A Practical Guide to Big Data for Hotels
By Kelly McGuire Vice President, Advanced Analytics, Wyndham Destination Network | March 08, 2015
Big data has become a big buzzword. Like any buzzword, all of the talk about big data has created big confusion in the marketplace, and it can be easier to tune it out than to take it on. The reality is, whether you want to call it big data or not, there are now new opportunities to take advantage of data to drive decision making and ultimately competitive advantage.
Identifying these opportunities and understanding what to do about them is the challenge facing hotel managers today, particularly in revenue management. It is time for some plain speaking and practical advice about this complex phenomenon.
What is Big Data? A Reminder
Gartner defines Big Data as occurring: When the volume, variety and velocity of data exceeds an organization's storage or compute capacity for accurate and timely decision making (Gartner 3-D Data Management 2001). The reason why big data has become a big deal is not just that we have suddenly have a lot more data, but rather that the technology to capture, store and analyze that data is now not only available, but also accessible.
Innovations in technology have dramatically improved the speed at which data is gathered and processed, and driven down the cost of data storage as well. Big data, therefore, is not a singular thing, but represents a variety of opportunities for organizations to improve business and drive innovation.
Hospitality transactional data sets are by no means as large as an online retailer or a credit card company's might be, but in many cases, they have started to stretch the limits of the legacy technology environment. Reports and analysis are bogged down, and sacrifices are made, both in the storage of data and also the analytics run against it. This is certainly a missed opportunity. However, in my opinion, the biggest challenge that hospitality companies face is in the variety and velocity part of the definition. Useful, even critical, information is coming to us in a variety of new formats, many that we have not had to deal with before, like text data from reviews, click stream from web interactions, or location data. Integrating this unstructured data into a traditional relational database is difficult, if not impossible. Further, much of the data, like tweets and location, is stale nearly as soon as it is created. If you don't have a mechanism in place for taking advantage of these fast moving data sources, opportunities will be missed.
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