University of Kansas Prof. Alfred Ho recently surveyed 65 mid-size and large cities to learn what is going on, on the front line, with the use of big data in making decisions. He found that big data has made it possible to "change the time span of a decision-making cycle by allowing real-time analysis of data to instantly inform decision-making." This decision-making occurs in areas as diverse as program management, strategic planning, budgeting, performance reporting and citizen engagement.
Cities are natural repositories of big data that can be integrated and analyzed for policy- and program-management purposes. These repositories include data from public safety, education, health and social services, environment and energy, culture and recreation, and community and business development. They include both structured data, such as financial and tax transactions, and unstructured data, such as recorded sounds from gunshots and videos of pedestrian movement patterns. And they include data supplied by the public, such as the Boston residents who use a phone app to measure road quality and report problems.
These data repositories, Ho writes, are "fundamental building blocks," but the challenge is to shift the ownership of data from separate departments to an integrated platform where the data can be shared.
There's plenty of evidence that cities are moving in that direction and that they already are systematically using big data to make operational decisions. Among the 65 cities that Ho examined, he found that 49 have "some form of data analytics initiatives or projects" and that 30 have established "a multi-departmental team structure to do strategic planning for these data initiatives."
One city that has been in the forefront of the collection and use of big data is Los Angeles, which created an "open data library" with more than 1,000 datasets from different city operations. It makes many of these datasets available to the public and uses them to improve city operations. For example:
• The city's "Clean Streets Initiative" uses multiple sources of data to develop a "street-by-street cleanliness assessment system." These data are used to more effectively deploy resources by the city's Bureau of Sanitation.
• It uses crime data to identify patterns that in turn inform the deployment of social-service and law-enforcement resources.
• It uses water and energy data to identify city properties that may be wasting resources and launches efficiency audits.
Los Angeles also has developed an ambitious roadmap for the increasing its use of big data in coming years with an eye on the growing interconnectivity of data from the Internet of Things, such as energy-monitoring devices and road traffic sensors.
Big-data initiatives, Ho concludes, "provide a new platform for policymakers, key stakeholders, and individual citizens" to bring data to bear on the problems that cities face, and to do so "more holistically." The effective use of big data can lead to dialogs that cut across school-district, city, county, business and nonprofit-sector boundaries. But more importantly, it provides city leaders with the capacity to respond to citizens' concerns more quickly and effectively.
