These aren’t her real categories or real numbers, but you get the idea.

Before: Reading Numbers

Her “before” version looked something like this:

She had small n’s — a unique situation!

My definition of a “small” number is less than 100 — an arbitrary cut-off point that I learned from a past supervisor, and I’ve stuck with for years.

Not only was the total under 100, but each of the cells was under 100, too.

After: Skimming Visuals

There are several ways to bring the table to life.

During a 1:1 consultation, we talked through a few ideas together.

Idea 1: Heat Table

This easy visual — made via Excel’s Conditional Formatting — would be a great addition to the appendix.

If you’re familiar with the 30-3-1 approach to reporting, then you know I put allllll the tables in the appendix.

In other words, I aim for zero or few tables within the body of the report. The report’s body should focus on key findings with graphs, not dilute the data with eeeeeeverything in a table.

Idea 2: Clustered Columns

This is Ann K. Emery’s least favorite chart of all time. I’ll never let any of my students use one of these bad graphs!!!!

It’s the default option — we simply highlight the summary table in Excel, and insert a chart — and we get this lazy chart.

There’s too much going on, so it doesn’t tell us anything.

The color-coding by category is off.

There’s a separate legend, which is an accessibility no-no.

Idea 3: Small Multiples Histograms

With a re-orientation and re-coloring, it’s easy to build small multiples histograms.

But, the vertical columns didn’t fit her portrait Word doc:

The horizontal bars would be totally fine.

My only hesitation was that bar charts are… boring.

I’ll never let my students have only bar charts in their reports, slides, dashboards, or infographics. Our viewers deserve variety.

Plus, this was a unique small n situation. Let’s capitalize on that!

Idea 4: Icon Arrays

To bring the small n to life, we tried an icon array.

The student liked this option because:

• It’s very, very, very fast to create — much faster than creating and formatting a chart.
• It was similar to her original table — the same rows and columns.
• Right away, she could see how much bigger Category A was than the other categories.

Yes, I realize the irony…

I just wrote a blog post asking you to humanize your data with realistic people icons, which would be a step above shapes like circles and squares.

We tried realistic people icons, too.

They look fine close-up.

But they simply didn’t fit. In other words, there would have to be fewer icons, and/or they’d have to be much larger, to even be legible.

They just look like chicken scratch, sigh.

Behind the Scenes

I’ve written and spoken about symbol fonts a million times.

Webdings, StateFace, and WeePeople are personal favorites.

Yep, these are simply Webdings n’s!

Never, ever add a bajillion individual circles to your Word doc or PowerPoint slide. What a waste of our own time. Just use symbol fonts.

Made Within Minutes

Can you type n’s into your table?

And change the font into Webdings?

Even if you’re the slowest typer in the world… I promise it won’t take long to type some n’s.

Then, simply adjust the font colors, so that you’re using one brand color per category.

Bonus: Download the Materials

Want to see the Excel file and Word doc used in the blog post? Download them here.

Researchers, evaluators, and scientists complete my online courses. Or they bring me in for private workshops.

And they start applying what they learned. GREAT!!!

But it’s a little off. OOPS.

This is entirely my fault. I’ve been recommending that we use icons for years now — but I haven’t been clear enough about how to use them, and how not to use them.

In this blog post, you’ll see 8 different types of icon use. The good, bad, and ugly.

(1) Multi-Color 1990s-Era Clip-Art: NOOOOOOOO

Let’s start with what not to do: clip-art.

Icons and clip-art are similar, but not identical.

Icons use one color, so they hold up well in grayscale printing, or when very small.

Clip-art uses several colors, so it doesn’t hold up well in grayscale printing, and it’s hard to see when it’s small.

For these obvious reasons — clip-art is outdated and hard to see — clip-art gets The Big Red X.

(2) Cheesy, Posed Stock Photography: NOOOOOOOO

Gosh, I hope this one’s obvious.

I love adding photographs to reports, slideshows, and infographics.

But not the cheesy, posed type, like this.

Another Big Red X.

(3) One-Color Icons to Replace Words: NOOOOOOOO

One-color icons are okay.

But icons can only accompany words, not replace words.

(4) Icons to Accompany Words: Yes!

Let’s start by adding words: males and females.

Then, we’ll turn those choppy phrases into full sentences to remove guesswork.

We’ll bold a few key words to make it more skimmable.

We’ll color-code the keywords to match the icons (blue keywords for blue icons).

Finally, we’ll color-code by category: blue for one group, and green for another. You’d obviously use your brand colors, not mine, but the technique is the same: one hue per category.

Even if you’re the slowest typer in the world, these bare-minimum edits should only take a minute.

(5) Icons to Categorize: Yes!

Next, let’s add some actual, ya know, graphs.

Bar charts are fine, but they’re super boring if that’s all we have.

These are binary variables — a.k.a. yes/no variables — so two-slice pies are perfectly fine.

(Here’s my list of pie chart guidelines if you’re not familiar with my stance on pies.)

This is where we can add icons to categorize.

You see the difference, right?

I’m not a fan of using icons on their own, like the previous examples. They feel overly-simplistic and dumbed-down. But I am a fan of using icons to accompany other graphs, and to aid with categorization, like this:

We’re not limited to pies for binary variables.

We could use pies, donuts, or square pies.

No matter the graph type, the icon usage is the same: They’re accompanying the graphs, and aid with categorization.

(6) Icons to Show Proportions: Yes!

We can also use icons as the visualization itself.

Collages of icons are called icon arrays. The square version is also known as a waffle chart.

For bonus points, we could add the male/female icons to aid with categorization, too.

You see the distinction, right? The primary icons (the collages of squares or circles) are used to visualize the data, not just decorate it.

(7) Overly-Simplistic Icons to Humanize: NOOOOOOOO

The only thing worse than one dumbed-down Gingerbread Person is a hundred of them.

NO MORE GINGERBREAD PEOPLE!!!

(8) Realistic Icons to Humanize: Yes!

I am a fan of using realistic icons to humanize the data.

You see the differences, right? We’re not using single icons just to decorate, like the first couple examples. We’re using icons to categorize and/or to show proportions.

And we’re not using dumbed-down Gingerbread People. We’re using realistic human silhouettes.

More Examples of Realistic Icons to Humanize

I want to normalize these realistic icons for you. Here are a couple examples from the wild:

• The proportion of female chairs in board or CEO positions in German companies
• COVID-19 won’t spread as easily when Oregon reaches herd immunity

Using Smaller Denominators

All icons — squares, circles, Gingerbread People, and realistic human icons — get tricky to read when they’re tiny.

In some projects, we can simplify our fractions.

I tried changing 42% of men to 42 of 100 men, and then to 21 of 50 men. That worked fine!

But when I tried changing 37% of women to 37 of 100 women, and then to 18.5 of 50 women… yuck. If our unit of analysis is people, we can’t talk about or visualize half a person. That’s confusing to our audiences.

So while I’d prefer to simplify the fraction, I can’t in this specific example.

Traditional and Storytelling Versions

Hopefully you’ve heard me talk about traditional vs. storytelling graphs before. If not, you can watch this video for a quick overview. Both versions are correct, but they’re correct for different types of audiences.

The Bottom Line

There are several different ways to use icons in data visualization, and some are better than others.

I don’t recommend clip-art (version 1) or cheesy stock photos (version 2).

I don’t recommend icons to replace words (version 3).

I don’t even recommend icons on their own (version 4).

Instead, at a bare minimum, we should be using icons to accompany other graphs and to categorize (version 5).

Better yet, I’d prefer that we use icons (like little squares or circles) to show proportions (version 6).

And when our unit of analysis is humans, I’d prefer that we use realistic human icons (version 8) and never the dumbed-down Gingerbread People (version 7).

Your Turn

Which version of icons are you currently using? Which one might you try in the future? Comment below with all your ideas! Bonus points for sharing links to your public-facing projects so we can learn from each other.

Beyond Graphs 1: I made a Great Graph after just a Few Course Modules

Soon after the course started, I brought Ann data about who connected with me on LinkedIn after I was listed as one of Nick Martin’s 9 Amazing Humans to Follow. Nick has a HUGE network and I got over 69 connection requests in the first day. And requests continued for more than a week!

So I made a graph to go with a post on LinkedIn, applying all the learnings from the first few course modules.

Beyond Graphs 2: 2 Things I Learned in 10 Minutes of Help in 1 Office Hour Session

I examined the few data variables on the LinkedIn connection requests. My impression was validated. Only 2 of 136 requests had a personalized message (despite LinkedIn experts emphasizing the need to personalize connection messages).

I tried different ways to display this finding (waffle chart, pie chart, and this one). Luckily, Office Hours were the next day. (Office Hours are a CAN’T MISS opportunity for immediate feedback!)

Ann took one look and exclaimed, “Ooh, let’s try the WeePeople font!” (Well, maybe not exactly like that!)

She then quickly used WeePeople to show the data.

Learning 1: More relevant and representative visuals with icons showing diverse silhouettes

(Hooray – No more using just the standard male icon.)

And then Ann taught us all how to make a gif which was even more effective at telling the “only 2 of 136 people” story.

Learning 2: Using a gif can give readers a quick result from your data

And, for those who follow LinkedIn stats to see how their posts engage, the post with the bar graph got 4,765 impressions and the 2^nd post (the next day) with the gif got 8,778 impressions!

Beyond Graphs 3: Now I’m Applying a Mental Checklist to Graphs and Charts

No – not only to the few graphs I’m making.

The course taught me and heightened my awareness to look at all the visual elements in the many graphics we see each day. There was so much learning from the course modules. And then many great opportunities in Office Hours to learn from what others were working on.

Here are things I find I am automatically looking for in these graphics:

• Color choice(s)
• Is it a Traditional or Storytelling title?
• The clarity of the data message
• Is the graph or chart the best for that message and the data being used?
• What elements could be removed for better clarity?

And a Beyond Graphs Bonus: Consistency and Efficiency

I consider myself a digital pioneer. But I didn’t know what I didn’t know, even being a longtime Word, PowerPoint, and Excel user.

I jumped into the course, and my efficiency increased in the first week! The course started – not with graphs – with ensuring basics including branding by setting my color and font defaults.

And then, a couple weeks later, I set up branding for a 3-part seminar series I did for Waey, the Association for Community Health in Saudi Arabia.

And I now have the consistency across Excel, Word, and PowerPoint and across my different PCs. What a difference!

This is just the tip of the iceberg of everything I am doing differently after Great Graphs – Excel!

Connect with Sue Griffey

LinkedIn: https://www.linkedin.com/in/suegriffey/

Twitter: @SueMentors

Youtube: https://www.youtube.com/channel/UC-rjWX4ZmTdo0S3ssKbut_A

SueMentors Resources: https://suegriffey.fyi.to/suementors-resources-for-your-professional-presence

A no-cost short course: Build and Update Your Professional Presence in 4 Steps at this page: https://www.linkedin.com/company/4-steps-to-build-update-your-professional-presence

There’s a misconception that accessibility takes all day, that’s it’s costly, or that it’s complicated. Those are all false.

Accessibility is woven into all my trainings, but since this is a topic I get asked about a lot, I decided to make a new talk that’s focused just on accessibility for dataviz. 

In Spring 2021 I gave a talk at the Good Tech Fest conference about dataviz accessibility quick wins. 

The talk was a “Choose Your Own Adventure” style where the audience chose what we discussed from a list of options. They chose: 

• direct labels, 
• lower the reading level, and 
• lower the numeracy level. 

You can watch the recording or read the highlights. Enjoy! 

Watch the Conversation 

You’ll learn about lowering the numeracy level. Then, you’ll see a case study that combines several accessibility quick wins. 

How to Lower the Numeracy Level 

We’ve discussed how to lower the reading level, but how do we lower the numeracy level?  

Lowering the numeracy level just means making sure the numbers are easy to understand.  

There are a couple of stages to this, so even if you only move one step, that’s a win.  

For example, let’s say you’re starting with 33.26%.

To lower the numeracy level, the first stage would be to round it to 33%. That’s a win!

The next stage would be to go from rounded percentages to fractions. So, we could turn that 33% into 1/3. Another win!

The final stage would be taking that 1/3 fraction and changing it to 1 in 3 in a sentence.

This is a general goal to aim for. It won’t work every single time for every single project. In other words, you can’t move from 33.26% to 1 in 3 for every project. Just try to move one step in every project.

Before: Percentages with Two Decimal Places

Let’s practice lowering the numeracy level.

Let’s talk about what’s already going well:

• It’s a donut chart with only two slices – check.
• It’s got dark-light contrast – check.
• And the sentence, “33.26% of participants agreed that the program was a good use of time” is readable. (It scored a 5.8 on the Flesch-Kincaid scale.)

After: Round to the Nearest Whole Number

Let’s make it even better!

I know you understand percentages. Of course you do. You’re reading a data blog. 😊

But percentages are tricky for people who don’t work in data careers.

Percentages.

Percent changes.

Percentage point changes.

Percentiles.

Those are similar-sounding terms with completely different math and meanings.

No wonder others get confused by percentages.

Let’s be proactive and stop confusion at the source—by avoiding percentages whenever possible.

One improvement would be to round the decimal places to the nearest whole number.

After: Use Fractions Instead of Percentages

Another quick win would be to turn the 33% into a fraction (1/3).

After: Put the Fraction into a Sentence

And the best practice would be to turn the 1/3 into one in three.

You could also adjust the chart, transforming the donut chart into an icon array.

That way, there’s cohesion between the chart and the text (i.e., they both talk about one in three).

I don’t recommend using gingerbread people.

• Men don’t have to wear pants and women don’t have to wear dresses.
• Some people don’t identify as men or women.
• You may not know if the data collected represents men or women.

So, what to do instead?

Use icons of real people.

This example is about people, so let’s show the people.

This is symbol font called WeePeople. You can download this for free and use it to visualize people as the real human beings they are.

Accessibility Case Study

By now, you’ve learned about direct labeling, lowering the reading level, and lowering the numeracy level.

Let’s look at a case study and put it all together.

Here’s a before graph based on a real-life project. This organization was running a workforce development program.

In the Good Tech Fest session, I asked the audience to describe what they saw going wrong.

Here’s what they came up with:

• Diagonal text
• Decimals
• Change from a column chart into a bar chart
• Add a takeaway title
• Reverse the order
• Color coding

Within three minutes, we made quick edits that made a big difference.

Rotate the Chart

The first thing we did was rotate it from a column chart to a bar chart.

(We wanted all the text to be horizontal.)

Round Decimals to Whole Numbers

Our next edit was to round the decimals to the nearest whole numbers.

Add a Takeaway Title and Dark-Light Contrast

Next, we added a takeaway title.

Instead of “Participants Working in Each Industry,” we now have “20% of Participants Worked in Retail.”

Then, we highlighted the retail data. We changed that bar to a darker color and grayed out everything else. Dark-light contrast is an easy and effective data storytelling technique.

Add Fractions within a Sentence and Icons

We changed the percentage to a fraction in a sentence.

Then, we added icons, which makes our data more memorable.

Accessibility doesn’t have to take all day.

Accessibility doesn’t have to cost anything.

Accessibility doesn’t have to be complicated.

With a few quick edits, we’ve made this chart faster to read; we lowered the numeracy; we lowered the reading levels; and we made it more memorable.

Download the eBook

Want to learn more about accessible data visualization?

In this ebook, you’ll learn 10 quick wins for designing accessible data visualizations. These small edits can have a big impact for our coworkers, board members, and funders who have color vision deficiencies, hearing loss, or learning disabilities–and for all of us who are pressed for time.

For your complimentary copy, use code: goodtechfest