Analytics

Can big data save agencies big bucks?

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With the federal government planning to spend at least $82 billion on IT in fiscal 2014, it is imperative that agency decision-makers stretch their knowledge of how big data can help avoid duplication, cost overruns and other common IT challenges. Quite simply, America's economic security depends on it.

The amount of data being generated is growing faster than agencies can analyze it, but the benefits of that data are immense. However, according to one recent survey, many agencies are still years away from realizing the benefit of advanced big-data analytics. It is time for them to catch up.

Incorporation of big-data analytics into agency management requires investment, but the same survey found that agencies have the potential to save nearly $500 billion -- roughly 14 percent of agency budgets across the federal government. To take advantage of those potential savings, a renewed, cost-effective and comprehensive big-data framework for executing IT programs is needed.

As we look toward fiscal 2014, we see specific opportunities to engage in a big-data framework discussion.

For example, the Digital Accountability and Transparency Act will strengthen federal financial transparency by providing visibility into the government’s $3.5 trillion in annual spending.

Separately, the recent "shared services first" mandate brings heightened relevance to this topic within the Federal Shared Services Centers, each of which could benefit from a big-data strategy that would ultimately drive inter- and intra-agency performance to the next level. Surely, that is worthy of investment.

Those developments and the required modernization efforts dictate use of a holistic big-data framework that would not just manage data growth but also help government transform in innovative ways by enabling new insights and intelligence and providing improved services to the public.

It is worth noting that the public services that would result from a big-data strategy are not limited to preventing fraud. They also include enhancing security and services to improve lives in an unprecedented manner.

For example, the White House's Neighborhood Revitalization Initiative is a living example of an innovative effort with the departments of Housing and Urban Development, Education, Justice, Health and Human Services, and Treasury to revitalize and transform neighborhoods and address the needs of distressed communities by preventing crime and improving education.

Similarly, the FBI is looking to parse large volumes of data to find suspects and to forecast and prevent crime. The Federal Aviation Administration is increasingly turning to text mining to better analyze airline and air traffic data. And the National Oceanic and Atmospheric Administration, which plays an essential role in helping Americans prepare for weather catastrophes, is trying to mitigate current gaps in weather satellite data to improve the accuracy of warnings regarding hurricanes and other serious storms.

It is true that some agencies possess partial frameworks to take advantage of big data, but those frameworks likely merit updating -- not just to bring them to real-time capabilities but to cover an integrated set of habits that allow agencies to collaborate holistically with one another.

In other words, a big-data framework needs to be an enterprise-based, cloud-enabled, real-time, secure platform that can act on any type of data, process or application regardless of the sources. It must also handle a wide diversity of scenarios that might involve predictive, text or spatial analysis, and it must render dynamic, rich visualizations to help operationalize insights into people and processes with innovative capabilities. And it must do all that in a short time frame.

A successful big-data framework that meets those criteria could help satisfy two important objectives: an agency's need to effectively and innovatively run its IT systems, and the public's need to recognize transparency and appreciate the government's accountability.

Now is the time for consensus on an investment in a high-tech infrastructure that would pay both societal and financial dividends and truly revolutionize constituent services.

About the Author

Ramani Vaidyanathan is a senior director at SAP Public Services. He can be reached at ramani.vaidyanathan@sap.com.

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Reader comments

Mon, Jan 13, 2014 Max Castaneda Florida

Each agency should post their data in a coo on format/s. We'll take it from there. No proprietary systems required.

Sun, Jan 5, 2014 Jaime Gracia Washington, DC

"In other words, a big-data framework needs to be an enterprise-based, cloud-enabled, real-time, secure platform that can act on any type of data, process or application regardless of the sources." That is an incomplete and parochial view of the potential of Big Data usage for improving government management, unless you are SAP an that is what you sell. Typical statement from a "leader" in the Big Data space.

Wed, Dec 11, 2013 OccupyIT

"the same survey found that agencies have the potential to save nearly $500 billion -- roughly 14 percent of agency budgets across the federal government" Wow! If this is like data center savings there's tens of dollars to be saved here! Most big-data value is concentrated in a few areas of a few agencies, program-wise. It is hardly a general issue that should, be clear implications result in a 14% decrease in agency budgets. Makes you wonder how much SAP *ahem* is charging in those big data hot spots. Looks like we have another silver bullet to put in our CIO quiver!

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