Presented by Teradata
Agencies can gain a better understanding of their financial data and create value for customers and other stakeholders with multi-genre analysis. The result is improved performance, better decision-making and added value for public information.
A multi-trillion-dollar enterprise such as the federal government cannot be run with basic 20th century bookkeeping. Agencies maintain large troves of financial data that is used in day-to-day operations, making decisions and measuring the success of their missions. At the same time there is a growing expectation by regulators and the public that financial information will be available for analysis in total and on demand
“It’s not enough to assign simple debits and credits to financial transactions,” said Rick Harmison, Senior Industry Consultant, “People need qualitative context around financial data,” including how money was spent, why it was spent, and what the benefit to the public is. To be useful, data sets should be comparable across government. “The technology exists to do this, that’s not an issue any more.”
The issue is putting the right technology, standards, and practices into place.
Under the DATA Act (the Digital Accountability and Transparency Act of 2014) federal agencies are to begin providing data for posting online at USAspending.gov by May 2017 using a standard data exchange schema.
Challenges to transparency
The transparency envisioned by the DATA Act not only adds value to data for the public, researchers, and regulators, but also enables agencies to improve performance and decision-making. State and local governments at every level can benefit from this type of visibility as well as federal agencies under the DATA Act.
“Knowing the benefit that government dollars deliver, especially for a specific topic, is very powerful,” said Darla Marburger, Principal, Government Sector. “The value is multiplied as it spreads across agencies and governments.”
Unfortunately, “a lot of agencies can’t do that today,” Harmison said. Much government financial data still is stored in siloed systems and the difficulty of accessing and using it greatly reduces its value. Assembling, normalizing and delivering this data can be time-consuming and labor-intensive. A recent study by the Government Accountability Office found that only 13 of 30 agencies examined were on track to meet DATA Act requirements for posting standardized financial information by May. Systems integration and a lack of resources remain challenges for 26 of the agencies.
Despite the challenges, the demand for and interest in government financial data continues to grow, however. For instance, former Microsoft CEO Steve Ballmer recently launched a beta website, USAFacts, to aggregate publicly-available government financial data in an attempt to bring transparency and accountability. It is incumbent upon Agencies and Government financial managers to get out in front of this movement towards greater transparency and more meaningful data.
Adding value to data
A key way for Agencies to get ahead of public and regulatory demands for transparency is through multi-genre analytics, allowing them to better understand their own data while meeting the needs of their stakeholders. Multi-genre analysis is a broad set of functions and visualizations that can be applied to financial and programmatic Government data which leads to greater insight and value.
As an example, creating transparency requires context as well as accessibility. By focusing not just on the numbers but also on the words that go with them, users can associate and compare similar activities across agencies by using data sets from a variety of sources.
Providing this kind of context on a per-request basis is expensive and time-consuming. Applying multi-genre analytics to structured and unstructured data creates transparent, useable information that users can access as needed. This analysis identifies not just the financial elements—debits and credits—but the full context of the transaction or activity, which might be stored in a variety of locations and formats. This analysis uses a variety of tools such as text analytics and path analysis, as well as visualization tools to present data in formats that are easy to understand and highlight relationships.
Making visible the full interaction and its context of a transaction provides a new level of understanding. Agencies gain a clearer insight into their own financial activities and the accuracy of the data. It lets users drill down to the information they need, without the data owners having to assemble and normalize it for every request. Value can now be extracted from data so that it becomes an asset rather than a cost center.
Teradata’s Government Rapid Insights Program (GRIP) can demonstrate to agencies how multi-genre analysis can open program, operational and financial data so that it can be mined for immediate insights and made available for use by other agencies, regulators, researchers and the public.
The end result is that agencies can simplify the use of financial data, extract value from it, and make better decisions about mission-critical activities all with a maximum benefit to the public.
This content is made possible by our sponsor. The editorial staff of Nextgov was not involved in its preparation.
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