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A Tiffany & Co. promotion declaring that they’ve made the US Open trophies for “over 36 years.” Source: Nineteen Insights.
Only say “over” or “under,” or “more than” or “nearly,” with round numbers. Otherwise you just sound silly.
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A headline claiming “the NYC Marathon is harder to get into than Ivy League schools,” edited for correctness. Source: The Wall Street Journal.
There are lots of correct ways to describe this data. The Journal didn’t choose any of them.
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A bubble chart forecasting the supply of and demand for recycled plastic in 2030. Source: McKinsey & Company.
There are lots of wrong ways to add visual interest to charts. McKinsey shows us the right way.
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Figure 1 from the book Atomic Habits, showing that if you improve at something 1% every day for a year you’ll be 37.78 times better at that thing by the end of the year. Source: Amazon.
James Clear has sold 15 million copies of a book that apparently contains nothing but made-up charts and graphs.
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Not quite Avogadro’s Numbrr of M&Ms. Source: M&Ms by Greg Willis via Wikimedia Commons, remixed.
The best way to explain an abstract number? Encourage your readers to imagine something concrete and familiar.
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We think square pie charts are amazing. McKinsey & Company agrees.
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Newspaper headline: “How the Flint water crisis set schoolchildren back.” Source: The Washington Post.
You can’t just present two facts that sound logical together and call it causation.
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A pitch deck slide claiming PhageLab’s technology eliminates “up to” 100% of salmonella. Source: TechCrunch.
When someone says “up to,” you can be pretty sure they’re the ones who are up to something.
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Bar chart showing that older US sports fans are more likely to follow baseball than younger US sports fans. Source: Statista.
Yes, data stories must be correct and reliable. But they have to be meaningful as well.
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An Emarketer chart claiming a market will grow eightfold in five years, but showing ninefold growth in four years. Source: Emarketer.
One day soon you’ll be glad you did.
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It’s amazing how much online “wisdom” is actually complete garbage.
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Image credit: Pinocchio [macro] by jessiefish | CC BY-NC-ND 2.0 DEED
When people tell you they’re making up numbers, believe them. Here are three clear indicators.
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Image credit: Horseshoes by John Loo | CC BY 2.0 DEED
Every day I encounter data stories that are both technically correct and wildly inaccurate.
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Image: Chart showing the share of skier visits at Vail Resorts that use a subscription lift ticket vs a non-subscription lift ticket. Source: Vail Resorts via Chartr via Gobbeldy.
Make sure your data copy is faithful by verifying the sample and the statement.
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Image: Screenshot of The Good Data Project featured on Fast Company.
Fast Company has featured our piece ‘Stop using data you can’t source.’
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Image source: BetterHelp Facebook page.
If a data source just doesn’t look right, don’t repeat it.
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Image credit: “ ‘Muhammad Ali’ by Australian-born artist Brolga” by Franco Folini | CC BY-SA 2.0 DEED
It’s your job to sniff out biased data so you can avoid repeating brand-funded nonsense.
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A Forrester report published in 2014 alongside a 2022 trade publication story citing that 8-year-old data. Image credit: Forrester and The Digital Restaurant.
Lots of things used to be true. But even good data doesn’t last forever.
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Image credit: The crunchy snack that smiles back by AllieKF | CC BY-SA 2.0
If you can’t find a number’s source, you cannot use it. Otherwise you’ll end up looking like a goldfish.
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A chart claiming to show worldwide data, with an asterisked note admitting that data comes from just Canada, the UK, and the US. Source: Insider Intelligence.
We know it’s obvious, but: Only use data that relates to your topic, and only make statements the data can support.
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