What came first the data chicken or the data egg? Calling time on #bloodyuselessdata

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The modern digital world is awesome in so many ways. But sometimes I get sent a piece of data, and I just wonder why? Not to be an advert, but I recently started to use a grammar / spelling plug-in called Grammarly (it just corrected the spelling of itself as I’d forgotten to capitalise). I find it helpful as it does things like contextual spelling – so it’s a bit better at spotting some of the common mistakes I make – for example, I am always typing deliverying instead of delivering which Word seems not to find.

Anyway, I get an email from them every week giving me a run-down on how I used it that week – I have displayed one of my latest stats in the picture.

When I first received this, I thought that this was great – look at me I’m 99% more active than everyone else. Then the following week my number of words went down 30%, and it worried me – thinking I’d been just as busy. As the weeks rolled on, I have made the same number of mistakes and my stats fluctuate – but they just don’t help me. It went from “That’s interesting”, “Wow” to “So what?” in about two weeks. It may just be that I am not learning from my mistakes….

Coincidentally, I wrote about the importance of learning from mistakes in one of my last blogs (Why the slogan “Fail Fast” is bullsh*t if you want to succeed with OneOfficeTM) and I think this is where much of the data explosion is failing. We’re provided with all this useless data, but without much guidance on what to do about it, how to act on it – how to improve for the future. I think that is the issue with all the data – we just don’t know what to bloody do with it!

Bottom line:  To avoid #bloodyuselessdata you need a data chicken, not just a data egg

HfS Research is calling time on bloody useless data. Pure data collection and naïve analysis are table stakes in the digital world. The only way to create business value is to provide a feedback loop. The data needs to be used to inform the person in a positive way and iterate the process. Just hoarding data with no purpose is pointless (and potentially expensive) and next level of statistical reports which generate little action are almost as bad. For data to have any power it needs to inform the process and it needs to be actionable.
From now on HfS will be looking for examples of useless data and calling it out. If you have any examples, please contact me via twitter @thewizeone #bloodyuselessdata or [email protected]

Posted in : kpo-analytics, smac-and-big-data

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