Your RMS is an indispensable tool in your business arsenal. Almost like having a crystal ball, advanced analytics offer data-driven pricing recommendations that give you an edge over the competition. However, if your system is dated and slow, don’t be surprised if you get left in the dust. Your RMS must keep pace with complex market ebbs and flows to give you the knowledge necessary to grow your business and meet revenue projections throughout the year.
It’s important to understand the latest features in revenue management analytics to ensure your RMS is providing you with the maximum benefit. This post is the first in a series of three that will focus on must-have features of the modern RMS.
The first thing your system should be able to do is analyze a variety of abstract and complex influential factors to help you better understand how different rates and segments can be controlled.
Consider a typical RMS that compiles transaction data into aggregated groupings. This might include market segments or reservations that are based on value alone. Too often, important information about controlling different rates is lost through this aggregation process. This means a hotel does not have access to the most optimal forecasts — basically, the crystal ball is a bit foggy.
Best-in-class systems capture individual information by transaction and separate those transactions based on a variety of influential factors. This allows a deep understanding of different aspects of the rate changes and how they should be controlled. Ultimately, this facilitates the creation of effective groupings to support extremely accurate forecasting so hoteliers can make thoughtful and intelligent decisions.
Let’s look at an example of two corporate rates:
- Rates contracted at a fixed price with the option of restricting availability as required on peak days.
- Rates contracted at a guaranteed 10 percent off BAR with Last Room Availability (meaning this rate cannot be restricted in its availability).
These two rates will often end up in the same market segment because they are both corporate contracted rates. However, this is problematic from a revenue management and analytic perspective because each will behave differently and therefore must be controlled differently.
The best RMS will consider many rate attributes when determining analytic groupings. Creating these groupings by identifying how rates will be controlled in your RMS will provide better forecasts and, ultimately, a stronger bottom line. Meanwhile, forecasts can still be available to revenue managers and other system users as necessary for organizational reporting needs.