An accurate forecast is the cornerstone of effective revenue management decision-making. Without a reliable forecast, it becomes impossible to make informed revenue-driving decisions, which could potentially harm the business instead of promoting growth. It is essential that everyone involved understands the objectives clearly and that the different types of forecasts are not conflated.
Types of Forecasts
There are two primary types of forecasts: financial forecasts for business planning and revenue management forecasts for operational decision-making.
Financial Forecasts:
The main purpose of financial forecasts is for business planning, with the budget serving as the primary forecast. It represents the financial commitment that the operator makes to the property owner. To ensure compliance with this budget, operators prepare monthly forecasts to identify any variations from the initial budget. These monthly forecasts include projections for occupancy, average daily rate (ADR), and revenue by market segment, as well as forecasts that support various other departments within the property.
While financial forecasts are crucial for ensuring the property is on track to meet the owner's expectations, they do not provide the granular detail necessary for making pricing and inventory management decisions. Typically, these forecasts consist of aggregated monthly figures.
Revenue Management Forecasts:
The revenue management forecast is specifically designed to guide pricing and inventory management decisions. Unlike financial forecasts, which may present monthly data, revenue management forecasts are more granular and must be calculated on a daily basis, segmented by market.
Key standards for a revenue management forecast include:
It should be prepared weekly for the next 90 days and monthly for up to 365 days.
The forecast must include daily figures, broken down by segment, covering occupancy, ADR, and
revenue forecasts.
Avoid the use of "regrets" and "denials" during forecasting; these are often inaccurate and can negatively impact forecast reliability. Instead, forecasts should be developed by segment and then aggregated into a total daily forecast—this is referred to as the unconstrained forecast. The process of “unconstraining” is a mathematical exercise in data analysis.
A revenue management forecast should never be artificially adjusted to fit the financial forecast. Inaccurate revenue management forecasts can lead to poor pricing and inventory decisions, resulting in revenue losses.
Given the extensive data required for an accurate revenue management forecast, utilizing a sophisticated revenue management system with advanced forecasting and optimization capabilities is essential for any hotel of a reasonable size and complexity. This will be discussed further along the Revenue Journey.
The Forecasting Process
Creating a reliable forecast involves several crucial data sources:
Historical Data: Initially, if no current booking data is available, historical data will serve as the foundation for the initial forecast. Patterns related to the day of the week and seasonality from past data will be projected forward to establish trends. Special events that occur in the upcoming period should be included, while any past events that won't recur should be removed.
Recent Trend Data: Analyze recent performance trends for weekdays. For example, if the last eight Mondays saw an average of 50 room bookings at the Best Available Rate (BAR) from OTAs, with a typical variation of about five rooms, you can reasonably expect similar results unless impacted by special events.
On-the-Books Data: Once the hotel enters its booking cycle, current booking data is incorporated into the forecast. Combining this with historical data and recent trends helps establish an "expected pace" for bookings. Comparing this expected pace with the on-the-books data will reveal whether bookings are progressing faster or slower than anticipated, prompting necessary adjustments to the forecast.
Competitor Rate Data: Keeping an eye on competitor pricing is also crucial. If competitors are raising their rates, it may indicate increased market demand, suggesting that bookings could exceed initial expectations. In this case, the forecast should be adjusted upward. Conversely, if competitors are lowering their rates, it might signal a weakened market, and the forecast should be reduced.
The most important aspect of any forecast is that it should be as realistic and accurate as possible; it should not be manipulated for "political" reasons. Pricing, inventory management, and other critical business planning decisions hinge on the reliability of the forecast. A distorted or unrealistic forecast can lead to poor revenue management decisions, ultimately resulting in subpar performance—which must be avoided at all costs.
コメント