War is ninety percent information," observed French general Napoleon Bonaparte. Even with his assessment of the crucial role of information, Napoleon would probably have been astonished by the unprecedented volume, velocity, and variety of data that characterizes our present age. This data, as Napoleon noted, is critical toward establishing a competitive edge —but possessing a glut of unfiltered data is more of a liability than anything else. In order to successfully utilize and extract value from data, organizations must first establish a quality-ensuring management strategy. A recent GBC issue brief outlines five key components of successful data management:
Data leverage – using data to advance the organization’s mission and decision-making
Data exchange – cross-agency sharing of data in order to further goals and open data to the public
Data enrichment – enhancing and refining amorphous data into an analytics instrument
Data upkeep – maintaining the accuracy and consistency of data
Data protection – safeguarding the privacy of data
Various organizations have applied these principles toward addressing state and local challenges. Indiana’s creation of the Management and Performance Hub (MPH) in 2014, for instance, has allowed policymakers to more efficiently tackle both bureaucratic and social issues – policymakers have notably used data to identify the root causes of and ultimately reduce Indiana’s soaring infant mortality rate. Arkansas has also successfully leveraged big data in spearheading its Arkansas Health Care Payment Improvement Initiative (AHCPII). Since launching in 2012, the state’s data analytics engine has enabled the Arkansas Division of Medical Services to process hundreds of millions of claims from thousands of providers – AHCPII has expanded Medicaid coverage while improving or maintaining costs, and healthcare outcomes across the state have seen significant improvement. Finally, programs such as the North Carolina Financial Accountability and Compliance Technology System (NC FACTS) are employing predictive modeling and threat mapping to detect fraud and enhance risk management at the state and local level.
These are only a few examples of analytics-driven innovation, but they hopefully indicate a larger trend toward government embracing the power of data. By implementing a comprehensive strategy to sharpen raw data into a tool, governments and organizations can use the information at their disposal to derive crucial insights, enhance program performance, and craft a better tomorrow for the citizens they serve.