Business Focused Analytics

I've been working in the field of digital analytics for the past few years. At my current organization, I have had some success in growing the analytics practice for three of our major clients. Starting off a couple of years ago, with a team of 1-2 people, we have a team of 12-15 working on those clients today. And I have learnt a few key lessons along the way. So here are a few ideas that have served me well:

1. Solve business problems, not analytical problems: As practitioners, we should remember that our end goal is to serve the business interest. We should ensure that our work adds value to the end goals of the business-whatever those may be. It is often tempting to lose sight of that fact, and wander down a deep analytical path that may be very interesting, but produces results that are not actionable in the real world. So before starting any analysis, ask the question: What do I intend to do with the results? And if the answers don't come through easily, reconsider your path.

2. The analysis is not the hero of your story, the business problem is : It is hard to imagine telling a story with data, but that's what we do, day in and day out. Effective storytelling is what turns great analysis into business transforming action. However, in doing so, keep the focus of your story on the business problem you're solving. That will make the analysis you did to solve it very interesting to the audience. As an example from Hollywood-would the action(the analysis) in the Terminator movies have been as interesting as it was, if the focus of the movie (the business problem) had not been preventing the ultimate annihilation of the human race by self aware robots? No one watches action for the action's sake.

3. To be effective, the analytics need not be complicated : Some of my most interesting insights have emerged from some of the simplest analyses that we have performed using Excel. In the age of big data, it is easy to imagine that terabytes of data will give us all the answers-and while that may be true some day-real insights lie not in the volume of data but in the art of effectively manipulating it. And with the right mindset, your tool set may often not matter.

4. Drop the jargon, tell them what it means for them : Data Analytics is complicated. There are a number of things that need to be considered, approaches to be used/discarded etc. But the end results should always be simple and easy to digest. I often think of our jobs being akin to those of physicians. They are the experts, knowing the intricacies of medicine, but when they talk to the patient-all the patient wants to know is "What's wrong with me, and how do you recommend I fix it". Leave the complicated jargon for the fellow analysts. Talk business with the business folks. And trust me, they will listen.