An average day in the life of the revenue manager will likely start, well, with a cup of coffee and a quick hello to the colleagues. But revenue management doesn’t allow for much spare time; quite the opposite in fact. Daily tasks start early in the morning: looking at the hotel(s) forecasts in your Property Management System (PMS), what happened yesterday, what was the pick-up overnight, what the forecast is looking like for next week, next month, the next 3 months etc.
After gaining a top-level overview of the hotel’s position, most revenue managers will start exporting numerous reports from their PMS; reports needed to analyse what is driving the business in those forecasts at a granular level.
Before you start analysing data, it’s crucial to know where your business comes from, and what the key drivers for your property are. Your PMS is the main source for this ‘on the books’ data, as it’s where every single reservation and group booking is recorded, manually as well as automatically.
Here are some of the key drivers you should be able to record and find in your PMS:
This ‘on the books’ data in your PMS is the foundation for any future decisions you make. So you should have a clear naming convention for rate codes, channel codes etc. It is equally crucial to train your front desk and reservation teams on the importance of data input. Explain why it is important to record the country a guest is travelling from, or using the correct rate code for a walk-in.
A PMS is no analytics platform, so in order to make its data actionable, it needs to be moved across to a tool which can make sense of it. For many hotels, this means exporting into Excel spreadsheets.
With as many key business drivers as this, it comes as no surprise that your PMS is unable to export all data in one single report. Instead, it is often a reality that revenue managers need to export multiple reports on a daily basis, applying different filters for each report.
For example, in order to see market segment data and statistics on room types from 1st March - 31st March 2018, two reports will need to be exported from your PMS; one report containing segmentation data, and one containing room type data. If you want to look at future data, you will need to apply a different date range and export again.
It’s a task requiring significant time and effort but key to getting access to your customer data. Once you have exported all your relevant reports, the focus shifts on comparing and correlating the data, so you can make revenue decisions.
A great many clicks and exports later, your PMS data is now accessible per business driver. In order to make sense of these separate silos of information, you will need to combine all reports, correlate the data and cross-check your different key drivers.
For example, compare a specific rate code with lead time to find out how long before the arrival date certain rate codes are booked, or with ‘day of week’ to see when people tend to stay in your hotel(s) for that rate code. Wednesdays and Thursdays may have a large number of BARRO Rate Code reservations, but the BARBB may not be producing on those days.
Cross-checking all this information identifies trends, and helps you see where your revenue and distribution strategy needs adjusting and yielding.
Now that you can see how certain revenue levers influence others, you can start taking action. Maybe certain channels need to be closed, or you need to apply rate and LOS restrictions on certain dates.
If you discover that a specific OTA is resulting in many deluxe room bookings on days you need them, talk to your OTA market manager. They’re there to help you drive revenue to your hotel, and may have ideas about how to increase bookings further.
Your ‘on the books’ data in your PMS changes constantly, with new trends arising and opportunities to be leveraged. It’s a labour-intensive, continual task for revenue managers to make changes, test the results and improve.
There are ways to help crunch the data, though, freeing up more time for analysing and decision-making.
These crucial factors can help you understand and leverage your PMS data: