Judged on the basis of U.S. Census data, swaths of Detroit would seem to be too poor to support much in the way of retail development -- a situation repeated in cities across the country. Social Compact, a 16-year-old nonprofit organization has been steadily working to correct such misperceptions, applying advanced data-mining and analysis techniques to spur urban development.
Using software from SAS and its DataFlux subsidiary, Social Compact researchers gather data from a broader range of sources than has often been used, including departments of motor vehicles, credit, mortgage and other financial histories, and utility records. All of the data is stripped of personal information that would identify specific people, but it is linked to individual neighborhoods. Citigroup is working in partnership with Social Compact, supplying analytics and depersonalized and aggregated data, as well as financial support.
Such partnerships are at the core of how Social Compact, which is based in Washington, D.C., is able to obtain and then analyze data that is much more complete and accurate than information from government and other sources. The organization's mission draws on the belief that "community development can no longer depend on public investment to succeed," that it must rely on public and private sector partnerships," Social Compact CEO John Talmage, says.
Doing that, using data to look at neighborhoods in nine cities and the entirety of three others, Social Compact has found 850,000 people who were not counted in the most recent Census in 2000, he says. By the end of next year, the organization's data-mining and analysis could boost that number to as many as 3 million people in just parts of 30 U.S. cities, "representing $80 billion in unrecognized household income."
With remarkable understatement, Talmage adds, "so the numbers are very large."