Is there really a shortage of data scientists? The conventional wisdom — based primarily on a 2011 McKinsey Global Institute study — is that there aren’t enough trained analytics professionals to meet current demand, a situation that’s expected to persist through most of the decade.
Many enterprise decision makers trying to build their own analytics team are struggling now to find trained data scientists and data analysts, which lends credence to the “shortage” theory.
But not everyone believes there’s a shortage of data analytics talent. Many data science experts argue that enterprises are making two mistakes: 1) They’re looking in the wrong places, and 2) they’re not taking the long view.
Regarding the latter, remember, analytics is an emerging field; thus it’s simply unrealistic to expect enough fully formed data scientists to currently exist to fill demand. This, however, doesn’t mean there is a lack of data science talent; rather, there’s a lack of trained data professionals.
The trick, then, is to find and develop that talent. Which gets to mistake No. 1 — looking in the wrong places. Instead of relying on headhunters, graduate schools and online job boards to find data scientists, enterprises should first look within to find employees who have the skills to become good data analytics professionals.
Here’s how Gartner research director Svetlana Sicular makes the case:
“Organizations already have people who know their own data better than mystical data scientists — this is a key. The internal people already gained experience and ability to model, research and analyze. Learning Hadoop is easier than learning the company’s business. What is left? To form a strong team of technology and business experts and supportive management who creates a safe environment for innovation.”
Easier said than done, no doubt. But the best professional sports teams aren’t built overnight; they rely instead on a process that requires a clear goal, patience, and an ability to spot talent. It makes sense to start with the talent right in front of you.