Even the most competent, tech-savvy civil servant is susceptible to data distraction, when one examines data for better managing an existing process without first clearly identifying the problem to be solved and whether the existing approach needs to be re-thought entirely.
As San Francisco's tax collector, Cisneros is very experienced in using data to chase down those not paying what they owe. But recently he's found that his job isn't so straightforward, coming to the conclusion that "fines and fees that exceed people's ability to pay them are often a lose-lose" for both government and people. His goal has shifted from simple collection to a more nuanced measure of success: to help fine- and fee-owing San Franciscans retain their jobs and avoid jail to increase the number of employed, tax-paying citizens while reducing inequities. Cisneros examined debts concerning towing, driver's license suspensions, child support, water shut-offs and more and found that fine and fee reductions often resulted in more revenue, not less.
Identifying the right problem to be solved as a threshold step makes a big difference. Data distraction is easy to fall into because each data stream, whether for tax collection, workforce information, 311 service requests or traffic patterns recognized by street-embedded sensors, opens so many insights that were previously inaccessible -- so many that they can obscure larger, underlying issues whose solution might need a different approach altogether.
Take, for example, the issue of flooded streets. The flawed, data-first approach would merely generate ways to more quickly close streets and pump water. A more fundamental examination would analyze maintenance patterns concerning clogged drains, types of grates on the sewers, tree foliage and weather reports to discover better ways to address the problem. Using a problem-first approach, a motivated employee or innovation team would work across city agencies to combine datasets and map flood risk around the city in real time to not only efficiently deploy relief but also prevent flooding in the first place.
Placing the problem front and center requires cross-agency collaboration and a broad examination of the underlying issues. Cities need to identify a person or office to nudge other officials to consider bigger questions and to advocate data sharing. Individuals located in different places within government should be able to easily access information from other agencies and integrate it into their workflows.
Breakthroughs begin with someone willing to challenge underlying assumptions and work across agencies to consider novel approaches to old problems. Data can obstruct or enlighten. It either narrows thinking or broadens the horizon for new solutions.
Cities across America and around the world are working to find new ways to discover and address civic problems and improve public services through the integration of data into governance. Best practices, promising case studies and the work of top innovators from government, industry and academia are the focus of Data-Smart City Solutions (https://datasmart.ash.harvard.edu/), a continuing project of the Harvard Kennedy School's Ash Center for Democratic Governance and Innovation. And for more on the subject from Stephen Goldsmith, follow him on Twitter at @GoldsmithOnGov.
