I’m at the American Marketing Association’s 2014 Analytics with Purpose conference in San Diego today. I’ll be speaking this afternoon on understanding customer needs with digital analytics. This morning, I’m attending sessions, which started with the keynote by Mark Earls, author of I’ll Have what She’s Having: Mapping Social Behavior. This was one of the better keynotes I’ve heard in a while.
The premise: big data = magic. Magic! He started with a fantastic quote from Arthur C. Clarke “Any sufficiently advanced technology is indistinguishable from magic.”
That blends together with something I referenced in my talk about “data artists vs. data scientists” at SUPERWEEK. In an article she wrote for Forbes, Judith Magyar, Strategic Communications Director, SAP Platform Solutions, notes that “If there’s one thing that gives a job an indefinable allure, it’s that no one really knows exactly what you do, or how you do it; they just know you do something important…”
Did you catch that? No one really knows what a data scientist does, but it must be important.
Data science is all about Big Data these days. And if I am hearing Earls and Clarke correctly, then something so technologically advanced that nobody understands it is akin to magic.
That sounds about right when I look at how most “big data” technologies are marketed — buy this thing, and magic will happen. Collect more data and you’ll be amazed by what it can tell you.
But it isn’t magic.
Lots of data and powerful tools ultimately won’t make a difference — the difference will come from people who know how to use those tools and who know how to make meaning of that data. It’s people that will apply the knowledge from such data to their business context to find meaning and drive action. Ultimately, it is action based on that data that leads to progress.
So, the question really isn’t about having big data or advanced technology… or magic. The question is about people: do you have the right people on your team to work magic with that big data — magic that leads to change?