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Revenue Management

Riding the Waves of Change with Hotel Revenue Automation

By , Solutions Engineer

In an environment where change is the only constant, how can hoteliers ensure their business stays afloat through the ups and downs to come?

As world events of the past two years—or even the past month—have shown, no one ever really knows what’s about to happen next or how the economy will be impacted. What we do know is that the time has come to upend old ways of doing business in order to remain agile and competitive, and this is especially true for hotel revenue management.

Manually collecting, evaluating, and calculating data for the purposes of price-setting via spreadsheets is not only a tedious process, but also slow and highly susceptible to mistakes and missed opportunities—especially in this era of uncertainty. This is where an automated revenue management system (RMS) makes a huge difference to both the top and bottom line. An advanced RMS not only generates prices that adapt to market changes, but it also considers the competitive landscape and a guest’s willingness to pay.

As hoteliers seek to control operational costs and management roles are consolidated, many hoteliers are taking a cluster approach to revenue management. This expansion of responsibilities means revenue leaders have real limitations on the time and task allocations they can provide to any single property, so having automated technologies is critical.

Forecast for Uncertainty

An accurate demand forecast assists hotels with pricing decisions, inventory management, staff allocation, property maintenance, and general operations. Forecasting is also critical for hotel owners and investors assessing the financial potential, or performance, of a property.

Even with historical booking data being less directly comparable to the conditions of today, revenue management professionals should be able to build out a range of forecasts based on all credible external and internal market intelligence that can be gathered, such as government announcements, travel policies, flight data, Google search trends, and market reports.

Revenue managers should build their forecasts based on several scenarios (optimistic, probable, and pessimistic) and review the actual demand versus forecasted results regularly to adjust long-term pricing strategies.

While some revenue solutions use a limited number of forecasting models at a level defined manually by users, high-performance forecasting, built into a sophisticated RMS, relies on hundreds of advanced forecasting models where the most appropriate model is selected by the system automatically. Then the forecast model parameters are calibrated to understand the impact of the specific price sensitivities, no-shows, cancellations, booking windows, etc. within the forecasting group to a granularity of individual rate codes/products.

Analytics can be employed to solve a variety of challenges, including adapting the forecasts to demand shifts and understanding demand as a function of price (the impact of price changes on the demand that exists for the room product). Predictive modelling and forecast data remain essential for forward planning. It is important to look at the right data though as not all data is created equal and only the relevant information should be considered.

Automate & Optimize

Given that a typical hotel will make roughly five million pricing decisions every year, it is not humanly possible for any revenue manager to get every decision right, every day, without the support of automated systems—especially when considering the sheer volume of data needing to be gathered and analyzed.

A robust RMS not only generates prices that adapt to market changes but actually anticipates these variations in advance. In a changing hotel market, slight pricing changes can have a big impact on demand. Therefore, any hotelier operating without systems that can analytically decipher the impacts of a specific price change (20 dollars higher or lower) on occupancy and the resulting revenue benefit (or lack thereof) for their property, is operating at a disadvantage.

A hotel not using an RMS and setting their own rates based on their unique business forecast can either base their pricing assumptions on a gut-feeling or look to match a competitor’s own pricing activity. Both approaches are misguided, if not dangerous. By following a competitor on price, a hotelier should be prepared to be dictated by strategies they are unaware of, which risks setting off a chain-reaction in price reductions between rival properties that cannibalizes revenues for both properties.

An automated RMS scientifically monitors competitor hotels’ pricing for an equivalent room type and its impact on your hotel’s pricing to gauge how aggressively (or otherwise) to react when a competitor changes pricing. Hoteliers must avoid overreacting to competitor pricing tactics. Rather they should focus on rational, analytical, and data-driven strategies to pricing that revenue science technology provides to protect their business in the long term.

Any savvy, revenue-minded hotelier knows that they must attract the right guest, through the right channel, at the right price. And only revenue management can make that possible. An automated RMS that can make effective pricing decisions to maximize business and revenue, even in a disrupted market, is no longer a “nice to have”—it’s a business necessity.

Solutions Engineer

Since joining IDeaS in 2011, Murphy Mathew has been involved with a variety of teams, including data analytics, client success, and user experience. Today he works closely with hotels across the APAC region to better align their business practices with IDeaS’ system capabilities, ensuring effortless, efficient, and profitable performance outcomes.

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