Data Quality Vital To Total Revenue Forecasting
Total Revenue Forecasting (TRF) enables hotels to get a better picture of both rooms revenue and ancillary revenue in order to plan more strategically. This may be in terms of resourcing. For example, anticipating demand before it arrives can enable you to spend marketing money more accurately. It can show where demand is weak, not only in rooms but also in other revenue-generating areas of your hotel.
Any hotels with ancillary revenue streams can be doing TRF, whether that is a manual or automated process.
There are many areas of ancillary revenue hotels can focus on, but here are two examples:
Breakfasts – How many people are booking rooms without breakfast but are actually buying breakfast? And how many people are coming to the hotel for breakfast who haven’t booked a room? If you can see the occupancy of the hotel and what percentage are having breakfast then you know what the conversation rate will be. From there, you can accurately anticipate what your breakfast revenues will be. This data can then also be used to more accurately manage staffing levels and food and beverage costs.
Group forecasting – This is inherently difficult, because it doesn’t always follow a pattern. However, if you are able to analyse pipeline and see what the characteristics of the groups are then you can calculate the likelihood of those groups to convert or wash.
TRF can also be used to forecast revenue for spas, car parks, meeting space, golf tee times – anything that can generate additional revenue and on which data can be collected.
Why Data Is The Oxygen
However, as with all areas of revenue management, TRF requires good quality data. This is where the hotel industry, with its current data stack, lags behind.
I think of data as oxygen – without it you can’t perform at the top of your game. For rooms we now have a consistent flow of data from the PMS. However, for the other revenue areas of the hotel that data, that oxygen, doesn’t always exist so you can’t perform to the same level.
At Duetto, we can get good folio data out of some PMS’. Using this data, we can see how much is being spent in different revenue categories. A PMS that can capture and then share folio data is essential.
Is that data enough? No, it’s not.
Folio data only shows us the final spend for those revenue streams but there is a lot that happened before the buying decision. Unfortunately, a lot of the processes capturing that data are still manual.
One of the biggest constraints in hotel revenue management is this lack of data and the ability to share data through different applications. I liken it to puddles. Historically some technology providers have created walled gardens, with puddles of data only they can use. But in order to provide a good service to the hotels we need to create a data lake – then you can do really interesting things, such as TRF. New technology entrants recognise this problem and there is a freer exchange of data now, but it’s still not enough. We have to share information.
Duetto operates with an open API. This means any of our customers can get any one of their technology providers to extract a forecast from our application. For example, that could be linked to a marketing system in order to trigger campaigns for low demand periods. The information we provide can feed into and get other applications working more effectively, driving more profitable business for the hotel.