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Beyond the Buzzwords:  What is “Data Science for Social Impact,” and why does it matter? 

By Jenrose Fitzgerald, program coordinator; Dan Ferris, assistant professor of practice; Katie Ragsdale, research assistant; and Joseph W. Roeder, research assistant.

Data science. Data maturity. Data governance. Data-driven decision-making.  

Much has been written in recent years about the need for nonprofits and other social impact organizations to become more data-informed. When entering conversations about the importance of data, however, we are often confronted with unrelatable
jargon. Data Science for Social Impact is a growing field of practice focused on building data fluency in the social sector. To do this well, it is necessary to move beyond the buzzwords and get to what actually matters.  

Social sector organizations can increase impact, both individually and collectively, by being more strategic in how they engage with data. Data Science for Social Impact (DSSI) is a framework designed to help organizations think broadly about how to utilize data to advance their missions, increase impact, and promote equitable outcomes. The Social Policy Institute and its advisory committee are developing a set of free programming opportunities for social sector organizations in the St. Louis region seeking to build capacity in these areas. There is no one-size-fits-all approach, but rather a range of processes and practices for individuals and organizations to consider as they grapple with complex challenges in their communities.  

Not Just for “Data People” 

One way DSSI stands out from other efforts to build data capacity is that it is re-imagining and expanding who we typically think of as “data people.”  People enter the conversation from many different vantage points and levels of fluency around data, from data analysts to frontline workers to project managers to program participants. Indeed, in order to have robust conversations about effective and equitable data strategies, we need to redefine who are data people. The goal of the DSSI initiative is to provide a space where people can join the conversation from wherever they are—and that starts with using accessible language.  

At a recent DSSI Advisory Committee meeting, colleagues highlighted a proposed event title that centered on the term “data maturity.” Some found it unrelatable, noting that if they saw the title, they would think the event was not for them. This was an important moment for our team. If the language didn’t resonate with social sector leaders actively engaged with us in thinking about data for social impact, surely others would have a similar response. The roundtable was reframed, and we resolved to think more deliberately about ways to minimize jargon in our materials while still creating shared language for this work.  

One of our key partners, Paul Sorenson of the St. Louis Regional Data Alliance (RDA), modeled this value at a subsequent roundtable event. “We were careful not to put data governance in the title of this session lest most of you would probably be like, I’m not giving up my Friday morning for that,” he said.  

He went on to unpack the term data governance, which refers broadly to a set of policies and rules that guide how organizations share, store, use, and protect data. “Really what we’re talking about is how do we come together around all sorts of things, including data policy and data practice.” 

While technical compliance with such rules is vital, Sorenson also insisted on the importance of two critical overlooked questions in conversations about data use: Who benefits, and who decides? Sorenson introduced the concept of community data governance as a way to move beyond technical and legal considerations and ensure that there is an equitable process in place for making decisions about data.1  While the terms themselves are less important than the spirit in which we approach the work, building this kind of shared language can be useful in shaping conversations around data for social impact. 

Centering Equity  

Of course, the above example is about more than shared language—it is also about shared values. Data maturity and data governance are useful concepts but don’t inherently speak to values such as promoting equity or centering community voice. As we engage in collective dialogue about using data to increase impact, we have an opportunity to do so in a way that upholds and highlights these values.  

At one event, for example, Esther Shin of Urban Strategies, Inc. discussed the importance of disaggregating data to achieve equitable outcomes. She provided examples of times when organizations failed to recognition disparate impacts of their programs because of the way they were collecting and reporting their data. “If you’re not disaggregating the data and developing strategies that are targeted towards … systemic issues, then you end up actually not helping the individuals that are at the greatest need of being served,” Shin explained. 

At another event, Riisa Rawlins-Easley of the St. Louis Regional Health Commission discussed strategies for addressing inequities in health care by bringing diverse stakeholders to the table when making decisions about what data is collected, and how those who are represented in the data are engaged and impacted in the process. “We want our stakeholders to see themselves in the data,” she said. “We want them to understand what they’re reading we want them to understand why it’s important why they care and what to do about it… It requires us to be bold and to take risks to include non-traditional voices in the conversation.” 

To this end, with the guidance of our advisory committee, we are committed to integrating equity and community across all DSSI events and materials. We want to provide a framework that helps organizations think not only about increasing impact, but also about strategies for engaging community in decision-making around data, and for promoting equitable outcomes. The roundtable series mentioned above provided some insights into how social sector organizations in St. Louis and beyond are grappling with these challenges. 

The DSSI fall roundtable series provided a great opportunity to engage with these and other social sector leaders who think critically about how to utilize data in ways that increase impact while centering community and promoting equitable outcomes. You can learn more about the roundtables and key takeaways from those conversations here

Join the Conversation 

Throughout 2022, we will host a series of learning events that build on this momentum and provide space for continued dialogue about best practices for doing this work. Whether you are just getting started or have been thinking about using data to increase impact for a long time, we hope you will join the conversation.  

Data Science for Social Impact is an initiative of the Social Policy Institute at Washington University in St. Louis, supported by Mastercard Center for Inclusive Growth and in collaboration with an advisory committee, the St. Louis Regional Data Alliance, and data.org.


1 For a more technical overview of this concept as it relates to the work of the St. Louis Regional Data Alliance, you can read their recent white paper on how healthcare and social service organizations connect to each other and share data.