What’s often missing from the big data echo chamber (and let’s face it, it’s become a bit of one, with people confusing metrics and analytics available on any dashboard with Big Data) is what problems we’re trying to solve. Vendors, and I proudly wear the badge of vendor, are part of the bigger problem. Vendors have sold customers a bill of goods that doesn’t match the true value of big data. In fact, the vision being sold today is that of big data as a solution that will show you where your organization has missed the mark, a barometer if you will.

But really big data can’t tell you anything unless you know the true questions you want to solve. It’s the ultimate in companies chasing after the causation equaling correlation and missing… hard. And this is a problem for the simple reason that companies control a lot of data and use it to make big decisions that affect people’s lives. So the reasons that a VP of Talent Acquisition or a CFO give to Broadbean or any data analytics platform provider have to be thought out first before the platform is built.

That’s right, I’m saying that big data has to be bespoke for it to work properly. You must identify the important questions, the never ending issues in your business, the things that keep your executive team up at night and then solve for x.  

Here are the issues with how big data is being discussed today:

It’s esoteric. 

While some people are talking very sensibly about big data because they understand its applications beyond HR and even BI, those people aren’t writing a blog post a day about the subject (yes I sense the irony). The reason it’s easy to digest the simple blog posts is because unlike big data, they aren’t overwhelming and can make you feel very secure, so the real value of big data is being obscured. The good information takes time to identify and dig up, which is why so few people take the time to listen to the people who understand the implications of big data.

It’s hard. 

It’s not that tough to start a big data project but as Clair pointed out, lots of projects fall apart in the middle. Big data is no exception to that rule, in fact, these projects are even harder to keep together because as we’ve discussed, data is messy and it can be very difficult to make sense of it all. As I’ve said before (not so cheekily) big data is called big data because it is BIG. Many organizations get halfway through the project with one manager and when that person (who often has additional duties) gets pulled away, the next person starts all over again with his or her own agenda and process. It’s HARD to get from start to finish without a dedicated, strategic plan that accounts for hiccups in the implementation process.

It’s bass-ackwards. 

One of the fallacies of big data is the thought that if we look at these points, we’ll see something interesting. But that’s the wrong way around the problem. You need to identify which levers need to be pulled in your organization before adding the big data layer on top of that. Simpler translation? Instead of looking at data to find what’s ailing your recruiting function, you need to look at your recruiting function, find out what you want to fix, identify the solution you will take if your theory is confirmed and then dive into the data. Make sense?

If I had to distil our thought process while building BDAS for the enterprise it’s this. Big data means nothing if you don’t have the right conversations. Before, during and after.

Bio: Kelly Robinson

Kelly Robinson is the founder and CEO of Broadbean Technology, a sourcing and recruitment technology company. Broadbean Technology has created a strong global presence with offices in the US, Europe and Australia The company remains true to the core fundamentals of its inception: “Keep it light and fun while getting the job done!” Kelly writes about leadership and culture, as well as reducing friction in the candidate experience.

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Comment by Katrina Kibben on June 30, 2015 at 12:26pm

Appreciate all of these points and the use of the word "backasswards" --> spot on. Thanks for sharing!

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