For the last 9 months, “big data” has been hotter than a new Thomas Keller joint in Manhattan. Everyone’s looking to get a reservation, scrapping other plans, ditching budgets, and looking to get in without really knowing what they’ll get out. Early reviews from the pro critics are good, but the “public” vote is still out. A bit too “experimental” and not enough lovin’.
Sound familiar? If your org has yet to really dig into the “big data” phenomenon it’s likely because a) you don’t think it applies to you (it does), or b) you already have “analytics” shops set up in your business units and don’t have time to add something new to your fiscal plans (or budgets). Then there’s also the c) option – you’re small, like data, but don’t have the “capacity” for it.
For most, it’s not time yet
Right now big data has a bit of the 1% er stigma to it, and for good reason. You need a lot of money and horsepower to make the most of large, complex data sets whether you host that data in house or in the cloud. It’s getting easier, no doubt, but there are significant barriers for organizations that are still learning the basics of Google Analytics. (To be fair, you should be way past the basics – there’s simply no excuse for not excelling in digital marketing.)
And right now, most organizations would be much better served by focusing on just that – getting the basics of analytics and business intelligence right. Big data is for the margins of optimization – for the companies who can eek out millions of dollars for an uptick in a .1% conversion rate.
To play with the 1% metaphor a bit more, more folks are better off investing in the indexes and balanced mutual funds (basic analytics and business intelligence) than in the risky, derrivative-laden funds (Big Data). Sure you can get higher returns with the latter, but you also need to have enough to be able to lose every once and a while and the barriers to entry are quite high. The little guys don’t have that wiggle room.
The good news
There’s a silver lining behind all of the hoopla behind Big Data. It’s getting cheaper, and better understood and more competitors enter the realm. I was especially excited to see how Arizona State University is starting to use it to track and support students better while leveraging outside data (like Facebook connections) to offer up recommendations on courses, groups, and more.
In the meantime, it’s a big girl’s game. That gives you, the manager, the whatever, time to prioritize your basics, get your KPIs right, and find a good analyst (or two). The Godzilla of data can wait (but not long).