When the stakes are so high, the data can’t be wrong

The federal government comprises a wide network of agencies and organizations that each have their own mission to accomplish. These missions range across a wide spectrum from the delivery of healthcare benefits to the protection of American citizens from threats both at home and abroad.

The tasks that government agencies are assigned are high level and affect every American. To ensure these tasks get done correctly, agencies need to rely on their people and their data. Unfortunately, government agencies are starting to realize that the human element in their processes sometimes leads to errors that result in data sets that aren’t always as reliable as they need to be.

Data quality is paramount for federal agencies. And when data is wrong, serious issues can arise.

Take homeland security as an example. Data quality and address consistency can be the difference between identifying a threat in time to prevent an incident or not. With government agencies, including law enforcement agencies, sharing data to better identify homeland security threats, data from multiple agencies is often aggregated and analyzed. Mistakes in this data could ultimately keep trends or suspicious behaviors from being identified.

How are these mistakes made and what possible impact can they have?

Address information is a part of approximately 70 percent of the records available to the federal government. This makes addresses one of the most relied upon source for identifying connections and relationships in different data sets.

But addresses are also complex and can be written multiple different ways. If one agency has an address entered as 54 South First Street, instead of 54 First Street South, a connection or comparison could be missed. This is one example of why data quality and data consistency are so important in today’s federal government.

Despite the rising importance of data, data capture errors are also becoming more prevalent. Agencies have information entering from a widening sea of disparate endpoints and sources. As this data enters the agency, it needs to be digitized and stored.

In the past, the process for this has been by manual, keyed entry of data from large, hard copy document collections. Unfortunately, this system can easily get strained from a vast amount of information entering the agency at once, and can also result in data quality issues simply because of the “human element.”

But what alternatives are available? In our next post we’ll take a look at how new technologies are helping to automate the process and reduce user errors, bringing many new benefits to the federal government.