Tech expertise is not the only skill needed to be a data scientist
For decades, amateur students of psychology have riffed on the so-called split brain hypothesis, which posits that creativity is housed in the right brain, while the left brain is responsible for analytic functioning.
The fact that I’m sitting here writing sentences instead of lines of code is a good sign that I’m a right brainer; but if you think that means I’d have no business sitting in on a Big Data project at a major marketing firm, you’d be missing one of the emerging trends of analytics hiring.
By one estimate U.S. companies will need 1.9 million more IT workers by 2015, and many, if not most of them will be involved in Big Data. But it’s a mistake to think all of them will be quants.
That’s because unlocking the benefits of Big Data is more than an exercise in technical prowess and requires a diverse team of individuals, including creative types who are able to think outside the box and rely on insight more than analytics.
According to Scott Gnau, president of Teradata Labs, pigeonholing Big Data talent into a narrow skill set limits your hiring pool and, more importantly, marginalizes the “artist explorers” who help turn data into operational strategy and provide direction for successful innovation.
Gnau, who was interviewed recently by InformationWeek, says that while left-brain technologists are vital to advancing any analytics initiative, they wouldn’t get very far without some right-brainers to provide “visionary direction” to the project. As to what those people look like, Gnau says:
“It’s going to be someone who’s completely operationally focused. It’s going to be someone who’s a little more creative and strategic in the way they think. Typically I see many of them showing up in the line of business and not in the IT department.”
In short, these are people who can see past the numbers to the people (consumers) generating them and draw broad inferences from trends and patterns.
During a panel discussion at a 2012 conference on analytics and creativity hosted by the ESCP Europe Business School, Judy Bayer, Director of Strategic Analytics for Teradata Europe, Middle East, Africa, described the importance of tapping creative sources for Big Data marketing projects.
“One of the problems we’ve seen is that sometimes analytics themselves and the use of data isn’t sticky enough within organizations and that’s just because of taking a very technical view,” she said. “Without creatives involved, there could be short term successes, but where there is creativity it tends to get stickier. Those organizations that really use creativity get the largest value.”
Perhaps no one embodies the intersection of creativity and Big Data quite like Nate Silver, the famous (or infamous depending on your politics) New York Times statistician-columnist who predicted the 2012 presidential election with near perfect precision. In a recent profile by Fast Company, writer Jon Gertner described Silver’s take on the creative expression of data:
“I think there are two types of creativity,” [Silver] says. The first is what he calls “pure expression”–a phrase to describe the work of musicians, poets, actors, dancers, and the like. “The other kind is finding different ways to approach and solve a problem. I’m not sure of the first kind, but I think I have a lot of the problem-solving type of creativity.”
When you add that kind of thinking to the equation, the skills gap may not be as critical as we think. Once we start thinking outside the box and broadening our ideas about what a Big Data specialist is supposed to look like, the possibilities are endless. Students who major in the social sciences – fields like psychology, sociology and political science – are trained to draw inference from numbers and turn statistics in theory (or campaigns depending upon where they sit). Add in all the former English majors working in coffee shops and the field of creatives expands considerably.
Analytics is great for answering questions, but it takes creative minds to know what questions to ask.