Martyn Richard Jones

Our bloke in Brussels, 3rd July 2019

It’s a simple, timeless, human truth; data must adapt or die.

Read between the lines, the writing on the wall, the fat lady singing and the barking dogs at the gate.

Think of it as a digital death by a million degaussers.

So far, so good?

BBC Test Card

Well done! Now you know all about degaussing let’s get down to brass tacks.

Time and time again, data is failing to step up to the plate and to deliver on its promise, it’s not reaching-out and it lacks the required levels of passion, and in doing so is causing Big Data, Hadoop, data science and Agile business projects no ends of existential problems.

As the famous French prankster and cartoonist Jean-Paul Sartre put it “In life man commits himself and draws his own portrait, outside of which there is nothing.”

We placed a lot of virtuous faith, generosity and good emotional capital in data, and in return data have coldly, tragically and aloofly let us down, time and time again. It just refused to push the envelope. It messed with our crayons and spoiled our selfies, besmirched our beliefs and belittled our sentiments. It’s beneath contempt.

Is no one thinking of the children? Think about all of the brave data explorers and data pioneers at places such as IBM, HP, Cloudera and Hortonworks, and weep! The self-evident truth of this drama reveals that facts are a thing, and the unquestioning trust that we all placed in data has not been reciprocated. Not one jot.

Data has returned neither the love, the optimism nor the hope. We have been continually disappointed, disillusioned and frustrated by data’s insensitivity to our needs, wants and desires.

But, even when data has adjusted, which has not been often, it has adjusted in completely the wrong ways, which is another reason that affirms that data must adapt or die.

It’s just not on!                                                                                                        

For many data evangelists, mongers and whisperers, data has behaved like a candidate for a top-flight executive job, turning up for an interview in sneakers, jeans, a Metallica t-shirt and a Jeremy Corbyn baseball-cap. Only in the case of data it travels up to the C-suite, takes its place at the table, farts loudly for what seems like an eternity, and then belches, gets up and leaves.

Which, is why I feel really badly for the Big Data gurus who painstakingly schlepped their love of data around digital-venues such as LinkedIn, Twitter, Forbes and other professional comedic-stages only to be slapped right-up the side of the head by data’s callous disrespect for prosaic, opportunistic and populist characters.

So, why hasn’t data adapted in the way we wanted it to?

First, because it is arrogant, ignorant and amoral. That’s why. And secondly, because there is so much of it. We’re surrounded by it. It’s become the digital enemy within, without and betwixt.

But it goes far deeper than that. We have been massively permissive with data; too obsequious; too impetuous; and, too rash.

We have allowed data to become uncontrollably Marxist, communalist and collectivist. So, be afraid, very afraid and hold these powerful thought-snippets in your head: “Enterprise Data Factory”, “Das Data Kapital” and “data workers of the world integrate”.

I might come back to these in just a moment.

But to loosely paraphrase Marx “It is not the consciousness of data that determines their being, but, on the contrary, their being that determines their mindfulness; sort of.”

And this is what we have let data do. We have let data live their own social lives which has inevitably led to bad things, unintended consequences and undesired patterns of behaviour.

Do you see where I am coming from with this?

We thought data integration would help create a great and good data melting-pot, a great cauldron full of nourishing, life-giving data-soup of which we all could avail ourselves.

It didn’t work, we were wrong. So sad.

We thought that data would provide us with the new oil; like the old oil, just better. So we rightfully poured a load into the motors of enterprises, and what happened?

It didn’t work, we were wrong. It was all sand and water. There was no way it could help businesses to get to warp factor 4. So sad. Fooled again.

We want good data, great data, and malleable data; data that encapsulates agile opinion, scalable speculation and the learning-journeys of innuendo.

We don’t want data that simply contains “facts”, so-called credible references or snowflake degrees of certainty, that’s just data-correctness gone mad.

It’s not good; it’s bad. Current operational data is like kryptonite to data scientists. What these poor boys and girls need in order to do proper jobs is apposite, aligned and bigly data; the right data at the right place and at the right time; and, the data that these folk have all been begging for and for so long. “Please, Sir. May I have some more of the right data?”

So, how can we fix this data-adaptability deficit in the world of data?

We have to reinvent the meaning of data; we must unchain data from the totalitarian restraints of legacy data; and, we must extract ourselves from the cloyingly sentimental treacle-swamps and quicksand of last millennium’s data governance, architecture and management.

Data must be made to give us what we want, not the mere bagatelles that data reluctantly concedes to give us now, but data that can make us look good in the C-suite; data that aligns with culture, strategy and agile at scale; and, data that doesn’t insolently answer back.

As George Bernard Shaw might have put it “Those data who cannot change their minds cannot change jack.” 

Data must adapt and align with our narratives, options and decisions, or its value is worse than marginal.

However, here’s a foolish question. What if I am wrong, and it’s not data that has to adapt, but us?

Heaven forfend! I don’t think we have to be so negative and jaundiced. The writing is on the wall, so why be fickle and petulant about it, right?

Data is weakening as we speak and you know what, if it doesn’t adapt soon it’s going to die.

Are there any alternative options to data either adapting or dying?

Data can continue as it has done for the last god’s how many years (even back before the Doomsday Book appeared in England i.e. well before Apple and Microsoft), but that would be entirely unacceptable, reckless and short-sighted and for perfectly understandable reasons that don’t need to explained here, or anywhere else for that matter.

It’s just a question of common sense, gut feeling and deep learning; absolute proof that we are right.

So, let’s get that data life-support ramped-up and let’s make data great again before it pops its clogs in failing to adapt.

To paraphrase the great Dottie Parker, “If you want to know what God thinks of data, just look at the people he gave it to.” 

Many thanks for reading and until the next time,

Well done! Now you know all about degaussing, let’s get down to brass tacks.

Time and time again, data is failing to step up to the plate and to deliver on its promise, it’s not reaching-out and it lacks the required levels of passion, and in doing so is causing Big Data, Hadoop, data science and Agile business projects no ends of existential problems.

As the famous French prankster and cartoonist Jean-Paul Sartre put it “In life man commits himself and draws his own portrait, outside of which there is nothing.”

We placed a lot of virtuous faith, generosity and good emotional capital in data, and in return data has coldly, tragically and aloofly let us down, time and time again. It just refused to push the envelope. It messed with our crayons and spoiled our selfies, besmirched our beliefs and belittled our sentiments. It’s beneath contempt.

Is no one thinking of the children? Think about all of the brave data explorers and data pioneers at places such as IBM, HP, Cloudera and Hortonworks, and weep! The self-evident truth of this drama reveals that facts are a thing, and the unquestioning trust that we all placed in data has not been reciprocated. Not one jot.

Data has returned neither the love, the optimism nor the hope. We have been continually disappointed, disillusioned and frustrated by data’s insensitivity to our needs, wants and desires.

But, even when data has adjusted, which has not been often, it has adjusted in completely the wrong ways, which is another reason that affirms that data must adapt or die.

It’s just not on!

For many data evangelists, mongers and whisperers, data has behaved like a candidate for a top flight executive job, turning up for an interview in sneakers, jeans, a Metallica t-shirt and a Jeremy Corbyn baseball-cap. Only in the case of data it travels up to the C-suite, takes its place at the table, farts loudly for what seems like an eternity, and then belches, gets up and leaves.

Which, is why I feel really badly for the Big Data gurus who painstakingly schlepped their love of data around digital-venues such as LinkedIn, Twitter, Forbes and other professional comedic-stages, only to be slapped right-up the side of the head by data’s callous disrespect for prosaic, opportunistic and populist characters.

So, why hasn’t data adapted in the way we wanted it to?

First, because it is arrogant, ignorant and amoral. That’s why. And secondly, because there is so much of it. We’re surrounded by it. It’s become the digital enemy within, without and betwixt.

But it goes far deeper than that. We have been massively permissive with data; too obsequious; too impetuous; and, too rash.

We have allowed data to become uncontrollably Marxist, communalist and collectivist. So, be afraid, very afraid and hold these powerful thought-snippets in your head: “Enterprise Data Factory”, “Das Data Kapital” and “data workers of the world integrate”.

I might come back to these in just a moment.

But to loosely paraphrase Marx “It is not the consciousness of data that determines their being, but, on the contrary, their being that determines their mindfulness; sort of.”

And this is what we have let data do. We have let data live their own social lives which has inevitably led to bad things, unintended consequences and undesired patterns of behaviour.

Do you see where I am coming from with this?

We thought data integration would help create a great and good data melting-pot, a great cauldron full of nourishing, life-giving data-soup of which all could avail themselves.

It didn’t work, we were wrong. So sad.

We though that data would provide us with the new oil; like the old oil, just better. So we rightfully poured a load into the motors of enterprises, and what happened?

It didn’t work, we were wrong. It was all sand and water. There was no way it could help businesses to get to warp factor 4. So sad. Fooled again.

We want good data, great data, and malleable data; data that encapsulates agile opinion, scalable speculation and the learning-journeys of innuendo.

We don’t want data that simply contains “facts”, so called credible references or snowflake degrees of certainty, that’s just data-correctness gone mad.

It’s not good; it’s bad. Current operational data is like kryptonite to data scientists. What these poor boys and girls need in order to do a proper jobs is apposite, aligned and bigly data; the right data at the right place and at the right time; and, the data that these folk have all been begging for and for so long. “Please, Sir. May I have some more of the right data?”

So, how can we fix this data-adaptability deficit in the world of data?

We have to reinvent the meaning of data; we must unchain data from the totalitarian restraints of legacy data; and, we must extract ourselves from the cloyingly sentimental treacle-swamps and quicksand of last millennium’s data governance, architecture and management.

Data must be made to give us what we want, not the mere bagatelles that data reluctantly concedes to give us now, but data that can make us look good in the C-suite; data that aligns with culture, strategy and agile at scale; and, data that doesn’t insolently answer back.

As George Bernard Shaw might have put it “Those data who cannot change their minds cannot change jack.” 

Data must adapt and align to our narratives, options and decisions, or its value is worse than marginal.

However, here’s a foolish question. What if I am wrong, and it’s not data that has to adapt, but us?

Heaven forfend! I don’t think we have to be so negative and jaundiced. The writing is on the wall, so why be fickle and petulant about it, right?

Data is weakening as we speak and you know what, if doesn’t adapt soon it’s going to die.

Are there any alternative options to data either adapting or dying?

Data can continue as it has done for the last god’ knows how many years (even back before the Doomsday Book appeared in England i.e. well before Apple and Microsoft), but that would be entirely unacceptable, reckless and short-sighted and for perfectly understandable reasons that don’t need to explained here, or anywhere else for that matter.

It’s just a question of common sense, gut feeling and deep learning; absolute proof that we are right.

So, let’s get that data life-support ramped-up and let’s make data great again, before it pops its clogs in failing to adapt.

To paraphrase the great Dottie Parker, “If you want to know what God thinks of data, just look at the people he gave it to.” 

Many thanks for reading and until the next time,

Martyn Jones

goodstrat.com – The Good Strategy Company