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Are You Investing in a Future-Proof Revenue Management System?

Don’t invest in a simple decision support tool just because it is easier to understand. There are significant benefits to implementing a decision management based tool.
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For hoteliers considering a revenue management system (RMS) investment—or reevaluating their current revenue technology—it’s important to fully understand your RMS options. Of course, each system comes with its own range of integrations, features, and visualizations, but a key differentiator is whether an RMS delivers decision management or decision support.

There’s a misconception in some corners of the hospitality industry that a decision-management RMS is too complicated to fully understand. Prospective RMS buyers may opt instead for what they believe to be a “simpler” decision-support tool because they can see how it works and manipulate it to their liking. But if people only used technology they fully understood, how many would drive cars or cook with microwave ovens?

A decision-support system relies on a rules-based approach to dynamic pricing. While perhaps an effective method for some master users, this technology requires regular manual intervention and will be difficult to navigate and maintain as market conditions shift—and especially as staffing changeover occurs.

Decision support can help provide analytics to aid infrequent strategic decision-making, but let’s not forget all the tactical decisions that also need to be made every minute of every day. How can one human—or team for that matter—handle it all without the intelligent automation that decision management provides?

For instance, a revenue manager can’t possibly determine a property’s true unconstrained demand at all times at any given moment. At a 400 room hotel, for example, the unconstrained demand could be 450 or it could be 600, but only a science-based, decision-management RMS can understand the fluctuating opportunity cost, day by day and moment by moment, and select the right rate at the right time.

Pricing Tools vs. Revenue Science

It may in fact be more appropriate to label a decision-support solution as a pricing tool rather than a full RMS. Many hotels rely on pricing tools to vary room rates and yield in order to grow revenue. Though these systems can provide information via reports and support rate changes, they are still largely reactionary, rules-based in nature, and are unable to process big data or provide deep analytics. Users must review and upload recommendations manually, or via automated rules, creating a higher risk for human error.

Alternatively, a decision-management RMS breaks down big data to deliver accurate and actionable data-driven insights and decision empowerment every step of the way. It also acts as a central solution in the overall technology ecosystem with data flowing between all tools to unlock more profitable opportunities across all revenue streams. It can handle heavy loads of operational and tactical decisions while also providing the data-driven support humans need to make the bigger decisions. In other words, a true RMS covers the full decision-making spectrum, from strategic decision support to automated decision management.

A Solution for the Age of Uncertainty

In the wake of the pandemic and the ensuing disruption, some in the industry have questioned the current value of the RMS. But this is a misguided notion as today’s sophisticated solutions are not burdened by the need for high demand or historical data to optimize revenue.

A decision-management RMS will optimally price all products, fold in cost and profitability, and do so on autopilot if needed. These advancements in technology actually help a hotel squeeze out revenue even (and especially) in times of the greatest uncertainty. The higher the degree of uncertainty, the higher the need for robust, accurate, and relevant data to back up decisions.

Smart forecasting, pricing, and analytics technology will always have the upper hand against a human seeking to manually make sense of things—there’s just too much data and too little time. Hotels can’t maximize profitability by managing rates alone, and a decision-support pricing tool will inevitably leave money on the table.

True Room-Type Pricing

In addition to an analytically-derived pricing strategy, hotels need to consider the varying products or room types they have. With unique demand for room types, a solid revenue strategy needs to support a customer’s buying behavior. An advanced RMS should have the capability to analytically determine the ideal price and rate availability for each different room type.

Some revenue technology vendors may claim to do this, but often only provide the ability to manually set rate differentials on each room type. Even using rules, this means you provide all the insightful data but still have to set rates yourself. With revenue managers already responsible for setting so many other rates as it is—and across multiple properties in many cases—they should be able to rely on their RMS to automatically and analytically handle this component for them.

Decisions, Decisions

Pandemic or no pandemic, revenue management’s ultimate goal is to price perishable inventory that results in the most overall revenue and profitability. The challenge facing revenue managers trying to do this manually, or with limited technology, is pricing different inventory types, through different channels, across different days, to different types of guests.

With a range of automated revenue management solutions and pricing tools on the market to consider, it comes down to rules-based, decision-support tools that provide recommendations versus analytics-based, decision-management solutions that automatically produce powerful decisions that manage pricing, rate availability, and more.

Pricing tools are certainly a step above spreadsheets but require time and effort to manage the rules and approve the recommendations. Investing in an automated, decision-making RMS will empower your hotel to enhance revenue with greater efficiency, long-term stability, and exponential growth.

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