Changing perspectives — data with a human face

What’s the first thing you think of when you hear the word “Data”? Unless you’re a science fiction fan, chances are you’re thinking “numbers.” One of our jobs as writers is changing perspectives on data—helping people to grasp what those numbers mean. What they reflect about the world, about us.

Changing perspectives
Sallie Krawcheck knows how to tell a story with data. Photo by Grace Villamil, CC BY 2.0

Sallie Krawcheck does this about as well as anyone I’ve encountered—including master storyteller and genius investor Warren Buffett. But that doesn’t surprise me. Krawcheck started out as a financial analyst. And successful analysts know how to turn numbers into memorable prose, raw data into recommendations people will follow.

Today, as CEO of the global professional women’s network Ellevate, she’s set her sights on changing perspectives—women’s perspectives about their relationship to money; the business world’s perspectives about its relationship to women. Judging from her book Own It: The Power of Women at Work, she’s doing a damn fine job of that, too.

Changing perspectives — name your data points

Let’s take the subject of how few women hold seats on corporate boards of directors. Depending on how you slice the pie, it’s 15%, 14%...I haven’t seen any number larger than 20%.

Now there are lots of ways to talk about 20%—one in five, two out of ten. Admit it: your eyes are already starting to glaze over. And you care about this stuff. Imagine trying to sell it to someone who doesn’t see how it affects him.

So what does Sallie Krawcheck do? Instead of reeling off numbers, she names her data points:

“There are literally more men named John, Robert, William, or James on corporate boards than there are women.”

Is that brilliant positioning or is that brilliant positioning?

Okay, it doesn’t tell you the actual data—she leaves that for the footnote. But giving human form to the numbers turns the data from an abstraction into something people can easily relate to.

Changing perspectives—getting people to look at a familiar subject in a new way—helps people develop empathy, and empathy creates change. We need a whole lot more empathy in the world. Telling stories instead of reciting data seems a great place to start.


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“If you’re asked for data, refuse to provide it”—great advice, but not what you think

“If you’re asked for data, refuse to provide it.” Now that’s what I call an attention-getting lede.

At first I thought this LinkedIn post by Avtar Ram Singh, a man I do not know, was about politics. During the recent U.S. presidential transition, the incoming administration asked for lists of federal employees who held views in opposition to their own. You know, about speculative things like climate change. They wanted to know which scientists still believed that their facts trumped (you should pardon the expression) the superior information found elsewhere, like in the Bible. The agencies refused to provide the data to their new overlords. A small victory.

But no, refreshingly, this wasn’t about politics. In the next paragraph, I discovered it was fundamentally about my very favorite subject: Storytelling.

data plus information is a story

Did I say this was about storytelling? This gobbledygook about CTR (Click Through Ratio, if you’re wondering) and conversions?

Yep. Mr. Singh may not realize it, but when he advises people to put data “into the context,” he’s actually saying, “Use data to tell a story.” Not only does a story make the data more useful, as he notes. It also makes it more memorable. And, as I’ve said before and will surely say again, if you don’t want people to remember what you’re telling them, then why bother?

Telling a story with data

Facts don’t stick in people’s minds. But stories do. So turn your 2,000 conversions into a story:

Our Click Through Ratio nearly doubled last month, and our conversion rate more than doubled.

If you need people to have the hard data, hand it to them separately, or put it in a chart next to the narrative. Do not—please, for the love of all that’s good do NOT—do this:

Our Click Through Ratio nearly doubled last month (from 3% to 5.2%), and our conversion rate more than doubled (840 to 2000).

The data points break up the flow of the sentence and make it harder to understand the point. If you must drop in the numbers, try:

Our Click Through Ratio nearly doubled last month, going from 3% last month to 5.2%. Even better, our conversion rate also skyrocketed: 2000 of those clicks converted into paying customers, up from 840 last month.

Or turn the percentage into people:

We’ve been seeing an average of 3 click-throughs for every 100 people who visit our page. But this month, that number rose to 5.2 click-throughs per 100.

Or—since conversions increased by a much higher percentage than CTR, I wonder if the page didn’t have more traffic coming to it. So you might add some further context:

Over XXX,XXX people visited our page last month and 2000 clicked-through to become paying customers. Our CTR of 5.2% is the highest we’ve seen in a while. nearly double last month’s 3%.

Mr. Singh is absolutely right: “If you’re asked for data, refuse to provide it.” Tell a story instead.


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Data, data, everywhere: we’re drowning in it

We are drowning in data. We create more of it daily—so much it seems impossible we’ll ever make sense of it.

Data—or, as it was known back in the 20th century, “paperwork”—has been a challenge for decades. As Frank Zappa wrote in 1989:

“It isn’t necessary to imagine the world ending in fire or ice. There are two other possibilities: one is paperwork, and the other is nostalgia.”

Data: the horse manure of the 21st century?

One of the most memorable stories in Steven Levitt and Stephen Dubner Freaknomics revolves around a seemingly insoluble problem of 19th century urban life. As traffic increased, so did the emissions generated by vehicles. But since the vehicles in question derived their horsepower from, well…horses, the emission in question was manure. Tons of it.

Cities struggled to keep their streets navigable. Pedestrians crossed at their own risk. Civic leaders despaired of handling the exponential growth of excrement as the population increased and commerce flourished.

In one sense, horse manure was the 19th century equivalent of our data problem
Henry Ford and his Quadricycle, 1896

No one saw the solution on the horizon. No one, that is, except Henry Ford. His gasoline-powered “horseless carriage”—he called it a “Quadricycle”—produced a different kind of emission.

The proliferation of vehicles powered by internal combustion engines solved the horse manure problem. Of course, it created new problems whose effects we’re dealing with today. But that’s beyond the scope of this blog.

Now obviously it’s an imperfect analogy. Data is much easier to brush off the sole of your shoe, should you step it in. Also it doesn’t stink, not even in the heat of summer.

Does data proliferation matter?

As Moore’s Law predicted more than half a century ago, ever-smaller devices now store ever-greater amounts of data. But what’s the point? Sometimes I wonder if companies aren’t collecting data for the same reason British mountaineer George Mallory pursued his passion.

In 1923, before he returned for his third and final trip to Mt. Everest, a journalist asked him, “Why did you want to climb Mount Everest?” Mallory’s admirably terse reply:

“Because it’s there.”

It’s worth noting that the 1924 trip was Mallory’s final visit to Everest not because he reached the summit, but because he died trying.

As a writer, I worry about the role I play—admittedly a small one—in the increasing amount of data bombarding our world. These bits and bytes assembling themselves into daily blog posts add to the world’s data stockpile. So does everything you’ll write today, and into the foreseeable future.

Every PowerPoint presentation, every white paper, every boring employee newsletter (and the few interesting ones, too)—every communication we produce gets socked away into the digital storage bin. So let’s make those words count, shall we? Let’s produce good work. Work worth reading.

That’s our Everest; I climb it daily. Come join me.