How Buffalo Broke Down Data Silos to Improve Services
Old infrastructure and departmental politics didn’t get in the way of progress in Buffalo, NY, when a popular program they call “Operation Clean Sweep” needed a big data upgrade. Instead, they broke down the data silos, integrated the data and turned a small but successful program into a much larger, and more effective one.
The program started off as a small experiment aimed at smothering some of the city’s poorest and most disadvantaged areas with services such as litter removal, graffiti clean-up, street repairs, vegetation pruned and cleared, vacant houses sealed, smoke detectors installed and more. Virtually every agency in the city would participate, sending their people to flood into the zone and providing help.
“Each agency will talk to residents about what they have to offer,” said Oswaldo Mestre, director of the Division of Citizen Services of the Office of the Mayor and the City of Buffalo 311 Call and Resolution Center in a recent article. “While we’re doing that, we’re gathering quality of life intelligence.”
It was a good program for this city during the middle part of the last decade, with roughly 7 or 8 sweeps happening a year. However, as the economy tightened, and resources dwindling, it became clear that the city would need more than a gut feeling to determine which neighborhoods needed the Operation Clean Sweep treatment the most.
They decided to turn to the data, which meant wading neck deep in departmental politics to get everyone on board. As Thor Olavsrud wrote recently, “The city’s Management Information Systems (MIS) department had to bring all the various city department heads together to break down the various departmental information silos, determining which data sets were useful and how best to express those data sets (for instance, selecting a unified way of identifying various properties).” Under the leadership of Mayor Byron W. Brown, they were able to get it accomplished, as well as get all of their departments integrated with their 311 civic issue tracking hotline.
Using the KANA LAGAN public sector CRM software, the city was able to centralize the data coming into the hotline, tracking issues, pin pointing locations, and logging data. With the departmental data integrated, and new real time information coming in via the 311 hotline, the city was able to start analyzing the data from the disparate sources, including 911 calls, poverty indicator data, census tracts, unemployment information, population density maps. The results have been transformative.
“Once we had all the data coming into one place, it made it easier to double, triple, even quadruple our efforts,” Oswaldo Mestre reported. “Having the leadership, equipment and software to bring this together has allowed us to expand the program and really add a lot of different partners. We used to do this once a month or every two weeks – we’re now doing it once a week.”
Olavsrud reports that by the end of October this year, when the Operation Clean Sweep Season ends, they will have completed 27 operations with partners volunteering 6,075 manpower hours addressing approximately 5,400 properties.
The program has been such a success, that Mestre was named a finalist in both the Constellation Research 2013 SuperNova Awards in the Data to Decisions and Next Generation Customer Experience categories.
“The use of Big Data in the public sector arena promises to be hugely disruptive, however many agencies have not yet realized its potential,” writes Constellation Research. “By extracting insights derived from the data, the City of Buffalo is using a targeted data driven approach to identifying neighborhoods most in need to direct the deployment of the appropriate resources. Pooling man power and in-kind services from federal, state and local government and community groups/non-profits, puts forward a new innovative model of an inter-department and inter-agency collaboration for cost-effective public sector service delivery.”
In the end, it’s just another example of how governments can use data to help improve the lives of its citizens. It’s hard not to look forward to seeing what other constructive uses of data bright minds in public and private sectors can come up with.