"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.
If a reframe is the fundamental change that you can see, empathy is the sensor that allows you to feel that reframe before you can see it. Empathy is the necessary ingredient that precedes massive growth and change. Empathy helps make sure that you’re in the right place at the right time to discover your next big growth opportunity.”
An organizational competency for empathy is critical because we’re deep in the experience economy.
While prior economic offerings -- commodities, goods, and services -- are external to the buyer, experiences are inherently personal, existing in the mind of an individual who has been engaged on an emotional, physical, intellectual, or even spiritual level.”
Big Data as a Sensor
In his TEDx talk Marketing Behavior, Peter Sells shares the story of the fish stew he sought out in El Bigote, Ibisza thanks to a conversation with his hair stylist. “I wasn’t just buying the fish stew. I was exchanging money for social currency. And that social currency allows me to tell other people. And now I’m part of the story. And I’ve just cashed in my social currency in front of 100 people.”
How does the story of the fish stew to be had in El Bigote spread through a culture network? What meaning does this story signal?
Much of the hype around big data and how it will revolutionize marketing is tied to old assumptions around market intelligence. I follow Tim Stock on Slideshare and love his work. He argues that we need a new model for insights (think epidemiology). That we need to reboot how we frame intelligence.
In a quest to become data driven, are marketers trapping themselves with outdated mental models of data and analytics? “Big data is being wasted on marketing. The true power of analytics is in revealing cultural dynamics.”
Does the real possibility of big data for marketing, as Tim Stock suggests, lie in an ability for us to identify and track the spread of micro-factories of meaning through cultural networks?
Meanings shift. Frames of reference change. The units of measure by which people make comparisons are subject to rapid and unpredictable change. And when that happens, there’s a disproportionate effect on behavior, value and growth. Rory Sutherland calls these shifts Trim Tab moments. Trim Tab moments are the opposite of proportionality of data. They’re the disproportionality of meaning where the smallest movement has the biggest effect on direction of craft.
- From quality of sound reproduction to 2000 songs in your pocket.
- From ownership to sharing.
- From booking hotel rooms to experiencing unique spaces.
- From fast food to slow food.
- From taxis to on demand private limos.
- From regulation to reputation.
Does one potential of big data lie in spotting early warning signs of possible Trim Tab moments? The emergence of tiny movements that hold the potential for shifting frames?
What if big data served as a sensor that helped us identify the emergence of extreme users and allowed us to track the spread of meaning between them? We could then follow up with deep dive ethnographic studies to build our empathy and understanding -- enabling us to design for possible futures that build on and extend the new meanings.
Power of Impossible Thinking
The impossible is merely something that we can’t yet imagine thanks to the mental models through which we understand the world today.
To solve the mystery of tomorrow, to survive and thrive in disruptive times, organizations need to leave the comfort zone of their data and venture into the impossible. They need to become empathy driven, not data driven. For empathy is the sensor that will allow them to design for what’s truly meaningful to people.
Like the powers of 10, can we leverage big data to zoom out and understand patterns and trends, then zoom back in for a dive deep into the hearts and minds of individuals? Changing focus, posing big questions, zooming in and out constantly to challenge our models, look for patterns and seek out new meanings?
Are we willing to develop hypotheses with the potential to disrupt our old mental models? Create experiments to test those hypotheses. Prototype to think. Collect feedback. Iterate. Learning from the future as it emerges.
Innovation requires imagination. And imagination comes from people, not data.
So let’s not get too caught up in big data. Let’s think a little more about big hearts -- building empathy as an organizational core competency. Only then will we be able to move beyond the comfort zone of the echo chamber that’s limiting us to the possible and restricting our ability to innovate.
Editor's Note: This isn't the first time Joyce tackled the big picture. Read more in Designing for Community: Mastering the Art of Narrative