Big Data: Analytics Are Essential to Corporate Profits

Analytics are essential to corporate profits today.

(My past comments on this include a review of Competing on Analytics, a link to Thornton May's comments on analytics, and my own thoughts on the growing need for business analytics.)

McKinsey Quarterly has a series of articles starting off with, "Are You Ready for the Era of Big Data." That article is great getting-started piece. It's followed by Competing through Data: Three Experts Offer Their Game Plans, which has some real gems from Professor Erik Brynjolfsson of MIT:

Our research has found a shift from using intuition toward using data and analytics in making decisions. This change has been accompanied by measurable improvement in productivity and other performance measures. Specifically, a one-standard-deviation increase toward data and analytics was correlated with about a 5 to 6 percent improvement in productivity and a slightly larger increase in profitability in those same firms.

OK, I usually try not to throw out terms like standard deviation in this blog, but if you don't have a grasp of what this means, you are not ready to work in an organization that uses analytics. Which means, you are not ready to work in a corporation that will grow in the coming years. It wouldn't hurt to dust off that old college statistics textbook. If you didn't take statistics, head down to your local community college and get learning.

Here's another interesting comment:

A lot of companies think they’re using data, and you often see bar charts and pie charts and numbers in management presentations. But, historically, that kind of data was used more to confirm and support decisions that had already been made, rather than to learn new things and to discover the right answer. The cultural change is for managers to be willing to say, “You know, that’s an interesting problem, an interesting question. Let’s set up an experiment to discover the answer.”

I talk to a lot of CEOs and senior executives, and I believe I hear about 50 seat-of-the-pants decisions for every data-driven decision.