How the US Government is Using Data Analytics to Make Decisions
Data analytics, or the process of looking for meaningful information and correlations in data, has become increasingly popular among governments in recent years. As a result of such efforts, governments are able to make more effective decisions. Through the integration and cross-referencing of data sets, calculations are undertaken to show trends, correlations between variables are found, statistical experiments are conducted, geographic data can be mapped to show areas where there is high activity, and charts and graphs can be used to visualize data. Furthermore, data analytics can be used to uncover the root cause of a persistent problem, diagnose breakdowns in a system, highlight obstacles, and predict future outcomes, allowing leaders to make more strategic decisions and be more informed.
The U.S state government makes decisions every day that affect the lives of its citizens. Policy decisions are made by legislators and governors, and public problems are addressed by them. As well as determining where budget dollars should be spent, and who qualifies for assistance, state agencies also determine how programs should be run. Keeping these daily decisions prudent and well-informed is a responsibility of state officials at all levels of government. To make strategic data-informed decisions, states are increasingly relying on administrative data, or information—like vital records, college enrollment data, and Medicaid utilization statistics—that are gathered and maintained primarily for the management of programs and services. An example of this type of information would be demographics, outcomes, and enrollment information that is necessary to implement and oversee a program.
Previously, the U.S Government traditionally used administrative data to prepare annual reports that detail the expenditure of funds and impact of a particular program, demonstrate transparency in describing what the agency does, and comply with federal, state, governor, or agency performance measures.
More recently, the U.S Government has started using data to make decisions, craft responses to problems in the country, improve service delivery, manage existing resources, and examine policy effectiveness. For example, several strategies using data analytics were sought by policymakers in Massachusetts to reduce overdose deaths. Several data sets from five agencies were integrated by the Department of Public Health. According to this analysis, illegal drugs were responsible for more deaths than prescribed opioid medications. The state passed Chapter 52 to address treatment, education, and prevention of the opioid crisis in 2016 as a result of these findings.
There was also an effort in Delaware to improve the efficiency of the state's fleet of vehicles. As a result of installing GPS devices, they received real-time data, such as unauthorized vehicle usage and excessive idle times. Using GPS data, Delaware's managers were able to optimize vehicle allocation across the state, saving $874,000 by reducing fuel consumption and driving miles.
These examples and more are evidence that data analytics is a beneficial tool to help governments make informed decisions and advocate for policy changes.