Sustainable Development Intelligence

SDI

Better aid targeting to ensure that no one is left behind

We help our partners improve how sustainable development investments are targeted — geographically and demographically — in order to translate resources into results for everyone.

We develop cutting-edge methods to pinpoint with greater accuracy which (vulnerable) groups of people stand to benefit most and least from specific development investments. We also monitor progress over time within these disadvantaged localities and demographic cohorts to ensure that no one is left behind.

Using these ‘last mile’ targeting methods, we help international development organizations more efficiently allocate resources to hard-to-detect pockets of need and opportunity.

Tracking Financing to the SDGs: Track and analyze all-source financing to the Sustainable Development Goals

Achieving the Sustainable Development Goals (SDGs) requires mobilizing resources from a variety of sources, including international partners, domestic budgets, foundations and philanthropy, as well as the private sector. Better data on these diverse financial flows will be key to achieving the SDGs, allowing decision makers to view progress on financing sustainable development from multiple angles.

To gain a clearer picture of SDG funding, AidData is spearheading a new methodology to track, integrate, visualize and disseminate all-source financing for the SDGs. AidData is also working directly with in-country stakeholders to help policy-makers use these data to effectively allocate resources, crowd in funding, and hold each other accountable for achieving national priorities and global goals.

No One Left Behind: Track and analyze development investments targeting vulnerable groups

In 2015, AidData developed a rigorous methodology to pinpoint with greater accuracy how different groups of people benefit from specific development investments.The No One Left Behind (NoLB) pilot project focused on tracking and analyzing financing for development allocated to people with disabilities, and we are are are currently adapting and extending the methodology to focus on different vulnerable groups.

The NoLB methodology was designed to be easily customizable for deeper analysis of funding trends by vulnerable population, development partner, and/or geographic location. The level of specificity of analysis can range from a quantitative scoping of donor commitments (illuminating investment trends and gaps); deep dives into results and outcomes (monitoring implementation and consumer feedback); and/or examination of best practice through in-depth country case studies and qualitative analysis to determine best practice recommendations.

Decision Support Tools: Help policy-makers use data effectively to improve decision making and resource allocation

Decision Support Tools (DST) help lower the barriers to entry for domestic policymakers and development partners to access and use timely, comprehensive, and disaggregated data to pinpoint at-risk communities and allocate limited resources more effectively.

Our DREAMS project in Zambia and Uganda is developing a DST to give local decision-makers a holistic view of the HIV/AIDS epidemic at the subnational level among different populations, such as young women and adolescent girls. The DST will support planning, implementation, monitoring, and evaluation through leveraging and layering geospatial information -- from upstream investments in HIV/AIDS prevention and treatment to intermediate project results and HIV/AIDS incidence and prevalence rates by sub-population. The tool aims to break down data silos, transform data into actionable insights, and improve targeting of investments to increase the resilience of young women and girls in fighting the spread of HIV/AIDS.

Natural Resource Concessions: Measure the impact of the extractives sector on sustainable development

In 2016, AidData launched a project to analyze the effects of natural resource concessions on economic growth in Liberia, and we are currently working to estimate the sustainable development footprint of the extractives sector in a variety of country contexts.

Better data can shed light on the extractives sector’s overall contribution to socio-economic and environmental outcomes and the relationship to a country’s institutional environment and distribution of resources. In addition to leveraging geospatial tools to analyze the subnational impact of extractive sector investment, we also help local stakeholders better utilize data on these activities to monitor their impact on the country’s environment and economy.