For the first time, TechnoServe’s beneficiaries, partners, donors, and prospective donors can view key stats about TechnoServe’s projects. TechnoServe is offering their data to the public, not because they have to, but because they want to. What’s not to admire about an organization that’s committed to transparency and information-sharing?

The portal includes a map of the countries and regions where TechnoServe works…

…and results by country and by project.

There are three features that make TechnoServe’s Results Portal easy to navigate:

• Consistent color-coding and icons by category;
• Consistent navigation; and a
• Consistent text hierarchy.

Consistent Color-Coding and Icons by Category

I like color-coding by category within a single document. I love color-coding across multiple documents and projects.

Remember TechnoServe’s 2016 Impact Report, which I showed you last time? They reported on three key variables: financial benefits, beneficiaries, and finance mobilized. Throughout the entire 16-page report, information about financial benefits was always displayed in green with the icon of the hand holding paper currency. Information about beneficiaries was always displayed in purple with an icon of several farmers standing together. And information about finance mobilized was always displayed in turquoise with the line graph icon.

We repeated the same colors and icons throughout the Results Portal, too. Can you spot the icons, terms, and definitions in the opening screen of the Results Portal? We added a fourth variable to this project, too. TechnoServe wanted to emphasize how many beneficiaries were female, so information about percent women was displayed in orange.

2016 Impact Report (left) and Results Portal (right)

We also worked on a third product, a series of Google Sheets dashboards that were designed for TechnoServe’s internal audiences. Those dashboards aren’t public. But yes, you guessed it, the internal dashboards follow the same color-coding. Financial benefits are green, beneficiaries are purple, percent women is orange, and finance mobilized is turquoise.

Consistent Navigation

Tableau allows you to insert drill-down menus just about anywhere: in the upper left, upper right, lower left, lower right, or middle of the page.

In earlier drafts, our lists of countries and projects that viewers could explore were in different places on different screens. We placed the lists wherever we found blank space and could squeeze them in.

In the final version, we intentionally placed the lists in the upper left corners. In Western cultures, we read beginning in the upper left corner and then read across and down in a z-shaped pattern. That’s why we placed the country and project lists in the upper left corner—because it’s the most valuable real estate on the page.

Our goal was to make navigation seamless. We wanted viewers to focus on interpreting the data, not on interpreting the dashboard.

Consistent Text Hierarchy

Do you really need font in size 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, and 18?

Sometimes, software programs give you too many different font sizes. You insert a chart and there are different sizes for the title, subtitle, axis labels, numeric labels, and category labels.

Other times, dashboard designers create too many different font sizes. We’re not sure what our final product will look like. We experiment. We try a graph title in size 12 on one screen and a graph title in size 13 on another screen. We try a body font in black on one screen and dark gray on another screen. We try a page title in bold on one screen and italic on another screen.

In the final version of the Results Portal, we paid careful attention to fonts, sizes, colors, and styles. We built a consistent text hierarchy. A text hierarchy tells your viewers which information is at the top of the food chain. The most important information is largest, the information that’s of medium importance is a medium size, and the regular ol’ body font is the smallest size.

Consistent text hierarchies across screens make you look polished and professional. More importantly, text hierarchies make your viewers’ job of interpreting the information faster and easier.

Has your organization built a public-facing dashboard like TechnoServe yet? Link to your websites here!

Consistent Color-Coding and Icons by Category

TechnoServe reported on three categories: financial benefits, beneficiaries, and finance mobilized. We introduced these terms, definitions, colors, and icons on the first spread. Then, the terms, colors, and icons are repeated consistently throughout the report. For example, you’ll never see financial benefits in purple or turquoise, or with any other icon.

These colors come from TechnoServe’s style guide, but they do more than just reinforce the organization’s branding. Colors are used intentionally to guide new readers through their terminology so that the content doesn’t feel overwhelming.

Graph-to-Paragraph Ratio

Not so long ago, the monitoring and evaluation field was plagued by hundred-page narrative reports. I’m a big fan of TechnoServe’s commitment to designing shorter reports that people can actually read.

Here’s the wordiest spread of the document, which isn’t even that wordy. On the left page, there’s an introduction (two short paragraphs) followed by a five-word diagram that explains Return on TechnoServe Investment calculations. Even the diagram contains icons. On the bottom of the left page, you’ll find a call-out box for the nerds (me!) who want to learn more. Since the call-out box has a light gray border, readers know that the content is different from the main narrative. It drills deeply into the topic, so readers can choose to read it or skip it.

On the right page, there’s an introduction followed by a dot plot. The introduction is just one sentence. You’re not aiming for zero words; you’re aiming for a sufficient number of words. In this section, one sentence was sufficient.

We strategically hid most of the text within semi-graphical elements, including the diagram, call-out box, and annotations. Graphical elements take up more than half of the spread.

A Variety of Graph Types

Throughout our discussions, we focused on including a variety of graph types. We knew that the only thing more boring than a hundred-page report was a hundred-bar-chart report. Within just 16 pages, we included:

• Photographs
• Icons
• Maps
• Diagrams
• Donuts
• Packed bubbles
• Column charts
• Stacked bar charts
• Call-out boxes
• Dot plots
• Line charts

For example, here’s a diagram about TechnoServe’s agricultural work. A donut within the diagram shows that 34 percent of the farmers were women. On the right page, packed bubbles show the relative size of financial benefits across grains, livestock, coffee, cocoa, and other sectors.

We didn’t include variety for variety’s sake. We included graphs that showcased patterns that we wanted to showcase.

Titles That Tell a Story

One of the hardest leaps for me in my data design journey was transitioning from generic, jargon-filled titles to titles that tell a story. I spent every semester and summer break during college working in research centers within schools of law, public policy, psychology, and education. We churned out peer-reviewed journal articles. After graduation, I worked in three more research centers before transitioning into a government contracting position. I was steeped in journal jargon for years. It took years to un-learn those habits.

Check out these exemplar storytelling titles. The spread’s storytelling title, We Create Lasting Impact in People’s Lives, provides more information than a traditional title like Chapter 4: Impact in Participants’ Lives Over Time.

Both graphs have storytelling titles, too. Our Impact is Sustained Year After Year and Beneficiaries See Lasting Effects interpret the data in layperson language. And they’re short; we only needed four to seven words each.

Have you seen exemplary reports that use consistent color-coding and icons, strong graph-to-paragraph ratios, a variety of graph types, or titles that tell a story?

Before

Here’s a screenshot from one group’s (public-facing) research report. The authors of the report talked about wheelchairs that were given to people in other countries. This was the demographic section of the report so there were a few graphs showing who those wheelchairs went to — men, women, kids, adults, and so on. There are 3D pie charts but I don’t fault anyone for their before graphs. We’ve all been there.

After

The first pie chart was about gender–the proportion of wheelchairs distributed to men and women. According to my seven pie chart guidelines, gender can stay in a pie chart. Gender is a nominal/categorical variable and there are only a couple slices. We just need to reformat things a bit to make the graph easier to read. The before version is 3D, so the chart’s height makes the slices look larger or smaller than they really are. 3D distorts data.

There’s a legend below the chart so viewers would have to zig-zag their eyes back and forth to figure out which color corresponds to which slice. And the viewers would literally be zig-zagging because men are on the left side of the pie and on the right side of the legend, a software oddity. The after version is 2D; has labels directly on top of the slices to avoid wasting time hunting for information in the legend; and it uses colors from the organization’s logo rather than the software program’s default color palette.

The second pie chart was about age ranges–the proportion of wheelchairs given out to younger people and older people. According to my seven pie chart guidelines, age ranges can’t stay in a pie chart because age range is an ordinal variable. There’s a natural order or progression from younger people over to older people, so we need the chart to reflect that built-in characteristic. You could display these age ranges in a stacked bar chart or in a histogram. I went with a histogram because the 0-5 years segment was tiny and nearly invisible in a stacked bar chart. It’s faster to read left to right (the histogram) than to start at 12 o’clock and read clockwise (the pie).

I never cease to be amazed how small edits lead to a big impact. This page of the report looks completely different!

No, I didn’t keep the tables. When we see tables and graphs beside each other, our brains wonder whether the table matches the graph. Is this the same thing? Or different? Wait, it’s the same, right? So why did they include both? Oh, for the raw numbers? The graph has the percentages but not the numbers? That’s the only added value of the table? Redundant tables and graphs are unnecessarily burdensome for viewers. My rule of thumb is to display raw numbers for anything below 100 (3 of 7 people, not 43%) and percentages for anything above 100. We’re talking about well over 100 units here (either 886 or 866 wheelchairs, what an unfortunate typo) so we could’ve just displayed percentages in the pie chart and left off the raw numbers altogether.

However, this report was written for a technical audience, and technical audiences love extra details like numbers and percentages, so I simply included both within the after version.

Sometimes workshop attendees are afraid that including graphs will lengthen their reports. On the contrary, data visualization often decreases your report’s length. I freed up space by deleting the redundant tables. I decided to use that space for titles and subtitles to explain each graph. Before, the graphs were just slapped into the report without any explanatory text. I’m a visual person and prefer to read graphs over paragraphs. Other people prefer to read the paragraphs over graphs. Both viewers’ preferences are met when we add explanatory text alongside graphs.