Collaborating with data for America's communities
Last week, the Urban Institute and the Federal Reserve Bank of San Francisco released What Counts: Harnessing Data for America’s Communities, a book of short, accessible essays and a website. What Counts helps answer some of the major questions raised by the prior volume in the series, Investing in What Works for America’s Communities, namely “how do we tell what is needed, what could work, and what is actually working?”
The launch event brought together many of the book’s authors and editors for a discussion with an in-person and virtual audience. This is the second of three posts about that discussion—read the first one here.
The power of collaboration
One of the underlying themes of What Counts, as of What Works, is the importance of bringing together public health and community development. The Healthy Communities Initiative of the Federal Reserve Bank of San Francisco has focused on the “social determinants of health”— how a community’s resources and connections are critical determinants of individual, family, and community health. The Robert Wood Johnson Foundation, a supporter of What Counts, has been a major proponent of the need for collaboration to build healthy communities.
At the launch event, David Fleming of Public Health-Seattle and King County tied this collaboration of public health and community development more directly to the data theme of What Counts.
Fleming noted that both community development and public health must rely on “dirty data,” rather than the purity of academic-level data. In both fields, randomized controlled trials are unlikely and ultimate desired results can take a long time to materialize, so it is critical to gather data on near-term outcomes that indicate whether strategies are on the right track and to use these data to make needed course corrections.
Data, Fleming said, give credibility and are powerful tools to elevate problems in public discourse and with policymakers. Noting that community development generally happens at the neighborhood level, Fleming called for neighborhood health reports, describing county and larger geography assessments as “useless” for community development purposes.
Using a different lens on collaboration, Victor Rubin of PolicyLink focused on collaboration within a region to take a systemic approach to promoting equity, citing PolicyLink’s work on the Fair Housing Equity Assessment. Effective regional coordination requires that partners be encouraged to think regionally, and to link their local stories to what is happening in the region in areas such as transportation and land use planning.
Like other types of collaboration, such as the communities of practice PolicyLink has developed in connection with the Promise Neighborhoods program, regional collaboration requires both trust among partners and commitment to furthering the work of the group.
Creating the data ecosystem
Discussing the work the MacArthur Foundation has supported in Chicago and beyond, Alaina Harkness stated that foundations need to invest in the capacity of organizations to use data to design and enhance programs and outcomes, not just for evaluation.
It is also critical to understand the ecosystem within which data is provided and used. Who are the players? What data do they have? What and how will they share? How do they connect? What is missing? As part of this ecosystem, foundations themselves need to spread what they are learning from field to field, and encourage a culture of sharing.
But, the panel was asked, could all these available data somehow enhance inequality rather than build equity? Harkness responded that this was indeed a risk, which highlighted the importance of equity in access to data on multiple dimensions, including price and speed. She also urged attention to the ethics of data sharing.
The Treasury Department’s Amias Gerety encouraged those working in community development to not be intimidated by the data and systems problem they face. Residents of low- and moderate-income communities are competent and eager users of technology, and the commercial activities of the last 10 years have made vast improvements in the systems available for everyone’s use. There are many tech-savvy organizations in existence whose purpose is to help community development organizations solve difficult problems.
Nevertheless, establishing and maintaining a robust data ecosystem to support community development is expensive, and because (like much infrastructure) it is often invisible, it is hard to attract investment. Responding to this problem, all the speakers stressed the need to make data indispensable to a wide range of users, who then become advocates for both existing and improved systems. This requires those providing the data to keep up with consumer expectations about the format, frequency, and speed with which data will be delivered.