Cross Industry Partnership Turning Community Data into Better Insights

There is an abundance of public community data that’s freely available but difficult to make sense of collectively due to the sheer amount of information that exists. With the mission to harness this data, leaders in local government, academia, data science, and performance measurement teamed up to rigorously assemble the nation’s most comprehensive public sector data set that exists today.

The project is called Government Performance Action and Learning, or GPAL. Partners include the High Road Strategy Center, community engagement and analytics company Polco, the International City/County Management Association (ICMA), Arizona State University, and the Hoover Institution at Stanford University.

GPAL brings relevant community information together in simple but comprehensive insights. It allows government officials, researchers, and academics to see connections between disparate community data that, before now, only lived in siloed sources. GPAL data is used for local government decision-making, community research, and so much more.

Where do GPAL data come from?

GPAL data are available on Polco through one proprietary national database—developed through decades of research and work with local governments. GPAL includes dozens of public datasets from credible sources such as the Bureau of Labor Statistics, the US Census Bureau, and many more.

GPAL also incorporates data from The National Community Survey (The NCS) by Polco. The NCS represents over 50 million American voices and is the largest public opinion database of its kind.

GPAL Dataset Examples include:

  1. Bureau of Labor Statistics Local Area Unemployment Statistics
  2. Center for Neighborhood Technology
  3. Climate Mapping Resilience and Adaptation (CMRA)
  4. County Health Rankings & Roadmaps
  5. Federal Bureau of Investigation Uniform Crime Reporting
  6. U.S. Bureau of Economic Analysis
  7. U.S. Department of Housing & Urban Development

And many more!


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What is the benefit to partners?

GPAL uplifts the industry by providing thought leadership and also practical help for association members (from cities and counties) to introduce or better maintain performance measurement in their community. Local and regional performance indicators can be leveraged to better understand the impact of Association initiatives and support state or federal advocacy. Through webinars, workshops and whitepapers, experts from Polco and other GPAL partners can provide training on optimizing performance measurement and management including using performance metrics in grant writing. 

Why now?

State and local governments are seeing a significant increase in opportunities for federal funding (Pew Charitable Trust). Local jurisdictions and their professional associations will be able to utilize GPAL performance metrics to gain financial support by using GPAL to identify needs,  allocate resources, and measure performance. Community insights from public input and performance indicators are key to receiving funding, showing effectiveness, and ultimately securing this amazing opportunity for local leaders.

What is the process?

GPAL was envisioned by Polco and the High Road Strategy Center in conversation with ICMA. Data scientists from Polco and the High Road Strategy Center vetted data from hundreds of potential sources and chose the highest quality, comparable and comprehensive performance metrics. Thousands of hours were needed to collect, clean and integrate hundreds of data points. This data was then added to Polco’s proprietary database of longitudinal stakeholder sentiment from hundreds of communities and it was organized into the domains from National Research Center’s model of community livability – a model developed through decades of research and work with local governments. Indices were developed to provide an overview of community health in each domain, with deep dives into the components. The indices and overall model were improved through review and discussion with key initial collaborators at Arizona State University, Harvard and Stanford.

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