In spring 2025, I livestreamed on YouTube as I created a 2-pager about NIH grant terminations.

Later, Michelle Grochocinski emailed me and wrote, “I applied your lessons to a two-page infographic fact sheet for the State Health Insurance Assistance Program (SHIP). The leaked HHS budget draft suggested cutting SHIP funding, and advocates mobilized quickly to highlight the importance of this program. (I could’ve kept tweaking the fact sheet forever, probably, but we wanted to get it out asap.) Thank you for the tools!”

Here’s what Michelle created:

I LOVED how she applied what she learned to her own project, and asked if she’d be willing to share it with you here.

Ann Emery: What did the “before” version look like?

Michelle Grochocinski: The “before” version was four pages of neutral program trends and contextual information; there wasn’t a clear audience.

The revised fact sheet is two pages of infographics and information that explicitly highlight program impact.

How long did it take to create the Fact Sheet?

The better part of two days.

We went through several versions before landing on the data points, visualizations, and stories that we agreed best illustrate the importance of the program.

Which software program(s) did you use?

Excel for the data.

PowerPoint for the page design.

How did you decide which data points to include?

We considered many more data points than were ultimately selected.

We identified our audience as consumers / constituents, who may not realize this is a federally-funded service, and the legislature. We chose demographic data that would emphasize to lawmakers that constituents on both sides of the aisle rely on this program, such as numbers and stories about higher-income and rural customers.  

I approached this with the hypothetical of “what would happen if SHIP weren’t available?” Immediately, the challenges of unsolved issues, trouble navigating coverage options, and lack of access to unbiased information came to mind. I worked backwards to select information that illustrates how SHIP meets these needs.

I consulted with colleagues in my program area and from my communications team to get fresh perspectives.

What do you like most about the Fact Sheet?

I feel we did a good job clearly and concisely communicating SHIP’s impact: empowering thousands of families and communities to understand and access their healthcare.

I believe the fact sheet shows how this is a popular, non-partisan program that helps all of us, including congressional offices and government partners.

We strove to use Reframe Aging principles in our verbiage and plain language.

It’s clean and succinct.

Did you run into any challenges?

I found myself wanting to insert my many graphs into the fact sheet. Pivoting to graphics and design that highlight the ultimate impact rather than trends over time took a mental shift, from program manager to consumer.

Selecting which data points to include amongst the vast amounts of data we collect was challenging.

Finding the right balance of context to provide without delving into complexities that require background knowledge and jargon was tricky.

Next steps??

I’ll keep tweaking the colors and formatting to polish it up.

I this it would be beneficial to have a national version of this state fact sheet, since SHIP is a national program, so I’m interested in working with my federal colleagues to make that happen.

Great work, Michelle! Here’s the before-after transformation. –Ann

What’s Inside

• 0:00 Intro
• 2:26 Behind the Scenes
• 3:12 Single Contiguous Dataset
• 3:50 Pivot Tables
• 4:15 Pivot Charts
• 4:24 Slicers
• 4:26 Helper Tables
• 5:35 Step-by-Step Demo

Technical tables have so much value, especially as visual appendices for reports.

In this blog post, you’ll get ideas for bringing your technical tables to life.

Before

Here’s what the “before” version of some technical tables looked like.

These are made-up numbers, but you get the idea.

The public health staff wanted to look at quarterly numbers, the total annual number, and the rate (the number of cases per 100,000 live births).

Even if you’re not measuring neonatal abstinence syndrome, I bet there are numbers that you track each quarter. You might even want to look at the total annual number, too. Get some inspiration from this blog post, and then adapt the ideas to your own workplace.

Re-Created in Excel

First, I re-made their table in good ol’ Excel.

The finished product will be a PDF, but the most efficient way to bring technical tables to life is to keep the numbers inside Excel the entire time. We’re not going to transfer anything to Word.

Declutter

Let’s tackle the easy edits, such as:

• removing all the borders;
• adding back just the gray horizontal borders;
• removing the background fill; and
• left-aligning the text and right-aligning the numbers.

Add Trendlines

We’ll bring the quarterly trends to life with sparklines.

Add Bars

We’ll bring the annual totals to life with data bars:

We’ll bring the rates to life with data bars, too:

Brand Colors & Brand Fonts

Time to format!

We’ll apply brand colors and brand fonts:

We’ll color-code the text to match the bars.

(Sometimes the table’s columns get so narrow that it’s tricky to tell which number corresponds to which bar. That’s where color-coding comes to the rescue.)

As a general rule of thumb, colored font should be bold so that it passes 508/ADA color contrast guidelines.

Text Hierarchy & Intro Sentences

A text hierarchy means the title should be largest, boldest, and darkest so that it’s easiest to spot. (Followed by H1s and H2s if we had them.) We’re developing a hierarchy of information so our readers can stay organized.

As a general rule of thumb, I make sure headings are twice as big as body font. The body font is size 11, so this title is size 22 and bold.

We’ll also add intro sentences, and move that footnote info about the asterisks to the top. (People need to read that sentence before the table, not after.)

PDF- and Printer-Friendly

We’ve kept everything in Excel — that’s the only way to add the spark lines and data bars, and pasting tables into Word is a waste of time — but the final version will be shared with others as a PDF.

In the real version of this project, the PDF was about 15 pages long. There were various tabulations on various topics, not just neonatal abstinence syndrome.

We’ll need to:

• set the Print Area;
• adjust the Page Layout (portrait to landscape for easier on-screen reading);
• adjust the margins (0.5 to 1 inches is sufficient);
• add contact info and a logo so people can get in touch with questions; and
• adjust the column widths and row heights so everything fits juuust right.

Optional: Sort by Rates, Not Alphabetically

Finally, we might choose to sort the table by the most important column (rates, in this example) instead of alphabetically by county name.

I’m usually a fan of sorting. But I’m on the fence here. I also see the value in the leaving the counties alphabetized so readers can search for their own county. Hmm.

The Final Version

The visuals help us spot the patterns (thanks, Picture Superiority Effect).

The branding will help us look more professional to outside audiences (so we don’t look Frankensteined — when all our colleagues use different colors and fonts, and we put everything together in one doc, and it’s a hot mess).

The PDF’d appendices can be merged with the PDF’d report (thanks, Adobe Acrobat).

The Before-After Transformation

Once you’ve got intermediate/advanced Excel vizardry skills, the whole process will take less than an hour.

Really, this should take you less than 15 minutes!

If not, you’ll simply need to brush up on your Excel skills.

Dataviz is supposed to be fast and easy.

Bonus: Download the Materials

Want to explore my spreadsheet? Download my Excel file and adapt it for your own project.

Maybe the numbers simply went up over time. Or down.

Other times, it’s more complicated.

Here’s how to explain multiple takeaway messages in presentations: with multiple slides, one per takeaway message.

Before: Everything Smushed on One Slide

Here’s what I typically see: lots of possible takeaway messages shoved into a single graph on a single slide.

The presenter says something like this:

“Next, let’s talk about gonorrhea diagnoses in our state. We’re looking at the number of diagnoses per 100,000 people. We’re also looking at age ranges. This is the person’s age when they were diagnosed with gonorrhea. We’ve got five years’ worth of data: from 2018 through 2022. Let’s look at a few key findings. Gonorrhea diagnoses were highest for people in their early twenties. In 2020, for example, there were 735 gonorrhea diagnoses per 100,000 people ages 20-24 in our state. Gonorrhea was lowest for ages 40-49. In 2022, for example, there were 88 diagnoses per 100,000 people ages 40-49 in our state. Here’s another pattern we found: Gonorrhea diagnoses generally went up from 2018 through 2020. For the three younger age groups, at least. And, gonorrhea diagnoses went down from 2021 to 2022 for all age groups.”

And while you’re talking through allllllll those numbers and age ranges and timeframes, the audience only sees this:

You see the problem, right??

The presenter is talking about one thing… but the audience is probably looking at something else.

That’s the very definition of Death by PowerPoint.

After: Describing One Takeaway Message at a Time with Multiple Slides

Instead, let’s use multiple slides!

We’re aiming for a single takeaway message per slide.

That way, what we say = what the audience sees.

There should be a perfect cohesion between sight and sound.

The presentation would look and sound like this:

“Next, let’s talk about gonorrhea diagnoses in our state. We’re looking at the number of diagnoses per 100,000 people.”

“We’re also looking at age ranges. This is the person’s age when they were diagnosed with gonorrhea.”

“We’ve got five years’ worth of data: from 2018 through 2022.”

“Here are the patterns at a glance. Next, let’s look at a few key findings.”

“Gonorrhea diagnoses were highest for people in their early twenties. In 2020, for example, there were 735 gonorrhea diagnoses per 100,000 people ages 20-24 in our state.”

“Gonorrhea was lowest for ages 40-49. In 2022, for example, there were 88 diagnoses per 100,000 people ages 40-49 in our state.”

“Here’s another pattern we found: Gonorrhea diagnoses generally went up from 2018 through 2020. For the three younger age groups, at least.”

“And, gonorrhea diagnoses went down from 2021 to 2022 for all age groups.”

Finally, you’d show the “full” graph again, pausing for questions and a discussion.

The Bottom Line: Use More Slides!!!

We’re not making the presentation longer. We’re speaking for the same amount of time as before.

We’re not rushing or slurring our words. We’re speaking at the same pace as before.

We’re not wasting paper or ink. These are the slides shown on screen during a presentation. If you want to print something, just print the “full” graph (which is slide 462 in the screenshot below).

We’re syncing our words and visuals.

We’re keeping our audience’s attention.

Because if they’re not even paying attention… How will they possibly understand, remember, and use the findings for decision making?!

Maybe you’re getting ready for a talk at a conference.

Or, maybe you’re sharing updates with coworkers in a staff meeting.

In this blog post, you’ll learn how to explain dense graphs one slide at a time, which makes it easier for our audience to follow along.

Before

Last summer, I was keynoting the National Birth Defects Prevention Network’s annual conference in Atlanta.

Here’s what one of the health department’s original graphs looked like.

We wanted to make a presentation-ready version.

If you work in public health, then you know that the tiny text and statistical terminology is pretty common in scientific graphs. (BUT IT DOESN’T HAVE TO BE!!!)

After

We don’t need a complete overhaul.

I made some very light edits to the existing graph:

• Direct labels (instead of legends) ensure that the graph is “Big A” Accessible (a.k.a. 508/ADA compliant).
• Horizontal text (instead of vertical text) is faster to read.
• I removed the grid lines.
• I enlarged the font (the body font is size 18, which is my bare-minimum font size for presentation slides).

Storyboarding for a Live Presentation

Now that we’ve tackled the quick edits, we’re ready to adjust the graph for a presentation.

We’ve already done the hardest part: Getting the “final” slide ready.

Now, with a few more minutes of planning time, we’ll create the “build-up” slides, like this:

What the Presentation Will Look & Sound Like

For statistical graphs, I often begin by explaining the axes.

I’d show the y-axis, and say, “Next, let’s talk about coarctation of the aorta. We’re going to look at the prevalence per 100,000 births.”

I’d click, move to the next slide, and say, “…and we’re looking at data from 2007 through 2019. The numbers vary a lot each year, so we’re looking at 5-year moving averages in this graph. The moving averages are going to help us focus on the bigger picture.”

“Here’s what we predicted would happen. You can see some slight variations over time, but we generally estimated that there would be 3.6 to 3.7 cases of coarctation of the aorta per 100,000 births.”

“Here’s what actually happened. There were slightly fewer cases of coarctation of the aorta than what we predicted. And the numbers are actually going down slightly over time.”

Finally, I’d click, move to the next slide, and say, “Here’s the confidence interval with a 95% band.”

The graph is explained piecemeal, RATHER THAN SHOWING EVERYTHING ALL AT ONCE.

If we show everything all at once, then my audience would be looking at one thing while I’m talking about something completely different. That’s Death by PowerPoint.

The Bottom Line

We don’t have to delete or dumb-down our statistical graphs.

We just have to explain them piecemeal.

It’s counterintuitive, but sometimes we need more slides — one slide per sentence or two of speaking points.

We’re not talking for longer, or running over time.

We’re not talking faster, or slurring our speech.

We’re simply clicking through our slides one at a time to match our speaking points.

A few more minutes of planning time on our end… to make sure our audience can follow our dense graphs. A necessary trade-off.

Learn More

Browse more examples of storyboarding in these blog posts.

You’ll also practice this technique inside Powerful Presentations.

We’ll call them the Statelandia Public Health Department.

Before

Here’s what their “before” version looked like.

The information on how many adults overall had been diagnosed with high blood pressure was tucked inside the title, while the graph focused on the breakdown by age group.

All the important details are there, hooray! But we all wanted more cohesion between the title and the graph.

Two Options for Visualizing “Overall” Data or Averages on Bar Charts

There are two primary ways to visualize our “overall” data or averages when we’re making bar or column charts.

The two options include:

1. Add a column. We can add intentional gaps between the “overall” data and the subgroups. In technical terms, the space is a preattentive attribute. Preattentive attributes help our audience recognize instantly that the overall vs. subgroups are a bit different.
2. Add a line. Another option is adding a line on top of the bars or columns. I’ve seen people add literal lines in Excel (Insert – Shape – Line). That works, but the fancier option is to use a Combo Chart in Excel. (If you’re not familiar with Combo Charts, you can download my template below.)

Let’s apply these two options to the blood pressure example.

Option 1: Visualize “Overall” Data by Adding a Column

I *think* this is my preferred approach. I’m still on the fence. Hmm…

A Few Quick Wins

I always start with Quick Wins. These edits can be tackled within minutes.

Quick Wins give us momentum so that we have mental energy to tackle the Not-So-Quick Wins.

Here’s what we edited:

• We changed the horizontal bar chart into a vertical column chart. Age groups are ordinal, and I generally try to arrange ordinal data from left to right. You can read more about my bar vs. column logic here, and you can learn how to make this quick rotation in Excel here.
• We rounded the decimal places to the nearest whole number. You can learn more about lowering the numeracy level of our graphs here.
• We moved the percentage labels inside the columns (so they don’t accidentally make the columns look taller than they really are).
• We decluttered the graph (removing gridlines, showing fewer increments on the y-axis, tucking the labels inside the columns, etc.).

Add an “Overall” Column with an Intentional Gap

Next, we added the “overall” data to the graph as its own column.

We also spaced the overall column apart from the others. These are separate types of data (an overall number is qualitatively different from a breakout by subgroups). They need to be arranged separately on the slide.

If you’re using Excel, simply add an empty row to the table that feeds into your graph.

You can learn more about adding intentional gaps in this blog post.

Adjust the Text Placement

Next, we moved around the text boxes.

All the important text was there — but in a single full-width text box.

We simply placed “like with like” — the overall text with the overall column, and the subgroup text with the subgroup columns.

We also moved the “year” data to the source at the bottom of the slide.

Bold the Key Words & Color-Code by Category

For extra skimmability, we bolded a few key words.

Then, we adjusted the colors. Separate colors for separate categories of information.

Color-coding by category is one of my all-time favorite dataviz techniques! You can see color-coding applied to one-pagers, recurring monthly reports, technical reports, and slideshows in these linked examples.

The final version would look like this:

Option 2: Visualizing “Overall” Data by Adding a Line

I love adding lines to visualize targets and goals.

We can add lines to visualize “overall” or “average” data, too.

BUT make sure to gray out something. Otherwise, the line chart gets messy.

You might gray out the columns, like this:

Or, you might gray out the line, like this:

Visualizing “Overall” Data on Line Charts

It’s easy to apply these techniques to line charts.

Just add another line!

Your Turn

Which approach is your favorite?

Adding a column?

Or adding a line?

And why?

For this case study, I prefer adding a column because it was easier to arrange the takeaway text in the right places (the takeaway text is simply above the columns). For the line charts, the takeaway text didn’t feel as seamless.

Comment below and share your own insights.

Bonus: Download My Spreadsheet

Not familiar with the intentional spacing in the bar chart?

Not familiar with the combo chart design in the line chart?

Download my spreadsheet here.