Hotel technologies have seen tremendous changes over the past few years.
Channels are evolving at a rapid pace, customers have more options for comparison, and selling systems are finally seeing satisfactory returns on investment.
But is your revenue management system (RMS) keeping up?
NB: This is an analysis by Alex Dietz, an advisory industry consultant at SAS Institute, on behalf of IDeaS.
In this piece, I will elaborate on some of the latest features in revenue management analytics that are needed to keep up with the evolving technologies.
They are the minimum analytical requirements for an advanced RMS.
1) Understanding How Different Rates and Segments Are Controlled
Many RMS systems roll up transactional data into aggregated groupings such as market segments or by classifying reservations based on value alone. This can result in losing important information on how different rates are priced and controlled.
Capturing information individually by transaction allows an RMS to separate transactions based on the influencing factors of their key behaviors, in addition to the critical aspects of how rates should be influenced, priced, and controlled.
It then becomes possible to build effective groupings that support accurate forecasting and optimization decisions.
Example:
Imagine there are two corporate rates: one is contracted at a fixed price, with the hotel able to restrict availability on high demand days; the other is contracted at 10% off the Best Available Rate (BAR) with Last Room Availability (LRA), which prohibits the rate from being restricted in its availability.
These two rates often end up in the same market segment, as they are both corporate business accounts.
But from a revenue management and analytics perspective, these two rates behave differently and must be controlled by using their rate attributes to separate them into relevant analytic groupings.
Creating analytic groupings by identifying how rates are controlled in the RMS results in optimal decisions and better bottom-line performance.
Forecasts can still be accessible to revenue managers and other system users in a manner that is consistent with their organizational reporting needs.
2)Demand Forecasts That Handle the Variety of Demand Patterns
Different customer segments have different booking and stay patterns and their respective booking channels can influence these patterns.
Customer behavior changes over time, so using a single demand forecasting approach applied across all segments and channels is problematic. Some RMS systems continue to apply this sub-optimal approach.
The advanced analytical techniques at SAS and IDeaS automatically review distinct patterns in each property / segment / channel to determine which model is best - different segments may have different behaviors and require different forecasting approaches.
The system regularly reviews properties and segments to determine if patterns are changing, and refreshes the forecasting model appropriately.
The result is a more accurate and dependable forecasting process that is not limited to a single approach or forecasting methodology.
3) Elasticity and Competitor Rate Effects
As the industry embraced the concept of BAR - a dynamically priced rate available to transient guests - the importance of measuring and accounting for price sensitivity has moved to the forefront in revenue management.
It simply is not possible to optimize this rate without understanding how demand will be impacted by increasing or decreasing it.
Elasticity can vary by market segment, time to arrival, day of week, season, and other factors. It is essential to account for these determining factors when selecting the right rate at the right time.
The consideration of competitor rates is an important part of understanding price sensitivity.
Guests do not view hotel rates in isolation; the internet has made rate comparisons accessible. Setting rates based solely on what your competitors are doing can lead to significant errors in revenue management.
Competitor rates should be just one of the influencing factors when estimating price sensitivity.
The type and amount of rate changes, in addition to its comparison with competitor rates, will provide the scope of any potential hotel demand impact. Will the hotel be higher or lower than the competition and by how much?
4) Managing Rates and Availability
Despite the prevalence of dynamic pricing and BAR in the industry, the majority of hotels continue to manage their rates through their entire availability window. But it is not sufficient to optimize rates in this type of environment alone, since the availability of these rates requires consistent management.
Rate pricing decisions made on demand makes optimizing rates and availability simultaneously extremely complex, particularly when accounting for length-of-stay reservations. This has become the reality of today’s marketplace.
Conclusion
The hospitality industry and travel distribution continue to evolve. Today’s revenue management systems need to keep pace, not only at a technical level, but on an analytic level as well.
The aforementioned capabilities will help you keep up with the latest practices to optimize revenue in the industry’s dynamic market.
NB: This is an analysis by Alex Dietz, an advisory industry consultant at SAS Institute, on behalf of IDeaS.. It appears here as part of Tnooz's sponsored content initiative.
NB2 Hotel image via Shutterstock.