Rapid Fire: Scaling a Portfolio with Design Components

A screen captured image displaying the top part of Tableau Cloud with 80 items selected. Partials of three data views are also visible. — This screen shot as of April 20, shows how close the team is to Club 100 and does not include the eleven viz found on our Tableau public data site.

My introduction to “Club 100” was a social media post about a designer’s hundredth data visualization on Tableau Public. A blessing of this achievement is that you can meet a diverse set of needs, assuming you diversify the subject matter. This is why generating a large, organizational portfolio appeals to me. Creating several series of interactive items would allow you to jump start data usage across teams while you then focus on deeper needs. But how do you generate this much content for an organization, particularly if your team is small?

My career developed with the data visualization field itself. Often I found myself on a “team of one” or was the only designer on an existing team. The way to stay effective in this circumstance was to master certain efficiencies and I have. As of this writing, I have been employed by The DeBruce Foundation for 91 weeks and have been able to generate 91 data visualizations while completing non-design tasks. This total includes some of the public visualizations, which are not pictured in the above total. My overall rate is one data visualization per week, where the actual rate varies from zero to six per week.

Nonetheless I am excitedly nearing “Club 100” in less than two years. So, how did I get here? There are many ways that can speed your development cycle from data cleanliness to clarity of your user’s needs. My efficiency lay in the use of component-driven design. Components are specific report functionalities that are used in a similar manner across visualizations, many of which you already know. These items limit the required cognitive demand during creation as you move them around. The goal is to act like a template while still allowing flexibility.

My current organization has several components that we look for in our internal visualizations: titles, summaries, framing, and the main graphic. These items may not align with you, which is okay, because needs and interests for internal designs are organization-specific. Over the next few sections, I will walk you through the guidelines used in applying these individual components.

A title to a report with a grey background and a thin line above it. The thin line shows three colors and the text speaks to Agile Work Profiler completions. — Typeface hierarchy is an important part of organizational design. Every facet of a visualization needs to reflect the order of the data’s messaging, even titles.

Titles

The importance of this text based component cannot be understated. As pointed out in Scott Barinato’s book, once a user looks for the most contrasting element in the visual display they will attempt to verify that information with an axis or a title. In conversations with my teammates over the years, some users even read a visualization from top to bottom looking at the title first. Every single one of my visualizations contain titles and knowing that in advance means less decisions later. We can go further by considering standards for titles.

Keep language around a fifth grade level and write in sentences where possible. It is unclear if an internal report will ever double as an external one. If you get a chance to share with someone special, then it is best to strengthen accessibility. This is all the more true given US literacy and data literacy levels vary heavily. Inclusive language like “our” adds a personal touch and avoiding contractions is a personal preference.

Always includes three levels, each in the same typeface with decreasing sizes. The first sentence is either the most memorable point, if this is a report, or the easiest description of what is being shown, if this is a tool. The second sentence provides a more technical definition of the title sentence and the final sentence walks users through the “fine” print of exceptions. Often the fine print sentence does not change in a series of designs, while the first two sentences will diverge a lot from design to design.

Under a thin line, composed of two colors, sits a light grey box. Over this box are three rows of text. The first outlines 197,164 Completions, the second identifies a date range and the third row speaks to the frequency of updates. — If you include a summary, it is best to keep those totals with their contextual texts in a similar area to the title. This helps others to see this summary as equal to the title.

Summaries

Whether from for-profit, not-for-profit, or education, all the organizational data consumers I have come across in fifteen years want to know the total of a design. The design itself could have nothing to do with counts as its sole objective is to invoke importance or maybe unknowable size and yet without change my first question will always be, “Christopher, say about how many dots are on this screen?”

Know your audience, do not fight your audience, build on their understanding. In this case, my audience feels better about individual data points when they can be referenced against a sum. This is why almost all my organizational reports have a summary component. Exceptions to this rule are some reports that look like slides and then it is best to work the total into the subtitle typically called out delineated with the uniform accent color of the deck. We can go further by considering standards for summaries.

Focus on the most important number and that becomes total. In the first wave of reporting at The DeBruce Foundation, there was a focus on growing the usage of our key digital asset, the Agile Work Profiler©. More about this free tool is on the linked website, but for us it was key to understand completions. You may not be lucky enough to have leadership like we do who set clear goals that can then be mapped out. In that situation, think back to your original request and pull out the most important component. If all else fails, create a unit total based on the level of detail that comprise the visualization. For example, use overall school count if you are looking at the rise of charter schools in a city.

Mirror the title with parallel formatting. This means text placement on the same line as the title with the same amount of rows, typeface, and topical focus. This second line is on technical definitions like dates and the third line on exceptions. This process equalizes the summary with the title. Remember, the audience has told you they need a total to contextualize and even use this information. That means the information is as important as the total, but not as important as the main graphic.

In corporate designs framing can help to focus the reader on components that matter most. That said, it is important not to be heavy handed in their design. Thin lines and white space when applied can create the best environment for data consumption.

Framing

There are different schools of thought on the use of lines, outside of charting data, inside a data visualization. If a design item negatively impacts the data/ink ratio, it should be avoided. That said, making a frame with two thin lines and white space allows for stronger attention to the main graphic while ensuring contextual information is afforded its own space. The added bonus here is that limiting focus to the main graphic increases reports are faster to create, but also faster to read as the audience knows where to look. Remember, the whole purpose of the report in the data found within the main graphic. We can go further by considering standards for framing.

Keep it thin, consistent, and branded. Organizational reporting, for me, contains a 32-pixel clear border on all sides with now additional buffers. Header and footer lines both are five pixels while evenly split the colors key to the brand. Smaller amounts of pixels on borders and headers/footers decrease readability. Less than five pixels is hard to distinguish color and less than 32-pixel margins make the main graphic feel oversized.

Keep the frame’s center between one and three sections. In my experience, it is best to have one dominant graphic with maybe one or two more supportive ones. The logic for frames in this way echoes the logic for pie charts. If the story is about a “big thing,” with one or two “small things,” then that is palatable because it reflects a hierarchy found in any collection of data. More than that, like three “big things,” and I find you minimize the point. Data visualizations should not have more than one point. Each image ends up being a part of the visual story, and in our industry, short stories are preferred.

A column chart covering years 2018 to 2024 with each year's number increasing. On top of that is a line chart that is measuring the cumulative total of the column chart. In both charts low totals are in grey and large totals in green. — The most important component is the one dedicated to exploring the data rather than explaining it. For the main graphic I try to stick to one, maybe two images. If there are two images, like here, they need to be explaining the same narrative.

Main Graphic

Already having a solid title, summary, and framing structure sets up success in the development of organizational or internal designs. Now is when the hardest work comes. Think about the single most important point of the report or the single most important distribution in the tool. This point, and there should be just the one, is what the main graphic should focus on. There is science behind chart selection, although I personally feel you gain an eye for it over time, but there are lots of resources for those younger in their careers. I would suggest Dr. Evergreen’s work, like all of it she’s up for GOAT in my book. I love Dr. Abela’s chart selection work and Scott Barinato as mentioned above. That said, few things are easier to visually consume than linear distance. When all else fails, work on perfecting column charts and lines charts; both will save you more than you expect. We can go further by considering standards for the main graphic.

Have one accent color, and use it to demonstrate significance. No one wants to read a chart with eight colors— it’s distracting and pulls focus. Besides, our goal is speed, and eight colors is the equivalent of changing the font for each letter in a sentence. Coloring by group versus by significance slows down developer and reader. Bonus points if “increase” is your trigger across a series of reports and that gets embedded in the readers as they consume your content. When doing this, please consider your brand standards and those consumers who may be color impaired.

Anything extra goes in the tooltip/pop up or another report. If it adds a layer of understanding, it goes in the tooltip. For example, the top three months for activity in a year are an excellent context when consuming many years of activity—good fit for a mini chart in a tooltip. That said, adding extra has its limits. Introducing a new level of detail, a new demographic, or a new narrative are often the indication for making a new report. This happens all the time to me. I make a report about ABC and the audience pivots to DEF asking about making the report now about ABCDEF. Offer to make a report dedicated to DEF with a timeline on the spot and that should help. Remember, one focus per report.

A report driven by a column/line chart combination measuring growth in AWP completions from 2018 until 2024 with green color being used to signify largest totals. — The blessing about reports in this style is that they prep the user for the next report. One time I accidently left off the title and immediately heard back on the subject, which is great! By investing in structured reporting I have been able to help define expectations as they pertain to the consumption of data.

Conclusion

These are standards and components that are most commonly employed in my organizational reporting, but they do go further than that. This idea is particularly true as it pertains to the main graphic component. It is not uncommon for me to pair the main graphic component with a small table or perhaps a small heat map to show different forms of the distribution. My hope is that you can take this mindset and apply it to your situation, finding unique standards and components that meet those needs. This is not a bad, broader conversation to engage in as well. “Hey CEO, I was considering creating more consistency in the components that comprise our reports and tools. Do you have a second to outline the things that you love the most in data? I know if I can nail this, it’ll increase development without sacrificing quality.” The key is to think about the system you are designing within and how you can improve it to help everyone.

Christopher Laubenthal

Christopher Laubenthal focuses on better data use with visualizations in an organizational setting. He has experience in both for-profit and not-for-profit sectors where he increases literacy, grows culture, and builds data visualizations. Christopher is the Data Design Manager at The DeBruce Foundation, a national foundation whose mission is to expand pathways to economic growth and opportunity. Current projects include his public viz and The DeBruce Foundation’s Career Explorer Tools.