by Stuart Rose
Last week... you learned that more and more data should in theory give us greater insight into our customers and their needs. This week... read about how new tools and techniques that help interpret data are becoming mainstream.
Low cost route to scale
Data is often seen as a competitive differentiator. However, in today's big data environment, is having too much data really a problem? Many organisations find it too costly to store all the data and too time-consuming to analyse it.
For a growing number of organisations, the answer has been to take advantage of distributed processing technologies such as the Hadoop file system. Hadoop is an open-source software framework for running applications on a large cluster of servers. Since Hadoop runs on commodity hardware that scales easily and quickly, organisations are now able to store and archive a lot more data at a much lower cost.
This is good news for IT, but it should also be music to the business professional's ears. No longer does data need to be destroyed after its regulatory life to save on storage costs. No longer does the business analyst or data scientist need to limit their data analysis to the last three, five or seven years.
Seeing the value
New tools and techniques which help to interpret data are becoming mainstream. In particular, data visualisation tools combine different graphical techniques to enable users and insurance executives to better understand the stories their data is telling. Companies taking advantage of data visualisation are able to extract maximum value from their data and take their businesses to new heights.
But what do organisations hope to derive from the increased volumes of data they collect? The end goal depends very much on the insurance company, the market conditions and the strategic imperatives of a given carrier. Organisations want more business value from big data, and analytics is an important route to value.
Analytics for better, faster business
Big data technologies are relatively new and still maturing. However, combining the power of analytics with distributed processing technologies like Hadoop will help insurance companies to transform big data to make better business decisions, faster. It will enable statisticians, actuaries and business users to examine and analyse more complex problems than ever before.
The ability to quickly analyse big data can redefine so many important insurance business functions, such as risk calculation, price optimisation, catastrophe modeling, fraud detection and customer experience. It's hard to imagine any forward-looking company that is not considering its big data strategy, regardless of actual data volume.
Insurers have long seen data as a source of competitive advantage. But data alone is worthless. It is insights derived from the data that matter and with the emergence of big data the possibility for deriving insights is increasing dramatically. Data can be the difference between success and failure. Better data leads to better decisions, which ultimately leads to more profitable business. Today, your return on information is just as important as the return on investment.
Stuart Rose is the Global Insurance Marketing Director for SAS.