A recent i360Gov webinar dove into detail about a successful big data initiative at the Social Security Administration’s (SSA). Jim Borland, Assistant Deputy Commissioner for the Office of Disability Adjudication and Review, and Judge Gerald Ray, Deputy Executive Director, Office of Appellate Operations joined Chris Steel, Chief Solutions Architect, Software AG Government Solutions, Inc. to discuss how SSA leverages big data analysis to advise disability appeals and streamline business processes.
Every year, SSA issues around 16 million new & replacement social security cards and processes 1.6 billion automated SSN verifications. They’re also involved in gathering earnings data from U.S. employers and processing retirement benefit claims. In addition, they hear over 12,000 annual court cases. Additionally, the agency issues more than half a million hearing and appeal dispositions each year, and appeals judges render the agency’s final decision in over 100,000 cases per year. The result of these activities is a mountain of data to process and information to analyze.
In order to perform this work, SSA has a network of over 1,200 field offices around the country, 162 hearing offices, a toll-free number and a robust Internet presence. Behind each of these service delivery channels are systems that gather tremendous amounts of data. SSA was interested in looking into that data to see what they could learn about the processes in an effort to improve service and maximize efficiency. On the webinar, Borland and Ray describe the process SSA went through in their quest towards becoming a more data-driven organization.
They began by looking at their business processes for efficiencies. They had business rules in place but weren’t sure if they were being followed by employees, so they mapped out how cases flowed from place to place using case status codes. They also mapped out service delivery requirements around disability claims, their primary type of work, stepping out over 2,000 possible decisions into a matrix that mapped to a decision tree. The next step was to gather actionable data around those steps. SSA built an analysis tool that converted raw data into various visual formats that made it easy to analyze the data. Mapping out the data this way and creating various views of the data, they were able to perform a root cause analysis that revealed that practices were inconsistent with procedures, in many instances because of inadequate or ineffective training.
Watch the webinar to learn more about the details and results of SSA’s big data analytics program and how in-memory computing helped make it possible.