Why data science is the next big disruptor

Sponsored By: IBM

Who would have thought that a mathematical model to predict earthquake aftershocks could be used to reduce crime in California? Data scientists came up with the novel approach and produced amazing results.

Police in Los Angeles and Santa Cruz wanted to find out how to deploy their forces to the right places at the right times to cut crime. The answers came when data scientists put 80 years of crime statistics into the aftershock model they found online. The results? Violent crimes were reduced by 21 per cent, and the number of burglaries fell by 33 per cent.

That’s the kind of thing that happens when data scientists use collaborative tools and analytics to pull useful insights from the data. But, according to McKinsey, much of the value of the reams of data being created today remains untapped.

“Every problem is a data problem,” says Rob Thomas, vice president of product Development for IBM Analytics. “The people who are going to have the biggest impact in this world are people that know what to do with the data.”

A profound impact
The impact of data science and machine learning will be significant for business, says Gartner, and can be “critical for differentiation and sometimes survival.” McKinsey states that “data driven organizations are 23 times more likely to acquire customers, six times as likely to retain those customers, and 19 times as likely to be profitable as a result.”

Gartner Research outlines five ways data science can improve, or disrupt, business.

First, organizations will be able to disrupt and innovate by using data to solve old issues in radically new ways. Think of the true story behind the movie, Moneyball, says Gartner, where data was used to question the old method of evaluating performance in baseball. Similarly, businesses will have increased ability to challenge the status quo with new solutions. For example, data science can be used by airlines to more accurately predict passenger no-shows.

Businesses can use data science to explore unknown patterns. It helps them discover what drives certain outcomes, such as equipment failure or customer satisfaction. It can also be used for “firefighting” to identify causes of a sudden crisis, such as a drop in profitability.

Finally, data science helps to continuously improve existing practices, as in the case of an F1 racing team that uses real-time data analysis to adjust a car’s performance during the race.

Data science is a team sport
An open, collaborative environment is at the heart of data science, says Nancy Hensley, director of analytics offering management at IBM. The business unit must be engaged to ensure that the starting point is a clearly identified business problem or opportunity.

Since no single tool can do everything, there should be a variety of open sourced tools available, Hensley says. “You want to invite other collaborators on projects so you can iterate faster,” she says. “To have speed to market, you can no longer be limited to sources within your organization. You need to use skills from all over the world.”
According to McKinsey, there is growing urgency to start using data science. Leaders are taking the advantage and those who hesitate face the risk of being disrupted.

For more, click here to download “Master the art of data science with IBM Data Science Experience”


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Sponsored By: IBM

Glenn Weir
Glenn Weir
Content writer at IT World Canada. Book lover. Futurist. Sports nut. Once and future author. Would-be intellect. Irish-born, Canadian-raised.