With U.S. hotel occupancy levels registering record-breaking performance, hoteliers must get creative when it comes forging a path toward higher rates and greater profits. And they increasingly look to their revenue managers to chart the course. As a result, we're seeing a transformation of the revenue management (RM) role - from revenue manager to revenue strategist.
Yield management decisions were typically only reviewed a few times per year (at best), with occasional adjustments made based on year-over-year pace 30 days out, or 90 days at the most. Relying on SQL programming skills and the advanced functions of Excel spreadsheets, revenue managers compiled a list of standard reports that were presented to the management team, who in turn made decisions regarding pricing and allotment.
RM took a tactical and reactionary position rather than a strategic one - working to manage incoming demand and pricing in ways that were focused more on occupancy and/or ADR than revenue and profit. Consideration of what source the business was coming from or length of stay pattern, although important, was difficult to factor into a pricing decision in a timely fashion. Therefore, an increase in year-over-year occupancy or ADR meant you were "winning" even though profit growth may have said otherwise.
RM in the hotel industry has bloomed in the past decade - particularly over the last few years - moving beyond its former role of simply managing rates and inventory to guiding hotels toward true revenue growth with long-term strategies. And big data in conjunction with technology have been catalysts for that growth.
Hotels now have access to massive amounts of data which can be used as part of a hotel's RM effort. Segmented guest data allows you to personalize experiences and promotions to gain repeat business, demand forecasts help improve pricing strategies, and up-close views of your operating expenses help you avoid revenue leakage - all of which mean greater profits for your hotel. But managing the complexity and accuracy of all this data presents a unique challenge.
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