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.
Make sure employees can easily see and analyze the data. The lesson from grassroots-driven older projects is that managers should not overlook the payoff that comes from enabling employees to see and use data. Giving this power to employees inspires insights into their own work. Those insights can help analytics programs evolve to deliver even more mission improvement. If you solicit users’ help, be sure to implement some of their ideas and let their insights guide how the program evolves.
Track the return on investment for analytics programs. Reporting improved outcomes, such as increased early detection of food-borne illness outbreaks, is a bottom-line requirement for mission analytics programs. But just reporting better outcomes is not enough, especially now that sequestration is compelling programs to compete fiercely for scarce dollars. Agency leaders need cost-benefit metrics and measures of return on investment to prove that their data-based efforts compare favorably with other programs during budget reviews. So don’t focus on core analysis so single-mindedly that you fail to develop data to demonstrate the economic or budgetary benefit.
Collaborate with other agencies to collect data and share expertise. Save money and effort, and increase the speed of analytics adoption, by acquiring data and services from other agencies—such as collection, analysis and modeling tools. Search for existing authorities that allow you to pay for help. And when your own analytics programs can help other agencies achieve their missions, consider striking memorandums of understanding so each partner can perform the work that suits it best.
Give agency leaders clear, concise analysis. Presentation is especially important for top officials whose time and attention are limited, but whose support is vital. Data visualization—charts, graphs, maps and models—make analytical findings easier and faster to comprehend. Agency leaders can more easily absorb key findings that are condensed into tight, sharply written synopses at the top of reports, in PowerPoint presentations and at briefings. That’s especially important when the data runs counter to leaders’ instincts or requires difficult action or change. And remember: Persistence is as important as presentation, and continual reference to the data can overcome initial skepticism and emotional responses. To support data programs, senior leaders need to understand the results and how they apply to achieving the agency’s mission.
Embed data usage into the agency culture. Making analytics your standard operating procedure means building it into your organization’s culture and climate. It pervades the culture when managers at all levels use data in planning, measuring results, budgeting, hiring and running programs, and when they demand that employees’ work activities and requests are data-based as well. That requires on-the-job training in data analysis, calibrated to each unit and each employee’s role within it. Sending out data evangelists with analytics expertise to spread the news about data-driven accomplishments and possibilities can entice employees to seek training.
These are just a few ideas to effectively make use of data to improve your agency program performance. If you have further suggestions, please share your insights and experiences in the comment section below. You can also email me at email@example.com.
Tom Fox, a guest writer for On Leadership, is vice president for leadership and innovation at the nonprofit Partnership for Public Service. He also heads the Partnership’s Center for Government Leadership.