Big Data – Does it apply to all hotels?
Gartner, in its IT glossary , defines Big Data as “data sets of large volume, speed and/or variety, which require innovative and profitable forms of information processing, allowing an amplified vision for decision making and automation of processes” (free translation).
The definition of the 3 V's, as it is widely known, is due to volume (the amount of data), speed (the speed of input and output ) and variety (diversity of types and sources of data). And as expected, these 3 V's are also present in the data that hotels have access to.
Hotels store immense amounts of data in their internal systems - PMS ( Property Management System ) , CRS ( Customer Relationship Management ) or ERP ( Enterprise Resource Planning ). Hotels have access to a funnel for guest acquisition by analyzing their website statistics. Hotels have access to the impact of campaigns/advertising through tools such as Adwords or Facebook. Not to mention other public data sources, which can also be extremely important for hotels, such as comments and reviews , meteorology, competitive intelligence (prices and social reputation), currency exchange rates, among many others. other sources.
It is understandable that hotels want to take advantage of Big Data , using the massive amounts of information at their disposal to build better descriptive models and thus understand patterns, trends or anomalies , by guest segments and other dimensions, to improve guest segmentation . or simply, to identify unknown relationships . However, the true potential of Big Data lies in Predictive Analytics - that is, in the development of predictive models, such as accommodation demand and revenue forecast, reservations with a high probability of cancellation, guests who may return to the hotel, guests willing to accept relocation or other alternatives in overbooking situations , among many others.
There are, however, still questions that must be addressed before these data become information and subsequently knowledge on which action can be taken. Namely:
It is common for data to fall short of what is desired in terms of quality, with missing, duplicate or incorrect values. For example, it is common to find multiple profiles for the same guest in hotels; or find guests whose profile has several unfilled fields or incorrect information, such as incomplete addresses, outdated phone numbers or incorrectly classified segmentation. Without good data quality it is impossible to extract reliable information from them .
To timely process large volumes of data from different sources, not only good computing capacity is required, but also storage capacity . This translates into a considerable investment in technical infrastructures to extract, transform and process data.
None of this can be achieved without collaborators dedicated to this task, such as data analysts , data scientists or at least managers with good analysis skills , essential for running models, understanding the analysis and making decisions based on them.
These are limitations that can be overcome by investing in internal resources or hiring them externally. The important thing is that the strategy to take advantage of Big Data is well outlined.
Still, it is expensive to implement a Big Data strategy , which does not make it easy for many hotels to access. Currently, these costs are only within the reach of some multinational hotel chains, but the truth is that with the availability of standard , more accessible and cloud- based solutions , the market is regulating itself, ending up forcing prices to fall, contributing to that small chains or brands, as well as independent units, can take advantage of Big Data.
And it is for this same reason that anyone who does not catch the Big Data train will most likely lose their level of competitiveness to the more expeditious competition.
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