Problem Solving means understanding our markets and operations better than the competition. It means connecting the dots between the little things we do every day and the outcomes we hope to produce. It means understanding causal relationships – at a detailed, actionable level. It powers superior decision making.
Since we live in the Age of Information, this should be increasingly easy. But I think the opposite is true. Because we’re surrounded with so much data, we fall into a false sense of complacency. “Of course we have the data we need – just look at all our ‘1s’ and ‘0s’!”
But why do we collect that data? How do we use it? And what insight does it provide?
All data, presumably, was chosen to be collected for a specific purpose. It was needed either to monitor parameters important to running the ongoing business, or to address a specific problem plaguing the business. The former would be collected continuously, without end, the latter temporarily. This is a thoughtful, efficient, structured approach to defining our data needs.
Is it how we actually approach data in our work? I don’t think so.
More often than not, our data needs are defined by the software and/or systems we purchase (“This is what data-driven companies collect; we’re a data-driven company; therefore, we must collect this data.”), or through brainstorming (“Let’s think of all the data we might possibly need.”) Our data is thus defined by others and endless possibilities, not OUR specific needs. We end up awash in data. And spend our time analyzing it whether it’s relevant or not, trying to fit it to our problems as they arise. This is backwards, inefficient and ineffective.
So, what data are you analyzing? What problem is it helping you solve?
Problem first, then data.