The federal government, like private industry, is inundated with data demands and susceptible to the hype that big data will improve productivity and process. However, there is evidence that the return on big data investments sometimes disappoints.
Unlike some of today's big data initiatives, federal analytics programs that began years ago had no choice but to provide and demonstrate value. My organization, the Partnership for Public Service, and the IBM Center for The Business of Government recently released a report examining some of these successful early data projects to see how they got started, what sustained them and how the data was used to improve mission-critical programs.
The report, "From Data to Decisions III: Lessons from Early Analytics Programs," analyzed efforts that started out small, asked hard questions and used data that focused on results. The report includes an look at how the Centers for Disease Control and Prevention used data analysis to sooner detect food-borne illness outbreaks and how the Veterans Health Administration was able to identify veterans most at risk of health problems and treat them without resorting to hospitalization.
Based on the experiences at these and other federal agencies, the report drew some basic lessons that could help agency leaders and program managers make use of data to achieve real value and accomplish mission goals.
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