We use ratings every day to guide our decisions about things to buy online, new restaurants to try, or repair services to use. Ratings relay information about how a person experienced a product or service, but unless they write a lengthy review, you can’t know why something is rated the way it is.

The same can be true for data on upward mobility, or measures of affordable housing, quality jobs, political engagement, and other aspects of a community that support mobility from poverty. Without more information on the local context, it’s hard to know why the numbers are the way they are or how to change them.

That’s why the Urban Institute has developed a dataset, called the Mobility Metrics which localities can use to learn more about local conditions for economic mobility. As part of the Boosting Upward Mobility project, Urban partnered with a cohort of eight county and city governments in 2021 and 2022 to help them identify local conditions that enable or prevent mobility and equity.

With Urban’s technical assistance, two localities, Boone County, Missouri, and Summit County, Ohio, engaged in a Mobility Action Planning process that used metrics and data to shape the priorities of their mobility efforts. From this process, we learned three lessons about how local governments can pair community engagement and local data with the Mobility Metrics to understand upward mobility in their communities.

  1. Invest in local data capacity
  2. Find local data sources that supplement the Mobility Metrics
  3. Engage community members to determine why data trend one way or another

Read the full article about upward mobility and data by Rayanne Hawkins at Urban Institute.