Optimization
Data Analytics

The Myth of Real-Time Revenue Optimization

By , Senior Account Executive

Behold the power of true optimization.

Different revenue management systems (RMS) use a variety of approaches to revenue optimization. Oftentimes terms are used interchangeably like “revenue optimization” and “real-time optimization” or “revenue management” and “price optimization.” What these terms actually mean—and how they relate to the needs of your organization—is important to understand.

The first component, optimization, revolves around data. Generally speaking, various amounts of data are sent and/or received from the primary reservations system—a property management system (PMS) or central reservations system, for instance—to your RMS with varying frequencies.

  • At IDeaS we work with partners to collect data, down to the reservation level. This data is often collected or received at the time when the reservation is created, modified or cancelled in the PMS. 

Secondly, you should understand how the RMS uses this data within the solution. Displaying data in reports and dashboards is great; however, if this is when the data is updated, the dependency is on the user to make sense of the data and put it to use. In other words, many RMS solutions update descriptive reports in near real-time, but the user must determine when and how to react to changes. Ideally, you’ll want to be confident your RMS makes the best use of data in a predictive, and not just descriptive, fashion (e.g., it’s used to understand and manage the demand and pricing for all segments).

  • At IDeaS, the collected data is used in each optimization, which aligns with peak booking windows. As the RMS already predicts booking activity within the business day, additional data across the day is used to proactively react to any unexpected changes in booking activity or demand. The RMS will react to those changes appropriately and update all controls to avoid any loss of revenue opportunity.

Thirdly, you may want to consider what data is being used within the optimizations. If this is just PMS data, consider at what level this data is actually used. It is also important to understand what additional data sources are incorporated and how.

  • IDeaS incorporates competitive and market data (rates, demand, reputation) directly into optimization, to ensure the RMS’ controls remain optimal and adapt to market and target property changes. These data sources are utilized optimally, rather than relying on user rules to determine how to react to changes in business conditions, which is often the case in many solutions on the market.

And finally, an important factor is how an RMS copes with shifts in demand. Other RMS solutions consider optimization differently, with an approach that looks only at price and changes rates based on a set of pre-configured rules should the number of bookings suddenly increase. Users may trigger an “optimization” which will, in essence, likely just re-run the rules.

This approach is overly simplistic for most businesses. The drawback being the prices and any other solution controls are not truly optimized in relation to the total demand of all types of customers. Instead, it drives the price up for a proportion of the customers, or drives up all inventory-type prices based on demand for the base inventory type and product, without considering relative demand and price sensitivity.

  • As a science-based company, IDeaS utilizes advanced analytics and machine learning to preempt and dynamically adjust to observed shifts in demand. The RMS applies relevant updates to dynamic controls to manage demand between optimizations while aligning with peak booking activity times and market fluctuations.

When identifying which approach works best for your business, consider where your teams should invest their time. Do you want your people constantly analyzing descriptive data and driving prices up based on pre-defined rules? Or are your teams better served by reviewing large changes from automated, dynamic revenue optimizations that use deep machine learning to understand the patterns in your business and achieve the optimal business mix?

  • As the market leader, IDeaS provides advanced automation where users trust sophisticated analytics to maximize profitability and productivity by optimizing business mix, capacity use and pricing.
Rachel Stanley
Latest posts by Rachel Stanley (see all)
Senior Account Executive

Rachel Stanley joined IDeaS in 2017, bringing with her nearly 20 years of experience in resort revenue management, IT, and systems expertise. She previously led sales and revenue teams as they delivered best-in-class client experiences. Rachel holds a BA in Hospitality Management from the University of Portsmouth.

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