In Depth Arizona's state capitol building

Published on December 9th, 2014 | by Travis Korte

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Data for Better State and Local Policymaking

Better data and analytics have the potential to transform state and local governments in a variety of ways, improving internal processes, helping provision services, and cutting costs. One underappreciated area where data can have a major impact is in policymaking itself. In particular, state and local governments are analyzing data to inform better policies around economic development, education, and health care.

The City of Palm Springs, California offers one example of using data analysis to improve its economic development policies. Working with data consultancy firm Buxton, the city mined data obtained from Visa to learn more about how people were spending money in the city. The data painted an unexpected picture of local commerce, showing that 73 percent of the city’s sales came from people from out of town and 13 percent came from people residing in the country’s wealthiest areas. Using these insights, local officials determined that they had been undervaluing the city’s luxury economy, proposing a sales and use tax increase targeting these out-of-towners’ purchases. In 2011, the city voted in favor of the increase, the money from which will be put toward parks, street renovations, and an investment in an upscale retail shopping area downtown. Other cities, including Bloomington, Illinois and Kingsport, Tennessee, have used data analysis to increase tax revenues through similar initiatives.

The State of Arizona is expanding its student data tracking systems to improve its education policy efforts. The state’s longitudinal data system, the Arizona Education Learning and Accountability System, has expanded from a pilot operation in 2008 to a sweeping operation that will cover every district, teacher, and principal by the end of 2014. Teachers update the system with student information regularly and a statewide aggregator has begun processing the data to generate weekly and monthly reports. The database, which provides granular data indexed over time, will reveal long-term trends in the state’s education system along with areas in need of short-term help. Although the project is still under development, Department of Education officials hope that it will ultimately provide state legislators with information on what aspects of the education system need greater funding and inform policies around large-scale interventions in the state’s schools.

The State Health Access Data Assistance Center (SHADAC), based at the University of Minnesota, helps states collect and analyze data to inform state health policy decisions. In particular, the center helps states bridge the gap between state officials and federal data sources, such as the American Community Survey, the Current Population Survey, the National Health Interview Survey, and other sources. SHADAC’s research includes a study to locate low-income uninsured individuals around the country in hopes of informing policy recommendations around allocating funding for community clinics. The center has also looked at the impacts of the Affordable Care Act on health insurance coverage in Minnesota specifically, to help state policymakers further close coverage gaps. After conducting this research, the center makes its work available in easy-to-use formats for state officials.

These are only a few examples of the ways better data and analytics can help state and local policymakers make better decisions, but as new data sources become available, policymakers need to consider how they can leverage these new sources. Data’s applicability to policymaking transcends individual issue areas, offering a tool for reducing uncertainty and predicting impacts in any number of state and local governance contexts. Ideally, this should lead to policymakers making smarter, more informed decisions based on the available data and best-available analytical methods.

Photo: Wikimedia Commons User Wars

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About the Author

Travis Korte is a research analyst at the Center for Data Innovation specializing in data science applications and open data. He has a background in journalism, computer science and statistics. Prior to joining the Center for Data Innovation, he launched the Science vertical of The Huffington Post and served as its Associate Editor, covering a wide range of science and technology topics. He has worked on data science projects with HuffPost and other organizations. Before this, he graduated with highest honors from the University of California, Berkeley, having studied critical theory and completed coursework in computer science and economics. His research interests are in computational social science and using data to engage with complex social systems. You can follow him on Twitter @traviskorte.



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