Good Data, Bad Data: The Value of Data Quality in Homeland Security
Homeland Security is a complex mission, one that is both vast in scale and broad in scope, and this creates a large volume of data that can help provide insight into operations and strategic decisions. From disaster preparedness to counterterrorism, Federal employees rely heavily on an abundance of data to assess problems accurately and implement effective solutions. Data is the backbone of any Homeland Security Enterprise, and Federal employees need proper management procedures to develop high data quality.
Data is high-quality when it is accurate, comprehensive, up-to-date, easy to access, and relevant to mission goals. How can agencies benefit from using high-quality data — or avoid the problems associated with low-quality data? What measurable effects can it have on the implementation of strategic plans and Federal policies? And how can it affect the processes of policy implementation?
Consider the ways leaders and the workforce in the Homeland Security Enterprise use data to gain insight into their performance and potential challenges and create solutions:
Airport Security: The Transportation and Security Administration (TSA) measures volumes of travelers going through airports by season, day of the week, time of day to anticipate demand and adjust workforce levels accordingly
Immigration: Immigration Customs and Enforcement (ICE) looks at trends in immigration and immigration-related crime to adjust investigation resources, discover new behavior patterns, and identify crime networks
Customs: U.S. Customs and Border Protection (CBP) uses data to identify high-risk cargo subject to additional inspection at border ports and understand changing cargo volumes at port locations
Disaster Preparedness: The Federal Emergency Management Agency (FEMA) tracks national risk data for natural disasters like floods and hurricanes, better informing disaster preparedness and response procedures
Conversely, lower quality data can have detrimental effects on mission goals. Without high-quality data, airport security would be unable to anticipate seasonal spikes in travel, which can lead to understaffing and slow performance. Immigration agents would have difficulty recognizing trends in movement and crime patterns, leading to insufficient law enforcement. Customs ports suffer from backlogs and long waits, as well as missing smuggled contraband in high-risk cargo. And natural disasters would have an even worse impact, with communities being unaware and having uncoordinated responses. These negative effects compound over time, leading to increasingly lost time, wasted resources, and missed deadlines.
With all this in mind, it is clear why data management should be vital to Federal agency leaders. Because while data may be the one of the most valuable assets in a Homeland Security enterprise, an asset is only as valuable as the extent one can use it.
