Did you know that “complexify” is a word? It means, not surprisingly, to make something more complicated. As a big believer in the value of big data, it’s hard to say this, but thus far it seems that data has mostly served to complexify hospitality. CRM data, PMS data, review data, guest acquisition data, marketing analytics… these moving pieces are a bit like a solar system without a sun to anchor them.
They float around serving little purpose rather than working in unison toward a common goal. To give data some gravitational pull, we must de-complexify it (this one may not really be a word, but you get the drift).
As we move through 2017, almost every trend that surrounds hospitality and technology will revolve around making data more accessible, integrated, and useful. Here are five ways we believe big data will evolve in 2017 to better serve the hospitality industry so that the industry can better serve guests.
From Silos to Full Integration
The first step toward making data more usable is integration. With so many different softwares built to serve different purposes, the hospitality industry is stuck with data silos. This leaves hoteliers struggling to simply manage the data, much less make meaning of it.
Take guest acquisition costs. This is just one essential data point among many that should inform sales and marketing decisions. Tnooz’s Sean O’Neill offers an apt metaphor for trying to sort out guest acquisition costs, saying that “at any given moment, you may not know what your tax cost for living in a particular place is. You usually have to pull information from multiple sources to calculate it.”
With so many points of distribution that have variable fees, it is still highly improbable that any hotelier has an adequate system for determining the true cost. Without this information, informed decisions are out of reach.
This idea applies to the whole of data. Most in the hospitality industry are scrambling to make sense of silos of data; however, if it is properly integrated into dynamic dashboards, apps and so on, it becomes instantly more usable.
This technology exists, but it will get smarter (i.e., more useable) and, as a result, will see more widespread adoption. Those that adopt will find they have a competitive edge in the speed and accuracy of analysis as well as decision-making.
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