People tuned in to self-development ask questions like this (which came from a workshop participant):

What has changed the most in the past 10 to 15 years about what we teach people about presenting data? What used to be a good idea but is not any longer?

These questions show you know trends shift, that you aren’t satisfied with regurgitating the status quo, that you scoff at midriff-bearing shirts but also at pleated and penny-rolled jeans.

So here’s what I’ve seen shift, as I write this in 2023. In a few more years I’m sure we’ll have even more to add to this list.

Six bullets per slide, six words per bullet

Believe it or not, the 36-word limit for slideshows was born from good intentions: Before that, slides customarily had EVEN MORE WORDS.

But just as the way that “controversial musician” once meant Elvis and, by today’s standards, that’s quaint, our standards around acceptable slide content has also evolved over time.

While you don’t need to go Steve-Jobs-minimalist for your slides (some text is certainly ok), we now know that asking the audience to read 36 words in six chunks while you also talk at the same time is a recipe for cognition disaster.

Shift your paradigm around what a slide can contain to this: One idea. Just one idea per slide. However many words that might be, keeping in mind your audience doesn’t want to read paragraphs on a slide.

Noise-to-ink ratio

Edward Tufte popularized this idea that it was desirable to have a low noise-to-ink ratio, where “noise” is anything that isn’t contributing to the understanding of the data.

He advocated that we go from this:

to this:

Where we ditch chart borders and unnecessary ticks marks and add in some white gridlines to demarcate units in the columns.

Cool. It’s definitely a great improvement.

You know how white cowboy boots are appropriate for a Taylor Swift concert, but not a hike in the woods? Same deal here: situational context matters.

A low data-to-ink ratio may be better suited for, say, meetings with your C-Suite. But that isn’t necessarily the visual approach that’ll grab the public’s eye while they’re doom-scrolling through Instagram.

In fact there’s good research that suggests more memorable visuals have gratuitous ink. Notice the Tufte-esque low data-to-ink visuals are in the forgettable half.

As it so happens, the research actually came out about 10 years ago but the Tufte influence has been so strong that it’s taking awhile for practice to catch up. The real trick is identifying the right circumstances for different visual approaches.

Ignoring accessibility and inclusivity

Some of you might be old enough to remember making graphs like this:

The intention was good: Ensure the graph will be interpretable when viewed in grayscale – which also tends to help viewers who are colorblind. We’re feeding two birds with the same seed.

Except…. doesn’t it look like some of the columns are leaning like Pisa? That’s called a moiré effect (something else brought to our collective attention by Edward Tufte).

These days we have better color technology and an increased understanding of colorblindness, so we can use different methods to reach the same goals.

And we’ve grown our awareness about accessibility far beyond attending to colorblindness. Start here and this will lead you to many other resources.

That said, for me at least, “accessibility” should extend beyond people who have disabilities. Accessible should also mean inclusive, right? Inclusive means, at minimum:

• we’re representing more voices (for example, with better qualitative viz options)
• broadening our view of what counts as viz to become more culturally relevant
• assuming responsibility for the data we’re graphing so as not to reproduce outdated norms
• showcasing equity data with chart types that tell that story well

… and on that last point, one more old idea that doesn’t work anymore:

Same old chart types

At the start of many of my workshops, I’ll ask people to rattle off the charts they know. Often (especially when I’m in DC – sorry, it’s true) I’ll hear these responses: Pie. Bar. Line.

Then I offer silence to see what else bubbles up from the quiet.

“Scatterplot?”

Ok. Sure. All of those are good ideas. Let’s not ax any.

But they can only take you as far as your college roomie’s rusty Volvo.

These sweet days we’ve got dots, dumbbells, overlaps, diverges, slopes, bumps, waffles, quadrants, sankeys, deviations, radials, waterfalls, proportion plots – and so many more.

Start here, where you’ll gain steam, impress your boss, and catwalk back to your office after your next meeting.

You don’t necessarily need fancy software. You just need to know how to hack the software you do have, and I can show you how.