The DATA Act standardized data for more than $6 trillion in annual spending across more than 100 federal agencies while enabling taxpayers to monitor how federal funds are allocated on USAspending.gov and trace those funds to direct investments in their communities.
Last month my organization, the Bloomberg Center for Government Excellence at Johns Hopkins University, celebrated the 10th anniversary of the DATA Act (a recap and recording of the event are here). U.S. Sen. Mark Warner, the Virginia Democrat who initially sponsored the 2014 legislation in the Senate, spoke at the event along with Chattanooga Mayor Tim Kelly and a host of other federal and local officials, reflecting on the origin of the law, its impact and the future of open data in the age of artificial intelligence.
Robert Shea, a former official at the Office of Management and Budget under President George H.W. Bush, moderated a panel on the lessons learned from the passage and implementation of the DATA Act. “What we’re going to talk about today is, not arguably — I don’t think it’s arguable — the most significant advancement in government transparency in the world before or after,” he said.
What made it possible to pass the DATA Act? What made it effective? How can we replicate its success in a rapidly changing data landscape? Before coming to Johns Hopkins University, I worked on the DATA Act, first as the director of the Task Force on Government Performance on the Senate Budget Committee. Then I moved to the Treasury Department to join the leadership team implementing the historic law.
In my view, the DATA Act succeeded for two key reasons. It had bipartisan legislative leadership and an innovative approach to implementation. As someone who worked on both sides of the effort, I’m often asked which was harder, passing the law or implementing it? Looking back, we landed on legislative and implementation strategies that offer some critical lessons for future bipartisan policy at every level of government:
Agree on the problem. Sen. Warner and Rep. Darrell Issa, a California Republican, were both deeply committed to solving a clear problem — lack of transparency over spending — and teamed up to fix it. Both leaders thought the Recovery Act transparency was a success, and they wanted to make that the new standard across government. I see successful data leaders do the same thing: agree on the problem and focus on what data is needed to solve it.
Form a bipartisan political alliance with a shared vision. Warner and Issa built alliances on both sides of the aisle. Issa found a Democratic co-sponsor, Rep. Elijah Cummings of Maryland, and Warner found a Republican co-sponsor, Sen. Rob Portman of Ohio, a former director of the Office of Management and Budget. They gathered more and more bipartisan co-sponsors who would add momentum for passage. This is critical for any legislative strategy.
Create a trusted team to collect facts and develop solutions. House and Senate staff worked together to gather common facts and learn together. We held dozens of bipartisan briefings and modified the bill together. I wore out the long path between the Senate and House office buildings for joint meetings. We formed trust — always critical to accomplishing big things.
Because time was running short to pass the bill, the House and Senate staff worked together to pre-conference the legislation before House and Senate passage of identical versions of the bill. This skipped the step of having to conference the two bills after passage and got the bill to the president’s desk sooner. That would never have worked if we had not developed trust.
Build external allies. We found support from the Data Coalition, the Sunlight Foundation, civil society groups, the financial management community and others. These stakeholders supported passage and continued to be involved during the implementation. They also held us accountable.
Be open to compromise while preserving the vision. The original bill was introduced in 2011 and called for standing up a new agency to provide standards and transparency. After discussions, debate and Congressional Budget Office cost estimates, it was decided that the best path was to embed the standards and reporting at the Treasury Department, which already had the expertise and mission to do this work. It took three years to pass the DATA Act and then three years to implement it.
Create a strong vision for implementation. On the implementation side, the vision was “better data, better decisions, better government.” We even created brand, logo and DATA Act stickers and circulated them everywhere across the government. This fueled the team to align and do big things even with short deadlines and resources.
Build an extensible standard for the data. We built a standard with only the minimally required data. Then we expanded the data requirements over time. We didn’t try to do everything at once.
When the next emergency happened — for example, during the pandemic — Treasury was able to add new identifiers to track the economic response. They also added identifiers to support the implementation of the historic infrastructure investments.
Understand that a data-centric model is key. We used existing data where possible. We didn’t create all new processes and giant new systems; we linked data from existing sources to gain access to the needed data. We created only a few new data elements to connect all the financial data across the government.
Include users in the implementation process. This is the hardest and maybe the most important point. When building the data broker to collect data from more than 100 agencies, we brought in agency data providers to test the data broker tool. And frankly, many didn’t want to test it. They said it was pointless. Until they participated.
Agency staff came to test sessions and gave feedback. They recommended changes. Two weeks later we invited them back and their changes had been fully implemented. They were shocked — usually it takes months to make any system changes. They said, “Wow! You already incorporated my feedback? I have more ideas.”
We turned those agency users into the biggest allies and champions for the data and the broker, because they could see how it would help them. We didn’t build the tool for them — they felt ownership and built it for themselves. We did the same for the public website, USAspending.gov, tapping external users as testers and allies.
Audit the data quality. This lesson, the last one learned, is also one of the most important: We included a provision in the law that required the data to be audited every two years. If Congress was going to rely on the data, we had to ensure its quality.
No one likes to be audited, but the findings of dozens of inspectors general and General Accounting Office auditors helped guide much-needed improvements in the data quality.
Based on what I’ve learned over the past 10 years, passing a new policy or law is challenging, but implementation is much harder. But as Sen. Warner said at our event, federal policymakers will likely need to pass another DATA Act to keep pace with changing technology, including the emergence of AI.
“We've still got work to do,” said Warner, a former Virginia governor. “I hope you'll continue to look to me and others. This is still a broadly bipartisan subject. The more we can move this along, the more we can have a better-informed citizenry, a more efficient use of our taxpayer dollars. At the end of the day that means a better community, a better state government and better federal government.”
Amy Edwards Holmes, a former deputy assistant treasury secretary and congressional staffer, is the executive director of the Bloomberg Center for Government Excellence at Johns Hopkins University.
Governing’s opinion columns reflect the views of their authors and not necessarily those of Governing’s editors or management.
Related Articles
