USAID Global Health adopts Tableau to improve data sharing, help people in need, and save lives
Built 100+ new data-driven applications for disparate worldwide users and teams
Empowered all organizational levels to use Tableau for 90% of their data needs
Evolved data culture from data silos to multi-level access within two years
The US Agency for International Development (USAID) integrates US foreign policy with the financial support needs of developing countries. The agency's mission is to expand democracy and free markets while improving the lives of individuals in undeveloped and crisis-ridden parts of the world. Within USAID, the Bureau for Global Health allocates over $5 billion annually to support programs that combat infectious diseases, help prevent child and maternal deaths, and control the spread of HIV/AIDS.
USAID Global Health wanted a more effective way of aggregating and disseminating the program data it had been collecting from health systems worldwide for over 60 years, in areas such as food security, child health, and pandemic threats. Due to unique data collection challenges in each of the 80 countries it served, the bureau struggled in its mission to empower front-line workers to improve health systems and outcomes through data-driven decision making and analysis. Not enough of the data was reaching the people who needed it, and when it did, the scattered nature of how it was collected resulted in a low level of trust of the data sets. USAID Global Health needed a way to collect more data and use it to its fullest potential.
By engaging local communities, among other strategies, USAID Global Health has steadily improved its data collection practices. Using Tableau, they built the Global Health Data Analytics Hub, which enables workers throughout the agency to visualize recently collected data and use those insights for the decisions they need to make. The bureau also created the enterprise-wide Data Fellowship program, which uses data from Tableau dashboards to drive shared global health initiatives like the Joint External Evaluation (JEE). The JEE dashboard at USAID Global Health assesses and scores individual countries' capacity to prevent, detect, and rapidly respond to public health risks. Using these visualizations, the Data Fellowship can recommend agency actions in coordination with other nations and groups.
The best part of Tableau has been the impact we see on the communities we serve. Data drives discussions about where we want to go, our expectations, our hopes, and the impacts we hope to have.
When it came to securing executive commitment for new data-driven resources across the agency, USAID Global Health developed hundreds of new Tableau self-service dashboards and other applications to present data in new and useful ways. To promote adoption, the bureau has pursued a data education program that helps users at all levels of technical ability achieve more in their roles and have a larger impact.
In less than two years, USAID Global Health has transformed from a data-siloed organization with limited data—and only a few expert users who used it—to an enterprise-deployed Tableau environment easily accessible to all levels of users, meeting 90% or more of their data needs. Storytelling, which used to be largely anecdotal based on field observations, is now based on solid reporting and benchmark discussions driven by high-quality, trustworthy data that's plain for all to see. In this new culture, data is a catalyst not only for organizational improvement but also for achieving positive outcomes in individuals' lives.
“Tableau lets us provide data and insights to the people who need it most,” shared Leeza Kondos, USAID Senior Data Scientist. “The better data we have, the better analytics we can perform, and the better outcomes we're able to show. The data gives us better evidence and supports better discussions with the people who implement our programs. Ultimately, it helps to produce better health outcomes, which is our goal.”
Decision makers in our headquarters talk to people all over the world, using data to drive decisions about everything from tuberculosis control and HIV, to family planning and infectious disease.