How Big Data Has Changed Public Policy

It is predicted that this year alone, global IP traffic will reach 1.1 Zettabytes, which is equivalent to 1 billion Gigabytes. We are inundated with more data than we can possibly analyze, but getting it in front of the right people who can make sense out of it is the era of Big Data that we have long since entered.

For some time of its earlier years, Big Data has been heralded as the savior to troubling businesses, working its magic throughout the private sector. But the public sector has also been using it to change the way in which public policy is made. The environment has completely changed, which is good news for all of us as policymaking becomes more targeted and relevant.

In fact, data mining and analyzing has already taken effect within the Government to mitigate fraud, in law enforcement to predict future crimes, in education to improve academic performance, and in infrastructure to monitor the citys usage of precious resources. More instances of Big Data being deployed in the public sector can be found in this infographic published by the Public Policy Masters Program at New England College (NEC).

Healthcare

Health and human services implemented a fraud prevention system that identified $210.7 million in improper payments to health care providers. Big Data not only helps save money but also saves lives as it expedites the development of new treatments and containment of viral outbreaks.

Last week, the World Health Organization declared the Zika Virus a global health emergency and predicts cases to rise to four million in the next year. Currently there are no reliable tests and vaccines for the virus, but utilizing a data driven infrastructure to identify trends and analyze clinical test results will shorten the race to the cure.

When managing and responding to viral outbreaks, time is of the essence as every second that passes without a vaccine may mean that a life could not be saved.

Government Fraud Savings

62% of local governments have already or are in the process of using big data and analytical technologies in their jurisdictions. With tax season right around the corner, fraudulent returns remain an expensive task to manage as identity thieves continue to steal billions of dollars a year.

By using algorithms to compare public records and information thats on tax returns, ones that dont match up are alerted to and audited. In 2014, the state of Indiana caught 75,000 fraudulent returns that amounted to a savings of about $85 million.

Law Enforcement

Implementing predictive policing is relatively new and is currently being tested and deployed in 60 cities across the country. The method involves algorithms and data from type, place and time of previous committed crimes in order to assign probabilities of future crime events to regions of space and time.

The city in which the practice was created, Santa Cruz, CA, saw burglaries drop by 11% and robberies by 27% in the first year the system was implemented. Same success rates were found in Reading, PA where crime dropped to the lowest it has seen in 35 years.

Education

Much like predicting future crime events, predictive analysis can be used to identify students at risk of dropping out. Monitoring student retention rates will make way for enhancing student academic performance and therefore overall satisfaction among students, teachers, and the administration.

Data gathered from individual students’ learning styles can also assist teachers as they can adjust their teaching styles according to the students”’respective needs.”Working from the inside out, this then provides insight on which programs are failing or succeeding in which to invest more or less focus and funds on.

Infrastructure

As Big Data is turned to smart data, it can then be used to turn cities into smart cities. Every city has its own intricacies therefore no master design exists, but behind every smart city is the narrative of Big Data that helps govern its public policies.

For example, the city of Boston uses the crowdsourcing app Street Bump to collect data from citizens smartphones in order to allocate maintenance and repair crews that resulted in savings from surveying costs of approximately $100,000. In the city of San Francisco, smart meters are used to provide digital reads of water flow to track citizens water usages which resulted in an extra 8% in water savings during the summer of 2014.

Watching out for the best interest of citizens and the cities they live in whilst saving money from expenses that are avoided with Big Data is a win-win for both involved, as benefits are reaped and tax dollars are used more sparingly.