Martyn Richard Jones

Laugharne 18th May 2017

“Our discreditable secret is that we don’t know anything at all, and our horrid inner secret is that we don’t care that we don’t.”

Dylan Thomas

Let me explain

I read a poster the other, it read “How To Turn Internal User Data Into Revenue”. It was one of those Facebook or LinkedIn hooks, you know, the ones used to get people to spend precious time on useless pursuits.

It reminded me of a book that my mother-in-law bought for my partner, many, many moons ago. “How to make a mint whilst you snooze”, or some such wacky title.

Now, I’m not saying that it isn’t possible to make money from data, but the idea that every piece of data is there just to be exploited, is also rather problematic.

For a start, there is no guarantee that “as is” raw data will be of any benefit in any qualitative or quantitative way.

Then there is the chance that exposing data to a whole flurry of complex, expensive and only partially explainable processing will still not result in a concomitant reaping of tangible rewards.

Then there was the aspect that stuck out like a blancmange nailed to an elephant.

Internal user data? What sort of person would willingly accept all of the complications, implications and pit-falls in flogging peoples’ personal and invariably identifying-data to a third party? Simply in order to turn a fast buck or to prove that data is the new WD-40.

I do think data monetization could be a good idea. If there are proper safeguards in place. Without the safeguards, the prospect turns into a dead-ended nightmare, only suitable for people on the lookout for trouble. You know, wide-boys and scallies.

Moreover, we talk about data as if all of it were an asset that we could cash in at the bank, whilst failing to understand what an asset means in financial terms. Like the possibility of an asset being a liability and an asset being completely illiquid.

An asset doesn’t have to be a profit centre, it can be a cost centre and a massive risk.

A legal responsibility. Unwanted, unloved and unusable, but necessary.

To paraphrase George S. Patton, for the purposes of business data, an imperfectly good pragmatic valuation of data executed today is better than a perfect theoretic valuation of data made in the next life.

The valuation of data, information and knowledge is complex and involves many intangibles, and although some may view the data, information and knowledge chain as a closed process, this is not in fact the case, as each step of the process is influenced by a number of factors that fall outside of a simplified view of any theoretical or practical progress from data to wisdom.

Just because you have data, doesn’t mean that it’s valuable. Just because you can mark up and sell-on data, doesn’t mean you should.

That’s it folks

Let’s see what lexogology.com has to say about all of this:


“The Federal Data Protection Act provides for fines in case of administrative offences, or even imprisonment in case of criminal offences. Fines may amount to up to €300,000 per case. Fines must exceed the financial benefit derived by the perpetrator the administrative offence. If the aforementioned amount is insufficient to do so, it may be increased. In case of a criminal offence, imprisonment for up to two years is possible.”


“Administrative penalties for non-compliance with data protection regulations are administered by the national authority for data control (CNIL). It can issue fines for natural persons of up to €150,000 for a first violation and €300,000 for a second violation occurring less than five years after the first violation.

The Criminal Code also lists a number of offences for non-compliance with or violation of data protection legislation, the gravest of which can lead to a five-year prison term and a €300,000 fine for individuals (the fine is five times higher for legal entities). These penalties are issued by national crime authorities.”

Are we still cool about all of this sharing of internal user data?

So, the propagation of the very idea that there is a simple, proven and fool-proof way of turning all “Internal User Data Into Revenue” is just tactless, shallow and imprudent. Deserving of ridicule as well as condemnation.

Just saying.

Many thanks for reading.

As always, please share your questions, views and criticisms on this piece using the comment box below. I frequently write about strategy, organisational, leadership and information technology topics, trends and tendencies. You are more than welcome to keep up with my posts by clicking the ‘Follow’ link and perhaps even send me a LinkedIn invite. Also, feel free to connect via Twitter and Facebook .

For more on this and other topics, check out my really old posts:

TEAM 2.0 Total Eminence Analytical Mapper – The highest level architecture -https://goodstrat.com/2017/05/13/team-2-0-total-eminence-analytical-mapper-the-highest-level-architecture/

AI and Big Data: A pig’s breakfasthttps://goodstrat.com/2017/05/10/ai-and-big-data-a-pigs-breakfast/

Data-Less Apps: Revolutionary IThttps://goodstrat.com/2017/05/09/data-less-apps-revolutionary-it/

BIG DATA GURUS: Trifling little fibbers?https://goodstrat.com/2017/05/08/big-data-gurus-trifling-little-fibbers/

Project Planning: Sharing makes it realhttps://goodstrat.com/2017/05/07/project-planning-sharing-makes-it-real/

Getting Agile Righthttps://goodstrat.com/2017/04/17/getting-agile-right/

Brand Aversion: Exhibit Onehttps://goodstrat.com/2017/04/16/brand-aversion-exhibit-one/

Big Dummies for Datahttps://goodstrat.com/2017/04/15/big-dummies-for-data/

Hadoop’s Revolutionary Data Warehouse


Contextual Aptitude: The Next Great Thing… Again


Here’s a thought… a mere data bagatelle


Post-truth, Fake-news and Big Datahttps://goodstrat.com/2017/02/02/post-truth-fake-news-and-big-data/

Data Supply Framework 3.0 – ETL Patternshttps://goodstrat.com/2017/01/26/data-supply-framework-3-0-etl-patterns/

Big Data is Bullshit – 2017 – https://goodstrat.com/2017/01/19/big-data-is-bullshit-2017/

What Every CEO Needs to Know About Big Datahttps://goodstrat.com/2017/01/18/what-every-ceo-needs-to-know-about-big-data/

Big Data Predictions for 2017https://goodstrat.com/2017/01/01/big-data-predictions-for-2017/

Here’s a thought… A Date with Coddhttps://goodstrat.com/2017/03/18/heres-a-thought-a-date-with-codd/

© 2017 Martyn Richard Jones