The Total Revenue Performance Journey
Practical Revenue Management Tips
By Paul van Meerendonk Director of Advisory Services, IDeaS Revenue Solutions | August 02, 2015
Total Revenue Performance is the intelligent calibration of demand across all hotel functions to meet overall business objectives. It is the ability to instantly and systematically decide which business to accept across multiple revenue streams at all times, based on greatest overall value to the asset. This kind of holistic approach to revenue management considers not only guest room rates or availability but also a myriad of other sources, including revenue streams across your business and other data, such as social media and sales data. Executed successfully, you can drive your revenue performance to whole new heights across your entire asset as you optimize all levels of your competitive positioning, pricing, and inventory management.
However, the journey toward Total Revenue Performance assumes that you are ready to expand the discipline of revenue management across your organization and use its principles strategically. And your readiness to embark on that journey means you've assessed your current revenue management processes and are applying best practices. This article outlines those practical tips for forecasting, pricing, optimizing and managing total hotel revenues, allowing you to determine your readiness for a Total Revenue Performance approach to your business.
- Do Consider Data Beyond Unqualified Transient Demand
An unconstrained demand forecast is defined as the true demand for a particular product in the absence of any limitations such as when a room or seat is unavailable to purchase. The data and methodologies for unconstraining affect the entire pricing and revenue management process. When it comes to unconstraining the demand forecast, predictive models using only the unqualified transient data are generally considered to be not reliable. Unconstraining requires considering each and all of wholesale, group, corporate negotiated, and unqualified transient demands. This is what we call "holistic unconstraining."
- Don't Include Regrets and Denials in Demand Forecasting
Most recently, hoteliers experienced claims about the use of regrets and denials data in demand forecasting. The claimed methods primarily source this data set from the booking behaviors captured from a hotel's main website (brand.com), without sufficient regard for the fact that brand.com can only be visible to a small amount of regrets and denials data that a hotel accumulates and is limited to the unqualified transient demand. Forecasting models that are based only on a fraction of the unqualified transient demand in fact disregard the demand for different market segments and/or additional channel behaviors.
Studies confirm that most guests use a variety of websites and meta-search engines to compare prices before they make their booking decisions. Therefore, this increasingly complex guest booking behavior makes it unclear when or if there is cross-usage of additional websites or multiple visits per guest that are unknown in the denial logic that hotels use to capture this type of data. That is primarily why leading data scientists of the world refer to regrets and denials as "dirty data." Use of regrets and denials may cause over-unconstraining of the demand data, which leads to over-protection of inventory and eventually to reduced occupancy levels.