By Karen Norris
There has been heightened interest on the part of the federal government to improve information technology (IT), standardize data elements, and strengthen data analytics. Financial assistance reporting, as a result, is now subject to data analytics.
The uniform guidance, legislation, the eGovernment Initiative, presidential memoranda, and the management agendas for the past two very different presidents have all pointed to the strategic management of data, particularly federal spending and performance data, all of which affects financial assistance.
Increasing Scrutiny in Reports
The two over-riding priorities of the uniform guidance include: (1) reduce administrative burden and (2) prevent waste, fraud, and abuse. It is the second priority that grips the attention of awarding agencies and recipients alike.
Pre-Covid, more than $750 billion was awarded annually with $175 billion in improper payments caused by unintentional errors or intentional acts of wrong-doing. Post-Covid, more than $5 trillion has been awarded, with $247 billion in improper payments, as reported by the Office of Management and Budget (OMB), the Government Accountability Office (GAO), and the Council of Inspectors General for Integrity and Efficiency (CIGIE).
The pressure is on for stewardship of federal funds. Digital assets enable awarding agencies to better collect and analyze data, detect mis-spending, and pursue action. Recipient authorized representatives who sign reports must certify that they are personally accountable (200.415(a)).
Increasing Role Of Data Analytics
The push for standard data elements to enable data analytics government-wide is evident in the Transparency Act, the Federal Data Strategy Act, the Evidence Act, and Treasury Department. Section Six of the Transparency Act established the data analytics center within Treasury to prevent improper payments and improve efficiency in federal spending.
GSA’s Federal Integrated Business Framework (FIBF) has identified more than 400 standard data elements for grants management alone. The GSA-managed website at https://digital.gov has established digital communities of best practices, including one for financial assistance.
The Evidence Act and Presidential Memo M-19-23 established outcomes for open data, a federal data catalog, secure access, and standardized data. Program outcomes are included in every federally-connected award agreement (200.211(a)). These outcomes are measured. The Government Accountability Office (GAO) now reports about federal use of data analytics government-wide.
More recently, Presidential Memo M-24-11 notes the creation of the Federal Program Inventory at https://fpi.omb.gov that crosswalks program requirements defined in Assistance Listings with spending requirements of the Payment Integrity Information Act (PIIA).
The government’s capacity to run data analytics on federal spending is not only a reality, but a routine. Nonfederal entities should recognize that the data submitted in their reporting can be reviewed and analyzed, not only by human program managers or auditors, but also by machines with algorithms that can detect anomalies, whether unintentional mis-spending or intentional wrong-doing.
Data analytics has quietly taken center stage, and then there’s artificial intelligence looming just ahead.
To view the FIBF grants management data elements, go to https://ussm.gsa.gov/fibf-gm.
To access Presidential Memo M-24-11, visit https://www.whitehouse.gov/wp-content/uploads/2024/04/M-24-11-Revisions-to-2-CFR.pdf.
To learn more about the digital community of grants, visit https://digital.gov/communities/results-oriented-accountability-for-grants.
To review one of the GAO reports about data analytics, go to https://www.gao.gov/products/gao-24-105358.
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Karen Norris, is principal at Kanoco Consulting, LLC, with offices in Gaithersburg, Maryland and Lewes, Delaware.
