With new computers and software enabling the ability to store and analyze data faster and at a lower cost than ever before, it’s all too easy for federal leaders to become overwhelmed, so much so that many are failing to tie that data to specific mission-focused goals.
But as agencies grapple with harnessing the potential of big data in the future, they would be wise to look to the past -- to an era before sophisticated data-collection technologies existed and federal analytics programs had no choice but to use data to provide and demonstrate value, according to a new report by the Partnership for Public Service and the IBM Center for the Business of Government.
The report, “From Data to Decisions III,” mines programs like the Center for Disease Control and Prevention’s PulseNet, a database that was developed in 1996 to connect foodborne illness cases to detect outbreaks, and a 2003 biometrics program at the Defense Department, to offer valuable lessons for agencies in how to apply data-based analysis to improve mission delivery and performance.
“Federal agencies, like companies, are susceptible to the deafening hype about how big data will improve productivity and process. But evidence is beginning to show that the return on big data investments to date is less than promised,” the report states, pointing to recent research by Wikibon that found that big data’s return on investment is currently just 55 cents on the dollar, far less than predictions of $3 to $4 for every dollar invested over the next three to five years.
Older analytics programs at agencies offer lessons in making analytics a default approach for accomplishing an agency’s mission, according to the report. Agencies, for example, should collaborate with other agencies to collect data and share analytics expertise, which could save money, improve productivity and increase the speed of analytics adoption.
In the age of budget cuts and sequestration, agency managers also must develop data to effectively demonstrate return-on-investment and give executives clear analysis and results they can use to support data-driven programs. Encouraging data use among employees and providing them with targeted on-the-job training also can help agencies make data analytics a standard operating procedure and an important piece of an agency’s culture and climate, the report states.
“What early data users didn’t do was consciously set out to use big data,” the report states. “Instead, they asked hard questions and sought data to answer them . . . Those questions and others propelled these users to collect and analyze data, which then became standard operating procedure and helped their programs evolve.”