Our work so far has built what you might think of as a company-wide innovation funnel, with the capacity to manage floods of behavioral data and simplify collaboration, governance, and metadata at scale. But especially in large organizations that may have hundreds, or even thousands, of people with “analyst” in their job titles, we need to make sure this broad user community has the right tools to actually do something with all the insights being generated by data. We need, in other words, to turn insights into action.
“There will always be high-end data science issues, but most business problems can be solved by the business users,” said General Motors chief data officer A. Charles Thomas. “Those business managers need to understand the levers to pull, but not necessarily know all the engineering that goes into the analytics.”
“If you want people to stop submitting tickets and get them to start thinking more analytically on their own, you have to package up the complexity into accessible tools,” Charles told us in an interview. “That’s essentially what we’ve done here. We’re giving them the means to follow that spark of curiosity that might get them saying, ‘Hmm, there’s a spike over here . . . an aberration over there. . . . Let’s experiment a little to figure out why.’”