Demand Calendar Blog by Anders Johansson

How to improve and develop forecasting in hotels

Written by Anders Johansson | 14 March 2023

Forecasts should be reasonably accurate, but they will never be entirely correct. Therefore, the revenue management system should take the first shot at forecasting. The second opinion is that the revenue manager will add the human touch based on extensive experience from the destination and the hotel. Once the forecast has been finalized, the revenue manager can then send the total revenue forecast to top management to be used for strategic decisions about resources for marketing, sales, and revenue, as well as decisions about improvements in the concept, product, and services.

Forecasting room revenue

Hotel revenue managers use a combination of data analysis, market knowledge, and collaboration within the commercial team to forecast room revenue for a hotel. They aim to maximize revenue while maintaining optimal occupancy levels and guest satisfaction. Hotel revenue managers use various techniques to forecast room revenue for a hotel. Here are some standard methods.
 
  1. Historical pattern analysis: Revenue managers analyze travel and occupancy patterns for several years at the destination. These patterns are stable over time (except for the demand during the pandemic), and revenue managers can, therefore, based on the patterns, forecast future demand.
  2. Market analysis: Revenue managers monitor market trends such as local events, seasonal holiday changes, and economic indicators to predict demand.
  3. Forecasting software: Many hotels use forecasting software, such as a revenue management system, to help revenue managers predict demand and adjust room rates. These tools use algorithms to analyze historical data, market trends, and other variables to generate revenue forecasts.
  4. Excel: Many hotels still use homegrown Excel sheets to forecast room revenue by extracting data from siloed systems, importing and compiling data into Excel, and analyzing and adjusting figures to produce a forecasting report to be handed over to management. These hotels waste time manually processing data instead of focusing on analysis and actions.

Challenges in forecasting room revenue

For experienced revenue managers, there are no challenges in forecasting room revenue. The processes have been well-known for many years, and there are very few surprises. However, all revenue managers struggle with a few factors.
 
  1. Data quality: The accuracy of revenue forecasts depends on the data quality. To generate accurate forecasts, revenue managers need access to accurate and timely historical data, including turn-aways, cancellations, no-shows, and other demand the hotel did not capture. Unfortunately, the actual demand seems hard to grasp, and most hotels cannot manage this.
  2. Changing consumer behavior: Consumer behavior is constantly evolving, and revenue managers need to keep up with these changes to adjust pricing and inventory strategies. Changes in travel preferences and booking channels can impact demand for hotel rooms.
  3. Internal communication: Effective communication within the hotel organization is essential to accurate revenue forecasting. Revenue managers must collaborate closely with sales and marketing teams and other departments, such as operations and finance, to generate accurate forecasts.
  4. Uncertainty: Many external factors can impact demand for hotel rooms, such as economic changes, political events, and natural disasters. Hotel revenue managers cannot control these uncertainties or predict these events or disasters. Instead, revenue managers can leave out all of these uncertainties, focus on what they can forecast, and adjust the forecasts when they happen or can be predicted.
  5. Competition: Hotels operate in a highly competitive market, and revenue managers need to consider the moves by competitors, such as promotions, product and service changes, distribution channels, and price. Evaluate all the competition's actions before making any changes to the strategy.
Forecasting room revenue is no longer a complicated process that requires careful consideration of many internal and external factors. Revenue managers can keep forecasting as they used to since the demand patterns have been restored as they used to be before the pandemic.

Challenges in forecasting other revenue sources

Many revenue managers are not used to forecasting other revenue sources and are experimenting with different approaches. There are two approaches. One is a siloed approach, meaning the hotel forecasts each revenue source separately. Another is a holistic approach, meaning that the guest is the focus, and the hotel forecasts the average spend per guest. However, the forecasting methods are almost the same as when forecasting room revenue.
 
  1. Historical pattern analysis: The consumption patterns are stable over time (except for the demand during the pandemic), and revenue managers can, therefore, based on the patterns, forecast future demand for any revenue source.
  2. Market analysis: Revenue managers monitor market trends such as local events, seasonal holiday changes, and economic indicators to predict demand and can then forecast any revenue source.
  3. Forecasting software: Very few revenue management systems have functions for other revenue sources, except for a few that can handle meeting space.
  4. Excel: The lack of revenue management software for other revenue sources means that many hotels still use homegrown Excel sheets to forecast other revenue sources by extracting data from siloed systems, importing and compiling data into Excel, and analyzing and adjusting figures to produce a forecasting report to be handed over to management. The time waste is even more significant when hotels manually process data instead of focusing on analysis and actions.

Final thoughts

Forecasting hotel room revenue on at least a rolling 12-month basis is necessary to maximize profits. After working with this for two decades or longer, professional hotels are good at this. Still, room revenue forecasting can be improved by collecting better demand data.
 
Total revenue forecasting is further away, and only a handful of hotels have started experimenting with this and are still figuring out the best way forward. The first step is probably a siloed approach to learning more about the behavior of each revenue source. The second step, further into the future, is to take a holistic approach and focus on the guest to maximize revenue per guest.