Picture it: a team of the greatest minds chickenkind could assemble, tasked with creating a better chicken. They stand around an egg, staring, until the first cracks splinter down the shell.And out emerges … a slightly better chicken.
This is the analogy I use when looking at a major dilemma facing businesses.
That dilemma is the knowledge gap growing between decision-makers and data specialists within organisations. And how businesses manage the issue could be the difference between boom and bust.
The chicken that makes the egg to make the chicken
This knowledge gap is so significant because of the way organisations are structured.They consist of decision makers at some level; the ones who set budgets, define challenges, and steer the focus of the workforce towards solutions.
It’s a necessity of business, but that model breaks down if those steering are unable to ask the right questions; questions that are informed by more than instinct and experience and are instead founded on an array of data that is complex to assimilate.
Think of it this way: if you asked a chicken to create a better chicken, its most likely starting point would be an egg. Unless it got lucky and jagged a miracle. But miracles are rare. The same goes for business.
There was a time in business when the way of determining direction and decision-making was to follow the instincts of the person who knew the business best – had often been there the longest – and had the best track record of producing successful outcomes.
It was largely reactive, sprinkled with some gut-instinct.
If a performance then does not match expectation, the analysis is dependent on the same instinct that posed the initial solution. It’s a tough cycle to break and the world has moved on. Experience, of course, remains invaluable, but it’s supported by data-driven insights enabling organisations to be proactive.
Those who understand how to use those insights are the ones steering the most valuable companies in history. The top of the pops is now dominated by the likes of Microsoft, Apple, Facebook and Alphabet. But those are data-native companies. They already get it. And they had a head start at getting it – they invented the new world order. Their success has most businesses understanding the answer is ‘data’, but unsure what the question is. So, they pose the same questions they always have, producing the same answers, simply supported by data, then analyse the results at the same level.
It’s like the chicken turning to the egg to create a slightly better chicken.
Ask a basic question, get a basic answer
In this scenario, businesses turn to the Chief Data Officer. They’ve never had one, so they get one – probably at what they consider to be a significant expense – which leads them to hang the Mission Accomplished sign in the staff kitchen. They sit back and wait for the 10-times exponential growth to begin, expecting stardust and unicorns. I’ll come back to the unicorns, but remember what we said about miracles?
Let’s say the average person with no data science capabilities can consider between 15 and 50 variables. Well, they pose their questions at that level. It makes no difference that it takes about 4000 data points to accurately predict behaviour, or that the business employed a data scientist capable of compiling those points.
It makes no difference, because they are not the ones posing the questions and steering the focus. That is why this knowledge gap is rapidly becoming one of the most significant challenges facing businesses and their leaders. The knowledge gap of previous eras was less vast, meaning the repercussions of asking the wrong questions were not as fatal and companies could often react before serious damage was done.
How can a business extract the value it desires from its data team if its executives are posing questions formed at an insufficient level?
Or, at least, at a level beneath that of its competitors (including the start-up it’s not even aware exists yet)?
At best, they make incremental progress – a slightly better chicken – but by the time they get to where they need to be, they’re too late.
The unicorn has bolted.
There’s only one type of unicorn
Now, those unicorns.
This knowledge gap is why the average employment duration of a Chief Data Officer seems to be about 18 months.
That’s an anecdotal figure, but I have no reason to doubt it after asking a room full of data specialists at a recent Corinium Global Intelligence CDAO conference in Sydney. Executives know they need these people, but don’t know why, or how to use them. They look at them like they’re the company’s unicorn: a magical beast that will gallop in and turn everything sunshine and rainbows through data and insights.
But there’s only one type of unicorn in business and that’s the billion-dollar start-up.
Companies such as Stripe, a payment processing platform that launched publicly in 2011 and was valued at $1.75 billion three years later. Today, it’s worth $22.5 billion. US Dollars, by the way. That’s the speed at which the new world is moving under data-driven insights.
Ask the wrong question and you’ll watch the unicorn gallop into the sunset before you’ve even received an answer.
A matter of chickens and unicorns
Don’t misunderstand me: I’m not on a mission to turn the world into data scientists. That would have its own detrimental effects for business (the quality of office humour would plummet, for a start). But a change in perception is required if businesses want to survive and thrive.
A few years ago, I attended a computer analytics program at Harvard Business School, assuming I would be joined by 20 or so likeminded data geeks. What I found was about 60 C-Suite executives from various industries, there to gain a conceptual understanding.
They were the executives sitting beneath the leaders, who were data-aware enough to bridge the knowledge gap and ask the right questions.
They got it.
And that’s the lesson.
It’s not a case of every worker in a business becoming a data expert. It’s a case of gaining enough awareness to steer the experts. That’s how the chicken is reimagined. That’s how unicorns bolt.
However, if it’s only a slightly better chicken you’re after, then maybe stick with the egg
This post was first published by Pieter Vorster on Linkedin - republished with permission