Business decisions didn’t used to be numbers-based, but now the pendulum is swinging to “In God we trust, all others bring data”, for good reason. One of the best analogies I’ve heard is that a company built on analytics is like an animal while a company with no analytics is like a plant. Analytics enables the former to respond dynamically to opportunities and dangers while the latter can only sit and wait hoping that nothing bad happens. Back when everyone is a plant (i.e. not analytical), you’re probably fine being the neighboring tuft, but the day one of them turns into a cow (i.e. becomes analytical), well, good luck.
This evolution is to a great extent accelerated by the proliferation of consumer data and the many good things you can get out of it. While you can certainly observe customers in store (people still do), it is infinitely more scalable to use web mining to “observe” thousands perusing the net, estimate what stage they are at in their purchase process and tailor your messages accordingly. Few would have heard of Signet Banking Corp but many are familiar with its spin-off Capital One, the 8th largest bank in the country – and one that was built to a great extent on the strength of analytics.
But just like anything with massive impact, analytics can also go massively wrong and the failure very often has less to do with the tool itself than with the one wielding it. The only thing worse than no data is bad data, and the only thing worse than bad data is bad interpretations. Here’s how you go down that slippery slope and how you can climb back up: Read More »