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Businesses turn to the sciences for answers in analytics

Businesses turn to the sciences for answers in analytics

Deloitte trends report finds more businesses are using what’s been applied with data analytics in scientific fields to solve their problems

What do scientists know about everyday business challenges? A lot more than you think, according to a new report. Deloitte Analytics Trends 2016 report has found data analytics in the science world can help solve business problems.

“Universities, research labs, and other science-focused organisations have been applying and refining analytics approaches to solve some incredibly complex problems through the years, in everything from molecular biology and astrophysics to the social sciences and beyond.

“Already we are beginning to see techniques borrowed from the world of science and applied to business challenges. In one example, an organisation leveraged tools used by DNA researchers as the keys to unlocking insights buried in tens of thousands of emails,” the report stated.

Deloitte said businesses using novel analytical techniques for scientific research and problem solving is still in the nascent stages, but sees this quickly picking up.

“There are plenty of signs of a coming explosion in shared analytics tools, techniques, and processes between the sciences and the business world.”

Some of these signs are apparent in the finance, airline, insurance and natural resources industries, according to Deloitte.

The consulting firm gave an example of a financial services client using text analytics to parse half a million customer messages a year, which its few hundred employees would not be able to do all of it manually. The company was able to use text analytics technology to pick up on key phrases and terms that could then be directed to the right person to handle.

However, the company wanted to take that a step further. It turned to scientists working in bioinformatics who use advanced techniques to match sequences of DNA, which is represented by a series of letters in non-random patterns.

It was able to find a link between the algorithms used for DNA sequencing to more efficiently identify different customer messages and prioritise them, going beyond just finding key phrases and terms.

“This organisation cracked the code on thousands of messages received every day. This approach was deployed in the organisation’s workflow to tag, route, and prioritise messages, allowing the company to get its customer interactions back under control.

“Any single one of them [messages] could contain information that causes serious trouble for your organisation if not handled quickly. If the wrong message falls through the cracks, you could be exposed to a ton of risk immediately,” the report said.

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Tags data analysisbusiness analyticsdata analyticsmachine learningstatistical analysisscientific research

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