To Be Honest, Here’s Why I Really Hate Analytics and Big Data

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Dec 5, 2014
This article is part of a series called Classic TLNT.

Editor’s Note: Readers frequently ask about past TLNT articles. That’s why we republish a Classic TLNT post every Friday.

Don’t kid yourself – you hate analytics.

It wouldn’t be politically correct to say that you hate analytics, so you won’t. That’s why I’m here.

You hate analytics because using them in your organization increases accountability.

  • Increased accountability = Increased stress.
  • Increased stress = Increased job dissatisfaction.
  • Increased job dissatisfaction = Increased turnover.

You see the cycle, right?

The dark side of analytics

So, who likes analytics? Bosses. Why? Because they like having increased accountability on you. It makes them feel all strategic and shit.

When analytics are used against you like a weapon – they suck. Too many organizations use analytics as a weapon to judge your performance. Leadership justifies this because ultimately they are held accountable to the ultimate analytic – the bottom line. So, they feel you should be held accountable too.

We would like analytics better if they weren’t used to bash us over the head, and instead, if they were used to help make us better, to help us improve, to help us understand.

Harvard Business Review had a great post on this subject: The Real Reason Organizations Resist Analytics by Michael Schrage:

The evolving marriage of big data to analytics increasingly leads to a phenomenon I’d describe as “accountability creep” — the technocratic counterpart to military “mission creep.” The more data organizations gather from more sources and algorithmically analyze, the more individuals, managers and executives become accountable for any unpleasant surprises and/or inefficiencies that emerge.

For example, an Asia-based supply chain manager can discover that the remarkably inexpensive subassembly he’s successfully procured typically leads to the most complex, time-consuming and expensive in-field repairs. Of course, engineering design and test should be held accountable, but more sophisticated data-driven analytics makes the cost-driven, compliance-oriented supply chain employee culpable, as well.

This helps explain why, when working with organizations implementing big data initiatives and/or analytics, I’ve observed the most serious obstacles tend to have less to do with real quantitative or technical competence than perceived professional vulnerability. The more managements learn about what analytics might mean, the more they fear that the business benefits may be overshadowed by the risk of weakness, dysfunction and incompetence exposed.”

It’s really more about CYA

I recall a very technical business acronym I was taught in my Master’s program called: CYA. Be very careful with your big data initiatives because many turn into CYA projects.

If I can show these analytics, it will show why this major issue doesn’t have anything to do with my department but everything to do with another department. Days To Fill reports are filled with CYA. “It’s the hiring managers not getting back to us in a timely matter to set up interviews – this is why are Days to Fill is so high.”

Accountability sucks when it is happening to you. It’s great when you’re holding someone to it.

Big Data might be the biggest weapon in your tool box – be very careful who you point it at.

This was originally published on Tim Sackett’s blog, The Tim Sackett Project.

This article is part of a series called Classic TLNT.
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