Why Business Data Accuracy is Important in Government

We know governments at all levels have terabytes of data and some of the data is based upon self-reported information by businesses and/or business owners. However, figuring out how best to use that data to effectively verify businesses, investigate businesses for fraud, waste and abuse or any suspicious activities can be a bit challenging.

But what if agencies could “break through the noise” by using big data, analytics and business network intelligence to quickly verify businesses that apply for grant programs? Or to help perform the business due diligence and evaluate potential risks behind the vendors or contractors within your network?

In GovLoop’s recent online training, “Why Business Data Accuracy is Important in Government,” we learned the importance of risk assessment, how agencies can start breaking down data silos to improve business data accuracy and why an agency should use a multi-layered approach to validate business data.

Participants heard from experts including:

  • Andrea Brandon, Deputy Assistant Secretary, Office of Grants and Acquisition Policy and Accountability, Department of Health and Human Services (HHS)
  • Joah Iannotta, Senior Advisor for Data Analytics and Performance Metrics, Do Not Pay Business Center, Bureau of the Fiscal Service, Treasury Department
  • Scott Straub Director, Director of Federal Market Strategy at LexisNexis Risk Solutions

So how is business data separate from just data? Business data refers to the information about people, places, things, rules and events in relation to operating a business.

“All these corporations and organizations request grants and get loans, for example, but there’s so much other data associated with business itself,” Straub from LexisNexis said. LexisNexis provides risk solutions to help organizations better manage their business data.

When we apply business data to government, many agencies process vast volumes of data like names, social security numbers and addresses. The Treasury Department and HHS, for example, collect and process vast volumes of business data.

“We award grants more that amount to more than $600 million annually for healthcare purposes,” Brandon from HHS said. “For us, the delineation between biomedical and healthcare and business data (how we run our organization) is how we distinguish business data i.e. human capital data, human spend and budgetary data.”

The Treasury Department’s Do Not Pay Business Center works with agencies to detect improper payments through occurrences such as error, fraud, waste or abuse.

“We have data-centric tools like an online portal with automated data matching to help detect improper payments,” Iannotta from Treasury said. “We use data as a source to determine eligibility. For example, an agency may have recently paid someone who is deceased or a corporation that has recently been barred from doing business with federal government.”

The challenge for government agencies like HHS and the Treasury Department is processing increasing volumes of data while still needing to ensure data accuracy.

“Having accurate data is the foundation for making a good decision about whether or not to take action on an improper payment,” Iannotta said. “Taking those decisions based on inaccurate data, however, is going to cause a lot of heartbreak.”

Not only can inaccurate data cause heartbreak for government but also serious financial loss as well as public distrust.

“Our biggest problem is the amount of data we have,” Brandon said. “We have more than $100 million grants going out and we have to verify hundreds of millions of sources. Assuring that all the data we have is good quality and tells the right story is also the biggest challenge.”

Government’s biggest data challenges boil down to quantity and quality of data.

“When it comes down to it, there’s a quality and a quantity issue,” Straub said. “As people go out and enter data into the system, it stays in the system. Once you get a lot of data, it becomes really difficult to manage. We have a lot of algorithms to run in various forms. The data gets used in so many different ways for so many different purposes. So it depends on how the data is organized and indexed.”

Many agencies are turning to a multi-layered approach that combines technical skills, data and human interaction. These three factors all are important to better data accuracy and analysis.

“We have both manual methodologies as well as technological help with different algorithms run on the data as it goes through the systems,” Brandon said. “We want to use it to do more predictive analysis to help run our programs better.’

In addition to ensuring accuracy, it’s important that staffs follow regulations and guidelines accordingly. “The why of collecting data matters less; the rules and requirements around the data’s intended use is more important,” Iannotta said

“Have data standards,” Brandon said. “In some data systems if you put ‘st’ instead of ‘street,’ it can be very difficult to reconcile those differences. Putting appropriate data standards in place is very key. Sometimes you even have different business owners who want to standardize data in their own ways. As we see across the government, we have to make sure we agree on lines of business and data standardization.”

To ensure such standardization, agencies can pair their data scientists and technologies with accuracy checks against a larger database.

“What we do as a data company is offer a really large database that agencies can use to accuracy check against,” Straub said. “Organizations have multiple registrations and layers of data. We can take the data and bounce it off our database i.e. addresses, names, numbers to help increase the accuracy of the business data.”

Such databases combined with the right technology and human interaction can greatly improve agencies’ business data strategies. Ultimately, everyone knows the importance of data. But how to manage the quantity and quality of that data is another challenge in itself. With the right multi-layered approach, government can better manage its business data. Effective business data accuracy and discovery tools have the power to increase accountability and reduce risk for all of government.



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