No doubt the guys from ReD Associates are on to something when they write in the Wall Street Journal that one of the latest fads in the business world is big data. (The Journal requires a subscription. Here’s a free version of a similar article.)
You can’t turn around without bumping into the phrase, whether you’re talking about health care, marketing, e-commerce, urban planning, social networking and on and on.
But maybe without knowing it, Christian Madsbjerg and Mikkel Rasmussen are also talking about another fad, one that hasn’t yet gotten as much ink: Warning that big data alone is not enough to reach big goals.
“In fact,” Madsbjerg and Rasmussen write, “companies that rely too much on the numbers, graphs and factoids of big data risk insulating themselves from the rich, qualitative reality of their customers’ everyday lives. They can lose the ability to imagine and intuit how the world — and their own businesses — might be evolving.”
Their message is that the numbers, even numbers that are gathered and crunched and re-crunched, tell only part of the story. I think we all know that on some level, but the allure of massive data sets is a powerful thing. They draw us in. They reassure us. They provide cover for our decisions.
Madsbjerg and Rasmussen, authors of “The Moment of Clarity: Using Human Sciences to Solve Your Toughest Business Problems,” are pushing the case for “thick data,” a phrase that is about to join “big data” on the list of phrases you can’t go 10 minutes without seeing or hearing.
Thick data, the authors say, allows businesses to look beyond the numbers and get a handle on squishy things. Thick data provides emotional context into how people approach their products and services or whatever it is they might be selling. It’s the information about how one individual is different from another.
Thick data is an idea that is popping up in different places, and in a bow to thick data, in different contexts. Madsbjerg and Rasmussen write about how it was deployed in consumer marketing and health care. West Chester University professor Paul Stoller writes in the Huffington Post how big data could better inform the Obama administration’s national security decisions.
Often these stories, like Joshua Klein’s in Fortune, include examples of where big data has steered people and organizations wrong. Yes, big data snafus can lead to $27.7 million books on Amazon and outrageously offensive machine-designed T-shirts being offered online in England.
And as Madsbjerg and Rasmussen point out, big data can steer businesses down the wrong path, like when medical technology company Coloplast failed to take its customers’ body differences into account when it tried to solve the problem of leaky stoma bags. Or when Lego crunched the numbers and decided a dramatic sales decline meant kids didn’t want to build toys anymore — they wanted instant gratification.
ReD researchers went and played with kids playing with Legos (what a job) and found — surprise — not all kids are the same. Some really did want to build things. It just wasn’t what every kid wanted.
Where some of those who fret about big data go wrong is in thinking that this reliance on digital information is a binary problem. In fact, it’s not black or white; about either crunching numbers or connecting meaningfully with your customers.
In order to be successful, enterprises must understand the data, but they must understand their customers — and even their customer’s customers — as individuals; as people or organizations with anxieties, priorities and aspirations.
Successful companies look at the bigger context surrounding their customer’s lives: Is there a difference between shopping on a mobile device and a desktop? Does an east coast resident asking for a soda want the same thing as midwesterner who orders a pop?
Charlie Whelan, a senior lecturer at Dartmouth, made a similar point in talking about airlines and how they rarely demonstrate that they understand that their customers are people who do things other than sit on airplanes.
Smart companies pay attention, not just to the data, but to the tools they use to interpret that data and to the expertise of those building the tools and analyzing the numbers that those tools yield.
Tricia Wang, writing for Ethnography Matters, lays the double-barreled approach out very convincingly in the sort of scholarly way that you would expect from a journal called Ethnography Matters.
“Big data reveals insights with a particular range of data points,” she writes, “while thick data reveals the social context of and connections between data points. Big data delivers numbers; thick data delivers stories. Big data relies on machine learning; thick data relies on human learning.”
And Wang wins the prize for finding the most entertaining way to make her point that stories drive data’s conclusions home. Citing Frans de Waal’s work demonstrating that monkeys have a sense of fairness, she points out that de Waal used a video (below) of Capuchin monkeys to illustrate the story his data tells.
There is no denying that video is striking — that’s one mad monkey, after all. But, then again, without the data, it’s just a Capuchin throwing stones.
Mike Cassidy is BloomReach’s storyteller. Reach him at firstname.lastname@example.org follow him on Twitter at @mikecassidy