That was the overarching theme of my Lightning Talk at the DATAcated Expo, which was held virtually in October 2021.

You’re not going to keep the ugly, outdated defaults. Great!

But what should you do instead?

And how do you modify a graph so that it’s just right for your audience?

Surely a group of scientists will need something different from a group of policymakers.

Some audiences adore data. Others don’t.

Some audiences have plenty of time. Others don’t.

In this blog post, you’ll learn about:

• the differences between default, traditional, and storytelling graphs;
• which techniques can help you tell a story with data (e.g., dark colors); and
• when to use each type of graph.

Watch the DATAcated Expo Lighting Talk

Missed the live event?

Watch the Lightning Talk here.

This is a 17-minute video. If you’re short on time, just watch a 10-minute segment — minutes 2 through 12 of the video.

Here’s a summary of what’s inside.

Defining the Term “Data Storytelling”

This is a tricky term with lots of definitions.

Some people love this term.

Others hate it.

In the recording, you’ll see me ask the attendees to share what “data storytelling” means to them.

You might define data storytelling as:

• “What does data really mean, and what do you want it to tell.” — an Expo attendee
• “Translating data for non-data centric users.” — an Expo attendee

And data storytelling is NOT:

• Fiction
• Making things up
• Biasing our audience
• Fudging the numbers

Data Storytelling in a Bar Chart

In the Lightning Talk, I showed attendees three versions of the same graph: default, traditional, and storytelling.

We’ll look at each of these side by side, so that you can see how they’re similar and how they’re different.

At the end, I’ll ask you to comment and share which style you think each of your audiences need.

The Default Bar Chart

We never, ever keep the default settings.

The Traditional Bar Chart

Instead, at a bare minimum, we need to design a traditional graph.

We would:

• Enlarge the font
• Enlarge the bars (by decreasing the gap width)
• Remove the border
• Add labels (optional—if we think our audiences would want specificity)
• Adjust the scale
• Use brand colors
• Use brand fonts

It’s up to the viewers to read the chart and figure out the “so what?” for themselves.

The Storytelling Bar Chart

Sometimes, our audiences prefer storytelling graphs.

You already spent 60 seconds cleaning up the default settings.

In another 60 seconds of editing, we would:

• Sort the bars (e.g., greatest to least)
• Gray everything out
• Highlight one takeaway finding with a dark color
• Add the takeaway finding to the graph title
• Bold a few key words to make the title even more skimmable

Data Storytelling in a Slope Chart

You can apply these principles to any and all chart types.

Here’s what the three different styles look like in a slope chart.

(A slope chart is just a fancy name for a line chart that has exactly two points in time.)

The Default Slope Chart

Defaults are for 2005.

We know better.

C’mon, Excel. And Tableau. And PowerBI. And and and.

The Traditional Slope Chart

At a bare minimum, we need to:

• Enlarge the fonts
• Adjust the scale
• Remove the border
• Add brand colors
• Add brand fonts
• Remove the legend and directly label the data

(Direct labels have three key advantages: They’re faster to read; they’re better for people who are colorblind; and they print better in grayscale.)

The Storytelling Slope Chart

Take the edited graph you just made, and keep going!

In a storytelling slope chart, we would:

• Gray everything out
• Highlight one thing at a time
• Re-write the title and put the takeaway message in the title
• Bonus points: Bold a few key words to make it even more skimmable

Which finding will you highlight in a darker color?

You might highlight:

• The Success Story (Project A)
• The Debbie Downer Story (Project C)

Be careful with red; in Western cultures, red means caution! warning! But colors are culturally-specific; in Eastern cultures, red doesn’t necessarily mean anything bad.

Data Storytelling in a Scatter Plot

We didn’t have time to discuss scatter plots at the DATAcated Expo, but I’d still like to share this example with you.

Here’s how data storytelling would be applied to a scatter plot.

Never keep the default settings!!!!!!!!!!

Traditional graphs are all one color and they have topical titles.

Storytelling graphs have a dark-light contrast and takeaway titles. For bonus points, you could label a few key points.

Data Storytelling in a Map

Finally, here’s how data storytelling would be applied to a choropleth map.

Never keep the default settings!!!!!!!!!!

In traditional maps, none of the colors stand out, and they have topical titles.

In storytelling maps, we’d add an intentional dark-light contrast and takeaway title. For bonus points, you could label a few key points.

When Should You Use Data Storytelling?

Comment below: When would you use each style?

Which of your audiences prefer traditional graphs?

Which of your audiences prefer storytelling graphs?

In the video, you’ll also hear the conference attendees share their perspectives, and you’ll hear from me, too.

The post Are Viewers Expecting a Story? Lightning Talk from the DATAcated Expo appeared first on Depict Data Studio.

About Sharp Insight

At Sharp Insight, we support our clients wherever they are on their program evaluation path, often creating reports and presentations for funders and other key stakeholders.

The majority of my clients are youth-serving nonprofit organizations, including those that run out-of-school time programs and adolescent sexual and reproductive health initiatives. I find joy in being able to produce data visualizations that tell their own story, with one of my proud moments being when a client shared, “I just love this, it’s like it reads itself to me.” 

Producing Reports that “Write Themselves”

Of course, we all know that reports with easy-to-read visualizations and clear messaging don’t just “write themselves!” 

Our team works hard to produce meaningful deliverables with charts and graphs that honor best practices in data visualization. 

However, creating effective visuals is just one part of our jobs.  We have to balance our time in chart development with not only report writing but other key tasks including research, tool development, data analyses, site visits, and workshops. 

This led us to wonder, how can we work smarter by streamlining our internal data visualization development processes?

Developing a Data Visualization Toolkit with Examples and Templates

As a team, we knew we needed a go-to resource that would guide each of us in developing powerful visuals without (re-)creating them from scratch each time.  We also knew we needed someone to “own” this project for our team – me!  

And so, in October of 2018, I enrolled in Depict Data Studio’s Great Graphs online course, and what a meaningful, practical professional development opportunity it has been!  

Over the course of months and inspired by Depict Data Studio’s Chart Chooser, I was able to gain the skills needed to develop a comprehensive data visualization toolkit for our team, with:

• visualizations to show big numbers,
• approach toward a target,
• change over time, and even
• qualitative data visual examples and standards.   

Building on our existing visuals, I worked to generate these templates in our company branded colors, easily adapted to client colors with our handy saved color-palettes.

The Impact of Developing a Data Visualization Toolkit

Across our team, we’ve developed even more. 

Thanks to Great Graphs, gone are the days of each of us taking the time to adjust Microsoft’s default formats by removing vertical and horizontal bars, shrinking gap widths, increasing data label font sizes and alignment, and the list goes on and on.

Our new data visualization toolkit allows us to maximize our ability to exceed our clients’ expectations for visual-heavy reports while still giving us the time and energy to fulfill our numerous other tasks associated with being productive, responsible evaluators.  And for that, we are genuinely grateful!

The post Goodbye Microsoft Defaults, Hello Data Viz Toolkit! appeared first on Depict Data Studio.

Color is about much, much more than simply making your graphs look pretty.

When used well, color can enhance branding, guide viewers’ eyes to the most important pieces of the graph, and reinforce the underlying nature of the data, all while being legible when photocopied in black and white and for people with colorblindness.

I talk about these techniques in depth during our workshops, webinars, and courses.

Today, let’s focus on just one technique–matching your publication’s color palette to your brand and logo.

Avoid Default Color Palettes

First, the enemy we’re avoiding: the software program’s default color palette.

(And major bragging rights to anyone who can correctly identify these software programs in the comments section!)

Default color palettes scream I have no idea what I’m doing, or, worse!, I know I should be customizing my graph’s colors but I didn’t take 30 seconds to do it.

Use Branding Colors Instead of Default Colors

Here’s what we’re aiming for instead: selecting colors from an organization’s existing branding and identity.

Custom colors make our work look polished and professional.

Custom colors shout I care about my work and this graph was designed specifically for YOU with special thought and attention and data is central to our work and our stellar graphs reflect that commitment to data.

Here are the custom colors from a few groups we’ve recently worked with.

Whose Colors: Yours, or the Recipient’s?

Will you use your own organization’s colors or the viewers’ colors?

For example, a consulting firm might use their own color palette when writing the proposal for the work and switch to using their client’s colors for the deliverables.

A nonprofit might use their own color palette when publishing their annual report on their own website, but switch to their funder’s color palette when submitting quarterly reports on the outcomes they have achieved.

I don’t care whose color palette you use. I care that you’ve put conscious thought into this decision and can explain your reasoning to someone else.

Matching colors to branding is just one piece of the effective-use-of-color puzzle. But it’s the first and perhaps most important step.

Your Turn

But wait! Here’s where you come in.

Bonus points for helping me find organizations that are doing a good job of customizing the colors in their graphs.

Share a link to their reports, to their handouts, or to their slidedecks.

Celebrate the good work that’s being done!

The post Matching Graph Colors to Branding appeared first on Depict Data Studio.