Seven Ways We Can Help Local Organizations Transform Data into Impact

I’m in awe of the dedicated individuals working locally to advance social issues by harnessing data. After all, they’re on the front lines of marshaling numbers to push forward their work, and it’s not easy work. They may need data to help inform policy decisions; increase funding for a cause; or perhaps even to try to change a health behavior, such as bolstering physical activity in a community.

The question that fascinates me, however, is whether these folks in the trenches using data for decision-making have the tools they need to take on this important work. Increasingly, I realize that we collectively offer folks doing local work what we assume they need with data, not what they actually could benefit from. Based on the work that I’ve been doing to help local organizations communicate with data, I put together this compilation of ideas on how we can build up the capacity of those doing community-level work to transform numbers into impact.

Individuals Working Locally Desire Tools that Address the Need for Face-to-Face Communication, not Digital Dissemination

There’s a digital arms race these days, with major media outlets churning out data visualizations that are beautiful and highly interactive. These visualizations make your jaw drop and your head spin, but will these gorgeous displays of data be useful to achieve change at a local level? I haven’t seen evidence of that type of use — and there’s a good reason for that. If you’re disseminating data nationally and, like most media outlets, your goal is to raise awareness of and educate people on an issue, you’re likely to choose a highly viral presentation format, one that’s geared for digital dissemination.

But in the conversations that I have every week with people on the front lines, they need tools for face-to-face, not digital, communication. They may have an in-person meeting with a local business leader, so a one-page fact sheet is far better at generating conversation (and less awkward to use) than something meant for display on the computer. Likewise, these same individuals may speak to the county board of supervisors or to a community organization, so they may want to use a presentation or a slideshow. I’m finding that these face-to-face tools, plus a sprinkling of social media for some organizations, is the bread and butter of local data dissemination.

Example: One health department with which I work created data posters; think of them as dashboards with graphs and maps that they enlarge for group display. They’ll bring these data posters to community convenings, and ask attendees to jot down questions and ideas on sticky notes that they place on the posters. In the process, this health department took a format (the dashboard) geared toward one-way communication and turned it into a discussion tool.

The Steady Drumbeat of Outreach Needed for Effective Communication Isn’t Easy to Accomplish

I’m sure a lot of us can identify with the feeling of relief you have when you finish a data project. It likely took forever to find and analyze the data, and you then poured tons of energy into releasing the results. You probably have a report; maybe some kind of supporting charts and graphs; and perhaps a press release and media strategy to highlight key findings. All that’s great, and, yes, you should feel relieved, but a lot of organizations whose data is meant for local consumption lack the bandwidth to go beyond this initial outreach. I’ve found over the years that it takes a repeat dosage of dissemination to get the data to stick. For example, you can tailor your presentation to deliver it to different groups on an ongoing basis, or find news pegs related to your findings, then tweet out your results as news warrants.

Local organizations — for example, a county health department — isn’t really built for such steady, ongoing outreach like this; they understandably must move on to the next obligation by the time they release findings. So it’s incumbent on funders, as well as consultants offering communication support, to help these local organizations communicate in simple, practical ways via ongoing outreach. Foundations, for example, could fund not just the big unveiling but also tactics geared toward repeat dissemination.   

It’s Hard to Be Cogent When Describing Something About Which You’re Passionate

I sympathize with the local epidemiologist who has done amazing and granular analysis of findings. That epidemiologist may understandably assume that others locally will be as interested in the findings as he/she is. So the epidemiologist creates a 40-page data report with roughly 20-30 charts and maps as supporting evidence. I’m sure you’ve all come across a data report like that.

The trouble is that those of us on the receiving end of that impressive report are likely overwhelmed, not enthusiastic. We often just skim through that report quickly, ignoring the supporting narrative as we look for an engaging chart or two that can capture key concepts. Sometimes, we’re so overwhelmed, in fact, that we may just simply turn the other way, closing the browser window or deleting the e-mail announcement, as we move on to the next thing that crosses our computer screen.

I don’t expect the data analyst on their own to know how to avoid this data dump and to think about communication practices, such as targeting specific audiences with tailored messaging. That’s not their job, so it’s probably ineffective to put the tools of communication solely in the hands of the data analyst. Instead, there needs to be a collaboration when it comes to summarizing findings, and in particular, the data analyst needs assistance from individuals who can help them boil down findings to a few key points and add depth incrementally, from an attention-grabbing graph that leads to a one-page summary and, finally, to the full report.

Example: A few years ago, I was tasked with creating report cards to be used by opioid coalitions working locally to combat this growing epidemic. The report cards contained roughly a dozen maps and graphs on opioid prescriptions, emergency department visits, and deaths, and all of the data compared a local county to the state average.  In other words, our reports cards were brimming with useful information.

The problem we faced, however, is that the report, while comprehensive, wasn’t really a good introduction into the topic. If you clicked on the report, you might feel like you were joining a conversation midstream. So we built a landing page that could serve as a teaser to grab people’s attention and to prime them for the larger report. On that landing page, we noted how significant an issue opioid misuse has become, with death rates that are higher than deaths from guns. We then asked the reader at the bottom of this brief teaser how many people in their community they think died from opioid misuse, a question that we answered when they clicked into the report card.

Those Working Locally Need Help Developing an Emotional Story that Can Color the Seeming Dullness of Data Findings

In local settings, we tend to paint by numbers only, forgetting that our brains are collectively wired for stories. Or we’ll resort only to the story, and not seek out related data findings. When you’re working at a community level, I’ve found that there’s a deep well of poignant, relatable stories from which you can draw. And, of course, there’s likely to be some facts you can stitch into this narrative to help you make an even more compelling case. Data storytelling means that you don’t need to choose between reaching the heart or the head, the intellectual side or the emotional side of your audience. However, bridging the two doesn’t come naturally to folks working locally, who may have strengths with data or stories, but typically not both. Fortunately, there are some simple tactics and approaches to help these individuals create evocative, persuasive data stories that can yield the change they seek, and communication experts typically have the knowledge to draw on these approaches and help local communities find their story among the mass of numbers.

Example: I recently traveled to California’s Central Valley with a colleague who runs a communication firm. We were supporting an initiative to help individual communities across California make headway on a particular topic — in this case, heart disease and diabetes — by implementing sustainable, community-wide tactics that addressed root causes, not just clinical factors.

One person in the room, a community organizer in a rural, poverty-stricken and crime-stricken area, talked so passionately about the local park that was in desperate need of rehabilitation. She noted how valuable that park could be to the community, including by encouraging exercise, if the county invested a relatively small amount of funds to renovate the park. We were able to turn a story she told about one grandmother, who cares for her three grandkids, into a persuasive narrative that encapsulates the problem; provides an idealized solution; and integrates data that expresses the situation, all in a two-page fact sheet. It was the story that this community organizer told that made the issue so compelling — far better than data alone could do.

Big Numbers Don’t Guarantee Big Results

The bigger the number, you may assume, the more impact it will have. For example, if there are tens of thousands individuals suffering locally from poverty, not hundreds, you may think you have a stronger argument. Yes, that’s true, you have a strong case to make from an intellectual point of view. But from a practical, more visceral standpoint, large numbers tend to be an abstraction and something we have a hard time conceptualizing. Keep in mind, too, that, seemingly large percentages (e.g. 25% who lack a high school education) or, even worse, rates (e.g. a rate of 20 per 1,000 who have asthma) also are hard for a reader to make concrete.

Local communities — many of which are metropolitan areas the size of small states — regularly resort to spouting off large numbers, but they understandably don’t realize that people may need help unpacking what that number looks like. There are ways — with both words and visuals — that we can demonstrate to our audiences how big these numbers are. For example, we can create visualizations that show numbers as a series of dots to show how big a number that is, or we can use social math (e.g. that’s enough people to sell out the local arena three nights in a row). Here again, though, those of us on the outside, rather than the data analyst, may be better at finding these opportunities where we can unpack the meaning of a large number.

By the way, the opposite also true: Some rural communities face a small-number issue — for example, a relatively small number of deaths (3 or 4 a year) from a major problem like opioid misuse. Here, too, there are strategies to employ to help people understand the significance of these numbers.

Example: I recently was handed a study for one community with which I’m working. It was an excellent, well thought through analysis of cost savings if this particular county could reduce hospitalizations from a particular disease over a multi-year period. They factored in cost savings from avoided hospitalizations and from worker productivity (given that addressing this health issue mean less absences from work). The savings were impressive: more than $100 million in all. But that number is hard to grasp, particularly given their goal of using this cost savings as a way to encourage local employers, who understandably don’t have a good grasp of public budgets, to join their initiative. What does $100 million really look like? Fortunately, there are tactics we will employ to make that number more meaningful to reach this audience.

Finding Data Is Still a Challenge

You might understandably think that the open data movement, whereby governments and others are publishing their data in more accessible formats, has made it easier for folks locally to find the data they need. But open data portals are best at distributing data. The tools to help people initially find the data are somewhat rudimentary on open data portals. This means that people in local communities — most of whom don’t “own” the data they need —  don’t know where to begin their data search. If they want data on school fitness results, do they go to the local school district? The state department of education? The state or the county’s public health department? A federal agency? There are not road maps that point where to go, so organizations end up spending unnecessary time searching for the data they need.

But what if instead there were data navigators — for example staff in state government who could point people in the right direction? Someone who could answer queries like the one above no doubt would make it easier for those working locally to efficiently obtain useful data, allowing them to get on with the work of analysis and communication.

These data navigators, too, would be in a great position to share insights with data publishers (e.g. state agencies) on how else to release data. These data navigators may learn, for example, about the need to provide data at a more granular level — by zip code or Census tract, not by county, for example, or by other valuable breakdowns: gender, race/ethnicity, income, age, etc.

Local Communities Don’t Have Ways to Break Down Big Concepts like Equity or the Social Determinants of Health

If you work at a local level, the concepts of equity and social determinants of health are bound to come up. Yet these terms are just thrown around, as if we all know what they mean. Equity refers to inequality, or those on the fringes that are in most need of assistance, yet many audiences you want to reach may understandably think equity refers to home ownership. And the social determinants of health? That describes the concept that upstream, “root” factors, such as education, poverty or where we work, play a role in downstream impacts, like heart disease or stroke. But the words “social determinants…”, let alone the concept, is enough to make someone who’s unfamiliar, perhaps including an elected official, tune out.

Local communities need devices and simple illustrations to help explain these concepts with brevity. We can’t expect them to come up with this language on their own; it’s better if we can all borrow from the same set of explanatory tools, as the upstream-oriented organization, Health Begins, has begun to do with the social determinants and as FrameWorks Institute also has done.

Example: I’m working with one local community that recognized this challenge of unpacking impressive-sounding terms. Although their work is focused on cardiovascular disease, they need to address the complicated interrelationships that exist when addressing cardiovascular disease, including explaining the root causes of heart disease and the layered levels of inequality. They observed to me that, although they need a tool for face-to-face communication, like a slideshow, the linear nature of a presentation where you go from one slide to the next would not do the complexity of this topic justice. So we’re thinking instead about other ways to present this information and data that can better express this concept of interrelationships.

These are just a few observations that come to mind for how we collectively can help those working in the trenches with data better achieve the impact they’re after. I’m eager to hear what others think — both additional ideas for what else is needed and thoughts on how to address some of the challenges noted above. Please add comments below.

2 Comments on “Seven Ways We Can Help Local Organizations Transform Data into Impact

  1. Thoughtful piece about the nuances of data, and what to amplify, how to showcase numbers with stories, and the attendant challenges for organizations and community activists to pick through choices of data and approaches for presenting data. Nicely stated! I would have loved to have seen some data visualization examples to differentiate between a dashboard (or “placement”) one-pager vs the more complicated and overwhelming batching of data report out. The illustrations helped.

    Like

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