Two years ago this fall, I provided an update on AidData’s strategic direction. I announced that, under a three-year plan called Vision 2020, our team of 30+ faculty and staff would focus its efforts on helping leading development organizations make better-informed decisions with next-generation sources of data and evidence. To this end, we prioritized partnerships with development organizations that are willing to challenge the status quo and innovate at multiple stages of their policymaking and programming cycles.
We’re now approaching the end of Vision 2020 and beginning to take stock as an organization of where we’ve had the most and least success—and why. We’ve seen many encouraging signs of take-up of our data, methods, tools, and analysis over the last two years across all five of our program areas (more on that below).
Yet much of the uptake that we’ve witnessed has been concentrated among aid agencies, development banks, and international organizations headquartered in high-income countries. So, we are beginning to think about what course corrections we might need to make to increase uptake in low- and middle-income countries.
Where are we going?
One important lesson we’ve learned is that it’s difficult to achieve lasting influence in the absence of a strong ground game and credible local partners. We are also mindful of the fact that, across the developing world, there are organizations—inside and outside of government—already doing important work to bring granular data and rigorous evidence to bear on the design and implementation of development policies and programs. So, the key question for us is how we can best support, extend, and leverage the work of such organizations.
To this end, we’re currently engaging in a year-long exercise of listening to and learning from like-minded groups in the Global South—with generous support and counsel from the Hewlett Foundation’s Evidence-Informed Policymaking team and William and Mary’s university leadership team—prior to the development our next three-year organizational strategy. We see a particularly promising set of opportunities for increased evidence uptake via strategic partnerships in Africa. We’re prioritizing engagement with leading think tanks, policy research institutes, NGOs, and networks and communities of practice on the continent. Some of the collaborative activities that we hope to pursue include the development of shared research priorities, co-generation of data products and analysis products, and co-investment in research dissemination, policy outreach, and capacity-strengthening activities.
AidData will not abandon its ongoing efforts to influence those in Western capitals who make and shape policies and programs that influence development outcomes in low- and middle-income countries. This work remains central to our core mission of producing evidence that helps policymakers and practitioners more effectively target, monitor, and evaluate sustainable development investments. But we want to devote more time and money to decision-makers on the ground in the developing world, because a growing number of consequential decisions about development policies and programs are not being made not in places like Washington, D.C. and Brussels, but rather in places like Abidjan and Kampala.
This would not represent a seismic shift for AidData. Since 2012, we’ve had a near-continuous presence on the ground. We’ve co-created decision support tools with Zambia’s National AIDS Council and Côte d'Ivoire’s Ministry of Health; strengthened the aid information management capacities of 6 African finance and planning ministries (in partnership with Development Gateway); deployed dozens of AidData summer fellows to work alongside CSOs, universities and think tanks in East Africa and West Africa; and organized hackathons with the Resilient Africa Network for local innovators interested in novel development data applications. However, it would represent an effort to redouble and recalibrate our organizational commitment to data and evidence use in the Global South.
If you are working for an organization that has pursued or is considering a similar strategic direction, we’d love to hear from you. My colleagues and I have already benefited from conversations with USAID, 3ie, CEGA, ODI and IDInsight, but we’re keen to hear from other organizations that are active in this space.
You can connect with us via Twitter (@AidData) or write to me directly at bparks@aiddata.org.
Where have seen uptake thus far?
Over the last two years, we’ve seen lots of encouraging signs of uptake of our data, methods, tools, and analysis over the last two years. Here are some examples from our five program areas:
- Listening to Leaders (LTL): We’ve seen our leader feedback data and analysis used in USAID’s 2018 Education Policy; the UNDP Administrator’s 2019 address to the UNDP Executive Board; a design proposal for the creation of an International Finance Facility for Education; the performance measurement efforts of IFAD, the Multilateral Organization Performance Assessment Network (MOPAN), the World Bank’s Public Opinion Research Group; and a TAI Guidance Note for funders on Improving the Design and Effectiveness of Investments in Governance Data.
- Geospatial Impact Evaluation (GIE): We’ve seen our GIE methods taken up across a wide variety of organizations, countries, sectors, and programmatic contexts, thereby helping to fill a “missing middle” in development program evaluation. USAID used GIE methods to evaluate a $900 million rural roads program and a $104 million municipal governance program in the West Bank and Gaza, a $25 million irrigation infrastructure program in Afghanistan, and an $80 million food security program in Malawi. Meanwhile, the Millennium Challenge Corporation (MCC) commissioned GIEs of road investments in Ghana and Tanzania; the Global Environment Facility (GEF) completed a portfolio-level GIE of 202 projects that sought to slow, halt, or reverse land degradation; the World Bank’s Independent Evaluation Group used GIE methods to rigorously evaluate a $500 million insecticide-treated bed net distribution program in the DRC; and the German Development Bank (KFW) completed a long-run GIE of an indigenous land demarcation program in the Brazilian Amazon. We’ve also seen evidence of institutional mainstreaming of GIE methods. USAID, for example, published an official guidance note on long-run impact evaluation methods, featuring GIE as a methodological innovation that the organization should use to track post-program impacts. Similarly, the Government of Sweden’s Expert Group on Aid Studies (EBA) commissioned a report on the utility of GIE methods for evaluating Swedish aid programs, while the World Bank created a Wiki for M&E specialists who wish to use various GIE-related tools in their own work.
- Sustainable Development Intelligence (SDI): We’ve engaged with education and health ministries — in Zambia, Uganda, and Côte d'Ivoire — to advance the “no one left behind” agenda by facilitating better geographic and demographic targeting of sustainable development investments, and these efforts have borne fruit. For example, in Zambia, we’ve influenced how budgetary resources are allocated in the health sector by working with two Lusaka-based organizations—Akros and BlueCode—to redesign the health management information system (MIS) for the National AIDS/HIV Council (NAC). When we first launched our DREAMS project in Zambia, approximately 500 implementing partners were manually entering data into the NAC-MIS, none of which could be disaggregated by age, gender, or location, or visualized. Only half of implementing partners were reporting into the system, with a 30% field completion rate. By the end of the program, 86% of implementing partners were reporting into the system (via digital data entry), and the field completion rate had increased sharply—from 30% to 90%. These data can now be disaggregated by age, gender, and location, as well as visualized—helping make the NAC-MIS more responsive to the needs and preferences of local decision-makers and bringing more granular data to bear at the targeting and planning stages of the programming cycle in Zambia’s health sector.
- Geospatial Data and Tools (GEO): In 2017, we launched GeoQuery, a spatial data integration platform that enables individuals and organizations without significant computing power or data science expertise to freely find and aggregate georeferenced data on development investments and outcomes into simple-to-use spreadsheet files. Since that time, GeoQuery has fielded over 12,500 requests for customized datasets from more than 3000 users across approximately 880 organizations worldwide. These organizations include Oxfam, World Vision, IPA, USAID, the State Department, and the IMF, among many others. In parallel, we’ve helped cultivate a next-generation cadre of development professionals who can use spatial data in their day-to-day program design, monitoring, and evaluation activities through a targeted set of training and capacity-strengthening activities at the French Development Agency, the World Bank, the Global Environment Facility, the Green Climate Fund, and the Norwegian Agency for Development Cooperation.
- Transparent Development Footprints (TDF): We’ve influenced the policy conversation about China’s role in the global development finance market—by publishing detailed and comprehensive data on Beijing’s vast portfolio of overseas grants and loans, and showcasing cutting-edge research on the effects that these underreported financial flows have on economic growth and inequality, governance and corruption, environmental degradation, and public opinion. Our data and analysis has regularly featured in elite media outlets—such as The Washington Post, The New York Times, The Financial Times, CNN, The Economist, and The Wall Street Journal—and in multiple sessions of congressional testimony from experts and organizations across the board. We’ve also seen some preliminary indications that we’re beginning to move the needle inside the Chinese Government and several of its organizational peers and competitors.
