By Greg Pellegrino and Pasquale Nigro
As the federal government works through the budget for the upcoming fiscal year and beyond, one message has become clear: Federal agencies must learn to do more with less. Whether through improper-payment reduction or decision optimization, agencies will need to strategically allocate resources to meet the challenge.
Improper payments totaled nearly $125 billion in 2010 — an increase of $15 billion over 2009. Spurred by public outcry, Congress has taken action. By more strictly regulating federal programs, strengthening the False Claims Act and passing the Improper Payments Elimination and Recovery Act (IPERA), lawmakers are signaling that waste, errors and fraud must be addressed.
Passage of IPERA in July was a key step toward reducing improper payments by $50 billion between mid-2010 and 2012. The law outlines activities for boosting the campaign against improper payments, including risk assessments, payment recapture audits and agency incentives.
At the same time, Secretary Robert Gates launched an initiative to transform the Defense Department through cost-cutting measures. Our conversations with a number of other federal agencies indicate that many are considering similar measures.
In the midst of this cost cutting, the digital universe is exploding. When many of us first entered the world of computing, we spoke of floppy disk kilobytes and hard drive megabytes. Today, terabytes are giving way to petabytes, which will evolve into exabytes and so on.
With seemingly infinite potential for data growth, how can federal agencies prevent improper payments, ferret out waste and reduce costs? It is no longer sufficient to carefully construct databases and file data accordingly. The paradigm has shifted toward deriving value more broadly from the digital universe.
To harvest value and actionable intelligence from the digital universe, agencies should consider the capabilities of data mining, advanced analytics and predictive modeling.
Forensic analytic tools enable agencies to sift through massive amounts of data to identify potentially anomalous behavior from the "past" — or "pay and chase." Even more sophisticated are continuous monitoring technologies that can screen data in real time, allowing action in the "present." In this way, agencies can prevent problems from developing.
For example, continuous monitoring technology can be deployed to help prevent payments for medically unnecessary services, for duplicate invoices or to deceased individuals — thereby bypassing any need for a retrospective pay-and-chase approach. This technology can also be applied to nonfinancial data streams, such as social media or news feeds, to search for emerging issues and provide mission- critical alerts based on real-time analysis of those data sources.
Predictive modeling technologies are among the most advanced, performing data analysis to identify patterns and outliers and to make predictions about potential future events. This form of analytics can provide insights into a variety of activities, including the number of improper medical insurance claims that may be filed; which financial institution transactions are indicative of money laundering; and the likelihood that a loan will default — just to name a few.
Agencies can also combine the best attributes of these three tool types into hybrid technology platforms. The resulting 360-degree view of operations can be an effective way for agencies to address waste and improve operations and performance.
The cost savings and efficiencies gained from current technologies are limited only by the imagination and ingenuity of the tool wielder.
