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Truth About Data Will Set You Free
February 12, 2016 Blog big data

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In a world of causes, crises and injustices, the crew at British customer experience company Qubit has picked its spot in terms of how they can help make the world a better place: by starting a push to wipe out data illiteracy.

And why not? We are swimming in data. Data is driving our cars; determining our credit worthiness; deciding the colleges our kids get into; defining political candidates; finding us jobs — or employees — and informing business decisions that drive billions in spending and determine the fate of enterprises and their workers.

But the Qubit effort, led by CEO Graham Cooke and global communications director Mark Choueke, has a narrow initial target: marketing professionals. And they have no intention of doing it alone or necessarily even leading the charge. Instead they are attracting a growing number of allies who are pushing marketing practitioners to better understand big data — the very data that marketers often cite to make their case, whatever their case might be.

“Data used to be considered a small part of marketing,” says Choueke, who describes Qubit as a data-led customer experience technology. “But now, customer data really is marketing. If you take it to the nth degree, you can’t really be a good marketer without understanding how to do data and most marketers just simply don’t. We didn’t learn this in school. We didn’t learn it in college. It wasn’t part of our makeup. We didn’t need it.”

And so, he and his boss, Cooke, have launched “Truth about Data” and, an initiative that involves video tutorials, data heroes and a planned data-fest celebrating data victories some time this year.

“With TruthAboutData, we’re looking to help give marketers access to a fuller understanding of the data in their organizations and open their eyes to the sort of marketing that is possible,” CEO Cooke says. “While businesses are generating around 200 times more data than they were, say, three decades ago, we’re not really looking at, or working with, a great deal more data or metrics now than we were back then. This means there’s a potential opportunity being missed. The opportunity to go deeper, become more skilled, personalize and predict more. It’s about giving marketers the tools to ask much bigger questions.”

It’s the kind of story that oozes with geek cred and might make you chuckle a little. Crusading for big data understanding, after all, is like pushing for a National Algebra Day or lobbying for an official state algorithm.

But it is no publicity stunt or short-lived fuzzy promotion. Cooke and Choueke have been sketching out their plan for about a year and when Choueke talks about both the problem and the solution, he is practically breathless. It is not about him, he says. And not about Qubit. In fact, he very much wants other companies to join in and he’s been spending a good amount of time recruiting them.

“All this came about because we were sick and tired of marketers having the wool pulled over their eyes,” says Choueke, a former journalist and onetime editor of a marketing trade publication. “It doesn’t do any of us in our profession any favors, in fact, all it does is undermine the reputation that marketers have around the world.”

He says marketers — even marketers buying technology solutions from other marketers — at times accept at face value data provided by vendors. Data, for instance, that shows staggering increases in revenue or website traffic, feats akin to “getting a man to fly.”

And if the marketer doesn’t understand enough to ask the right question or doesn’t understand where those fabulous numbers in a particular pitch came from, he or she can end up buying into a product or program that doesn’t deliver as promised.

When that happens, it’s the marketer that needs to answer to the boss — and, Choueke says, often the best answer the marketer has is, “Ah well. Things happen, you know.”

Not to mention: In a world of data illiteracy, how do the honest vendors compete with the unscrupulous ones pushing inflated promises based on faulty or cooked data? It is a case in which no one is the wiser, literally.

But what really excites me about the Truth in Data campaign is the potential for the movement to push beyond marketers to the population as a whole. I think of it like the recent efforts of nonprofits and education policymakers to establish universal computer science education.

The notion behind the push is that understanding how code works and what it can do, is fast becoming a prerequisite to good citizenship. It is a way for citizens to stop feeling as though machines are doing things to them, and instead learn to use machines to help them realize their aspirations.

Big data education is an extension of that kind of thinking. Coding and data education are fast becoming foundational elements of the well-educated 21st century citizen. Scholars once studied Latin, not because they intended to speak it, but because it helped them understand civilizations past and present. Likewise, today’s students should study big data, whether they intend to muck around in the inner-workings of it or not. It is a way to understand so much of what is happening around them.

Kristen Berman, one of Truth About Data’s data heroes, says people often trust their intuition too much when interpreting data. Instead, the co-founder of San Francisco’s Irrational Labs says it helps to have a bigger picture. She is a behavioral scientist who believes that sterile data sets are not enough.

Instead, data sets are best understood in conjunction with an understanding of what humans do and how they do it. It’s an approach with a lot in common with what’s been called “thick data,” the idea that big data is most meaningful when it’s digested in the context of the emotion and every day lives of people.

Berman appreciates that different disciplines — behavioral scientists, data scientists and artificial intelligence engineers — have different approaches to data. But she is confident that almost everyone could benefit from a better understanding of what’s behind the numbers.

“I don’t think that we, as consumers of information, understand statistics enough,” she says. “I think generally, we are getting to the point where data competency is something that if it’s your role, you’re good at it. But that’s a small minority of people doing it day-to-day. And then the question is, how much do we generally, as a society, understand numbers?”

Good question. Maybe we should assemble the data to answer it.

More importantly, maybe we should look ahead to the day when data literacy will be so prevalent that it won’t even be a question worth discussing.