Episode 19 | How To Make Numbers Sticky: Chip Heath on Making Data Count February 06, 2022

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GUEST: Bestselling author Chip Heath, Making Numbers Count

When we look at the world through numbers, our brains can’t always compute the full picture, says Chip Heath, co-author of Making Numbers Count. On this episode, this New York Times bestselling author (Made to Stick, Switch) shares how the right numbers told the right way can be absolutely illuminating. The trick is translating those raw numbers and stats into a language that is more transparent and meaningful, and, ultimately, easier for our brains to understand. Why is this important? Data drives decisions in our lives, as well as for society, whether that’s tackling climate change, making capital investments, or urging for change. When employed correctly, those numbers can bring about powerful “a-ha” moments.

GUEST BIO:

As an academic, strategist, and author, Chip Heath has spent his career helping people make their ideas and messages stick. He’s the bestselling author, along with his brother, Dan, of several books, including, Made to Stick and Switch. Their books have sold more than 3 million copies worldwide and have been translated into 33 languages. His latest book, with co-author Karla Starr, Making Numbers Count: The Art and Science of Communicating Numbers, provides practical tools and tips to help anyone “speaking” numbers to create more compelling messages and better engage with their audiences. Heath is a professor emeritus in the organizational behavior at the Stanford Graduate School of Business, where he has taught since 2000. He also has helped hundreds of clients develop ideas and messages that stick. He lives with his family in Los Gatos, California.

LINKS:

Making Numbers Count

Heath Brothers publications 

Bestselling authors and brothers Chip and Dan Heath. Contributed photo: Henry Medina

Full Transcript

BRAD PHILLIPS, HOST, THE SPEAK GOOD PODCAST:

Do you know the difference between one million and one billion?

I mean, you could do the math, and certainly you know that one is larger than the other. But can most of us comprehend just how profound the difference between six and nine zeroes truly is?

In their new book Making Numbers Count, authors Chip Heath and Karla Starr offer this thought experiment. They write:

“You and a friend each enter a lottery with several large prizes. But there’s a catch: If you win, you must spend $50,000 of your prize money every day until it runs out. You win a million dollars. Your friend wins a billion. How long does it take each of you to spend your lottery windfall? As a millionaire, your encounter with runaway consumerism is surprisingly short. You go bust after a mere 20 days. … For your billionaire friend, resources would hold out a tad longer. He or she would have a full-time job spending $50,000/day for…”

And here, I’ll pause for a moment to allow you to hazard a guess.

The answer? 55 years.

I don’t know about you, but I was shocked when I first read that. So much so, that I did the math – and it checks out.

Big numbers like one million and one billion are, for most of us, abstractions. But putting them into relatable terms helps us to grasp how much of a difference three little zeroes really make. And it makes clear that learning how to translate numbers well – is a skill that can radically alter the success – or lack thereof – of your communications.

In my day-to-day work as a presentation trainer, we often work with financial types – people who serve as the Chief Financial Officers for their companies. And they almost always begin our discussion with the same self-deprecating line: “My talk is boring – I’m just the numbers guy,” or “I’m just the person who reports the numbers.” When they say that, I always push back. Because behind every number is a decision. A surprise. A story. Behind every number is a product that sold less than expected, or more than expected – or exactly the same as they predicted, which would be a remarkable testament to their forecasting skills. Behind every number is a disappointment, an achievement that didn’t come to pass – or a reason for celebration, for one that did. Behind every number is a trend that suggests a course correction is necessary, or the timeframe needs to be adjusted, or new personnel needs to be added to the head count in order to meet surging demand.

Great communicators first learn to see numbers as a core part of the narrative. Then, they learn how to translate them into numbers that stick and persuade and lead to action.

Say, for example, that some politicians have started attacking the National Endowment for the Arts. Perhaps they object to a certain artwork, or they believe the federal government shouldn’t fund the arts at all, especially given existing budget deficits, or maybe they just want a wedge issue to drive a week’s worth of cable news chatter. So, they go on television and blast the $148 million that the federal government allocated to the NEA and they say that hard-working Americans shouldn’t have to spend their money so that someone else can paint a watercolor.

The authors of Making Numbers Count first offer how most supporters of the arts might respond, with something like this: “In 2016, the $148 million allocated to the National Endowment for the Arts accounted for .004% of the federal budget expenditures.” That framing does put into perspective how small the expense line really is – but is .004% really going to stick, or lead anyone to change their mind?

As a better alternative, they offer this pithy example, which also makes for a pretty nice media soundbite or tweet: “Trying to balance the budget by eliminating the NEA would be like editing a 90,000-word novel by eliminating four words.”

As the authors write, “We believe in numbers not as background, not as decorations, but as central points, with profound stories to tell. We believe in numbers, deeply. We believe in making them count.”

My guest is one of my favorite business writers of all time. Chip Heath has, along with his brother Dan, written four New York Times and Wall Street Journal Bestsellers, including Made to Stick, Switch, Decisive, and The Power of Moments. Chip is also a professor at the Stanford Graduate School of Business. In Making Numbers Count, he and his co-author offer 30 different ways to translate numbers, along with loads of practical examples that you can put into practice immediately.

By the way, in the episode, I reference a baseball player named Mendoza. I didn’t have all of my facts at hand during our discussion, so here they are: the player’s full name is Mario Mendoza. He played for three teams from the mid-1970s to early-1980s, and his career batting average was .215. That’ll make more sense to you when we get there.

(MUSIC PLAYS)

I have to tell you that I feel like I’m speaking to one of the Beatles having you on the podcast. I have read each of your books. I’ve probably recommended your books to hundreds of people through the years. Before we get to your new book, which I’m excited to talk to you about, I do want to share one line with you from your book, Made to Stick, that really captured my view of effective communication, and that very much changed the way that we speak with our clients. The line you wrote was this: “Common sense is the enemy of sticky messages.”

CHIP HEATH:

(LAUGHS)

PHILLIPS:

Can you talk about why common sense doesn’t stick?

HEATH:

Well, I think common sense doesn’t stick because most of the people who have messages that they want to get across are experts. And, there’s a fundamental curse of knowledge that has been identified in behavioral economics and psychology research that says that when we become experts, one of the things that becomes harder and harder for us to do – we’re better at solving problems – but what becomes harder and harder for us to do is imagine what it’s like not to be an expert. And so, if you’ve ever talked to a doctor or a lawyer, and you’re not trained in medicine or law, you’ve been on the other side of the curse of knowledge. That expert cannot imagine what you don’t know about their field. And it’s not just fancy people with fancy titles. Pick an 11-year-old boy and ask him about his favorite video game. And you’ll be on the other side of the curse of knowledge. That 11-year-old cannot fathom the depth of your ignorance about that game. And so, common sense is the enemy of sticky messages because most of the things that experts know and treat as common sense are things that the world is still needing to discover. And that’s why they come to an expert in the first place. But we get frustrated when talking with the experts because they assume that we know things that we don’t.

PHILLIPS:

And I suppose the same is true of statistics. I wonder if you think I’m overstating the case if I were to say that raw data and numbers by themselves aren’t sticky, and in order to make them sticky, they need to be surprising or counterintuitive or framed in some particularly relatable manner. Is that overstating the case, or do you agree with that?

HEATH:

I don’t think that is overstating the case. And, in fact, we may have understated the case, because it’s not just big numbers or elaborately produced statistics that are counterintuitive. It’s numbers above six. There’s a phenomenon in psychology called subitizing. And if you’re a parent and you’ve ever read a counting book with your kids, you know that if you turn the page and there are two goldfish on the page, your brain just shouts out two. You don’t have to count them. You’re teaching your kid how to count one, two, but you, as an adult, knows that there are two. And if you turn the page and there are five objects on the page, you know that there are five. But that subitizing insight breaks down at around six or seven. And so, you never turn the page and immediately see they are eight objects and go “eight.” And so, it turns out that when we bring our brains to the problem of numbers, we’re really, really good up to about the number five. And the problem is that’s not enough for dealing with the numbers that we deal with in our lives.

PHILLIPS:

Right. And one of the things you write about is a lot of times is that we’re trying to communicate about items that are almost incomprehensibly large or incomprehensibly small. You give examples like the size of the universe, the amount of money that $1 trillion represents, or, on the other end of the extreme, the size of a nanoparticle. So, given what you just said about five being kind of the highest number we can intuitively immediately wrap our brains around, how do you go about translating those data about those incomprehensibly small or large things into something more relatable?

HEATH:

Yeah. Let me give you an example that that both captures the difficulty that we have in understanding large numbers, but also provides a suggestion of a way out that we can use. So, suppose that you were counting off a million seconds. How long would that take you? How long would it take you to count up to a million?

PHILLIPS:

I mean, this is one of those great Chip Heath questions. A million, you’ve already made your point. I have no idea. Let’s arbitrarily throw it out there. I don’t know. 12 years.

HEATH:

Yeah. Most people overestimate. It’s 12 days.

PHILLIPS:

Huh.

HEATH:

So, a million seconds is 12 days. A billion. Now, you probably don’t have much intuition about that, but you can kind of quickly do the calculation and get a ballpark number. That’s still incomprehensible. The answer is 32 years. And I’ve used that question with lots of people, ranging from people who are not numbers’ people and they are not surprised that they mess up the numbers, and numbers’ people, like mathematicians, engineers, or physicists. You ask that question and it’s clear that they don’t know that there is a gap between 32 years and 12 days that is captured by that millions and billions (comparison). And so, we run into these figures all the time in our culture, and we know that a million is a big number and we know that a billion is a bigger number, but we don’t know how much bigger it is.

PHILLIPS:

What’s interesting about that is I wonder how often in our politics, politicians intentionally don’t translate numbers because they like to hide behind the very fact that those numbers are incomprehensible. If you give a number like billion or trillion, we can’t really understand how large that is. But, if they did a better job of translation, putting it in terms of a family budget or an individual income, suddenly then we might be outraged by it. So, I do wonder if sometimes public of officials and others are using large numbers to purposely obscure what more granular detail would illuminate.

HEATH:

Yeah. And I think there’s a sense whenever somebody sees through that, it’s always remarkable to us. I remember a friend of mine, James, as a junior in college, there was a controversy at the time over the National Endowment for the Arts that made some grants to people that turned out to be controversial artists. If you’re making grants to artists, you’re going to get different kinds of lifestyles and views. And people on campus where we were at, Texas A&M, were up at arms about National Endowment for the Arts funding these artists. They did provocative work that offended some people at the university I was at. And so, James would listen to them rant for a while, and then he would pick a quarter out of his pocket and hand it to them and say, ”You’re right. You shouldn’t have to pay for this as a taxpayer. There’s no reason they should be spending your money on this. Let me refund your money that you contributed this year to the National Endowment for the Arts.” And all of a sudden the demonstration brought home to people like, even if this is millions of dollars that go to this agency, it’s not much on a per capita basis. And shouldn’t we reserve our time ranting for ranting about something that’s more robust and meaningful in the context of the budget discussion.

PHILLIPS:

You know, one of the things that surprised me toward the beginning of your book, Making Numbers Count, you wrote that the secret to translating numbers is simple, avoid using them. And that’s pretty surprising in a book that is ostensibly about numbers. You’ve already given a couple of examples, but can you provide another example of how you would go about the thought process of taking a number and then translating it into something that doesn’t have numbers, but suddenly transforms into a much more powerful and effective message.

HEATH:

So, suppose you were talking about the position of women in society, and we’ve gotten to be more egalitarian over time, but we still haven’t reached probably where it should be. And so, there’s some writers in The New York Times, a few years ago, that were thinking about the percentage of women in various fields, percentage of congressman and senators, the percentage of movie directors who get the big budgets to work on blockbuster movies. But one of their comparisons was very poignant — Fortune 500 CEOs. So, these are the CEOs of business organizations that are among the top 500 biggest revenue producers in the economy. And the number that they were trying to capture was something like 3.5 percent, 3.5 percent of the CEOs of Fortune 500 companies are women. And yet what they did was they took that away as a number and they just said, you’re more likely to find a James running a Fortune 500 company than a woman. And that’s just, this is really wrong, you know, when we’ve got a whole 50 percent of the population that’s represented by fewer people than the number of James that are running corporations.

PHILLIPS:

So why do you think that is? Because most people – just doing some quick math 3.5 percent of 500 CEOs would be something on the order of 18 people. I think most people would come up with a shocking statistic that something like, can you believe that only 18 of the Fortune 500 CEOs are women and they would leave it there. Why would you then translate it into that very clever framing of there are more James, more CEOs named James than women. Why do you think that suddenly has so much more power?

HEATH:

Well, I think there’s an emotional component about James that it’s not present in the 18 out of 500 and kudos to the people that would actually translate to 18 out of 500, as opposed to talking about it as a percentage because our brains are bad at percentages. And so, moving from 3.5 percent to 18 out of 500, that’s a good move. That’s an improvement, but we can improve it even more because we’re still not capturing the ludicrousness of 18 out of 500. And that’s what the James comparison does. We take a name that we know and certainly are familiar with. In years past, when the current generation of CEOs were growing up, that was probably the No. 1 boy’s name. But it’s still only 3 or 4 percent of the population. And somehow we have a better visceral understanding of frequency from the talking about name distribution, you know, which names are more common and less common than we do about the distribution of women in positions of power. And that hint that we borrowed in that translation to James is a good one, in general, because there are lots of times when we have information in our brain that’s packed in one way. And, if we unpack it in the service of something else, we’re going to do better than in a situation where our brain has no information at all.

PHILLIPS:

And what I think about is the power of that translation you did to the James. I always think effective communication are when it really works. You make your audience more effective carriers of your message to other audiences. And I don’t think most people would remember 18 to 500. There’s nothing particularly memorable or sticky about 18. They’ll surely remember that there’s not enough women, but the raw data they probably won’t. So that information probably lives and dies in the room, because what are they going to say to other people is that there’s not enough women CEOs. Everybody already knows that. But, when you suddenly put it in the James terms, it seems like you’ve just made that audience member who heard that message a much more effective carrier of your message to other parties. So, if you want to talk about spreading and making an idea go viral, it seems like that’s a really good way to do it.

HEATH:

Yeah. That’s a great analysis. I wish I’d come up with it on the fly. But, it’s exactly right. The living and dying in the room, I love that phrase, because you know entrepreneurs go and pitch their ideas to venture capitalists. And if you’re really good, you get asked to pitch in front of the whole group of VCs at a particular firm. But before that, you’ve got to pitch to one person, who then goes back and pitches your idea to the group as a whole. And that person better convey your message effectively because they’re the only person in the room at that time. And so, I love the situation that you’ve highlighted, because if it lives and dies in the room, there are so many times when we’re not going to get the big opportunity because the room was the small-scale opportunity on the way to the big opportunity. And if the small-scale people can’t convey the message, then we’re sunk.

PHILLIPS:

And, you know, sometimes we get resistance. You mentioned a few moments ago about how the human brain doesn’t really know what to do with percentages. And you give this tip in the book to avoid fractions and offer, what I think is, a really surprising example about the A&W Restaurants chain and what they learned. Could you share that anecdote?

HEATH:

Yeah. So, the CEO of A&W was writing his memoirs of his time in the food industry and talking about a particular irritating thing that he ran into when he was CEO and McDonald’s had come out with a quarter pounder. It was a big hit because it was the biggest beef patty that we had in fast food hamburgers at the time. And so, A&W was trying to combat this, and they decided we’re going to do one better. We’re going to go a third of a pound and we’ll sell it to you for the same price as a quarter pounder. Did consumers rejoice about this? No, they were complaining because they thought a third pound is smaller than a quarter pound. And, therefore, you’re asking us to pay the same amount, so you’re ripping us off. And it’s kind of crazy if you’ve been well drilled in fractions, but know that a lot of the people in the population are looking at three versus four and four is bigger than three. And, therefore, the quarter pounder ought to be the better deal at a same price. And so, that’s a simple example, but if our brains are not prepared automatically, even with training in second through seventh grade about fractions, to interpret a third pounder versus a quarter pounder, we’re kind of sunk on most of the rest of the fractions.

PHILLIPS:

You’re reminding me. I know we’re here mostly to talk about Making Numbers Count, but there’s another example you give in Made to Stick. I forget the details. I think it was about a group talking about the calorie counts of Chinese food and wheeling out the actual food on a tray to make the point. And it just goes to your point about if you are sticking with just sheer numbers and saying Chinese food is whatever it is, 2,500 calories for a dinner portion, it’s not going to stick. Do you remember what that example was and how that group made the case that Chinese food is a lot more caloric than people usually assume it is?

HEATH:

Sure. It is actually even more unassuming than Chinese food because we’re always skeptical a little bit about main courses. It’s actually movie popcorn.

PHILLIPS:

Ah, okay.

HEATH:

There’s a group, a nutrition group, that had analyzed samples of movie popcorn from four different metropolitan areas. It was a beautiful analysis, four different metropolitan areas. They went to 10 different theaters in each area, and they sampled movie popcorn. And, at the time, they would pop popcorn in coconut oil, which is high in saturated fat and then they would put that butter goop on top of it. Who knows what makes that up, but it’s high in saturated fat, as well. And so, a typical movie popcorn had 32 grams of saturated fat. Now that’s probably not ringing any bells in your mind unless you’ve closely followed the nutrition news, but that’s about twice the FDA recommendation for saturated fat in a diet. And you’re consuming it in one afternoon snack. So, to roll this out, they didn’t talk about twice that FDA requirements or that the CDC recommends less than 16 grams per day. What they do is they rolled out a buffet of a bacon-and-egg breakfast, a burger and fries, and a steak potato dinner. They had all the food laid out and they said, if you eat all those three meals, your saturated fat will equal the saturated fat of one popcorn. And, all of a sudden, sales plummeted of popcorn and movie theaters across America. And it’s because a nutrition group for once got it right. Instead of talking about the numbers and the calories and saturated grounds and things that we don’t comprehend, if we’re not scientists in the area, they talked about a day’s meal and taking the fattest meals that you can think of and putting them all together and you’re about equaling one afternoon snack.

PHILLIPS:

Yeah, when you talk about that, that is visceral. You give another example in Making Numbers Count of the amount of sugar. I think it was in a bottle of a 12-ounce bottle of cran-apple.

HEATH:

Yeah.

PHILLIPS:

It’s similar to what you just shared. It’s a way of making clear how useful it is and really persuasive it is when you put numbers into some kind of emotional term. And I know that seems counterintuitive to people because a lot of people are under the illusion that stories are the heart and stats are the head. You use the phrase, an emotional number, and that example of cran-apple, I think, provokes an emotion.

HEATH:

So, what we did is we translated it into things that are commonly regarded as a kind of measuring stick for sugary foods. And so, we said, what is a Krispy Kreme glaze doughnut? What does it have in terms of sugar? And the answer was one Ocean Spray cran-apple juice has the same number of grams of sugar as three Krispy Kreme glazed doughnuts and four sugar cubes.

PHILLIPS:

Ugh.

HEATH:

And so, clearly the Krispy Kreme doughnuts have calories and fat and carbohydrates other than sugar, but just on a sugar dimension, that comparison really helps us understand how crazy it is to have a sweetened drink that has that much sugar.

PHILLIPS:

I’m curious, when you are dealing with, let’s say you’re dealing with a client, and it’s a client that says, we really want to point out that these types of beverages, like cran-apple, have loads of sugar. Do you begin with what is the emotion we’re trying to elicit? And we want people to feel repulsed or disgusted by that amount of sugar. And then, from that emotion, reverse engineer a statistic to match that. Could you talk about how you can create a statistic? Because, I mean, you could go so many different directions, but how do you go about creating what matches the outcome that you hope ultimately it has?

HEATH:

I think that the thing is that there are domains that are relevant for your purposes, and you want to survey broadly the things that people are going to think are relevant. And so, for example, suppose we’re trying to convey, and I’m going to miss the right figures on this because the statistics don’t stick very well, the global games industry, video games industry, is about 180 billion dollars or something like that. And that may not mean a lot to you, but what if I told you the global games industry is four times the size of Hollywood and nine times the size of the global music industry. That’s just astonishing to me and it’s surprising and it’s meaningful. It makes you pay more attention to video games when people talk about them as problems in the social world.  As an entrepreneur making investments in places to spend your career, video games is a good idea. And it’s such a good idea, it starts to look ludicrous that we have the Oscars and music awards for industries that are way smaller than the video games, but we don’t have the same awards for video games. And I suspect that it’s kind of a geek discrimination thing. I think it’s just that games just you don’t look as good on runways or red carpets, as the movie industry and music industry people. But, it really brings home the fact that that there’s a big difference here. And so, I think what you want to do when you’re tackling your statistic is to think about the relevant domains and think about what lends emotion in those domains. And many times, there’s a striking statistic that we’re not taking advantage of.

PHILLIPS:

Maybe I’m quoting you back to yourself. This may have come from your book Switch, but when you were just saying that, it struck me that one of the things good speakers do a lot of times is open up a curiosity gap and point out to people what they don’t know. And it seems like that statistic, if you’re talking about the power of gaming, and you begin with the statistic, “(as in) you think you know about gaming, let me shatter that illusion,” they’re yours from the opening minute of your talk by exposing that lack of knowledge to people.

HEATH:

And I think the curiosity gap is a really, really intriguing phenomenon. George Loewenstein at Carnegie Mellon wrote a review paper about curiosity gaps. And we often complain that we can’t make people listen to our ideas, that the world is noisy and that there are tons of messages, and we can’t get our message across to the key opinion leaders, but, it turns out if you surprise people, you automatically rivet their attention. And so, if you think about the emotion of surprise, we get the jaw drops and the eyes get wide. And, that’s your body telling you that your brain just made the wrong prediction. Widen your eyes, take in new information, drop the jaw, stop talking. Don’t do anything. Freeze in your place because your brain just made the wrong prediction. You better update something about your mental model. And so, I think that emotional surprise in that standard shock expression that people have when they’re surprised, those are clues that we can get our message across, even in crowded environments, if we can find what shocks people. And, you know, telling you that there are more Jameses than women in CEO ranks that shocks people. That telling people that instead of Ocean Spray cran-apple juice you could have had, for sugar content reasons, three Krispy Kreme glazed doughnuts, and four sugar cubes, that’s all of a sudden message that gets our attention.

PHILLIPS:

You know, Chip, you’ve actually had the opposite effect, because now I’m going to eat three Krispy Kreme doughnuts and say, well, at least it wasn’t a cran-apple.

HEATH:

That’s right. We’ll do that fat comparison for you later.

PHILLIPS:

(LAUGHS) That’s right, you’ll wheel it out on a tray for me. You know, speaking of those kind of jaw-dropping numbers that you just alluded to, I think, there were several in your book, but one of them that really caught me off-guard was when you were talking about experiencing numbers and you gave the example of how quickly a batter in a Major League Baseball game needs to be able to decide whether or not to swing at a pitch.

HEATH:

Yeah.

PHILLIPS:

I think it’s a great example of experiencing numbers and, by the way, my arrogance and probably hubris when watching a ball game and yelling at the screen and saying, why did you swing at that?

HEATH:

Yeah. Yeah.

PHILLIPS:

Your example really makes clear what the answer to that is. What did you find? How did you turn that into experiential numbers?

HEATH:

Well, what people throw around a lot is when we have extremely athletic performance, people talk about the milliseconds with which people react. And if you think about a millisecond, what is that? That’s carving a second into 1000 increments and it turns out it about 250 milliseconds for a batter to recognize a pitch. It takes about 150 milliseconds to react to that pitch. And that sounds impressive, and it is impressive, but the way to bring it home is to do something a little more physical. And so, suppose you’ve clapped as many times as you could in one second, that’s four claps in about one second, each one of those claps is 250 milliseconds. And so, translating that statistic that we had about batters back into claps, the first clap, you have to recognize the pitch in the second clap you’ve got to execute the pitch. And by the third clap, play is over. It’s already gone. And so that’s how fast batters react. And when I heard that and did the calculations and did the translation, it was just an amazing, amazing thing that I had never considered before.

PHILLIPS:

It really gives you a new perspective. I’m a baseball fan. There’s something in baseball known as the Mendoza Line. It’s based on a batter. I think this was a player in the 1970s, who I think his batting average was something on the order of .206, and people used to kind of derisively say, oh, he’s below the Mendoza Line, meaning a really inferior batter. When you hear this kind of experiment that you just did, it’s kind of a miracle that everybody’s not under that Mendoza Line. So, baseball is a good example to stick with for a moment, because it gets to a question about when precision of numbers is important. You give an example of, if you’re a baseball fan, you understand what a .263 or .302 batting average is. So having three numbers to the right of the decimal point is fine. But, in general terms, when do you think translation becomes a negative and that precision is truly important?

HEATH:

Well, precision is truly important where you need the precision. And so, if we’re calculating the fuel that we need to do an elaborate maneuver in space, we’ve got to dock two things together, or know the angle at which it’s coming in, or the speed at which is coming in, I want those calculations to three or four decimal places. That’s good. But, for the most part in life, we don’t need that many decimal places. And so, if the new place your office your firm moves into is actually just 5.73 times the size of your current office, you can round up to six and nobody’s going to be less excited if they find out it’s only 5.73 later on. Rounding is good. And, and I think the trouble is, very often, we confuse the number of situations where we need precision and overestimate that dramatically. So for example, if you give people numbers like 3 million, as opposed to 2,793,462, we get more confused when we hear the more elaborate number. We’re less likely to remember. We’re less likely to be able to use it in a calculation later on, on the fly, than if we use the 3 million. And so, I think we’re actually doing a disservice to kids when we teach them mathematics, because we teach them backwards. We spend a lot of time dealing with the decimal places. They’re closest to zero first in the multiplication. And then,we’ll gradually get to the top of the chart. But when physicists and engineers and doctors are using numbers in their normal life, they’re more likely around the 2.7 million up to three. And use a three in a calculation because they can get that right. And they can get some insights from that they wouldn’t get if they’re bogged down and calculating the fourth or fifth significant digit.

PHILLIPS:

One of the parts of your book that made me kind of chuckle as I was reading it was, and I’ve never seen this in my 17 years of doing communications work, I’ve never seen somebody get a standing ovation for delivering a statistic well. You had that happen to you in one of your classes. Could you share that story about the student who had got the standing O.

HEATH:

Yeah, let me make that clear. It wasn’t happening to me; it was happening to the student and the student did a brilliant job. So, I had assigned the students the task of justifying the purchase of carbon fluorescent bulbs when they first came out and they were expensive. There were seven bucks a piece and you could buy four standard incandescent bulbs for about buck or two. So, the bulb cost you $7, but it saves you three quarters of the electricity every time you turned on for a lifetime and lifetimes could hit seven years for these bulbs, whereas the standard bulb was burning out in about a year. And so, I asked people to take this abstract notion of savings on electricity and make it tangible and concrete. And they were going around the room and people were calling off their equivalence for saving three quarters of electricity. And one group said, we decided not to do your electricity thing. And I said, “Oh really?” (They said) “Yeah, because it’s very abstract. What you want is concrete. We went with the idea that it was seven years, these bulbs would last seven years between changing.” And I said, oh OK, that’s interesting, seven years as opposed to an abstract statistic. And, they said, no, we’ve got an even better version of that. Suppose you change that bulb when your child is learning to walk. The next time you have to change that bulb, your child will be in second grade, learning about oxygen as a gas. And the third time you change that bulb, your kid will be in driver’s ed. And, I was stunned by this, and the class was stunned. And then they broke into applause, and it was the first time and the only time I ever saw MBAs giving a standing ovation for anyone but much less in the context of finding a statistic, but that’s just brilliant work. And it shows us how little we know even of seven, that I let that number seven pass without remark. But as soon as you unpack it, in terms of the events of being alive, it’s astonishing because you think, wow, this bulb really does last a long time, but you also think, wow, life is short. I better get my kids going to that zoo trip that we’ve been talking about.

PHILLIPS:

And I remember when this was a piece of legislation and there were a lot of lawmakers and schools who were opposed to changing to that sort of light bulb. And I remember there being a lot of data thrown around at the time and how much longer they lasted, but I don’t remember anybody in the public sphere using something as concrete as what that student of yours came up with. And I wonder, you know, there are times when just coming up with that maybe is enough to move needle in a public debate. It’s too bad your student wasn’t at that moment working for the staff of one of those lawmakers.

HEATH:

Exactly.

PHILLIPS:

In thinking about speaking with you, I wanted to think about a statistic that really moved me. And I wanted to, I mean, a.) I’m just curious if you think it’s an effective stat, but also, what I don’t know is what the technique was that they used and maybe how it could be applied to other things. So, the thing that jumped to mind is something that’s based on a horrible story. It was when dozens of women accused Bill Cosby of rape and sexual assault. And if you remember, at that time, a lot of the individual cases that were brought forward were treated by some, as “he said, she said” stories, we can’t ever know what happened it was just two people in the room. So, the New York Daily News ran a cover. And the cover said, he said, she said, she said, she said, she said, and they did that dozens of times on the front page. And what that in effect made happen, I think, is that every “she” became a real person. It wasn’t just an abstraction of 55 women accusers. And so that, out of everything, as I was thinking about this conversation with you, that was the thing that jumped out at me as one stat that I thought really got it right. And, sent a message in a unique way I’d never seen elsewhere before. That changed the way that people perceive the story. I mean, I guess, first of all, I’m curious what you make of the step, but again, what device were they using to try to create that impact?

HEATH:

I think it’s brilliant and I can see why it made the impact that it made on you. The fundamental psychology that we’re pulling against when we’re trying to unpack numbers is that there’s a psychophysical numbing, that’s the jargon term and the literature for it. But psychophysical numbing says that the first increment of 10, if you’re going for $10 to $20, that’s a substantial amount of change. If you go from $30 to $40, that’s a little less, 120 to $130. That’s a really tiny amount. So, there’s this almost physics kind of law in our brains that as numbers get bigger, our brains get worse and worse about detecting differences between numbers. And so the idea that there are 10 women or 50 women that have accused somebody of an awful pattern of behavior, by unpacking those 10, 12 women, 20 women, whatever it was at the time into individual lines of text, all of a sudden you get the visual weight of what 25 means or what 50 means, but in a way that you’ve missed before, just because of psychophysical numbing. And so, I think that principle of unpacking the difference is an incredibly powerful thing, especially when our brains are going to tend to get numb over time.

PHILLIPS:

Right. I’d like to end our discussion with something you wrote toward the end of your book. You wrote that going into this project, you didn’t expect to feel awe from the statistics you ultimately gathered. I’m just curious if, out of everything you discovered in the research and writing, was there one particular statistic that left you feeling truly awed?

HEATH:

Probably my favorite, and it’s a quirky favorite, but I love, love science and I love biology. There’s a desert ant that is really tiny. It’s like you could fit a hundred in an inch, probably. And the desert ant is an incredible explorer because it lives in turf that doesn’t have much food. And so, researchers who’ve studied these things, have documented treks of 30 and 40 meters from the nest of these little soldier ants, desert ants looking around for food. And then the amazing thing is no matter where they’ve wandered to, if they find food, they make a beeline back to their nest. And so, no matter where they are, they’ve got GPS that tells them exactly where their nest is. And it’s an astonishing, astonishing fact, but it didn’t mean much to me until I translated it into human terms. And so, I said, what if you scaled up a desert ant to the size of a human, what would be the area that they would be looking for food? The answer was Washington D.C. The Washington D.C. Metro era would be crawling, not just the area around the capital and the Washington monument, but all the way out to the defense department, the Pentagon and all the way up to the embassies on the other side of the town. And the trick would be you could search all this area for a sandwich as an adult, but then when you find the sandwich, you grab it, and you make a beeline back to your apartment or your hotel room with no mistakes. And when I put that in human terms, it’s like, I became awed with what, I mean, we don’t understand GPS because our GPS isn’t that good. And, you’re running it on the computational power of whatever neurons fit into an ant brain. And so that’s part of the tragedy of losing aspects of our environment. You might have just wiped out the desert ant and you will never understand GPS in a different way then you understand it today.

PHILLIPS:

That was a great example. You gave another one, and I’m not going to give a spoiler because ultimately I’m hoping that listeners will be inspired to pick up a copy of Making Numbers Count, but you give another example from the natural world. I think it’s a frog at the three-point line and yeah, that was another one of those awesome things that will change the way I see that species. I think it’s also one of the strengths of your book that the examples you pull from are from all over the place, the natural world, astronomy sports, race, wealth. It’s a terrific work that adds to your collection. I literally have all five of your books now, and, at some point, you’re going to have to put together a gift box for people like me that are Heath nerds. And, I just also want to give a shoutout to your co-author here, Karla Starr, who co-authored the book with you. Chip, thank you so much. It is a real treat to have the opportunity to speak with you.

HEATH:

Thank you for this interview.

• Chip Heath
• Making Numbers Count
• statistics