On “monetisation of data” and other phrases that should be banned

I’ve been thinking a lot about monetisation of data. Horrible word I know, but it keeps appearing in corporate circles, generally in the context of what companies want to achieve with all that data they are producing, or which is now available to them from external sources — social media and so on. As per a conference I was recently at, the conclusion frequently reached is that monetisation of data — that is, making money from it — is becoming a high-priority goal for any business.

Why ‘monetisation’? Is it just that it is a nicer word than ‘profiteering’? Or possibly because it sounds slightly like the ultimate goal presented by Maslow’s pyramid of needs, ‘self-actualisation’? Although the former deserves scrutiny (which will be the subject for another day), I’m mostly with the latter. The fact is that organisations know they can do better if they use information better, and doing better primarily means either making more or losing less money.

So, yes, monetisation it is. For some industries, turning data into so-called ‘business value’ is nothing new — anything to do with finance, for a start. Accounting, for all its complexity, is ultimately about managing tables of figures and their relationships; banks are purveyors of mathematical transactions. Healthcare, engineering and other scientific disciplines also have a substantial data element. Retail supply chains have long been driven by data, as are manufacturing systems and utilities plants.

What’s changed the game for all companies (which is why all businesses are ‘going digital’) is that customer-related data has engulfed business strategy, at the same time as all other data sources proliferating. Marketing used to be a relatively isolated set of activities, feeding the other parts of the business on a regular basis with information and potentially sales leads. Today however, such information has become incredibly accessible, so it appears, with customer expectations changing equally quickly.

And meanwhile, in principle at least, you can now know exactly how a business is functioning to the n’th degree, second by second. Through a myriad of sensors, via a multitude of sources you can check everything from the humidity levels in a container crossing the ocean to the stress levels on a paving slab. Nobody really knows how much data is enough, so the response can be to keep adding to the pile of sensors. From a client I have heard of an tendency to plan the right number of sensors in advance, but this is emerging best practice.

The result of all this data, both external and internal, is that many companies have ended up paralysed. Even senior corporate strategists flounder like a dwarves in Smaug’s cave, arms already laden with the gold nuggets of information they see before them but unable to do much more than grab handfuls of it at a time. The opportunity is tantalising; meanwhile other, slicker organisations simply wade in with buckets and take what they want. What an opportunity, what audacity!

Is it any wonder, then, that consulting firms and computer companies are promoting solutions to this challenge? In honesty, not that they really have a solution to the challenge as a whole. For all the machine learning and information management frameworks, the open APIs, agile delivery and DevOps strategies, nobody has a magic sieve that can separate useful data from the shrapnel. Instead, such advice usually turns to scoping — what beneficial goal are you trying to achieve and what specific information you need to do so.

Monetisation is therefore a shorthand term for not wanting the opposite, i.e. not wanting to remain in a state of uncertainty where everyone and their dog seem to be having an easier time of making sense of it all, and potentially cashing in, than you are. The valuations of some of the digitally enabled startups may be vastly inflated, but who wouldn’t want some of that? Find me a company that says, “No, sir, please don’t give me that vastly inflated valuation.” But just as not all singers are destined to be pop stars, the majority of companies need to set more realistic goals.

There’s a further irony. Money is itself just a form of data, a (frequently poor) measure of value of anything, derived to simplify exchanges of goods and services. The fact we have worked out how to exchange the measure itself (as illustrated by currency) is an indicator of how complicated this can get. In other words, even if an organisation successfully achieves ‘monetisation’, it will have managed to convert a partial representation of reality into an arbitrary estimate of what that might be worth.

If that sounds vague, it’s because it is. The real trouble with the monetisation of data isn’t that the idea is grubby. It’s that it takes companies away from the things they have been able to understand, their products and services, and heads them en masse towards a cave where all that glitters is not gold. It may well be a necessary step for companies to consider how they can get more value out of their data, just as they are looking at services (another horrible word — ‘serviceisation’). But in doing so they should be careful not to lose touch with what they were setting out to do in the first place.

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