“You should never tell stories. Stories are the worst.”

“Stories are terrible. You should never tell stories. Stories are the worst.”

I would never disagree with Nobel Prize-winning economist Daniel Kahneman about anything economic. But he’s making proclamations about my areas of expertise here. And Nobel or not, he’s dead wrong.

Stories
Stephen J. Dubner, photo by Audrey S. Bernstein, CC BY-SA 4.0

Okay, that’s not a direct quote from Kahneman. It’s Kahneman as told by Stephen J. Dubner, co-author of the Freakonomics books.

Storytelling propelled Freakonomics to the best seller lists. Let me rephrase that: a book about economics hit #2 on The New York Times Best-Seller list. A book about economics.

Because it wasn’t just a book about economics. Freakonomics melds story, theory, and data into such a compelling package that anyone can get drawn into the story. Even the kind of person who fell asleep in the back row of Economics class. Even the kind of person who would never register for Economics class.

Stories vs. anecdotes

So why does Dr. Kahneman hate stories so much?

It turns out he didn’t understand what Dubner meant by the term. In his interview on Tim Ferriss’s podcast, Dubner explained Kahneman’s objection:

“…he said, ‘Stories don’t contain any data and they don’t have any time – they don’t have a time series attached to them.’ And I realized that Danny kind of, Danny thought I was talking about was not so much what I think of as a story, but what I think of as an anecdote.

An anecdote would be, like, let’s say we’re talking about drunk driving and the actual data and the numbers and so on. And I can tell you that the data seem to show that if I’m a drunk driver vs. a sober driver I’m 13 times more likely to get involved in a fatal crash. That’s what I tell you the data say.

And then you say, ‘Well I’ve got an uncle, my uncle’s accountant drinks every night at the tavern and drives home and he’s never even had a fender-bender.’ That’s an anecdote.”

Heck, using that definition even I would hate stories. So what’s Dubner’s definition?

“…to me what a story is it’s got the narrative but it does include the kinds of things that Danny Kahneman says you need to include, which is data and time series. Data, because you need to know the magnitude of the story —is it really important? And time series because you need to know if it was a kind of blip or if it really persisted. And that to me are the elements of a good story: data, a time element, at time series and a narrative with characters that people can identify with.”

Dubner had one other requirement for a story.

“And, by the way, it needs to all be true. I’m a journalist by training, I’m a nonfiction writer. And I believe that the best kind of storytelling is where you’ve got real reporting, real numbers, and you can make an argument that acknowledges my argument is not perfect, it’s not meant to be, but it is compelling because it is true.”

I couldn’t agree more.


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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.

Making data interesting: Advice from a word-alchemist

A while back, I wrote about facts being inherently less interesting—and less memorable—than stories. But you can’t avoid data forever; sometimes you have to talk about it. And when that happens, you need a way of making data interesting.

Enter your best friend, the Story. Yes, stories can include data. In fact, journalist Stephen Dubner says they must.

Why should we care what Stephen Dubner says? Because he’s not just a writer. I believe he’s actually an alchemist. A word-alchemist.

Alchemists in the Middle Ages searched for a way to turn base metals like lead into gold. Dubner and his co-author, award-winning economist Steven Levitt, have actually done that. They’ve taken the “dismal science” of economics and turned its principles—and data—into best-sellers with stories so compelling you can’t stop reading.

If you haven’t read Freakonomics, Super Freakonomics, Think Like a Freak, or When to Rob a Bankperhaps because you assumed that any book about economics had to be dull and boring—I forgive you. That kind of thinking kept me away from them for so long. But, boy was I wrong.

Here’s the opening paragraph of the Bookrags study guide for Freakonomics:Freakonomics, a case study in making data interesting

What trait is shared by both Ku Klux Klan members and real-estate agents? In what way do the working worlds of Chicago schoolteachers and Japanese sumo wrestlers intersect? These questions might seem puzzling at first glance, but the answers provided in Freakonomics: A Rogue Economist Explores the Hidden Side of Everything reveal that fundamental notions of economics can be used to interpret just about everything in modern society.

I’m sorry—anyone who can put KKK members and Realtors in the same group has my attention. Talk about making data interesting. And teachers and sumo wrestlers? Can you imagine? It doesn’t matter if you can’t, because Dubner and Levitt have imagined it for you.

Making data interesting: Tell stories

Tim Ferriss interviewed Stephen Dubner on his podcast a couple of years ago—I just got around to listening to it this week—and Dubner’s description of a good story fascinated me:

But to me what a story is it’s got the narrative but it does include…data and time series. Data, because you need to know the magnitude of the story—is it really important? And time series because you need to know if it was a kind of blip or if it really persisted. And that to me are the elements of a good story: data, a time  series and a narrative with characters that people can identify with. And by the way, it needs to all be true.

It all needs to be true. The best stories always are.

So don’t think you have to bombard people with data to get them to trust you. Facts—even millions of them—can’t build trust on their own. And people won’t remember them, anyway, unless they’re set in a story. A true story. Told by you, from your heart, with memorable characters that people can identify with.

It’s simple. Even when you’re talking about a complex subject like economics.

Malcolm Gladwell on Conversation & Speaking

This morning I heard an interview Malcolm Gladwell did for Stephen Dubner’s Freakonomics podcast. In discussing his analysis of Anders Ericsson’s “10,000 hour rule”—that it takes that many hours of practice to become an expert—Gladwell talked about his own evolution as a public speaker.

“I didn’t spend a lot of time studying others. Because I thought that what people respond to as an audience is authenticity.”

Readers of this blog will recognize that as my favorite A-word. Gladwell continues:

“So I spent a lot of time thinking about …what is the image I’m trying to project about the kind of person I am, the way that I see the world. And I finally realized that what I am is someone who’s not too formal or studied or…I’m conversational.”

I have heard this from so many speakers who insist on going into a speech armed with nothing more than a list of bullet points. “I want it to be conversational.”

So how does Gladwell achieve that conversational tone in his speaking? Let’s listen in:

“That meant that I had to, I really had to memorize everything. I couldn’t use slides and notes and it couldn’t seem like a classroom lecture; it had to seem like a conversation with me.”

In other words, he treats each speaking engagement like a TED Talk.

Most speakers don’t have the time to memorize a speech—especially if they speak on many different subjects at different venues. And, to be fair, it is part of Gladwell’s job to speak well. At this point in his career, his appearances command a hefty fee.

But communicating is part of an executive’s job, as well. Speaking can help raise the profile of the organization they lead, sell more of its products, increase its prestige. I encourage my clients to think of speech-giving not as something that takes them away from their “real”responsibilities, but as another facet of their job as leaders.

Being conversational doesn’t mean speaking off the top of your head—please, please never do that. But it does mean practicing. A lot. And as you practice, you will find yourself memorizing parts of the speech naturally.

I don’t share Gladwell’s aversion to looking at notes from time to time. Unless you’re an actor in a play, no one will fault you for having a script in front of you. But don’t  deliver your speech to the podium—if you glance at your notes, stop speaking and don’t open your mouth again until you’re looking at the audience. If you haven’t practiced your speech, those silences can seem interminable. Practice enough and your audience reads them as thoughtful pauses.

Conversational and thoughtful. Not a bad way to present yourself.