Usually big trends in business follow on the footsteps of new research or data staking the claim of transformational ROI. Whether it’s a system (HRM, CRM, ERP/M), a process (six sigma) or a style (management rotations, profit sharing) just about all of these major business trends came about after extensive trial and error, piloting, testing, and researching. We live in a fundamentally changed world if you didn’t notice.
Everything that is now “social” went just about backwards – all of a sudden “social” was producing disruptive amounts of data that cut across organizational units and so a new business trend emerged… big data.
As we’re just beginning to see the way big data plays out across different functions and industries, it got its start in some way as a way to find ROI for everything “social”. In fact, as Dion Hinchcliffe pointed out last month, just about everyone is trying to buy their way into “social” (but more on that another time). Whether it’s because staff expect it (they use it in their personal lives) or it’s how their customers are spending their time (mobile, social, both), for- and not-for profit organizations have dramatically amped up their digital analytics teams to make the most of the change.
But there’s a bigger question that comes first: is Big Data for you?
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.
I’ll tell you a secret – I was a history major who thought my chosen path had as little to do with data as Jackson Pollock’s masterpieces did (although I do see some nice parabolas). As I changed directions my senior year and joined a group of incredible and passionate people to “teach for america” there was data everywhere. It wasn’t what I expected – little did I know I was walking into one of the most data-driven organizations I’ve ever heard of or worked with.
In recent months, we’ve seen a growth of protests against and arguments for the rise of value-added test data. The big question? How is value-added data (and the need to get it) leading us in the wrong direction or making us better educators? The basic theory goes something like this: value-added data can be good, but only at the macro level over longer periods of time. Just about everyone actually agrees on this point, but that yearly test data seems too good to give up and drives hard battle lines.
So what was different 10-15 years ago when standardized tests were used as the macro indicators that they are?
What does it mean to be data driven? Hopefully your first thought wasn’t a dashboard with pretty lines – a way to check your PTG. Being data-driven in some ways is harder than ever, not because of the the type of data or analysis needed, but because of the need to simplify the tidal waves of it coming from all spaces around us. While Business Intelligence is nothing new, we have more real inputs into our business models than before, and thanks to more accessible CRMs and so forth, more ways to pull up and look at that data for the lay worker. This is ultimately a good thing, but not so good until you really know how to use data, and that starts not by getting your degree in statistics or advanced math, but by getting in the right mindset about how you should be using data in your role.
First, a story.
Somewhat surprisingly, it seems like the only area in the non profit sector where big data is making much of a splash is in marketing with social media taking the spotlight. It’s a shame we’re not seeing more out of something like mission- or fundraising-oriented analysis. Here are a few good picks on the topic:
A recent post about Linsanity from the Enterprise Irregulars crowd went almost unnoticed. Not a lot of retweeting. Maybe because NY basketball isn’t what most folks in big data are paying attention to these days, or maybe it’s because Lin is a perfect Black Swan. However you cut it, Jason Corsello ends his short post with a question: “why aren’t most companies analyzing their employee data to find the rising stars?” Good question.