Tackle GDPR with a Minimum Viable Dataset

Tackle GDPR with a Minimum Viable Dataset



Every other post on LinkedIn these days seems to be about GDPR. Well, if you don’t count the ones complaining about recruiters, or the ones from recruiters complaining about candidates.

I’ve been keeping tabs on this subject so that I can provide sensible advice to my customers, and have had some interesting conversations about GDPR in that time (a highlight being a chat with Simon Morrissey from Lewis Silkin) and how the Information Commissioner is likely to operate once it is effective next year.

Chris reporting from the very last ship-bound IT Directors’ Forum.  Including interviews with GDPR expert Simon Morrissey from Lewis Silkin, ITDF stalwart Richard Blandford from Fordway, and Kim van Rooyen from Turner & Townsend.  More WB40 podcasts here


Something that has come up regularly is the idea that data, having been generally seen as an asset, is now also to be regarded as a liability. The logic is pretty straightforward, if you manage your data badly it can lead to a blow to reputation, a cost to fix the result of a data loss, and at worst action from the ICO. So maybe we should think of it like stock in a warehouse, great to have, and an asset on the balance sheet, but costly to maintain.

Most manufacturing businesses now see stock in this way and operate lean methods to keep their stock to a minimum, releasing cash and also reducing the risk of stock being damaged, lost or becoming devalued through commodity price changes.

Should organisations such as retailers and recruiters take the same view of the personal data they hold? How realistic is it to think in these terms?

So, borrowing from the poor, abused notion of the Minimum Viable Product, I wonder -could you define your Minimum Viable Dataset? And would it be a better business if you could learn to live with that standard?

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