December 14, 2022
At a Glance
Organizations can define strategy and boost systems impact with the right investments and tools.
Most small organizations are lucky if they have even one or two people with the technical capacity and responsibility to collect, manage, and report data, let alone craft the story that data tells. Even if an organization has a dedicated data team, team members generally have other responsibilities—managing projects and seeking new clients, for example—all of which means that if your data team frequently looks stressed, it’s probably because they are juggling a lot of requests, each with their own “can’t miss” deadline, and they are the only ones with the expertise to get things to the finish line.
In two prior data blog posts, we’ve shared how the 14 organizations that make up the Building Equitable Pathways (BEP) community are centering people in their data practices, as well as serving as both translators and advocates. In this post, we call out gaps in our capacity to do what we aspire to do with data as a field. But this post isn’t simply about a change in how much we invest in data capacity, but about reevaluating the primary work that data teams do. As one BEP partner said, in a comment that resonated with many in the community of practice: “Our data ambitions as an organization are completely misaligned with our data capacity to execute on those ambitions.”
Data teams are uniquely positioned within an organization to drive strategies addressing racial inequities. Data is instrumental in informing organizations on equity gaps and opportunities for impact in their communities, especially those impacting Black students, Latinx students, and students experiencing poverty. Consistently, we heard from BEP community of practice members that if intermediaries are to improve their impact, they must solve for how they prioritize data use and data organizational capacity.
Data is of minimal use if it’s not driving strategy internally and externally, informing local stakeholders, and shaping policy with an eye toward systemic change.
Aligning Goals and Capacity
Data is of minimal use if it’s not driving strategy internally and externally, informing local stakeholders, and shaping policy with an eye toward systemic change. Organizations must consider what they want from their data teams. If the answer goes beyond data collection to sophisticated analysis and storytelling, then organizations will need to find ways to prioritize accordingly. Philanthropic and government organizations should ensure that they provide sufficient capacity for data work and related efforts—being mindful of what requests are made and providing funding for data collection and analytical support to ensure that systems-building steps are strategic. What if, with better data capacity, we could better plan backward from the impact we seek to the changes we can make in our immediate work, using data as lights along the way?
Below, we summarize the BEP intermediaries’ reflections about how they’ve structured and deployed their small data teams and what they might ideally do to track, interpret, and message urgent equity goals.
Taking Stock of Data Capacity
Small, scrappy BEP data teams are constantly caught up in urgent requests for new reports and analyses of program data from stakeholders. Public officials question success outcomes and ask for evidence, reporters ask for costs per student, and funders need answers for their reports. And only the data team has the tools to tell the real story. Meanwhile, intermediaries are working with youth, educators, employers, and policymakers who need help leveraging data to make informed decisions and advance equitable outcomes.
Within our community of practice, most organizations reported having a “team” of one or two data staff. We asked them how they spend most of their time:
- Data teams spend the majority of their time collecting data, extracting data, then analyzing and preparing data for various requests, most of them from funders and external stakeholders, most with specific deadlines.
- Data teams spent variable time managing data access and security and also on program evaluation, development of logic models and metrics, and tracking grant requirement metrics and activities.
- They spent the least amount of their time helping stakeholders interpret data, helping stakeholders understand inequities that may be at play or opportunities for more equitable outcomes.
Data teams want and need to perform each of these functions well. Responsible data management and responsible data use and application go hand in hand. But each function demands access to different sources, skills, and technical capabilities. As currently structured, the data teams spend the least time doing what is arguably their most important function—informing and persuading stakeholders and the public with powerful actionable information.
Sometimes the solution is not about having 'more data' but instead about how to best deploy the data you have.
Investments in Data
Data teams can think big. They want and need to have time to reflect with their project leads on data’s influence on their ultimate impact—how data is displayed, communicated, and how it can inform local, state, and even national change regarding equity goals.
Most organizations reported that the data functions within their organizations are funded primarily through philanthropy, with federal funding coming in second. The BEP organizations agreed that increased funding for additional data staff is important, but equally important may be investments in data-focused professional development for staff who are not strictly assigned to working on data, in tools that automate and speed up data cleaning and analysis, and in dedicated organizational capacity to share and use data with external partners. These additions would allow organizations to conduct stronger analyses and convey those more effectively with youth, educators, employers, and policymakers in ways that build trust and prompt action. One BEP partner put it bluntly: with increased data capacity, “we would be proactive in the information we provide, supply context, be able to reach out to stakeholders and support their needs, teach, [and] engage in larger projects to shape policy.”
Sometimes the solution is not about having “more data” but instead about how to best deploy the data – and data resources – you have.