3 Ways to Help People Understand What Your Data Means
By Nancy Duarte
Last year, Jeff Bezos became the richest person in the world with a net worth of more than $130 billion.
The world was abuzz trying to make sense of just how rich the Amazon CEO really was, and headlines grabbed hold of this tweet from Neil deGrasse Tyson.
“Not that anybody asked, but @JeffBezos’ 130-Billion dollars, laid end-to-end, can circle Earth 200 times, then reach the Moon & back 15 times then, with what’s left over, circle Earth another 8 times.”
Wow, that sounds like a lot.
…but then again I’ve never personally circled the Earth and I’ve never been to the moon. In the past 50 years, only 24 people have.
So, how far is that really?
If you’re serving your organization in any kind of analytics-enabled role, you likely spend most of your days digging through data — whether that’s about customer lifetime value, shopping cart abandonment, or market share.
When you do uncover a statistic that feels shocking, you know you must communicate that insight to decision-makers immediately.
In doing so, you may want them to feel the gravity or to marvel at the magnitude of your finding. Most importantly, you want them to feel inspired to make a decision.
But often, the narrative gets lost in numbers they can’t really comprehend. The more data we collect, the more mind-boggling these figures become. Though an audience may intellectually understand the measurement, they might fail to relate or connect with it emotionally.
To do that, develop a sense of scale by attaching data to what’s relatable and familiar for your audience. It can be tricky for an audience to wrap their heads around how big or how tiny a number might be. Complex numbers are made clearer by comparing them. Your audience can sense scale through relatable size, known distance, a familiar segment of time or rate of speed.
Here are some strategies you can use to make the magnitude of your statistics both manageable and meaningful for your audience.
Connect Data to Relatable Size
Connect data to a relatable size by comparing length, width, height, thickness, or distance.
Tyson’s tweet demonstrated how we can create scale by using distance — but for that scale to be truly effective in making meaning, it has to be grounded in what’s relatable or known to your audience.
Sadly, most of us will never make it to the moon. Fun Fact: The longest flight on Earth is Singapore to Newark, clocking in at 9,534 miles.
If Tyson had said, “The thickness of 130 billion stacked one-dollar bills is 8,822 miles, which is equivalent to driving back and forth across the United States 3.4 times,” that would have been easier for the non-astronaut to comprehend.
Connect Data to Relatable Time
Time is another good source for comparison.
We measure time in seconds, hours, minutes, days, months, and decades, but we can create more relatable timeframes by communicating work hours, flight time between cities, an episode of a sitcom, a TED talk, or the time it takes to microwave a bag of popcorn.
Time is money — and that makes it an effective way to develop scale when it comes to making meaning out of a $130 billion sum.
Forbes communicated Bezos’ annual earnings as an hourly wage — which was the staggering sum of $4,474,885 per hour.
According to the Social Security administration, that’s twice what the average American man with a bachelor’s degree will earn in his entire lifetime.
Connect Data to Relatable Things
In addition to using size, time, and speed to help your audience understand a number, you can use nouns, or people, places, and things that are familiar to them.
Let’s say you have one million users. It’s easier for an audience to get a sense of that quantity if you compare it to the number of people who could be seated in a stadium.
For example, the San Francisco Giants baseball field has 41,915 seats. So, if communicating this number to a Bay area audience, you might say: “Our users would fill the San Francisco Giants stadium almost 24 times.”
Looking at what Bezos’ wealth could buy here on planet Earth is another approach. Another popular tweet making headlines during this time calculated that Bezos could buy a new house for every single homeless person in the United States and still have $19.2 billion left over.
Data signals a problem or an opportunity. The insights are meant to move us to decision making.
We can help audiences move from making sense to making meaning by developing a sense of scale. When they understand the scale of your numbers, they’ll better understand the scale of your recommendation.
Maybe this final comparison meant something to Bezos. Just a few months after this news cycle had run its course, Bezos launched a $2 billion fund to help homeless families and children.
But, how much is $2 billion really?
A version of this article originally appeared in HBR.
Illustrated by Jonathan Valiente and KareyAnne Hill-Peterson
Data and analytics, Storytelling