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It’s an election year in the United States and it’s also time for the nation’s annual college basketball “March Madness” event. Both contests bring out the data geeks who lay claim to having the best predictions about which side will take first place; whether it’s hardball politics on the podium or roundball on hardwood courts, understanding the troves of Big Data involved gives the smart money the best insights into who will win and lose.

As a citizen of Great Britain, I do not take sides in either contest. However, I am rather partial to the data geeks who, increasingly, are helping democratize the use of analytics in daily life. By exposing the average citizen to the value of analytics, these data geeks are not just improving the public’s understanding of their world, they are fostering an interest in the field at a time when we need more analytics experts.

For example, computer scientists at the University of Illinois have created a website that uses analytics to help college basketball fans pick the most likely winners in the NCAA Men’s Basketball Tournament. At the same time, the New York Times has hired a well-known psephologist to write a regular blog about Big Data and politics. Both efforts not only raise awareness of the use of data in our lives, they underscore the accuracy analytics brings to an event before any hoops are shot or votes are cast. They show, with reliable track records, that using analytics can improve your understanding of not just the past, but of the future as well. That’s very appealing to people.

Hollywood also gave a boost to understanding analytics when it touted the sports movie Moneyball as an Oscar contender for Best Picture at this year’s Academy Awards. The movie raked in more than $100 million in ticket sales where a few million filmgoers witnessed Brad Pitt’s character discuss the importance of analytics in picking the best ballplayers for the least cash, a classic business intelligence decision process. As a Tinseltown flack might say about analytics, “You can’t buy that kind of publicity.”

More important than high-profile exposure of analytics to wider audiences is encouraging the broader use of the technology. Arguably, no one has done a better job at putting BI tools into the hands of everyday people than Google. In addition to publishing blogs and articles aimed at small business users to help them exploit their own business data, it has posted ten, simple how-to videos targeting analytics tyros. Like the tools themselves, Google offers the instructive videos for free.

I suspect that the current popular interest in analytics will continue because data increasingly has become intertwined with our modern lives. More than ever, we see ourselves and our actions in the context of data. And I hope that the hype that Hollywood movies, election cycles, and sporting events bring to the technology translates into genuine interest among younger people to study the underlying math in analytics. As we all know from the now-famous McKinsey report on Big Data, we face a shortfall of hundreds of thousands of analysts, data-savvy managers, and analytics experts in the coming years; a shortfall that could put many enterprises at a competitive disadvantage.

Without attracting more young people to the field, the competition for the few skilled practitioners available will become heavily weighted in favor of only the largest and wealthiest organizations. But if all of this recent publicity does, indeed, spur more students to major in mathematics and statistics, the building blocks of analytics, then the democratization of analytics will have been a great success at more than just the box office.