Is Bad Data Costing Philly Millions?
When governments collect bad data, it isn’t just a headache for bureaucrats and taxpayers. It can also cost states and cities millions of dollars. Take California, where workers in the Controller’s Office incorrectly recorded eight hours of leave as 80 and even 800 hours time and time again, adding up to $6 million worth of mistakes. Or Oregon, where an employee error led to a contractor receiving a check for $1,748,304.24, although it was supposed to get just $323.88.
California and Oregon aren’t alone. We may live in the age of Big Data, but a new report by Governing found that governments throughout the country still collect reams of shoddy data:
In a Governing telephone survey with more than 75 officials in 46 states, about 7 out of 10 said that data problems were frequently or often an impediment to doing their business effectively. No one who worked with program data said this was rarely the case.
In case you’re not convinced that crappy government data can impact your life, consider what happened right here in Pennsylvania when the Department of Environmental Protection screwed up while collecting fracking data:
In 2012, the secretary of environmental protection in Pennsylvania told Congress that there was no evidence the state’s water quality had been affected by fracking. “Tens of thousands of wells have been hydraulically fractured in Pennsylvania,” he said, “without any indication that groundwater quality has been impacted.”
But by August 2014, the same department published a list of 248 incidents of damage to well water due to gas development. Why didn’t the department pick up on the water problems sooner? A key reason was that the data collected by its six regional offices had not been forwarded to the central office. At the same time, the regions differed greatly in how they collected, stored, transmitted and dealt with the information.
Dave Yost, Ohio’s state auditor, went so far as to tell Governing, “The poor quality of government data is probably the most important emerging trend for government executives, across the board, at all levels.”
In Philadelphia, sloppy data causes problems all the time: City Controller Alan Butkovitz issued a report earlier this year that accused the Department of Licenses & Inspections of keeping outdated records on dangerous, vacant buildings. The Philadelphia Prison System lost countless records prior to 1991 due to water damage, which has led to maddening legal troubles for former inmates. And the city’s poor data maintenance means that it can’t prove whether tax breaks for dozens of nonprofit-owned properties are justified or even provide an accurate tally of vacant properties in Philadelphia.
This comes at the same time that governments are talking about — and relying on — data more than ever before. Cities such as San Francisco, Los Angeles and, yes, Philly, have a chief data officer. Among Mayor Michael Nutter’s chief accomplishments are creating a new data governance structure, hiring lots of smart, young data geeks, and harnessing data to make policy decisions. The city releases a new, juicy data set seemingly every other week, and the Philadelphia Police Department has successfully driven down crime by turning cops into data scientists.
So what’s going on? Why is there still so much unreliable data in Philly and beyond?
Governing found that problems often arise “in small units of government — those with inadequate IT skills and very decentralized agencies that are heavily reliant on local administration of state services.” The magazine also wrote that siloed departments, old technology, poor equipment and untrained employees can lead to bad data collection. Plus, “In many agencies … it isn’t a question of good or bad data. There isn’t any usable data being collected at all.”
Philadelphia definitely has a lot of these problems: siloed agencies, ancient tech, ailing equipment. The good news is that it is working to address some of these issues. Philly’s new land bank, for instance, is supposed to bring together data from a host of different departments that usually never interact; plus, the city has invested in technology upgrades in some problem departments in recent years.
But it’ll be up to the city’s next mayor — presumably Democratic nominee Jim Kenney — to really get the city’s data up to snuff. He says he wants to keep Philadelphia’s chief data officer, continue to release public data, set aside money for technology improvements, and break down silos in city government. That’s a start. But he’ll have to put all that into action, as well as probably retrain employees, to ensure a $6 million mistake isn’t happening here in Philly.