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By Dan Skodol

In 1972, an employee of British Overseas Airways Corporation by the name of Ken Littlewood provided the genesis of what has become today’s revenue management (RM) discipline. He established “Littlewood’s Rule,” a yield management rule that addressed revenue maximization by proposing that discounted fares be accepted if their revenue value exceeded anticipated revenue from the expected value of full-fare tickets. Littlewood’s algorithm led to experimentation with “fenced” pricing and a forecasting system based on seat inventory. Airlines also tried to fill as many seats as possible by predicting how many booked passengers would not show up for their flight, and then overbooking by the predicted amount to ensure every seat was filled.1

A few years later, the 1978 US Domestic Airline Deregulation Act abruptly dropped the airline industry into the free market system. This, combined with the recession of the early ’80s, triggered the rapid rise of low-cost carriers (LCCs) and fierce price competition. Domestic airlines saw a substantial drop in profits. In Albuquerque, New Mexico, for instance, fares fell by 32 percent once Southwest Airlines entered the picture.2

In response to this disruption, Robert Crandall, chairman and CEO of American Airlines took Littlewood’s Rule a step further and pioneered the world’s first true yield management system.3 To maximize revenues, he invested millions in analytics-driven inventory control and demand forecasting system called Dynamic Inventory Allocation Modeling Optimizer (DINAMO). Over the next year, American Airlines saw profits rise 48 percent, and the system’s net impact was estimated to be $1.4 billion in additional revenues over a three-year period.4

As hotels began to adopt revenue management, hotels and airlines alike were impacted by further disruption in the RM world. This disruption was fueled by the exponential growth of internet distribution channels, the emergence of online travel agencies (OTAs), and the era of price transparency – giving consumers the ability to quickly shop and compare fare options before purchasing.

Hotel Revenue Management Takes Flight

Crandall ultimately shared his yield management successes with Bill Marriott, CEO of Marriott International, who recognized that hotels dealt with issues similar to that of the airline industry, such as perishable inventory, advance bookings, lower-cost competition and fluctuating bouts of supply and demand. Marriott took the proverbial “yield management” ball and ran with it. He developed a more holistic RM system that not only made inventory recommendations, but encompassed consumer behavior, competition, dynamic pricing, and addressed the issue of optimizing room availability according to variable lengths of stay. By the mid-90s, Marriott’s successful implementation of RM was adding between $150 to $200 million in annual revenue.5

Today, the concept of integrating advanced analytics with RM to optimize prices is nearly ubiquitous. Gone are days spent wrestling with Microsoft Excel spreadsheets to organize data. Hotel guests are more plugged in than ever, booking more and more via mobile devices6, and connecting with new information sources like meta-search engines and social media. In response, modern technological advances are driving the evolution of RM, and enable the discipline to impact hotel revenues in most significant ways.

Cloud-based RM solutions efficiently integrate and automate processes, providing detailed data from digital channels – both historical and real-time – and analytics that allow hotel operators to drive increased profitability by optimizing price positioning versus their competition. Distribution data empowers hotel operators to further improve their bottom lines by establishing strategies that lower customer acquisition costs. And state-of-the-art RM systems increase conversions along with Average Daily Rate (ADR) by identifying repeat guests and loyalty members at the point of booking and presenting customized pricing and availability.

A key component of today’s RM systems is the ability to break down customer business based on multiple factors, such as customer type, geography, booking channel, demographics, or purpose of stay. Effective segmentation combined with predictive analytics allows revenue managers to view industry data in new ways to accurately forecast demand, increase direct bookings, deliver precision pricing, and maximize profit opportunities that might otherwise be lost.

The Exciting Future of Hotel Revenue Management

The discipline of RM has changed dramatically over the past few decades and going forward is poised for further transformation. Increasing reliance on data, automation, and analytics will improve RM decision making and strategy development.

Sheryl E. Kimes, expert in hotel revenue management, and professor of operations management at Cornell University’s School of Hotel Administration, surveyed some 400 international RM professionals. Her findings are published in the report, The Future of Hotel Revenue Management.7

According to Kimes’ research, RM roles will continue to evolve, and emerging trends indicate that RM practices will progress from the pervasive silo mentality to become more strategic and centralized. More hotels will recognize that to be effective, RM must align with other departments such as sales, e-commerce, and particularly marketing. And we will begin moving away from revenue per available room (RevPAR) as a critical metric of hotel performance, turning instead to gross operating profit per available room (GOPPAR) and GOP per available square foot.

Until now, RM implementation of non-rooms revenue has been low, but 63 percent of revenue managers believe that “total hotel RM” will begin gaining traction over the next five years. Hotels will recognize that they can significantly increase profits by applying RM practices to all revenue streams, including non-rooms areas such as function space, restaurants, spas, golf, and parking.

Taking this a step further, there are several exciting new concepts and trends emerging in the world of RM. Personalized pricing involves positioning and promoting room rates and offers to customers based on their spending habits, preferences, and lifetime value. Also, the same predictive analytics and rules of supply and demand that revenue managers apply to room rates can also be used for ancillary products and services.

For example, if a frequent hotel guest regularly books a round of golf and a spa treatment for his spouse, a hotel revenue manager may look to bundle these with a room at an attractive price in order to drive a direct booking. Segmentation and one-on-one marketing will reach new levels, and as a result revenue managers will be able to develop optimal pricing strategies that maximize overall revenue and profit from every segment of their business.

RM has come a long way since the development of Littlewood’s Rule. Moreover, as hotels strive to grow revenue, market share, wallet share, and of course, customer loyalty, the role of RM will grow in importance as well. RM will transition from reactive to proactive, leveraging analytics and next-generation capabilities to develop more customer-centric offers and an integrated profit-optimization strategy that involves all parts of a hotel’s revenue-generating process.

While the future of hotel RM has yet to be fully defined, the true essence of it remains as it is today: providing the right customer, with the right product, at the right time, for the right price, via the right channel.


SOURCES
1Stuart-Hill, Trevor. “Revenue Management: An Overview on Past, Present and Future.” HotelExecutivecom Daily Headlines, 16 Sept. 2012, hotelexecutive.com/feature_focus/3194/revenue-management-an-overview-on-past-present-and-future.
2Committee on Commerce, Science, and Transportation, U.S. Senate. “AIRLINE DEREGULATION: Changes in Airfares, Service, and Safety at Small, Medium-Sized, and Large Communities.” Apr. 1996, doi:Committee on Commerce, Science, and Transportation, U.S. Senate.
3Rose, Paul. “A Lifetime in Airline Revenue Management.” Journal of Revenue and Pricing Management, vol. 15, no. 3-4, 2016, pp. 197–202., doi:10.1057/rpm.2016.21.
4“The Cornell School of Hotel Administration Handbook of Applied Hospitality Strategy.” The Cornell School of Hotel Administration Handbook of Applied Hospitality Strategy, by Cathy A. Enz, SAGE, 2010, pp. 515–515.
5“Room at the Revenue Inn.” The Book of Management Wisdom: Classic Writings by Legendary Managers, by Peter Krass, Wiley, 2000, pp. 199–208.
6Sheivachman, Andrew. “Mobile Travel Bookings Will Reach 40 Percent of Online Sales in 2017.” Skift, Skift, 21 June 2017, skift.com/2017/06/21/mobile-travel-bookings-to-reach-40-percent-of-online-sales-in-2017/.
7Kimes, Sheryl E. “The Future of Hotel Revenue Management.” Cornell University, Cornell University School of Hotel Administration, 13 Jan. 2017, scholarship.sha.cornell.edu/cgi/viewcontent.cgi?article=1239&context=chrpubs.

About Dan Skodol

Dan Skodol is Vice President of Revenue Analytics at Rainmaker. Dan came to Rainmaker with over ten years of Revenue Management experience in gaming, hotels, multifamily real estate, and airlines. He is responsible for researching and designing enhancements and innovations within Rainmaker’s hospitality product suite, as well as supporting thought leadership topics and studies via analytics. Dan previously held Director of Revenue Management roles for two casino organizations in Atlantic City, and Archstone Communities. He holds a BA from Yale University and a Master of Management in Hospitality degree from Cornell. Dan and his wife reside in Denver, CO with their two-year-old son and enjoy skiing, hiking, and travel.

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