What's the foundation of memorable data visualizations and infographics? Good data.
[Picture by Florence Nightingale (1820–1910). [Public domain], via Wikimedia Commons
Several years ago, a board member at a nonprofit I was at gave the evaluation department a gift: Edward Tufte’s The Visual Display of Quantitative Information – a not so subtle hint that he was underwhelmed by the reports we were generating.
This gesture made me a little defensive. It also made me laugh. Because the board member wasn’t asking us why we were getting particular results; what they meant for the program; how the organization was responding to the data. Or even if the data he was seeing was good quality. He was simply asking us to present the data differently, so it was more exciting to look at.
In the years since this happened, nonprofits – along with everyone else - have embraced visual representation of data; a gesture made possible in large part by the free/low-cost tools through which data collection, analysis and reporting can be carried out.
It’s great to see so much interest in data and presenting it. The focus, though, seems to have gone – like that of the board member - straight from collecting data to selling it. Nonprofits, including small ones who have little budget for research and evaluation, are more and more being encouraged to tell their stories via data visualizations and infographics.
But unlike the graphics you see on Tableau, nonprofits are not analyzing robust, clean, large n datasets that you need R or another statistical package to produce images around. We’re analyzing home grown surveys and self-administered assessments. The data that’s collected with the most consistency (though I'm not saying anything about their quality) are output metrics like attendance, people served, and meetings held.
What does this mean for nonprofit data displayed via infographics and data visualizations? That it’s not focused on implementation and outcomes; there's usually not enough of it to generate a visualization. Instead, visualizations are used to provide context (using someone else’s data); tell a story; and tabulate outputs.
I completely understand and am sympathetic to nonprofits and social impact organizations’ need to make their work easy to understand and good looking. I’ve got infographics and video on my own website. Organizations need to raise awareness, interest and funds. In our content saturated age, eye catching pictures that also quickly and easily convey information are a good way to hold attention for more than a couple of seconds. A strong marketing story can be the difference between a well funded or a poorly funded cause.
What bothers me is to see effort put into visualizations and infographics that at first glance seem to be telling you something interesting and in-depth – but at second glance are doing no such thing. As I’ve argued, many nonprofits can talk in great depth about i) a problem and ii) their outputs, the activities they engage in to address the problem. But tying the two together – charting how their activities specifically address a problem and what this looks on the ground – is often a black, unopened box. Greater interest in and use of data visualizations and infographics haven’t addressed this issue.
What you usually end up with, instead, are:
Bells and whistles around what’s straightforward, contextual data
Infographics or visualizations that tell a data story, but not a clear one once you scratch the surface
Output numbers but not a good explanation of what they mean for implementation or outcomes
What can nonprofits do to improve their use of data visualization and infographics? Florence Nightingale provides some answers.
[If you have the time, go and read this article in Atlas Obscura about Florence Nightingale and her pioneering use of data visualization. Then come back! The quotes that follow are pulled from this piece.]
Nightingale “in addition to caretaking and advocating” was also a “dedicated statistician, constantly gathering information and thinking up new ways to compare and present it....Her months in the war hospitals of Crimea provided her with plenty of opportunities to gather information.” As she returned home with her data, the timing was propitious. Britain was “gripped by its own numerical fervor…journalists and politicians were comparing sets of numbers in order to demonstrate particular correlations.” When asked by a high government official to “’communicate her opinions’ about hospital treatments in Crimea,” she was ready. She synthesized the wealth of information she had collected – in the form of stories and observations as well as tabulations (of how many were sick at a given time, when they died, what they died of) into a magisterial 850 page report.
Notes on Matters Affecting Health, Efficiency, and Hospital Administration in the British Army included beautifully designed charts, tables and graphs. She used these graphical representations of her data to bring home her main points: i) many, many more soldiers died of preventable diseases than combat; ii) when a sanitary commission was sent to Crimea to clean up the Scutari hospital there were drastic reductions in mortality. This report, and the advocacy she engaged in around its findings, were key reasons sanitation standards in the British Army and general population eventually improved.
There are many lessons to be learned here, including the importance of persistence, patience, daring, and conviction. There’s also a data lesson: how important it is to understand your own work - and the very particular context in which you’re doing the work – when telling your story and getting people invested in it.
Nightingale was involved in both program implementation and data collection; she knew they reinforced each other. She had a particular intervention she’d implemented, seen success with and wanted to scale. Because she had thoroughly documented her work, because she didn’t use what was readily available (the poor data collected by the Office of Army Medical Statistics) or settle for a handful of anecdotes, she had the material with which to make a highly specific case. Her visualizations are the product of a brilliant mind, yes. But also the product of a methodical and deliberate one, who tracked her own work and used it to advocate for her cause.
Context-rich, on the ground, programmatic data is the foundation of compelling visualizations. They’re also the basis of visualizations donors and other stakeholders can tie directly to your organization. If you’re one of the innumerable nonprofits producing national or even international context about a problem, you run a couple of risks. First, having someone understand the problem – but then decide someone else’s approach is the way to go. Second, having someone decide the problem is too big to handle – for them and for you.
Every nonprofit has something relevant and data-driven to say about its own program and what results it's generating in the field. Instead of focusing so much energy on context, broad storytelling and outputs – none of which open the black box of implementation to outcomes - go out there and look at what you’re doing. What makes it great? Why is it important? What do you want people to take away from your findings? What do you want them to do in response to your data? Highly specific data will produce not just pretty pictures for your website, but - as Florence Nightingale so ably demonstrated - images you can tie to action.
I know, I know. You're not being funded to do this work. But you're not a novice; you are collecting some data. If you've read this far, you know data visualizations and infographics can be put to better use.
Here are some ways - taking into account existing resources - to get the work started.
· Instead of putting staff time and energy into yet another generic customer satisfaction survey, go out into the field and watch your users interacting with your program. What do you see? What’s standing out as a strength you can publicize? What's great about this approach is that you can start with a handful of service recipients.
· Examine a segment of your logic model (if you don’t have a logic model, make a hypothesis about a short term, observable result you expect to see from your work). Then go out into the field and see what the data says about it. You can collect data via observations, interviews or even a single question survey.
· Think about how your board can advance your data cause. Do you have a board member that has expertise in data collection? If not, can you recruit one? Board members can serve different purposes. Not all of them have to be champion fund-raisers; they can also bring in-kind resources in a field you need to invest in - like data collection and analysis.
· Talk to a funder. No, not all your funders are interested in helping you produce stronger, more program-specific data. But there’s a good chance there's one who is. You might have a particularly good relationship with one, or they have a special focus on knowledge management and best practices, or they’re looking to build capacity, or they're looking to support a new project of yours.
Nonprofit staff, I'd love to hear your thoughts on data visualizations, infographics and other ways you tell the world about your work. How do use data to create a narrative and make an argument? What kind of support do you need to do this work more effectively and efficiently?
As always, I can be reached at firstname.lastname@example.org