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Better Government through Better Metrics

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Richmond Mayor Dwight Jones wants to tackle the city’s entrenched poverty, and he wants to do it by investing smartly in community revitalization efforts. The big question is, what works?

Supporting job training might seem a logical way for the city to lift people out of poverty. But what good is job training if poor people can’t find jobs near where they live? Perhaps the city should try to stimulate job creation in poor parts of town. But what if job creators don’t want to do business there because the crime rate is too high? And around it goes in circles…

Poverty is not a simple problem and there are no simple solutions. What’s needed, says Andreas Addison, a management analyst in the city’s chief administrative office, is to view the city as a complex system, develop metrics to identify and track the key drivers of change and understand how the pieces interconnect. Then the city can invest its finite resources with greater confidence of positive results.

Creating a Smarter City Decision System is one of the key recommendations coming out of a IBM Smarter Cities Challenge project with the City of Richmond undertaken last month. Richmond was one of seven localities in the United States, and 32 worldwide, to win free IBM consulting services and technical assistance.

Richmond asked IBM to help devise a way to create economic opportunity in targeted neighborhoods. IBM flew in a team of experts from around the country, and Addison acted as the point man, setting up 33 meetings with 38 people over seven days. The result is not another anti-poverty plan. The product is, in essence, a plan for creating a plan. It starts with collecting good data in order to make informed decisions.

The consultants recommended the creation of metrics in five key areas:

  • Poverty cycles
  • Neighborhood vitality
  • City government
  • Workforce development and education
  • Jobs

The city can map zoning, the location of businesses, population density, crime, vacant properties, tax revenues, tenancy vs. home ownership and dozens of other variables. “We have a lot of data but we haven’t connected it together,” says Addison. The Smarter City Support System will help do that. He says he would like the city to be able to build scorecards, or statistical profiles, of some 126 neighborhoods and, through social-scientific analysis, identify the key levers.

The Church Hill area north of Broad Street makes a fascinating case study. Gentrification has created a critical mass of customers capable of supporting local retail and service businesses — enterprises that can provide jobs to the poor inhabitants in the area. From a job-creation perspective, gentrification is a good thing. But gentrification increases property values and taxes, which puts financial pressure on poor homeowners. Good metrics can lend insights into how those dynamics might play out in a particular neighborhood. How many gentrifiers does it take to spark business and job creation? What’s the impact on the neighbors? Specifically, what is the ratio of tenants to home owners? Tenants can relocate fairly easily; home owners have more to lose from rising housing prices and tax assessments.

Those are the kinds of questions that Addison is asking right now. The IBM team will return in August with detailed recommendations on which metrics to collect, how to align stakeholder groups around neighborhood revitalization and which social enterprise business models — like urban garden co-ops — might make sense.

Mayor Jones summed it up in a city press release: “This new research and analysis can help provide us with a solid road map that will enhance our focused budgeting work and improve our economic development and neighborhood revitalization efforts.”

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