The revenue management myth: More data equals better financial performance
Op-Ed: RoomPriceGenie CEO Chas Scarantino says hotel operators need to shift their mindset from “what other data can we include?” to focusing on the signals that actually drive profitable outcomes
By Chas Scarantino, CEO of RoomPriceGenie
For years, revenue management strategies have been guided by a simple consensus: more data points lead to better pricing decisions and ultimately, more revenue.
This argument made complete sense when revenue management system (RMS) technology was in the early phases of being able to process and analyse complex data signals to improve their pricing recommendations.
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As RMS technology has evolved, solutions have improved the quality and quantity of the forward-looking data used in their algorithms, with the assumption that it would continuously improve pricing outcomes. And for a while, it did. The shift from static pricing to dynamic, data-driven decision-making fundamentally changed how hotels approached pricing and demand strategy.
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But the industry didn’t stop at enough data.
The result is that most hoteliers are now operating in environments where dashboards are fuller, forecasts are more detailed, and pricing updates happen faster than ever before. And in many cases, more isn’t helping; it often gets in the way of long-term profitability.
That’s not a data problem; it’s a prioritisation problem. And it’s not the first time that the hospitality industry has seen this pattern play out.
In recent years, the conversation has shifted toward profitability-focused metrics – instead of traditional, top-line metrics such as occupancy and RevPAR – to ensure the demand that actually drives meaningful business outcomes is prioritised.
Revenue management has always been about making trade-offs: which demand to accept, which to reject, at what price, and at what time. And over time, general managers and revenue teams have learned that not all demand is equally valuable.
High occupancy can come at the expense of margin. Distribution costs can quietly erode what looks like strong performance. Some demand segments generate volume while adding disproportionate operational strain.
We’re now at a point where the same discipline in decision-making needs to be applied to data.
If not all revenue is worth accepting, it follows that not all data is equally valuable – but the majority of the industry still behaves as if it is. When low-impact inputs are treated as meaningful, it creates the illusion of precision without increasing confidence, and pulls attention away from the data and metrics that actually drive performance.
Pricing becomes more reactive, not more strategic. Short-term fluctuations are treated with the same importance as structural demand shifts. Decisions change more frequently, but not necessarily more intelligently.
And over time, that discrepancy has negative consequences. It becomes more difficult to rationalise revenue decisions, to maintain consistency across teams, and almost impossible to replicate strategies that worked well in the past. In some cases, it can even push performance in the wrong direction.
Let’s look at an example… If a hotel’s revenue manager updates room rates reactively when a competitor offers a huge discount, the end result is that they will cannibalise the property’s own demand because the wrong data signal was prioritised.
There is an important lesson to be learned from this example: revenue management decision-making should always be made based on the overall market dynamics, and the property’s own performance, rather than blindly following competitors’ pricing.
So, I’m here today to challenge the status quo…
For success in today’s market, the hotel operator mindset needs to shift from “What other data can we include?” to “What will help us accomplish the outcomes we want to achieve (and what won’t)?”
It sounds simple, but it requires discipline to implement.
It requires the prioritisation of signals that directly influence profitable demand – rather than reacting to every fluctuation in the market – and deprioritising those that don’t. It means aligning data interpretation with the business outcomes that actually matter, rather than defaulting to legacy metrics.
Today, forward-thinking revenue leaders are already adopting this mindset and, as a result, are becoming far more selective with data.
They are asking harder questions about which signals genuinely influence profitable outcomes, which ones simply create distraction, and which should carry more weight in decision-making. They are increasingly focused on building frameworks that are consistent, explainable, and aligned with profitability to ensure that pricing decisions are driven by relevance, not just availability.
In practice, that often means stepping back from constant optimisation; instead, they focus on the signals that truly matter and build proactive strategies that are easier to execute, rather than reacting to every minor change in the market.
The goal isn’t to reduce the role of data; it’s to restore its quality and usefulness.
Because in today’s environment, a property’s competitive advantage doesn’t come from having access to more information. It comes from knowing what data to trust, and having the discipline to question the rest.
In a highly dynamic marketplace, clarity – not volume – is what ultimately drives performance.
As such, the best strategic revenue management decision you will make all year will be which data you choose to prioritise and which you choose to ignore.
Here’s where you should start…
Audit your data inputs against your actual pricing decisions
Pick three recent rate changes and trace them back to their triggers. Were they driven by your own pick-up pace, demand shifts, or a competitor discount? If competitor moves are consistently steering your decisions, the wrong data is being used to make pricing decisions. For groups and chains, run this same audit at brand level, because what looks like destination-specific market behaviour, can often be a system-wide reactive pricing habit in disguise.
Define your “primary signals” in writing
Agree on the two or three data points that most consistently correlate with profitable outcomes; pick-up pace against forecast, length-of-stay patterns, and segment mix are strong starting points. Once defined, use them as your decision-making filter: if a signal isn’t on the list, it shouldn’t be the catalyst for a rate change. For multi-property operators, it’s important that they’re interpreted consistently across properties so pricing decisions are comparable and strategies are scalable.
Integrate profitability metrics into your strategy
Integrating profitability metrics – such as GOPPAR or net RevPAR – will identify demand that looks strong but erodes margin through distribution costs or operational load. For chains, this is most powerful done comparatively between properties because the same occupancy across two similar properties can tell very different profitability stories.
Schedule a monthly data audit
Review the data sources your team engaged with most frequently each month to identify which signals informed a decision that improved outcomes, and which prompted a reaction with negative results. Use that distinction to continuously refine your primary signals list to amplify what is working and eliminate what isn’t. For multi-property operators, a monthly data audit also flags where individual properties are shifting off-strategy and creates a natural touchpoint for tightening decision-making frameworks across the portfolio.
None of these steps require a complete overhaul of how you work but, as a whole, they will fundamentally sharpen your approach to pricing.
Get this right and you won’t just make better pricing decisions; you’ll make decisions that are actually reflected in your bottom line.
Author: Chas Scarantino – CEO of RoomPriceGenie
Chas Scarantino is the CEO of RoomPriceGenie, where he leads the company’s mission to make sophisticated revenue management accessible to independent hotels and groups worldwide.
A SaaS executive with experience scaling technology companies across five continents, he is passionate about building teams that turn complex challenges into simple, powerful solutions for customers.
