Today, a state-of-the-art hotel revenue management solution is capable of generating tens of thousands of optimal pricing decisions on a daily basis. There is reason to believe that capabilities will get even better as the analytics continue to evolve.
NB: This is an article by Jeff Zabin at Starfleet
In fact, according to research conducted for The 2018 Smart Decision Guide to Hospitality Revenue Management (now available for complimentary download), more than half (53 percent) of today’s hotel operators believe that revenue management will become increasingly automated with further advances in data analytics capabilities.
How can a hotel operator be assured that the solution they implement will best meet the needs of the hotel and enable revenue managers to achieve optimal results?
The following are just a couple considerations for hotel operators to keep in mind as they compile their checklist of need-to-have and nice-to-have capabilities.
Technology interoperability and data integration
Hotel operators today can gain a deep, unprecedented understanding of their guests —who they are, what they do, what their preferences are, and how much they spend across the property. Combining the platform capabilities of a next-generation property management system (PMS) and an advanced revenue management solution, hotels can automate decision-making processes in ways that can make a world of difference in terms of pricing and inventory management.
Technology integration is key to revenue management success. The PMS, the central reservations system (CRS) or channel manager, and the revenue management solution all need to seamlessly connect and share data —preferably, in a real-time manner. Inventory-related data needs to flow into all distribution channels, including direct booking platforms and call centers, as well as the global distribution system (GDS) and OTAs. The CRS needs to publish optimal pricing decisions and channel recommendations based on input from the revenue management system.
In short, no revenue management solution can be treated as a standalone application. It needs to seamlessly integrate with multiple data streams. It needs to integrate with marketing, sales and distribution systems as well as with OTAs and other third-party channels. Internally, point of sale (POS) data needs to integrate with PMS data to provide a holistic view of a guest’s stay, including their ancillary spending on food and beverages, guest services, spa visits, etc.
Buyers need to know that all technology components and data sources are compatible with the solution and also that all historical PMS data can be readily extracted and validated.
Cloud computing data processing power
Advances in data processing power, largely enabled by the rapid growth of cloud computing, are enabling solution providers to develop capabilities that revenue managers have been striving towards for more than a decade. Advanced revenue management solutions are capable of processing increasingly large volumes of data, and faster than ever.
With the advent of a next-generation hospitality platform built for the cloud, the grand movement to unify the disparate and fragmented technologies and data silos has become an achievable goal. Hotels can connect and seamlessly share data in the cloud across all parts of the property or properties and across all of the various hospitality solutions. For a large property, the totality of the data set may include dozens of guest segments, a dozen or more room types, several years of historical booking and reservations data, and upwards of a dozen length-of-stay buckets.
Advanced processing power makes it possible to include real-time integration of customer lifetime value (CLV) into pricing and availability, modeling consumer behavior from click-stream data, and integrating loyalty and total property spend data. Add to the mix competitive rate data, demand data, multi-market economic data, and even air traffic and weather predictions, if desired.
Combining all of these data sets for just one hotel could amount to several hundred million observations. Generating the pricing and distribution recommendations could easily require result in thousands of decisions being generated each day for every day into the future. Multiply that number for a hotel chain with dozens of properties and it quickly becomes clear that, more than anything, revenue management is a big data challenge. As an example, one major hotel brand recently revealed that it generates more than 45 million forecasts nightly for each hotel, segment, room type, and channel for the next 365-day period.
Needless to say, the processing and algorithms require an enormous amount of data storage and processing capacity to accomplish this task. While even global hotel brands may not have data processing requirements that are in the same league as Amazon, Apple, Facebook or Google, their data processing needs are certainly large enough to constantly stretch the limits of on-premise data storage and computing capacity, hence the need for cloud-based deployment.
Prospective buyers need to know that any revenue management solution under consideration can handle the rigors of big data processing and optimize pricing calculations in highly compressed timeframes.
A number of additional considerations, as shown in the chart, can be found in Chapter 2 of The 2018 Smart Decision Guide to Hospitality Revenue Management. The new edition of this popular resource is currently available for complimentary access (click here to learn more and to download), courtesy of the underwriters and media partners.
