statistics

From the Lab: Make It Human

Posted on by Nick Enge

In The Science of Speaking, I cite research showing that human stories are significantly more impactful than statistics. Here’s yet another study that sheds light on this bias, and suggests that it may be hard-wired in us.

In a 2007 study at UCSB, researchers asked participants to detect subtle changes in pictures, like those games in children’s magazines that ask you to spot the differences. When the changes to the pictures involved inanimate objects, 70% of the changes were noticed, in an average of 5 seconds. When the changes involved humans, however, 96% were noticed, and they were noticed even faster, in an average of only 3 seconds. Changes to other animals were in the middle, with a recognition rate of 83%. Interestingly, changes to animals were more recognizable than changes to vehicles, which suggests that these differences are evolutionarily hard-wired: despite that fact that vehicles are much more dangerous to us today, our visual attention is still more attuned to animals, which would’ve been dangerous to our ancestors.

When humans are involved, we pay greater attention. Therefore, the more human you can make your presentation, the better. Rather than simply citing statistics, tell human stories that make them come alive. And instead of simply showing the audience pictures of your product, considering showing them pictures of people using it, as humans will be more likely to draw their attention.

 

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Off the Shelf: Stories > Statistics

Posted on by Nick Enge

In Made to Stick, Chip and Dan Heath tell the story of an experiment that Chip runs in his classes at Stanford. Students are asked to give a one-minute persuasive speech, after which their classmates rate the speaker’s delivery. Then Chip distracts them with a short video clip.

When the clip is over, Chip asks the students to write down, for each speaker, everything they remember about the speech. Here are the results, according to Chip:

The students are flabbergasted at how little they remember. Keep in mind that only ten minutes have elapsed since the speeches were given. Nor was there a huge volume of information to begin with—at most, they’ve heard eight one-minute speeches. And yet the students are lucky to recall one or two ideas from each speaker’s presentation. Many draw a complete blank on some speeches—unable to remember a single concept.

 

In the average one-minute speech, the typical student uses 2.5 statistics. Only one student in ten tells a story. Those are the speaking statistics. The “remembering” statistics, on the other hand, are almost a mirror image: when students are asked to recall the speeches, 63 percent remember the stories. Only 5 percent remember any individual statistic.

 

Furthermore, almost no correlation emerges between “speaking talent” and the ability to make ideas stick. The people who were captivating speakers typically do no better than others in making their ideas stick.

There are several important things we can take away from this.

First, it’s essential to remember the iceberg. While the advice to think about what you want the audience to remember in terms of a tweet of 140 characters or less may seem extreme, this exercise shows that this is simply the way things are: your audience will remember at most one or two ideas from your presentation—if you’re lucky.

Fortunately, there are ways you can make your own luck by specifically designing your ideas to be sticky, in this case by presenting them using stories, not statistics. Rather than leaving it to chance what your audience remembers, you can (and should) consciously choose what you want them to take away, then design your presentation specifically to make that happen.

Finally, although good delivery can certainly help you, it’s not the only way to success, and it’s not enough by itself—memorable content is also essential.

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Between the Lines: Human-Scale Statistics 

Posted on by Nick Enge

In The Science of Speaking, I note that when numbers are very large or very small, it’s often good to present them by using an analogy. For example:

The accuracy required to land a spacecraft on Mars is like Steph Curry throwing a basketball from the three-point line of the Oracle Arena (in California) and hearing it swish in Madison Square Garden (in New York) just as the buzzer sounds.

In Made to Stick, Chip and Dan Heath present a similar analogy along with data to back up its utility. Compare the following two examples, they say:

  1. Scientists recently computed an important physical constraint to an extraordinary accuracy. To put the accuracy in perspective, imagine throwing a rock from the sun to the earth and hitting the target within one third of a mile of dead center.
  2. Scientists recently computed an important physical constraint to an extraordinary accuracy. To put the accuracy in perspective, imagine throwing a rock from New York to Los Angeles and hitting the target within two thirds of an inch of dead center.

When presented with the first analogy, 58% of people thought this feat was “very impressive.” When presented with the second analogy, 83% of people thought so!

The key, then, is not just to use an analogy, but to use an analogy that lives at the human scale, placing numbers on a scale that we can wrap our heads around. As the Heaths note, this can take some finessing. In both analogies, the distance from California to New York is still a bit intangible. “The problem,” they explain, “is that if you make the distance more tangible—like a football field—then the accuracy becomes intangible. ‘Throwing a rock the distance of a football field to an accuracy of 3.4 microns’ doesn’t help.”

As another illustration of human-scale statistics, the Heaths present an example taken from Stephen Covey’s The 8th Habit, in which Covey presents the findings of a survey of 23,000 employees from a variety of industries. Here are the findings:

  • Only 37 percent said they have a clear understanding of what their organization is trying to achieve and why.
  • Only one in five was enthusiastic about their team’s and their organization’s goals.
  • Only one in five said they had a clear “line of sight” between their tasks and their team’s and organization’s goals.
  • Only 15 percent felt that their organization fully enables them to execute key goals.
  • Only 20 percent fully trusted the organization they work for.

As the Heaths note, this is “pretty sobering stuff. It’s also pretty abstract. You probably walk away from these stats thinking something like ‘There’s a lot of dissatisfaction and confusion in most companies.'” But “then Covey superimposes a very human metaphor over the statistics.”

If, say, a soccer team had these same scores, only 4 of the 11 players on the field would know which goal is theirs. Only 2 of the 11 would care. Only 2 of the 11 would know what position they play and know exactly what they are supposed to do. And all but 2 players would, in some way, be competing against their own team members rather than the opponent.

As the Heaths note, “the soccer analogy generates a human context for the statistics. It creates a sense of drama and a sense of movement. We can’t help but imagine the actions of the to players trying to score a goal, being opposed at every stage by the rest of their team.”

Whenever you are presenting statistics, see what you can do to humanize them, either by shrinking them (or blowing them up) to a human scale, or presenting them in the context of a human story. By doing so, you’ll make your numbers even more impactful.

Note: This advice is a nice practical supplement to yesterday’s post about how great leaders appeal more to emotion and intuition than they do to logic. By humanizing your statistics, you can begin to transform logic into emotion and intuition, making your appeals even more effective. For a good example of this in action, see Hans Rosling’s TED talk about the magic washing machine.

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