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Data collection and analysis is nothing new. However, in our increasingly data-driven world, data is being collected across the government at increasingly unprecedented rates. The scope of data that organizations collect grows as the capability of networks to share it expands. Agencies are moving from simply collecting, analyzing and owning data to sharing and leveraging data to create transformative impact.

The role of data has changed as agencies’ data needs have changed. Beyond developing a strategy for managing data, agencies now must look at data as a strategic asset – a proven enabler in driving missions and delivering services. The President’s Management Agenda prioritizes it as Cross-Agency Priority Goal 2: Leveraging Data as a Strategic Asset —federal agencies and its partners are driven to develop integrated cross-agency federal data strategies that encompasses governance, standards, infrastructure, and commercialization challenges of operating in a data-driven world. As such the Federal Data Strategy further emphasizes on the importance of data for mission success, delivery of services and the public good.

It is an important topic. My colleague Jason Porter just took part in an ACT-IAC webinar on just this topic, which focused in part on how COVID-19 is driving data sharing adoption, and on the role of access security in protecting data.

In the government, the collection of data enables better services, more citizen-centric decision-making and the ability to understand the needs of constituent populations more accurately and in more detail. And yet, the question of how much data is enough remains relevant. As a general guiding principle, government organizations should not collect data they don’t need, or share it more widely than intended.

People understandably are reluctant to share information. The PMA recognizes this, making “protecting the privacy, security, confidentiality and interests of data providers” a key caveat in the text of the CAP Goal.

Likewise, the Federal Data Strategy calls for the development of a data ethics framework and states: “Fully integrating a data ethics perspective into all aspects of agencies’ data management efforts will require substantial and long-term cultural change. It would involve staff at all levels undergoing training to support and refresh data literacy skills and reinforce protocols related to data privacy, confidentiality, and the ethical collection, use, storage, and dissemination of data.”

Even with these assurances, however, it might not always be obvious how much data an agency really needs to carry out its mission. There are no certain answers to the question of how much is too much, but the debate is important. Everyone interacts with the government in various ways; everyone gives up information in exchange for goods and services. With the focus on data increasing, when does enough information cross the line into too much information—TMI?

Gathering more information that is needed can actually hinder agencies as they seek to provide efficient services. The mission requirements should dictate decisions about data collection, ensuring agencies gather all the data they need but not more than they can use effectively. And as always, they should handle data from the public with the highest level of care and security.

Speaking broadly, then, there is no one right answer to the question of when the TMI line is crossed. Many agencies do gather vast amounts of personal data, including financial and health information, all of which is necessary for those agencies to do their work. Others may gather more than they strictly need for the sake of fleshing out files or simply out of habit.

As agency policymakers develop data strategies and move forward with data initiatives, they should ask themselves what their agencies really need to know.

For another perspective on the value of data, read my earlier blog, “Four pillars for treating data as an asset.”

About this author

US Expert Sumit Shah

Sumit Shah

Director, Consulting Services

Sumit serves as the chief data scientist in CGI Federal’s Emerging Technology Practice. He leads a team of data engineers and data scientists who are defining and driving technical direction of prospective business opportunities, and work with business stakeholders and client executives to develop overall ...