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Big Data: Quality Over Quantity

The majority of C-level executives agree that they could better leverage data, but they don't necessarily need more of it.

The global volume of data is growing by the millisecond. Every minute, 98,000 tweets appear in feeds around the world and add to its vast amount of data -- 90 percent of which was created in the last two years.  

In a survey of C-level insurance executives on their use of big data, KPMG determined that nearly 70 percent consider data and analytics of critical importance to revenue growth, said Garrett Flynn, managing director, at this year’s KPMG Insurance Conference held in New York. The research also indicated that insurers could improve their use of big data and analytics but lack the data quality or appropriate structure to do so.

Many organizations do not fully understand the meaning behind big data, said Flynn. Plenty of businesses believe that big data is solely about massive data volume, but it is actually defined by its volume, velocity, variety, and validity. Its volume is constantly expanding, its velocity and variety are increasing, but its validity continues to wane.

Another common misconception about big data is that it is a siloed organizational responsibility. “Data is not just an IT issue. It’s not just a business issue. It’s an organizational issue.” He also debunked the idea that more information leads to greater insights. “More is not necessarily better,” he said, when it comes to big data.

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Flynn also addressed false perceptions concerning analytics, which businesses use to derive maximum value from their data. Analytics is not a responsibility left to data scientists, as many organizations believe, nor is it entirely about software and tools. The true meaning behind analytics involves enabling employees across the organization to formulate better questions and improve their decisions through valuable insight. 

Despite its popularity, there are many who believe that analytics is just another business trend -- a dangerous perception, Flynn said. “It’s table stakes. If you’re not doing analytics, you’re going to get left behind.”

Insurers’ analytics adoption is on the uptick; for example, 80 percent of insurers are using predictive analytics for personal auto. However, there remains room for growth. Half of consumers would use UBI to receive discounts on their premiums, Flynn said, but UBI devices are installed in less than 1 percent of American vehicles.

Flynn suggested that insurers use their available data to prevent claims through proactive property monitoring, improved risk profiles, and better consumer segmentation, all of which can contribute to growth, cost optimization, and customer retention. Big data also enables insurers to access new channels, capabilities, and methods of presentation.

For those still organizing their big-data approaches, he suggested developing a strategy that will deliver value every three months. This timeframe allows insurers to prepare for technological or business change. 

Kelly Sheridan is Associate Editor at Dark Reading. She started her career in business tech journalism at Insurance & Technology and most recently reported for InformationWeek, where she covered Microsoft and business IT. Sheridan earned her BA at Villanova University. View Full Bio

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User Rank: Author
10/2/2014 | 4:56:42 PM
No choice
I think part of the problem is that insurers may have no choice about having to deal with more data. That is, it is constantly proliferating. Even if a company determines there is more available data than it needs to accurate underwrite, develop products, etc. -- inevitably there will be a competitor (traditional or non-) that will welcome that additional information and be able to do something with it. So companies either will need to develop better ways to deal with an ever-increasing volume of data, or will have to become much better at making faster, smarter and more accurate decisions using less data.
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