5 Keys to Asking Better Questions of Data Scientists - InformationWeek

Some enterprises struggle to drive business value from data science efforts because the business and data scientists are not communicating or collaborating well. Here are five things you can do to improve the cross-functional relationships and ROI.

Companies in all industry sectors have been clamoring for data scientists for the past couple of years, but some of them struggle to drive value from their efforts once they have data science talent on board. Common scenarios are shoving data scientists into a corner, hoping that they'll to do what they do best. In some cases, there's little or no alignment with business objectives and strategy, and not enough cross-functional collaboration.

As a result, data science can become an academic exercise that's not really driving business value or not driving as much business value as it could. It's not that data science doesn't work; data science and data scientists need to be integrated into the business.

Even when data scientists and business leaders come together, there are often disconnects in thought processes and language. "Real" data scientists (the ones with PhDs or master's degrees in math, statistics, and related fields) are often characterized as technically brilliant but poor communicators.

Business leaders can also cause communications to break down, however. The latest in-vogue business jargon may sound cool, but it may not actually convey the kind of substance and context data scientists need to do their jobs well.

"I appreciate the conversation. It’s the silence that bothers me," said David Goldberg, VP of Data Analytics at Prudential Financial. "We have people who are not so quantitatively oriented who see a lot of numbers and may be afraid of asking something that doesn't seem that relevant. I think there are some people who get intimidated by numbers."

Following are a few things you can do to drive more value from your data science efforts.