Visualizing data in charts, graphs, dashboards, and infographics is one of the most powerful strategies for getting your numbers out of your spreadsheets and into real-world conversations.

But it can be overwhelming to get started with data visualization. Does data visualization leave you feeling like the numbers are about to topple over on you??

If so, this step-by-step data visualization guide is for you!

I’ll walk you through the data visualization design process so you know what to do first, second, and third as you transform your spreadsheets into data stories.

Step 1: Understand Your Audience

Wait! Don’t start making graphs on your computer! First, we have to do some planning. A little bit of up-front planning will save you hours of blood, sweat, and tears in the long run.

First, we need to consider our audience and context. Who, exactly, is going to be using the data to make decisions?

Here are some discussion-starter questions to talk about with your colleagues.

Who is Your Audience?

A chart designed for a group of foundation program officers will not be appropriate for a group of high school principals, and vice versa.

List all your audience types on a piece of paper, or a whiteboard, or in a spreadsheet, or even on the back of a napkin. Share the list with your colleagues and make sure you’re on the same page.

Have you reached consensus about who you’re targeting with your data?

What’s Your Audience’s Numeracy Level?

Do they enjoy or fear data? Unless you’re designing charts for a group of economists or statisticians, you can usually leave out details like the effect size, power analysis, and margin of error. Laypeople are often more interested in practical significance (the “so what?” and implications of findings) than in statistical significance.

What’s Your Audience’s Data Visualization Familiarity Level?

If they’re brand new to dataviz, stick with the traditional charts like pie charts, bar charts, and line charts—otherwise they’ll spend more timing ooh-ing and aah-ing over the chart’s novelty than paying attention to the information contained in the chart.

How Much Time Does Your Audience Have?

Little time or interest: Simple static chart.

Lots of time and interest: Interactive charts.

What Types of Decisions Does Your Audience Make?

What information do they need? What information do they already have? What information are they expecting? How will your chart(s) add value for them?

If you can’t think of how your chart will add value for the readers, don’t make one. Every chart needs a purpose and so what?

How Much Precision is Necessary?

As the data visualization designer, you have the freedom (and responsibility) to select how much precision is necessary. Your selection should be well thought-out and intentional. Your decision plays out in two ways: the chart type you select, and how you label the data points.

When selecting chart types, remember that some charts are better than others in displaying precision. For example, charts that rely on angles and area to show differences, like pie charts, are for communicating general patterns. Charts that rely on length to show differences, like bar charts, are for communicating specific details.

How Many Decimal Places Are Necessary?

A related decision is how exact your data labels will be. Will you include decimal places? How many?

In most scenarios, you can safely round your decimal places to the nearest whole number. Your audience is rarely using the tenths, hundredths, or thousandths place to make decisions.

Are My Viewers Expecting a Story?

Think about whether your audience is expecting a traditional or storytelling graph.

You’ll learn about the distinctions in this video:

Step 2: Choose the Right Chart

It takes a while to understand all the different chart types and to pick the best one for your desired takeaway message. There are tons of great graphs to choose from!

Consult a Chart Chooser

My interactive Chart Chooser includes dozens of chart types, resources, tutorials, and templates.

New to Dataviz? Start with Classic Chart Types

If you’re not sure which chart to use, stick with classics like the bar chart to compare categories and the line chart to visualize how things change over time.

These charts will be “right” most of the time, so they’re a safe bet.

Use Pie Charts Sparingly

Contrary to popular belief, pie charts are not evil and don’t have to be avoided altogether. I have seven guidelines for using pie charts and donuts. In this pie chart makeover, I show you how to transform a 3D pie chart with way too many slices into a storytelling bar chart with icons:

Getting Comfortable with Dataviz? Branch Out and Try Other Chart Types

Once you’ve mastered the classic chart types, you can play around with less-familiar chart types like bubble charts, bullet charts, dot plots, heat maps, scatter plots, slope graphs, social network maps, tree maps, waterfall charts, and more.

Surround Yourself with Positive Inspiration

Surround yourself with great graphs so you can expand your worldview of what’s possible with data visualization. I suggest following top-notch data journalism teams like @PostGraphics, @NYTgraphics, and @WSJgraphics.

You can even create a physical or digital library of great graphs. For example, you might print full-page, full-color charts and tape them near your desk. Surrounding myself with a variety of chart types, all of which have been used in different reports and for different groups of people, helps me create brand new charts easily. All I do is glance up at my gallery, and then I quickly figure out which chart is best for my new situation.

Dive Into Your Dataset with Exploratory Data Visualization Techniques

I also use exploratory computer strategies, like Microsoft Excel’s spark lines, data bars, and conditional formatting, to help me narrow down the focus of my charts.

Spark Lines

Here’s a tutorial that shows you how to get started with spark lines:

Data Bars

And here’s a tutorial that shows you how to get started with data bars:

Conditional Formatting

You can set up rules in your spreadsheet that automatically change the color of certain cells based on their values. I regularly use heat tables to scan my dataset for patterns. You can follow my step-by-step tutorial to make heat tables for your data.

Sketch Rough Drafts on Paper

Step back from your software program. This is especially crucial if you’re using Excel or R (versus Tableau) where you usually need a solid idea of your chart’s design before implementing that design on the computer.

I sketch, draw, and doodle plenty of drafts before I create anything on the computer.

Here’s how it works: First, sketch plenty of rough drafts on paper. Give yourself permission to doodle as many drafts as you need. Share drafts with colleagues early and often. Gather as much feedback as you can. Next, create one or two of those promising drafts on the computer. Finally, edit, edit, edit! Put your easiest-to-follow chart in your final presentation or report. You might sketch five or more drafts. Only the single best chart will survive the editing process.

Step 3: Select a Software Program

Once you’ve got a rough mental idea of what your visualization might look like, sit down and build the first draft of your visualization on the computer.

There are dozens of software programs available for building data visualizations. Some are free. Others are low-cost. And others are quite costly, at least for smaller organizations.

I’m software-agnostic at my core, meaning that I don’t care which program you use. You can create great — or terrible — graphs in any software program.

That being said, 99% of my data visualization consulting is done in Microsoft products: Excel, Word, and PowerPoint. Those are the common denominator for the companies that hire me. I’d never create a dashboard in a specialty software program… if you don’t also have access to it and know how to use it. It would be useless!

Here’s an example of an interactive dashboard made in good ol’ Excel. You can learn how to make these, and many other types, inside my Dashboard Design online course.

Step 4: Declutter

After you’ve got the first draft of your data visualization created on the computer, it’s time to refine your visualization and make your message shine. No computer program is perfect. You’ll have to roll up your sleeves and make intentional edits no matter which software program you’re using. The very first edit I make is to declutter my visualization. Software programs come with way too many borders, lines, and unnecessary ink. Examine each and every speck of ink on the chart. Does it have a specific purpose? If you can’t articulate a reason for that ink, you don’t need it.

Apply the Squint Test

In these before scatter plot on the left, the cluttered appearance distracts us from the data. All these extra lines make the charts look overly scientific—and outdated. In the after version on the right, I removed the background shading and borders. I kept the x and y axes and some of the grid lines, but I intentionally changed the black ink to gray ink.

How do you know when you’re done decluttering? Apply the Squint Test. Here’s how it works: Squint your eyes so that you’re peering at the chart through your eyelashes. Everything should look a little blurry. Can you see the overall shape of the data? For example, you should be able to tell if a line chart is jutting upwards or downwards over time. If not, try removing more clutter.

Outline Shapes in White

You’ve got the gist of decluttering. Now, let’s fine-tune!

Sometimes reducing clutter means outlining shapes in white, rather than black, so that they match the chart’s background color.

Step 5: Clarify Your Message with Color

There are three goals for color:

1. Branding (Using your company’s colors, which saves time and helps you look professional)
2. Accessibility (Making sure your colors pass official guidelines so they’re legible for people with disabilities, like ADA/508 compliance in the United States)
3. accessibility (Using colors to make the graph feel intuitive)

Brand Your Visuals with Custom Colors

I’m begging you! Do not use the default colors from Excel, Tableau, or Google Charts. Nothing screams novice! or 2002! more than default color schemes. If you’re designing charts for a report, handout, or presentation for a client, use their color scheme. Consultants, this means the report will look like it came from the client. It will not have your firm’s look and feel.

In this example, Johanna Morariu and I were designing a slidedoc for the Working Families Success Network. We began by investigating the Working Families Success Network’s logo, website, and publications. Their logo has a distinctive blue, orange, and pink and their publications use dark gray text rather than black. Throughout their website they use color blocks with white text and white outlines. Next, we adapted that layout and color scheme for our slidedoc. The images on the right are separate slides (pages) of the report.

You can locate custom color codes in style guides, with a free eyedropper tool, or even with Microsoft Paint. Then, enter your custom color codes in Microsoft Excel or in Tableau.

Make Sure Your Colors Are Legible for People with Color Vision Deficiencies

Here’s how:

1. First, by proactive and avoid using red-green color combos.
2. Second, make sure you directly label your data.

Although we’re used to seeing legends, we rarely need them. Legends can lead to unnecessary zig-zagging around the screen or page, and legends can also be difficult to interpret if your graph is printed in grayscale.

Instead of using legends, directly label the data. Direct labels mean that you add labels as close as possible to the data. For example, in a line graph, you would delete the separate legend and place the category labels off to the right of each line. For bonus points, color-code the text in the labels to match the line.

This is what direct labels look like:

Then, you can upload your draft to www.color-blindness.com’s Color Vision Deficiency Simulator to get a preview of what it’ll look like for people with protanopia and deuteranopia.

Emphasize the Takeaway Message with the Action Color

When you want to tell a story with data, you can guide your viewer’s attention to your desired takeaway finding by creating a dark/light contrast. This example comes from one of my graduate school projects a decade ago, so I used the exact shade of green from my university’s logo. Then, I used dark green to draw my audience’s attention to a couple key parts of the slide. This slide comes from the fourth section or chapter of the presentation, the Limitations section, so that tab was highlighted in dark green so that it contrasted with the other tabs, which are in gray. The topic of this particular slide was Brevity of open-ended survey responses, so that text is in green so that it stands out against the rest of the text. And the box-and-whisker plot itself also uses dark green.

Step 6: Clarify Your Message with Text

It’s hard to get wording just right, so I usually save my titles, subtitles, and annotations for the end.

Brand Visuals with Custom Fonts

Rather than using Microsoft’s plain ol’ Calibri, make sure your visualization’s fonts match the project’s branding.

Write the Takeaway Finding in the Graph’s Title

Need to tell a story with data? Rather than using a generic title (“Figure 1” or “Number of youth served”), state the takeaway message in the title.

I first learned about this technique through Cole Nussbaumer’s Storytelling with Data workshop back in 2012—but geez, was it tough to apply! This is one of the hardest practices for social scientists to learn because we’re so comfortable with APA formatting and its generic figure titles.

Think Twitter-like and aim for six- to eight-word titles. Look to newspaper articles for inspiration; journalists know how to include the “so what?” in their title. You may or may not read the full newspaper story for additional details. Same thing with charts: your audience may or may not read your full chart, so your title must give them the gist of your findings.

Add Context with Annotations

Annotations are call-out boxes that provide important contextual details. In PowerPoint, Word, or Excel, you can easily create annotations by inserting a text box. No fancy software required!

Here’s a great example from Mother Jones. A generic title would’ve been “Number of children living in poverty” or “Relationship between poverty and geographic location.” This 6-word title, “In Climbing Income Ladder, Location Matters,” ensures that readers grasp the chart’s message instantly. A 2-line caption adds more details underneath the title, and a few cities are annotated. The tweet’s text also reinforces this message.

This is how likely poor kids are to grow up and move out of poverty based on where they live http://t.co/5A5VIZkLBN pic.twitter.com/7BBZQJ9bdg — Mother Jones (@MotherJones) January 31, 2014

Establish a Text Hierarchy

Size your fonts according to their importance. A text hierarchy tells your viewers which information is most important (headings) and which information is least important (the regular ol’ paragraphs). In this example, I transformed a university’s annual report simply by adding an intentional text hierarchy. I call this makeover a two-hour turnaround because these are changes that anyone can make in two hours or less. Before, all the font was the same size, so the headings didn’t stand out. The report looked like a sea of words. After, we made the headings stand out by with larger fonts and by overlaying the text on top of a photograph. We also used a different color for each section to break up the sea of words into manageable chunks.

Lower the Reading Level

The vast majority of reports, handouts, infographics, dashboards, and slideshows that I review with clients are written at a reading grade level that’s so high that reading the documents feels like homework. In this example, we assessed our draft’s reading grade level with a free tool called readable.io. Then, we re-worded the title so that it was a closer match for our intended audience.

Finally, go share your chart!

You’ll need to edit it slightly depending on the medium — a chart for a presentation should look different than a chart for a dashboard. You can learn about presentation-specific, dashboard-specific, and report-specific techniques.

Learn More

Sign up for my free online course called Soar Beyond the Dusty Shelf Report. There are several quick lessons that help you get started with data storytelling.

Or, contact me about online courses, private workshops, and conference keynotes.

Today you’ll learn from JC De Jesus, Vice-President of Service Delivery for an internet-provider based in Canada. Thanks for sharing, JC! –Ann

—–

“The world rewards people who are best at communicating ideas, not the people with the best ideas”

@david_perell

The ability to communicate effectively is a key skill in any venture, business or personal. Depending on your specific situation, effective communication skills can vary, and cover a wide range of topics. 

A student presenting in class with a set agenda topic and visual aids will communicate very differently from, say, a company CEO or a manager leading a team through a complex project over several weeks or months.

Communicating via Salesforce Chatter

In our company, Salesforce Chatter is one tool for effective communication. 

Chatter is like a social-media platform but for business.  You follow co-workers to see their posts (like Twitter or LinkedIn), you can join groups and see group updates (like Facebook).  It also has a top-notch mobile app.  

And as you can imagine, just like any social-media app, your newsfeed can get really, really busy!

For a leader sharing an update to the team or the entire company, it’s important for your update to be as concise and engaging as possible for it to be effective.

Using a 1-Pager to Effectively Communicate Internally

I run a large team and share updates in Chatter. One of the things I find to be effective is using 1-pagers. 

Instead of dense and text-heavy presentations, I minimize the text to include only the main points and actions I need from my team. This way, the 1-pager can be read in 2 minutes or less.

Here’s a 1-pager I’ve posted recently. This is for an ongoing project with many stakeholders. 

Notice some of the key elements:

• Headers. The header “We Deliver Better” is in large, bolded font.
• Page Layout. The layout is a 2-column format, which makes the sentences appear shorter and easier to read.
• Outline. Notice the five-topic outline with icons. Those 5 topics stand out because of the larger font size and font color (blue) that’s different from the rest of the text.
• Visual Framework. The icons emphasize each of the 5 topics. These are also used in slidedeck presentations for consistency.
• Branding. It uses our corporate brand colours and logo.
• Divider Lines. There are no divider lines between rows and columns. Those are not needed if we give the page a lot of white space, which I’ve attempted to do here by cutting down on text.  Cutting down on text while getting the full message is the hardest part in putting this together!
• Skimmability. Key phrases are in bold to make it more scannable.
• Hashtag. And, of course, the hashtag #DeliveryExperience on the top right.

My goal was to write something that can be read in 2 minutes or less by a wide audience (100+ people), and the 1-pager format helps me achieve exactly that.

And for anyone who wants to get into more detail, we also have a 30-minute slidedeck. It uses many of the same elements as the 1-pager.

By having a variety of approaches in communicating, I’m able to appeal to and share information with my audiences much more effectively.

Connect with JC

LinkedIn: http://www.linkedin.com/in/jc-dejesusus

Twitter:  @technophone

Nobody wants to pour blood, sweat, and tears into a document that sits on a dusty shelf.

In May 2021, I co-presented with Elizabeth Grim at the Eastern Evaluation Research Society’s annual conference.

Our session was titled, “How to Design Reports that Actually Inform Decisions with Software We Already Have.”

Attendees learned about:

• The 30-3-1 approach to reporting with unlimited visual appendices
• Adding a 20-minute report cover
• Adding color-coded divider pages
• Aiming for 1+ visual on every single page
• Including a variety of visuals
• Using inclusive, non-violent language

Today, let’s focus on one of those techniques: following the 30-3-1 approach to reporting, which is the bare minimum for designing useful reports.

Watch the 10-Minute Tutorial

I recorded a portion of our presentation for you. Here’s a 10-minute lesson about the 30-3-1 approach.

Hopefully you recognize this technique already; I’ve been speaking about it on panels for a decade. 😊

I’ve raised the bar over the past decade though. I used to simply encourage us to follow 30-3-1. I’ve clarified my advice to add visual appendices, too.

The Old Way: The 100-Page Technical Report

In the video, I show you the old way of writing reports in research and evaluation settings.

The single, 100-page technical report used to be the norm. And in some settings, it still is. (I’m thinking of the government agencies and government contractors that I work with.)

Nobody’s got time to read all 100 pages. I think we’ve known that for a while. 30-3-1 to the rescue!

The 30-3-1 Approach

Don’t want your reports to sit on a dusty shelf?

At a bare minimum, I suggest following the 30-3-1 approach, which includes:

• A 30-page report (30 pages maximum) with unlimited visual appendices
• A separate 3-page PDF
• A separate 1-page PDF

In a perfect world, with more time and a bigger budget, I’d love to see slideshows, dashboards, and infographics for every single project, too.

Reports are a good starting point.

The 30-3-1 approach with unlimited visual appendices is even better.

And adding slideshows, dashboards, and infographics is even better.

This approach is all about tailoring for our audiences. Rather than pouring everything into a single document, we design a 30-pager with one audience in mind, a 3-pager with another audience in mind, and so on.

Paring Down 100 Pages into 30 Pages or Less

This is the hardest step. You’ll need to get input from your boss, your report’s audience, a stakeholder group, etc.

I suggest following Marie Kondo’s advice: Focus on what you’re keeping, not on what you’re letting go of. In the video, I discuss her technique for decluttering our closets: Make a big pile of all your clothes, and then look at each item to decide what sparks joy.

We focus our mental energy on the best pieces that are worth keeping, rather than getting stressed by what we’re discarding.

We can apply the same strategy to paring down reports. Focus on the charts, pages, or chapters that are so valuable that they need to stay within the 30-page report body.

We don’t have to delete the rest of the pages. We simply move them to the back of the report, and they form the appendices.

The 3-Pager and 1-Pager

When we’re done with the 30-page report, we also need a separate 3-page report and a separate 1-page report.

Sometimes we’re tempted to count the executive summary as the 3-pager or 1-pager. That’s not enough!!! I recommend creating separate PDFs altogether.

And of course, we don’t have to follow the 30-3-1 approach exactly. We’re aiming for a full version, a mid-length version, and a short-n-sweet version. Your 3-pager might actually be 5 pages, for example. The spirit of the 30-3-1 approach is still there. I want us to avoid only writing a 100-page technical report. 20-10-2 or 30-5-2 will still help our readers tremendously.

A Case Study from a Public Health Agency

In the video, I mentioned a guest blog post from Sara DeLong about how the Wisconsin Division of Public Health applied this technique.

Her agency developed a 130-page report, a 10-page summary, and a 1-page summary. Then, they also created videos, images, and billboards (!!!) to ensure that the messages got off the dusty shelf and into the community.

Add Unlimited Visual Appendices

In the video, I also discussed adding unlimited visual appendices to the end of our reports.

Here’s the blog post where you can learn about visual appendices and get tips for creating them yourself.

Spoiler alert: I create these tables in Excel; add Data Bars, Color Scales, and Spark Lines; and then save them as PDFs.

Learn More

My co-presenter, Elizabeth Grim, also wrote a conference session recap.

Your Turn

Have you followed 30-3-1? Have you created unlimited visual appendices? Please comment below and link to your public-facing examples or describe your project. I’d love to learn from you.

Before

When asked to submit their existing visualizations to be redesigned, one of the conference attendees sent me this dashboard (shown below).

The attendee was responsible for monitoring key statistics about the university’s library.

The dashboard included information about the number of visitors, transactions, checkouts, and interlibrary loans.

These twelve metrics and their associated icons were intended to provide an at-a-glance overview about the library during a given month.

What’s Working Well: Length, Icons, and Text Size Hierarchy

A few things were already working well for this dashboard:

• The most notable accomplishment was that it already fit on one page! I typically see “dashboards” that drone on for way too many pages. I’m not an old school dashboard designer. I don’t believe that dashboards have to fit on a single page or screen. But sometimes the multi-page dashboards also contain so much narrative text that they’re more of a report than a dashboard.
• The icons were also working well. Michelle Borkin and her team found that icons make graphs more memorable, so I add or keep icons whenever I can.
• Finally, the dashboard already incorporated a text size hierarchy of sorts. A hierarchy means that the most important information should be large, dark, and bold so that it grabs our attention. The twelve big numbers are already stood out, which was a plus.

What Needs Editing: Clutter, Alignment, and Context

There are a couple easy edits:

• We’re going to do the usual decluttering for
  this dashboard. That’s a given, right? We’ll simply remove the borders that
  outline each of the twelve data points.
• We also need to adjust the alignment. The numbers and words are centered within their boxes. Yet
  the icons aren’t quite centered over them. Intentional alignment makes our visualizations
  look polished.
• The biggest edit needed is context. The dashboard
  currently shows February’s numbers. For example, 24,051 people visited the
  university’s library during February alone. I have no idea if that’s a huge
  number or a tiny number. A single number on its own doesn’t tell us much. We
  need more context. We need to be able to compare that number to something. There are a few comparisons
  we could make. For example, we could compare that number to the prior month
  (January vs. February). Or, we could compare that number to our goal
  (February’s actual number compared to February’s goal).  

After: Monitor Patterns Over Time

Here’s the first idea for this university’s monthly dashboard.

These are made-up numbers, but hopefully you still understand the gist of the makeover.

I:

• gave viewers the opportunity to monitor patterns over time. Each month has its own column. Now, we can compare the current month to past months, which adds much-needed context.
• added graphs, which I created with Microsoft Excel’s spark columns.
• decluttered the dashboard by removing unnecessary outlines. I chose to keep the single horizontal line beneath the months, but that line is gray, not black.
• color-coded by category. I grouped the twelve data points into categories: Visitors (blue), Transactions (purple), and New Materials Acquired (turquoise).
• applied a text hierarchy. The title is large, dark, and bold. The headings (Visitors, Transactions, and New Materials Acquired) are a medium size because they’re of medium importance.
• adjusted the alignment. The words are left-aligned and the numbers are right-aligned. The icons are center-aligned with one another, and they’re top-aligned beside each of their categories.

After: Track Progress Towards Goals  

Here’s the second idea.

It’s also clutter-free; includes graphs and a text hierarchy; and groups the twelve data points into categories (which are color-coded, of course).

The difference is the dashboard’s purpose. The before version only looked at one month at a time. To provide more contextual details, the first makeover allowed viewers to compare patterns over time. This second makeover allows viewers to track progress towards goals.

I included columns for Running Totals and Year-End Goals. Then, I indicated whether the goal was achieved with filled-in squares and empty squares. I taught you how to create these square icons in an earlier post. They’re just lowercase g’s and c’s in the Webdings font!

Finally, I visualized the percentage of the goal that had been achieved so far. I call these progress bars. In some areas, the library has already exceeded their goal, so the bars spill past the 100% mark—a cause for celebration!

The Winning Idea

Which dashboard is correct?! Both of them!

Two dashboards, two different purposes.

I recommend designing several options for your viewers. Ask which one they prefer. Gathering feedback is one of the most important steps of the design process.

Bonus! Download the Spreadsheets

These are Microsoft Excel files, which are then distributed to viewers as static PDFs.

(I rarely make interactive dashboards with drop-down menus or checkboxes anymore. Leaders are busy and simply don’t have the time to explore interactive dashboards. I’ve found that the busier the audience, the more they prefer receiving a PDF’d one-pager.)

You can download my file and adapt the templates however you’d like for your own metrics and numbers.

Hi, I’m Tyler Mason, a Juvenile Justice Strategist with the Indiana Juvenile Detention Alternatives Initiative (JDAI). 

This two-pager that I have created was born out of Ann’s “chose the right format” training from her Great Graphs course:

Here’s how I developed this two-pager.

Know Who Your Audience Will Be

It is vital that you know who your audience will be when developing your charts.

If you don’t follow this critical piece, you may completely miss your audience, and at that point, you may have lost the story you were trying to convey to them.

You will notice with the two-pager I am attempting to communicate the essential data points that I can in a concise way given “one” sheet of paper. 

Select the Right Type of Graph

By utilizing the “choose the right chart” lessons in Ann’s online course, I was able to use the chart that made the most sense with creating the data story.

You will notice that different charts were utilized to tell the data story. For example, we included line charts, bar charts, stacked bar charts, and clustered bar charts.

The first thing as Ann spells out is either draft what you envision on a piece of paper or start brainstorming in your mind.

Through the brainstorming and utilizing Excel, my graphs were born.

Create and Format the Charts on Your Computer

Entering the data and creating the charts is the hardest part, then comes the formatting, which can be the same.

The Less Noise, the Better

One thing as Ann mentions often is the less noise, the better. So, be sure to remove all the noise in the Excel graphs.

Using PowerPoint for Easy Layout Options

Once I had my charts created, I then utilized PowerPoint to lay them out and start telling the story from starting big picture to breaking out what was seen in 2018 for said county on the first page.

When you look at the other side of the page, I start to dig a little deeper into the data and what was seen with length of stay and average daily population.

The last two charts at the bottom are to tell a story about the work that still needs to be done.

How to Frame Your Two-Pager

As a recap, here’s what I considered in my project:

1. What data are you planning to present?
2. Who will be your audience, and what is their knowledge level of the data?
3. Brainstorm ideas to develop your charts from this point forward
4. Utilize whatever platform you like. I like to use Tableau or Excel. For this current project, I used Excel and PowerPoint.
5. Start drafting your charts. I also find it valuable to bounce your ideas of your coworkers and what they think of the charts and the story you are trying to tell. I find asking a coworker what they think my data story is trying to tell. If they guess correctly, you’re on the right path. 
6. Do not forget the formatting of your charts. The less noise, the more people will be engaged. Simple is ideal. Also, another important thing to consider and not forget about is what will my charts look like in black and white and if I used color, are they legible for people with color vision deficiencies. I find that is something that is often overlooked that is also a very vital piece to this equation.
7. You’re done! Good luck, and as always, be prepared for questions.

The Great Graphs course has been phenomenal and I highly recommend it for anyone needing guidance on how to create the best graphs for your audience.

I hope you find this information worthwhile. Good luck creating your data story.

The first of two data visualization workshops with @AnnKEmery is underway! #GRADprofdev #GradsDo pic.twitter.com/Dw15UFiFDh

— GradSchoolatUSC (@GradSchoolatUSC) April 5, 2019

Thanks to Heather Brandt and Chelsea Richard for making this learning opportunity possible!

My Rocky Transition from University to Non-University Settings

In the weeks leading up to the workshops, I spent a lot of time reflecting on my own time working in a university.

My transition from a university research lab to a non-university consulting job was rocky, to say the least!

Long ago, I had majored in psychology so I could take as many research methods and statistics courses as possible. And learning how we learn–the courses on cognition, memory, perception, and brain biology–are critical in my everyday work as a data visualization designer and speaker. I literally use those concepts every single day to design reports, slideshows, and infographics that translate dense, jargony data into materials that others can understand and learn from.

I had initially planned to become a psychology professor. Because what else would I do? 18-year-olds have a slim understanding of all the career paths available–or the brand new career paths that they can blaze for themselves, as I’ve been doing.

After graduation, I did what all my psychology major friends did: I worked in a university research lab for $10/hour and no benefits.

Well, I actually worked in four different labs, adding up to 60 hours/week, not for fun, but to make ends meet.

I worked on a longitudinal study about adolescent development (scheduling participants to come in for data collection interviews, entering data, transcribing interviews, and playing on SAS). I worked for a law school professor doing policy research (calling residents to see whether they would vote to ban smoking in apartment buildings). I worked for a local government commission (evaluating a community-wide system of children and family agencies and designing graphs for a community report card). I worked on a home visiting evaluation (driving throughout rural Virginia and interviewing parents and children during home visits).

These were the dream jobs that would look great on my resume and boost my chances of getting into a Ph.D. program.

However, less than a year later, I needed to go to the doctor. And I desperately needed to see a dentist. I left those research labs and found a consulting job with health insurance.

And so began the long, hard mental transformation from a university to a non-university researcher.

Communicating Data in University Settings: APA Format

I knew exactly how to write research papers for university settings: Times New Roman, size 12, double-spaced, with 1-inch margins and APA format. The goal was clear: Do amazing research and try to get some of those papers published in peer-reviewed journals.

Sometimes I helped graduate students and professors with conference presentations or posters. The formatting seemed pretty straightforward. For posters, it seemed like all you were supposed to do was copy and paste your APA format paper onto poster paper and then get it printed. I didn’t know how conference attendees were supposed to read the 12-point font from a few feet away. But I also knew not to ask. My, how times have changed!

Communicating Data in Non-University Settings: Whatever Format Is Needed to Get the Message Across

Business writing was a different world. We wrote single-spaced reports! And sometimes used 1.5-inch margins! Or 0.5-inch margins! Or landscape layout instead of portrait!

We provided reports whenever our recipients needed data, not just at the end of a project. Sometimes weekly, sometimes monthly. Sometimes at the very beginning of a project. Often all throughout the middle of a project.

We went well beyond reports. We talked with stakeholders over the phone, in conference rooms, through webcams, and over lunch. We gave formal presentations. We worked on press releases. We created separate one-pagers and three-pagers and five-pagers. We made dashboards and infographics. We never followed the Abstract-Introduction-LitReview-Methods-Results-Discussion order.

I was in disbelief most of the time. “We allowed to present data like this??” I would ask my (very patient) coworkers all the time. “We’ll present data however it makes the most sense for our stakeholders and project,” they would answer. What. It took me a while to get it. In the back of my mind, I thought the APA Police would come knocking on our doors.

Transitioning from University to Non-University Settings: What I Wish I Knew Sooner

As I was prepping for the dataviz sessions at the University of South Carolina, I decided to focus on the communications strategies I wish I knew sooner.

Turns out–that’s everything that I do for a living.

That may not surprise most of you. Duh, Ann. That’s what you do. You teach us how to communicate our technical information for non-technical audiences. I didn’t realize that so much of what I do has stemmed from those early, frustrating years.

I wanted to cover everything with this group of faculty members and graduate students.

I narrowed it down to top 10 communications strategies I wish I knew sooner.

Follow the 30-3-1 Approach to Reporting

At the very least, I advised the faculty members and graduate students to follow the 30-3-1 approach to reporting.

It goes like this: You limit your report to just 30 pages (with unlimited appendices). This is easy for those of you who primarily communicate with slideshows or dashboards. But for those of you who primarily communicate with hundred-page APA-format papers, this is a really hard transition.

Then, you write a separate 3-page summary and a separate 1-page summary.

Then, you keep going! You create dashboards, infographics, slideshows, or even bus campaigns and highway billboards.

Understand Your Audience’s Needs Before Analyzing Your Data

We talked about how business settings are audience-focused. You have an opportunity to be of service to others and think about the data that others would find most valuable in their data-informed decision making processes.

I wish I knew about the difference between a traditional graph and a storytelling graph sooner.

Go Beyond the Bar Chart

We talked about how pie charts and bar charts aren’t inherently evil. They’re just overused. And there’s so much more available to you, especially if you’re willing to hijack your software program’s default settings.

For example, I encouraged the faculty and students to try 2-slice waffles instead of million-slice pies.

We also discussed the pros and cons of regular geographic maps vs. square tile grid maps vs. hex maps vs. cartograms.

Hey check out this data viz! One of the examples @AnnKEmery shared with us! 👍 https://t.co/SraqIWOK0m

— Heather Brandt (@BlondeScientist) April 11, 2019

Use Software You Already Have

Purchasing new software won’t solve your dataviz problems.

Effective data communication is more about planning and strategizing than about googling which buttons to click.

Here are some one-pagers I made entirely inside good ol’ Excel:

Declutter All Graphics

I wish I knew that deleting half the software’s unnecessary ink is the easiest way to improve a graph.

Here’s a decluttering makeover:

Brand Your Visualizations with Custom Colors and Fonts

First, find your existing brand guidelines. The University of South Carolina has a robust brand toolbox with color guidelines, font guidelines, and presentation templates that all faculty and students can use. (And should use for every presentation to remove guesswork and increase professionalism, in my opinion.)

Second, enter your color codes into Excel or Tableau.

What an easy Five Minute Fix!

Improve Your Visualization’s Accessibility

Okay, this one deserves its own blog post or book because there are so many ways to improve your visualization’s accessibility.

Accessibility is a core feature of my work. It’s woven into each and every strategy that I teach.

During the workshop for faculty and students, we focused on three techniques.

Avoid Red-Green Color Combos

Avoid red-green color combos, and then test your drafts at https://www.color-blindness.com/coblis-color-blindness-simulator/.

Avoid Colored Text on a Colored Background

Avoid colored text against a colored background, and then test your drafts for color contrast at https://webaim.org/resources/contrastchecker/.

Avoid Using Separate Legends

Avoid using separate legends/keys. Instead, directly label your data.

Apply those Branded, Accessible Colors Strategically

If you have a binary variable, then use a binary color scheme.

If you have a sequential or ordinary variable, then use a sequential color scheme.

If you have a diverging variable, then use a diverging color scheme.

If you have a categorical variable, then use a categorical color scheme.

If you want to tell a story, then use a dark/light contrast.

Measure the Reading Grade Level of Your Writing

When I worked in university research labs, terms like standard deviation and confidence interval and p-value and beta weights were part of everyday conversation.

When I teach dataviz workshops for communications, public relations, and graphic design teams, we talk about the difference between a percentage increase vs. a percentage point increase vs. a percentile. These differences are obvious to those of us who make those calculations daily. But these differences sound like gobbledygook to everyone else who has devoted their carer to a specialty other than research methods or statistics.

I was actually really surprised to learn that most people outside of university research labs don’t use these words in regular conversations. I had been living in a bubble for a few years. It took me a few more years to find accurate synonyms for research methods and statistics terms. It took me a few more years to admit that those terms counted as jargon.

Here’s an article with more info on measuring (and the lowering) the reading grade level of your writing.

Increase the Inclusivity of Your Writing

Firemen –> firefighters.

Stay-at-home moms –> stay-at-home parents.

And so on.

(Yet another technique that really deserves its own blog post. I’m adding this one to the to-do list.)

Most of these techniques apply to all settings, not just non-university settings.

For example, you can definitely follow your organization’s font and color brand guidelines now, not just later on if you decide to work outside of academia.

And you should always strive to make your visuals as accessible as possible.

Your Transition from University to Non-University Settings

Before the workshops, I also asked you for tips on social media:

I especially wanted to hear from those of you who had a rocky transition like I did.

It turns out that a lot of us learned the hard way!

Here are some of my favorite responses.

Translating Academinutiae into a Summary Summary

Thanks, Kirk Knestis, for our favorite new vocabulary word!

During the workshop for faculty and students at the University of South Carolina, we practiced transforming their peer-reviewed journal articles into one-pagers.

The attendees had less than an hour to:

1. read a peer-reviewed journal article that one of their colleagues had written;
2. come to consensus about the article’s key takeaway findings; and
3. draft a one-pager to showcase those key takeaway findings.

Whoa! No small feat in less than an hour.

Coming to consensus about the article’s key takeaway findings probably took the most time. What really mattered in each article? What was so important that it deserved to go into a one-pager?

(Photo credit for all photos: @GradLifeatUSC on Twitter.)

A Template for Your One-Pagers

I gave the faculty and students a rough template to follow.

I advised them to choose 3-5 key points.

Then, illustrate each key point with a visual (a chart, map, diagram, etc.) to back up their claims.

Then, arrange the visuals on the page, perhaps with a simple 2×2 grid layout.

Write storytelling subtitles for each of the visuals.

Color-code by category (e.g., the heading and the graph in the upper left corner are both green, so you instantly know that this takeaway finding is different from the fuchsia heading and the fuchsia graph in the upper right corner).

Don’t forget to add contact information and a url to the bottom.

Check Out these One-Pagers!

The faculty and students had less than an hour. Here are some of their drafts. Tremendous progress for such a short amount of time! Well done.

(Photo credit for all photos: @GradLifeatUSC on Twitter.)

Many thanks to everyone who contributed their own advice to smooth the transition from university to non-university settings for these faculty members and graduate students!

If you’ve got additional advice to share, please comment below.