This elderly gent is 'head of transformation' for his company, a job he's had for two years. It's taken him two years to get the buy in - not even the budget but the belief - of his senior management to give him the go ahead to execute on his vision.
Now he had that buy-in he was looking for help. He'd spent 'phase 1' of his plan getting a grip on all of the data in the organisation, regardless of where it sits - documenting where and what it is - before creating a library.
'Phase 2' was understanding how to change the way the company treats its documents, its policies and its standards. Policy management and governance is a major operation that underpins a successful business and is for most, part of the 90% unstructured data. This means extracting anything useful from it is almost impossible.
Now, with the appetite of a man with his first job, this man is attacking all the data across an enormous organisation and trying to make it useful.
It occurs to me though that a better way to deal with data is by replicating the ease in which startups handle their data.
Startups are not just product companies but data companies; this makes them insight and knowledge companies.
Vendors selling to enterprise companies in data management and regtech often tell them that they have to get a grip on the unstructured 90% data - this isn't correct. Today, we capture tonnes of unstructured information almost as a bi-product of everything else we do. But do we really need all of this information to make decisions? How much is relevant?
The fintech companies that are growing so fast haven't spent years capturing tonnes of irrelevant noise and therefore don't waste time trying to figure out what to do with it. They're smart and selective with the data they invest in.
They therefore have beautiful clean data sets and don't get bogged down by noise. So when it comes to the major piece of organisational operations that is governance and conduct, they are leaner, more efficient and avoid having to hire armies of compliance officers.
If I think about the question of what compliance would look like if startups had invented it, my answer is that startups are inventing compliance. What it looks like, without decades of legacy noise, is quick, effective, unhindered by countless unconnected documents. Smooth processes are built around clean, comprehensive, accurate and granular data sets giving risk officers or policy managers exactly what they need to know in real-time.
Financial institutions are speaking at conferences saying: "we have all this data, and we're exploring artificial intelligence solutions to help us experiment with various chunks of our data that may make us more productive and competitive." But why are they wasting time experimenting with the 'noise'; the data that isn't directly relevant?
Startups don't have to spend time exploring data they know is without value because they've already figured out that smaller and more structured data sets drive success. It may take a generation for such a strategy to be widely adopted by the mainstream but sooner or later, we'll all learn that how we collect and select the data we use will create faster, better and more sustainable businesses.