Agencies can benefit by crunching huge data sets to improve operations and missions in a variety of ways, according to a report from the Partnership for Public Service: “From Data to Decisions III: Lessons from Early Analytics Programs,” which explains how the US Agency for International Development does so to fight famine.
USAID funds the Famine Early Warning System Network – FEWS NET, in collaboration with the US Geological Service, NOAA, NASA, USDA and UN Food
Security and Nutrition Analysis Unit, World Food Program, other organizations and regional governments to provide early warnings on food scarcity in 30 countries.
FEWS NET helps direct up to $1.5 billion a year in USAID food for peace assistance, and it does so partly with the help of a decision support system that is a mix of human analysis and software taking advantage of reams of data and scientific information.The system produces science-backed expert analysis forecasting food conditions, alerts and briefs for decision-makers in USAID’s Food for Peace and disaster assistance offices, the State Department, Congress, the White House, the United Nations World Food Network.
“Effective early warning combines a successful blend of Earth observations, hydrologic modeling, food economics, weather and climate modeling, and much more,” explained Chris Funk and James Verdin from the US Geological Survey who are quoted in the report, available here: http://ourpublicservice.org/OPS/publications/viewcontentdetails.php?id=233.
Rather than computerize all its warehoused data, the program prefers a blend of human and software analysis due to the complexity of the environments and political realities of the areas. For example, software might forecast famine conditions in Nigeria but that could be offset by substantial remittance funds from Nigerians abroad, whereas sending out a famine warning in another region could be unwelcome by a regime with a tenuous hold on power, underscoring the need to get its information exactly right.
