"The idea that business is strictly a numbers affair has always struck me as preposterous. For one thing, I’ve never been particularly good at numbers, but I think I’ve done a reasonable job with feelings. And I’m convinced that it is feelings -- and feelings alone -- that account for the success of the Virgin brand in all of its myriad forms.” -- Richard Branson
Data-driven marketing. That phrase is used as if it means truth driven. That facts (data) drive decisions.
But there’s danger in an obsession with being data driven.
The danger lies in seeing these numbers as facts or truth. And that, as a result, we should base our decisions about the future on what these facts reveal to us.
What’s wrong with that? Numbers bring with them an aura of legitimacy. And being data driven allows marketing to speak the language of the rest of the C-suite.
And while there’s a benefit in improving analytics skills, there’s a very real danger as well. A danger that increases with big data, for big data is fueling this obsession with numbers.
Where does the danger lie? And where is the opportunity?
Organizations Are Hypothesis Driven, Not Data Driven
The danger lies in our mental models. Our reality is distorted.
Data enters our organizations, our spreadsheets, our analytics programs through the lens of mental models that cause us to filter and fit data to those models.
The illusion of the Cartesian theater is that we think we see the world projected into our minds. But we see the world filtered and rearranged by the lenses of our models.
Image Source: The Power of Impossible Thinking
Thanks to the Cartesian Theatre, a gorilla could run through our field of vision and we’d fail to see it. Our mental models, our hypotheses of how the world works, filter out what seems to be irrelevant or is simply invisible to our untrained eyes.
Despite the best of intentions, we’re not data driven, we’re hypothesis driven. Our stories (our mental models) are merely hypotheses of how the world works. But we see them as reality and they influence what data we collect, how we collect it and the meaning we glean from it.
As Tim Stock asks in The Intimacy of Data, are we amplifying real intelligence or human error?
No Amount of Data about Yesterday Will Solve the Mystery of Tomorrow
Image Source: Gary Klein, Seeing What Others Don’t
Data draws us into an analytical mindset. It gives the illusion of the solution being in the data.
But the solution isn't in the data. The data is merely a sensor. A sensor that only works if it’s pointed in the right direction. A sensor whose purpose is to provoke us to ask questions, not reveal answers.
It’s impossible to analyze our way to the future.
For the future is a mystery. A messy place filled with uncertainty and risk. But also with tremendous opportunity. A story yet to be written.
To write the future we must question accepted truths, change the frame through which we analyze the world and forge new connections between previously disparate things.
Instead of trying to analyze our way to the future, we must play, write or experiment our way into the future.
But how can we experiment our way into the future if being data-driven means we need to prove a future model or get it right the first time? If our current reality is distorted, no amount of data about yesterday will help us prove a solution to the mystery of tomorrow.
Empathy as a Sensor
Image source: Design Thinking
Dev Patnaik in "Wired to Care" suggests that “Most companies are corporate iguanas … They have a reptilian brain to act. They have a neocortext to think. They just don’t have any way to feel.”
Collect data. Analyze data. Those are both functions of the neocortext.
Act on data. That’s a function of either the neocortext (when the action is thoughtful and measured) or the reptilian brain (if the action is reactive or a response to a perceived threat).
Feel data. Is it even possible to connect emotionally with data?
What’s missing is empathy. We empathize by emotional cues. And data is void of emotional cues.
To solve the mystery of tomorrow, we need a deep understanding of and insight into what’s meaningful to people. We need to make empathy an organizational core competency.