By Rachel Grier, managing director Asia Pacific, IDeaS

 

 

Forecasting hotel demand is an essential ingredient in the practice of revenue management. Hotels use forecasting to help accurately predict the time frames throughout the year that will bring them higher or lower than normal occupancy, demand and revenue. A good demand forecast assists with room rate decisions, staff allocation, property maintenance and hotel operations. Utilising data and analytics through accurate forecasting is also the best way for hotels to determine future marketing and pricing strategies that drive successful changes.

 

There are typically three types of forecasts in a hotel: operational, financial and revenue management. Hotels often overlook the differences between these forecasts; however, it is important to distinguish their differences because they are used for different functions. An operational forecast is often used to manage the hotel’s resources such as: how many room attendants will be needed to clean rooms, how many front desk agents will be needed to check guests in and out, or how many servers and cooks will be needed to attend to guests in the restaurant. Financial forecasts are often used to determine the end fiscal results to provide owners and investors with an outlook on revenues and profitability.

 

A revenue management forecast, however, is intended to estimate the expected future demand for a hotel so they can manage that demand to achieve the hotel’s ultimate revenue objectives. This forecast is also referred to as an unconstrained demand forecast. The calculation of unconstrained demand is a critical forecasting requirement because its success affects the entire pricing, inventory and revenue management process.

 

Having clear, accurate and objective data can be considered the “special sauce” in the forecasting mixing bowl. Hoteliers need detailed data that is both historical and forward-looking. At the very least, data should include the number of occupied rooms, coupled with revenue by market segment by day. Hoteliers should also ensure that number of rooms and revenue on the books by day (and by market segment) for a minimum of the next 90 days is included. When data is collected every day, it allows the hotel to establish simple booking pace forecasts by segment and day of week, from which they will be able to compare to historical data. By doing this consistently, hoteliers will be able to quickly identify any changes when demand increases and adjust their strategies accordingly.

Importantly for hoteliers across the APAC region, there has been an increasing amount of emerging data sources – including social media, reputation management engines, web traffic sources, weather and airline data – that hoteliers also have to contend with. But what do all of these emerging data sources mean for hoteliers?

When it comes to decision support and accurate forecasting, some data sources should be incorporated directly into the demand modelling and optimisation processes. Online reputation data, for example, is set to reshape hotel revenue management strategies across the region. Customer-centric data, such as the online reviews found on Tripadvisor, Facebook or booking.com, are increasingly being used by hoteliers to compare their reputation and rates to competitors in the same market space or geographical location.

Savvy hoteliers should look at the larger picture to understand all relevant data sources for their business. Taking in the larger picture of traditional forecasting data points, along with online reputation, will lead to more accurate revenue management practices. Accurate forecasts are important in revenue management because they not only influence rate decisions and strategies, but they also impact any displacement evaluations for potential group business. If a hotel is acutely aware of where it stands from a forecasting standpoint in relation to group bookings, and have an accurate picture of future demand, then a group’s potential displacement will help them accept the most valuable business.

 

This is an area where an advanced revenue management system is key, going well beyond the limited functionalities of other revenue management systems and giving hoteliers the insights they need to capture the most profitable groups for business. Advanced revenue management systems ignore extraneous data that can negatively affect forecasts, focusing on the important factors and combinations that will lead to successful business practices.

 

With emerging data sources like social media, online guest feedback and web traffic sources, hotels are able to access information from more data points than ever before to build their revenue strategies. Combining advanced demand forecasting capabilities with reputation insights and group evaluations presents hoteliers with a comprehensive and accurate base to execute successful revenue management strategies now and into the future.