The Big Data concept, so fashionable these days, refers to the management of large amounts of digitally stored information. This very generic definition shared by all, diverges when we begin to talk about what Big Data is or is not and what are the most frequent applications of this technology.
We currently have vast amounts of information. To give some examples, today in the world there are more than 180 million blogs and more than 89,000 million emails and 140 million tweets are sent daily.
Thinking about the insurance sector, currently insurers can have new sources of information unthinkable to date: GPS installed in vehicles, sensors in smart buildings, body sensors (very useful in health insurance), etc.
The growth of available information, as well as the technological development that allows us to analyze it, opens the door to extracting knowledge from this enormous amount of information. Today it is already possible to make decisions and base business strategies on the knowledge provided by Big Data.
Being Big Data a very broad concept, at CognodataConsulting, an international consulting firm specializing in customer strategy, we understand that to talk about Big Data it is necessary that the following properties, better known as the 3 Vs , be met :
- Volume: Access to large volumes of information.
- Speed: High speed in the generation, storage and analysis of data, collected both in real time and offline.
- Variety: Access to various types of data, which can be structured or unstructured.
It is common to think that to ” do Big Data “, it is necessary to work with external data from different sources (linkedin, facebook, twitter, etc), but this is not the case. What defines what Big Data is are the 3 Vs and not the origin of the data, nor its typology.
Big Data initiatives in companies must add value to the business , so that Big Data capabilities translate into tangible competitive advantages for the organization.
Specifically, for insurers to benefit from the competitive advantage provided by Big Data, they need to implement initiatives such as those described below:
- Implementation of analysis tools for calls to customer service.
- Digitalization of expert reports and their analysis, using textmining capabilities.
- Analysis of external information generated on social networks to identify complaints and service problems.
- Improve the perception of quality and the value of the products, by not applying strong discounts on the original price.