We have all been there: you, sitting at the table with the rest of your Executive team, going through a demonstration and sales pitch of a revenue management system. Yes, they all have pretty screens that include a ton of information to help you manage your business. But not all systems are the same!
Two of the key differences to note when evaluating systems are what information is used and how the system forecasts. You will run into both types of systems, rules-based and science-based. This blog will help you understand the differences out there and why it matters to you and your organization.
A rules-based system operates in a way where the system has a set of rules in the backend. A rule will change the strategy if certain criteria are met. Example: If A happens, then do B. These rules can be very simple; however, you have to write a rule for every scenario you encounter. This kind of system is effective as long as you know and understand all the situations that are encountered in which a decision should be made. In the hotel business, this methodology was used a long time ago. The methodology was sufficient at that time to forecast since the data available was very limited. The rules have to be changed often as situations or exceptions occur. The forecast is not dynamic and is based on a system not reacting to what is happening in the marketplace. Some hotels do still operate this way, but it is not optimal.
In a rules-based system environment, a Wednesday in April that is running 80% would be forecasted and priced the same as a Wednesday in November that is at 80%. This method does not take seasonality, market conditions, competitive pricing, pricing elasticity, and other such factors into account.
Today, we have more data available to learn about the buying behavior of our customers, including what they do before they arrive on property, what they do at every touch point during their stay, and even what they do after they depart. All these behaviors create data points and can happen via multiple channels. The buyer behavior information collected throughout the lifespan of the guests’ stay can be used to evaluate the precise meaning and profitability of each customer to your organization. Science-based revenue management systems forecast and accurately price each segment of business based on the data collected in the methods described. Sophisticated systems will use machine learning to evaluate the results it produces and will switch between several forecasting methods to achieve better results.
With so many different scenarios and the abundance of data available, a science-based system improves forecasting accuracy by understanding each segment’s willingness to pay. This improves pricing and yielding. The science-based approach couples these details with in-depth knowledge of the competitive landscape and each competitor’s actions and trends.
In today’s hotel environment, manually changing rules as things change in your property is not the best way to forecast, price and yield your hotel rooms. There are too many changes to make in today’s world to keep up with a system like this. Your company and shareholders depend on you to make the best decisions. There are science-based systems out there that have been proven to work much more effectively than the rule-based. You owe it to yourself to dig in to understand how these systems work!