.
• Do not open a peak period too high. Roz has seen teams price high after a big event announcement and then drop all the way down.
• Ask whether price is the problem. If you convert well and still lack demand, look at marketing or distribution, including how your rates reach partners through a hotel booking API.

One bet that worked, per Charles: a modest city hotel that held its rooms until a week before big football matches. Such bets only work when operations and frontline staff are part of the plan.

Where AI helps hotel pricing and where it hurts

For revenue management in hotel industry teams, AI is a multiplier of the strategy already in place. Roz says it can supercharge a lot, but a bad strategy just runs faster. A language model gives the most probable answer with great confidence, which is close to repeating last year or following the competition.

“I think that everyone assumes the systems and the tools will be the answer, but actually, it's how you prioritize, how you set up, how do you get that to go work.”

Roz Hunter, 76:20

She sees value in using AI to challenge your thinking and to automate reports. On one early project, a team spent the whole day building reports by hand and had about an hour left for pricing. In her view, a black box is as bad as no box, and changes still need human oversight. To hear the full discussion, watch the full conversation or explore more episodes in The Revenue Playbook series.

Frequently asked questions

What makes revenue management in hotel industry teams effective?

In the consultants' view, effective teams work from one source of truth on about two screens, share the thinking across the team instead of leaving it to one leader, get recognition for rate as well as occupancy, and set prices as calculated bets rather than copies of last year.

Why are hotel revenue teams often too conservative on price?

Nobody gets reprimanded for selling out too soon. If leadership only comments when occupancy falls short, the team learns that pushing rate brings questions and no recognition. According to Roz Hunter, teams start taking reasonable bets once good work on ADR and RevPAR is noticed too.

Should a hotel copy its competitors' prices?

Watch the competition, but do not simply copy it. Check whether a competitor has the same concept, size and segments, and ignore public prices that are never really sold. The best performers, in the consultants' experience, decide when to bet against the market.

Can AI set hotel room prices on its own?

Not in the consultants' view. AI can speed up reporting and challenge your thinking, but it gives you the most probable answer with a lot of confidence, which is close to repeating last year or following the competition. Without a clear pricing strategy it runs a bad strategy faster, so changes still need human oversight.