Last month, Starfleet Research, the leading provider of best practices IT market research for the hospitality industry, released The 2019 Smart Decision Guide to Hospitality Revenue Management. Now in its fifth edition, this title is widely considered to be the hotel industry’s most authoritative and comprehensive resource on this topic. The new edition is now available for complimentary access.
Ask any hotel revenue manager of a certain age what it was like for them to do their jobs before the advent of next-generation revenue management systems. Few, if any, will wax nostalgic about “the good old days.”
Certainly, none will say they miss spending their time and energy continuously collecting and integrating endless pieces of information dispersed across multiple data silos. Or creating macros to run calculations on Excel spreadsheets. Or constantly logging into the extranets of distribution platforms to enter updated rate information. Or obsessively pouring over mountains of data in search of discrepancies and input errors with the analytical equivalent of a fine-toothed comb. Or manually reviewing forecasting models and demand reports in the hope of identifying opportunities for improvement in pricing and inventory control decisions.
Technology innovation has rendered the mundane, tedious, and cumbersome tasks associated with revenue management practices of yesteryear virtually obsolete, to nobody’s chagrin. By taking the most repetitive — including the most complex — tasks off their plates, new technology solutions have liberated revenue managers from the daily grind of manual data collection, entry, analysis, and updating.
The best of today’s solutions fundamentally redefine what it even means to be a revenue manager. The job is no longer about crunching numbers and updating prices. Instead, it’s about creating high-value, big-picture strategies that serve to optimize financial performance across all parts of the organization.
Enabled by artificial intelligence (AI) and machine learning, the science of pricing optimization is now capable of running largely on autopilot. The best of today’s solutions adapt in real time to dynamic markets characterized by ever-changing numbers, patterns, and results to optimize pricing decisions in much the same way a jetliner uses autopilot to find the best flight path while minimizing turbulence by automatically changing speed, direction, and altitude and by oscillating the wings.
The best of today’s solutions automatically calculate demand forecasts for future use of every guest room, recommending selling strategies and overbooking levels to maximize yield with an unprecedented degree of accuracy, and with little need for human judgment, which is often erroneous.
AI has played a crucial role in the evolution of revenue management capabilities, making it possible to handle increasingly large volumes of data with ease and develop increasingly sophisticated algorithms to improve decision engines. With the latest advances in machine learning, a next-generation solution has the capacity to gain knowledge and insights, enabling it to progressively improve the accuracy of its forecast models by itself.
Simply put, AI makes it possible for a machine to accurately predict not only how many guests will check into your hotel at any given point in time (often, months into the future), but also what types of guests they will be, what kinds of rooms they will want, the maximum rate they will pay, and how much they will spend during their stay at the hotel.
An AI-powered revenue management solution tends to be far more precise in its predictive capabilities — and, also, quicker to react to unexpected situations — than the most cutting-edge solutions of only a few years ago. It also tends to be less dependent on historic data, which has long been the bread and butter of revenue management solutions.
Generally speaking, an AI-powered solution can detect emerging patterns related to guest bookings and competitive actions much faster and more accurately than was ever before possible, giving revenue managers the ability to enact strategies that are proactive rather than reactive.
Importantly, the best of today’s solutions have proven out their value in terms of ROI, improving the financial performance of a hotel in highly predictable ways and with decidedly positive outcomes. In fact, according to research conducted for The 2019 Smart Decision Guide to Hospitality Revenue Management, large and very large hotels have enjoyed an 11 percent increase in RevPAR, on average, which can translate into millions of dollars in additional profit. Midsize and limited-service hotels have faired only slightly less favorably, with an 8.5 percent average increase in RevPAR.
This Smart Decision Guide explores the myriad of benefits, financial and otherwise, that AI-powered revenue management solutions deliver. It offers a framework for thinking about revenue management (hint: it’s not just about guest rooms and nor is it just about technology) and a roadmap for not only selecting the right technology solution but also for driving continuous performance improvement.
The Smart Decision Guide was independently produced, providing for unbiased, fact-based information. The research is based on data collected in Q2 2019 from more than 250 qualified survey respondents. The underwriters of the new Smart Decision Guide are the following industry leaders: Atomize, Duetto, Infor, Rainmaker (a Cendyn company) and SHR.
The 2019 Smart Decision Guide to Hospitality Revenue Management is now available for complimentary download. It can be accessed here.
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