It's 2016. Yet, current rates in the hotel industry still depend on human decisions and actions. There are several software companies on the market creating great price recommendation tools. But at the end of the day, pricing is still a recommendation process.
Those systems have made great strides, but they're not good enough to operate without human intervention and guidance.
Decisions on price will still need to be automated at some point. Most industries have already automated these processes. Why shouldn't hotels?
It's because we lack proper big data feeds that would improve predictions and quantity of information enough to increase precision.
If, for example, hotels knew the flight arrivals and departures to their city several months in advance or plugged in to the train and bus system APIs to understand how many people would be arriving to their city, they could predict changes in demand far in advance.
Currency changes could also be used to further predict demand. If one knows that a certain percentage of one's guests comes from Japan and the Japanese yen's value is dropping, one could predict fewer Japanese visitors in advance and allocate rooms elsewhere.
The list could go on - weather, destination marketing organization, traffic, event ticket sales - all valuable data sets that influence demand. Point is, there are countless big data sets that hotels could and should be tapping into to increase the accuracy of their demand forecasting.
Instead of working on the forecast for just the coming days and weeks, hotels could instead put in place dynamic rates and automate the process thus increasing both precision and performance, not only in the next weeks but next months, even years, if the data is good enough.
The need for proper big data integrations for hotels isn't a luxury any more. Now that the data is there and that APIs to such information exist, hotels need start tapping into it. The sooner they do it, the sooner they will be ahead of the competition.
However, before hotels can begin to use big data, they need to get small data under control. You see, the problem with small data is that it's already there.
You might be asking, "Wait, what? Why is this a problem?"
Well, because it's so inconspicuous, so obviously available, small data often doesn't get the priority it deserves. Yet, organizing one's small data- curating it properly, correlating it, and working on it to bring it together so one can run proper analytics on it is one of the most important things a modern hotel can do.
The moral of the story? Pay attention to small data. It is the most actionable data a hotel has.
So what are some actionable steps for getting a handle on your small data, and working more efficiently with big data?
For an in-depth look at how to manage and use hotel data, stay tuned for our upcoming post on Data Organization.