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Last week, we discussed the current strategy of the federal government (Part I and Part II) and the important role analytics can play in providing agency leaders improved data to make informed decisions for an organization, while reducing costs. We also discussed how the president’s budget echoes this by placing an emphasis on analytics and performance, especially through the passage of GPRA 2.0. Over the next two posts, we will focus some more of the presidential directives and how departments and agencies can save money through the use of analytics.
Doing more with less
As the federal government works through budgets for the fiscal years, 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 reallocate 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.
Shifting paradigm to derive value
In the midst of this cost-cutting frenzy, the digital universe is exploding. With seemingly infinite potential for data growth, how can federal agencies prevent improper payments, ferret out waste, and reduce costs? We have said it before; it is no longer sufficient to carefully construct databases and file data accordingly. As in one of our previous posts, we explored how analytics will allow department and agencies to learn from data in the moment to predict and influence possible outcomes. 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 analytics tools
For example, 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 continuous monitoring technologies screen data in real time, allowing action in the "present." In this way, agencies can prevent or minimize problems from developing.
Coming up next
Join us next time as we wrap up discussion on the final two advanced analytics methods: continuous monitoring technology and predictive modeling.
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Mr. Treworgy has over 20 years of analytics and project management experience. In addition to his primary focus on United States departments and agencies, he also has carried out work for a number of government organizations in Europe and Africa. A thought leader in the area of strategy and information analytics, Mr. Treworgy publishes frequent articles, presents often at conferences, and has provided expert witness testimony on several occasions, including at a joint Senate / House of Representatives hearing. He graduated with a BA in Economics from Williams College and an MBA from Harvard University.
David Treworgy (firstname.lastname@example.org)
Greg Greben is Vice President and Market Leader for Business Analytics and Optimization (BAO), IBM Global Business Services, US Public Sector.