From Managing Demand to Generating Demand
By Jon Higbie Chief Science Officer, Revenue Analytics, Inc. | October 27, 2013
Co-authored by Dax Cross, President, Revenue Analytics
Over the past 25 years, Revenue Management (RM) has grown from a new idea in hospitality into a core competency that is essential to any hotel's success. In recent years, the internet has made pricing transparent and social media has empowered consumers. These dynamics have resulted in Revenue Management rapidly evolving from a function of managing demand to playing a critical role in generating demand. At the corporate level, hotel chains are investing heavily in new Revenue Management analytics to inform pricing, promotions and marketing. At the hotel level, Revenue Managers are pricing more dynamically across multiple market segments to drive demand and maximize revenue. It is an era of big data, and new Revenue Management capabilities are turning data into dollars.
In the late 1980s, hoteliers began to recognize an opportunity from applying the yield management techniques that airlines had used to drive revenue gains following airline deregulation. The airlines had focused on using data and analytics to forecast demand for different fare products, then optimizing inventory availability. They developed yield management systems that maximized revenue by precisely determining how many seats on each flight to protect for late-booking, high-fare travelers, and how many seats to offer at discounted fares to more price sensitive leisure travelers with more flexible travel plans. Following a chance discussion between Robert Crandall, then CEO of American Airlines, and J.W. "Bill" Marriott, Marriott International became an early pioneer of yield management in hospitality. These early efforts resulted in revenue gains of $150 million to $200 million for Marriott.
As a result of this success and similar success with other hotel chains, Revenue Management became a core discipline in hospitality. Similar to the airline practices from which it had been adapted, Revenue Management focused on managing inventory availability to maximize revenue based on expected demand. Revenue Management systems, some of the earliest "big data" analytics, crunched data for every reservation for the last two years to produce demand forecasts for every night for the next year, across various room types, seasons and days-of-week. For a hotel chain with 3,000 hotels, that means the Revenue Management system produces over 40 million new forecasts each night! These forecasts feed an optimization program that generates inventory controls for each hotel to manage the availability of different rates across various lengths-of-stay and to set overbooking levels.
When demand is strong, using analytics to yield manage demand to "cherry-pick" the highest value bookings is extremely effective. However, over the past 10 years, as pricing became more transparent and consumers were empowered by the wealth of information available to them through the internet, the fundamental Revenue Management problem for hospitality began to change. These changing dynamics also highlighted key differences between hotels and airlines that drove hospitality Revenue Management to evolve. First, hotels sell to a variety of market segments that can have different demand patterns and pricing models. Second, hotels have far more differentiated products than airlines. They can offer luxury, full-service, limited service or economy products, each with various room types and amenities. They are differentiated from competitors by brand, quality, and, most importantly, location. Based on these different market segments and differentiated products, hotels fundamentally have more pricing power than airlines, whose products are often viewed as commodities.
Limitations of Traditional Revenue Management
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