Publications

    BenePhilly, City of Philadelphia: Innovations in American Government Award Case Study

    Betsy Gardner, January 2022 

    The American social safety net exists to meet needs for: unemployment assistance, supplemental money for food, help with health care costs and medical expenses, and more. However, the process of signing up for these services is often time-consuming, confusing, repetitive, and frustrating.

    To address these challenges, the Philadelphia-based nonprofit Benefits Data Trust (BDT) developed BenePhilly, in partnership with the City of Philadelphia and the Pennsylvania Departments of Aging and Human Services, to inform people of their eligibility for benefits and assist them in quickly and efficiently enrolling. This paper is a case study of the BenePhilly program and will serve as a guide to replicate its success. By using proven, data-driven methods, the program connects high-need, eligible individuals with up to 19 different benefits, all while reducing overall poverty, providing a better application experience, and increasing trust in local government.

    BenePhilly is a network of government agencies, nonprofits, and community-based organizations connecting Philadelphians to benefits through targeted, data-driven outreach, referrals from a network of organizations, and in-person and telephone application assistance. The trained staff at both BDT and the nonprofit organizations embedded in the communities they serve help individuals easily find and enroll in benefits. According to BDT’s Chief Strategy Officer Pauline Abernathy, BenePhilly has helped more than 125,000 Philadelphia residents secure over $1.6 billion in benefits as of January 2021.

    Bloomberg Harvard City Leadership Initiative, July 2020 

    Dr. Josh Sharfstein, Vice Dean for Public Health Practice and Community Engagement at Johns Hopkins Bloomberg School of Public Health, provided a briefing of critical public health information on COVID-19 within the United States and guidance on how to safely reopen schools. Juliette Kayyem, the Senior Belfer Lecturer in International Security at the Kennedy School, addressed mayors on strategies for effective communication in the midst of a complex and evolving crisis, contradictory or unreliable information, and a constantly shifting operational environment. The session was moderated by Harvard Business School Professor Rawi Abdelal, the faculty co-chair of the Bloomberg Harvard City Leadership Initiative.

    Randall K.Q. Akee, Eric C. Henson, Miriam R. Jorgensen, and Joseph P. Kalt; May 2020 

    Title V of the CARES Act requires that the Act’s funds earmarked for tribal governments be released immediately and that they be used for actions taken to respond to the COVID‐19 pandemic. These may include costs incurred by tribal governments to respond directly to the crisis, such as medical or public health expenditures by tribal health departments. Eligible costs may also include burdens associated with what the U.S. Treasury Department calls “second‐order effects,” such as having to provide economic support to those suffering from employment or business interruptions due to pandemic‐driven business closures. Determining eligible costs is problematic.

    Title V of the CARES Act instructs that the costs to be covered are those incurred between March 1, 2020 and December 30, 2020. Not only does this create the need for some means of approximating expenditures that are not yet incurred or known, but the Act’s emphasis on the rapid release of funds to tribes also makes it imperative that a fair and feasible formula be devised to allocate the funds across 574 tribes without imposing undue delay and costs on either the federal government or the tribes.

    Recognizing the need for reasonable estimation of the burdens of the pandemic on tribes, the authors of this report propose an allocation formula that uses data‐ready drivers of those burdens.  Specifically, they propose a three‐part formula that puts 60% weight on each tribe’s population of enrolled citizens, 20% weight on each tribe’s total of tribal government and tribal enterprise employees, and 20% weight on each tribe’s background rate of coronavirus infections (as predicted by available, peer‐reviewed incidence models for Indian Country).