Back in October, Kelly rather succinctly stated that “Revenue management has always been a “big data” problem.” This is very true. This week, as we continue our exploration of big data in hospitality, I’m going to delve deeper into the data needs for revenue management. I’ll be exploring the important sources of information that should be driving revenue management decisions – what they are, and why they are important. My primary focus here will be data used to support automated revenue management decisions – but I’ll also touch on the type of data that revenue managers should be looking at regardless of whether they use an automated system or not.
For any revenue manager looking to make data-driven decisions, the starting point is to make sure that you have the following types of information at your disposal:
- Stay history – data regarding the final number of rooms sold by date, and the revenue generated in the past
- Inventory history – data regarding the number of rooms available for sale by date in the past
- Future reservations – data regarding on-books reservations (this data should be captured and stored regularly – daily or weekly) for future arrival dates
- Future Inventory – data regarding the number of rooms available for sale for future arrival dates
- Future Rates – information regarding the rates that are available for sale in the future
If you are a revenue manager trying to do this job by hand, you probably have a spreadsheet that contains the stay history and future reservations data. You might also have some of the other data listed above in that spreadsheet – but my experience is that most revenue managers don’t. Why? Because that information is in their head! After all, every competent revenue manager knows the capacity of their property, as well as the rates that they are selling. Many revenue managers are surprised to learn that an RM system needs these other pieces of information – after all, they don’t have them stored – why would a system need them? I’ll cover some of this as I describe the uses of each of these pieces of information, starting with the data most commonly kept by revenue managers.
This information is absolutely critical to understanding the overall demand patterns for a hotel. What are our high seasons and low seasons? What is our day of week pattern? Is the property full on weekdays or weekends? Does our average rate fluctuate according to this pattern, as well? The most important and basic information that we need to manage revenue is based off of this data.
Future reservations information is critical to understanding how many rooms are left to sell. It’s pretty difficult to manage revenue on a date that’s already sold out – so this information tells us how much space is left to manage. In addition, as we keep track of this information, we’ll be able to discern a booking pattern for our property – how far in advance of arrival do guests book reservations – and determine if this booking pattern fluctuates by arrival day of week or by season?
Future Inventory and Inventory History
Revenue management is, at its heart, the act of balancing demand and capacity through management of pricing. As such, future inventory information is essential to every revenue management decision imaginable. In fact, capacity is essential to the understanding of information provided by both stay history and future reservations – without matching capacity information, those other pieces of data are of limited value. In particular, the process of unconstraining (i.e. estimating sales lost when rates and rooms were unavailable for sale) depends upon the availability of accurate historical capacity information over an extended period of time.
This is why I am so surprised at how frequently hoteliers fail to track this data: the assumption that capacity is stable over time in a hotel is frequently an incorrect one. Wings are upgraded, and rooms out of service for a long period. Everyday maintenance issues take individual rooms out of service for short periods of time. Room type configurations change – and so on. If you are a revenue manager that is currently managing revenue using spreadsheets, but thinking that you might look at a revenue management system in the future, do your future vendor a favor, and start collecting this data today. They’ll thank you later, I promise.
Future Rate Information
This, of course, is where it all comes together. After all, if managing rates and availability is the problem, then knowing what the rates are and how they are sold is pretty essential information, isn’t it? And most revenue managers do have a strong understanding of the rates that they sell, including important factors such as qualifications for rates, typical contract elements (for contracted rates at the property), distribution costs (for distributed rates), and so on. It is this broad understanding of rates that allows the typical revenue manager to handle what is obviously a very complex job.
Capturing this information outside of a Property Management System (PMS) or Central Reservation System (CRS) is often quite difficult, though – rate data is both tremendously complex and highly dynamic. In fact, revenue management systems frequently don’t really even try to keep up with all of the complexity and change. They do this by simply capturing historical average rate information and forecasting the rate value patterns forward. In most cases, and done properly, this compromise works fine.
But that’s not all…
Next week I’ll continue our investigation into “big data” and revenue management, with an exploration of the data that is critical to revenue management analytics, including the “next generation” needs of true rate optimization solutions.