Implementing the DATA Act for greater transparency and accessibility
The federal DATA Act could increase internal management efficiency and transparency by creating an open data set for all federal spending. A Deloitte survey examines how to navigate the cultural and technological hurdles for successful implementation.
With data an often-underutilized asset in the public sector, enhancing availability and transparency can make a big difference in enabling agencies to use data analytics to their advantage—and the public’s. Thoughtful use of data-driven insights can help agencies monitor performance, evaluate results, and make evidence-based decisions. Having access to key facts can drive impressive improvements: When the United States Postal Service compiled and standardized a number of its data sets, the office of the USPS Inspector General’s data-modeling team was able to use them to identify about $100 million in savings opportunities, as well as recover more than $20 million in funds lost to possible fraud.1
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For government chief data officers (CDOs), one of the key drivers for data transparency is the federal government’s effort to implement wide-scale data interoperability through the Data Accountability and Transparency Act of 2014 (DATA Act), which seeks to create an open data set for all federal spending. If successful, the DATA Act could dramatically increase internal efficiency and external transparency.2 However, our interviews with more than 20 DATA Act stakeholders revealed some potential challenges to its implementation that could be important to address.
The DATA Act’s intent
Before addressing these implementation challenges, it may help to know how the DATA Act sets out to make information on federal expenditures more easily accessible and transparent.
Implementation of the DATA Act is still in its early stages; the first open-spending data set went live in May 2017.3 If the act is successfully implemented, by 2022, spending data will flow automatically from agency originators to interested government officials and private citizens through publicly available websites. This could save time and increase efficiency across the federal government in several ways, possibly including the following:
Spending reports would populate automatically. Agency leaders wouldn’t need to request distinct spending reports from different units of their agencies—the information would compile automatically. For example, a user could see the Department of Homeland Security’s spending at a summary level or review spending at the component level.
Congress could make appropriations more transparent. When crafting legislation, Congress could evaluate the impact of spending bills with greater ease. Shifting a few sliders on a dashboard could show the impact of proposed changes to each agency’s budget. Negotiations could be conducted using easy-to-digest pie charts reflecting each proposal’s impact.
Auditors would need to do less detective work. Auditors would have direct access to data describing spending at a granular level. Rather than often digging through disparate records and unconnected systems, auditors could see an integrated money flow. Using data analytics, auditors could gauge the cost-effectiveness of spending decisions or compare similar endeavors in different agencies or regions. These efforts could help root out fraud.
Citizens could see where the money goes. With greater spending transparency, citizens could have real-time clarity into how government decisions might influence local grant recipients, nonprofits, and infrastructure. It could be as easy for a citizen to see the path of every penny as it would for an agency head.
OMB’s data schema: The foundation for change
The DATA Act has the potential to transform various federal management practices. While much work remains to be done, the technology to support the DATA Act has already been developed, giving the act a strong foundation.4
The DATA Act mandates that the White House Office of Management and Budget (OMB) maintain a unified data format, or “schema,” to organize all federal spending reports. This schema, known as DAIMS (DATA Act Information Model Schema), represents an agreement on how OMB and the Department of the Treasury want to categorize federal spending.5 It’s a common taxonomy that all agencies can use to organize information, and it could shape how the federal government approaches budgeting for years to come. To allow other agencies to connect to DAIMS, OMB has built open-source software—the “Data Broker”—to help agencies report their data.
While the DATA Act deals with federal government data, it can indirectly affect how state and local governments manage their data as well. Data officers from state and local governments will likely need to be familiar with DAIMS and the Data Broker if they hope to collect grants from the federal government. And when contractors adopt federal protocols, they’ll likely prefer to report to states in a similar format.
Implementation challenges and approaches
As federal CDOs transform their organizations to meet the DATA Act’s new transparency standards, they could face a number of challenges, both cultural and technical.
If users see the DATA Act as a reporting requirement rather than as a tool, they are unlikely to unlock its full potential. Bare minimum data sets, lacking in detail, might satisfy reporting requirements, but they would fail to support effective data analytics. Likewise, users unfamiliar with the DAIMS system may never bother to become adept with it.
Technical challenges also threaten DATA Act implementation. Legacy reporting systems may not be compatible with DAIMS. The federal government currently identifies grant recipients and contractors using DUNS, the Data Universal Numbering System, a proprietary system of identification numbers with numerous licensing restrictions. A transparent federal data set won’t be able to incorporate new data sets from state and local partners unless those partners also spend scarce resources on the DUNS system to achieve compatibility. Lastly, the DAIMS schema, while a monumental achievement, will continue to need improvement. The current DAIMS schema fails to account for the full federal budgeting life cycle. Therefore, the ability to use the data to organize operations is incomplete at best.6
With care and commitment, however, these problems can be surmountable. Two steps CDOs can take are:
Convince managers to see the DATA Act as a tool, not a chore. To truly fulfill the DATA Act’s promise, workplaces should approach it as a managerial tool, not merely a reporting requirement. If managers use the DAIMS system to run their own organizations, the data they provide would be granular and more accurate. That said, one of the best ways to convince managers to adopt DAIMS for daily use will likely be through active congressional buy-in. If congressional budgeters and appropriators begin relying on DAIMS-powered dashboards to allocate funds, agency managers could naturally gravitate to the same data for budget submissions—and, eventually, for other management activities.
Educate users and managers to show them the benefits. Education can encourage agencies to incorporate DAIMS data into their own operations. One of the test cases for Data Broker, the Small Business Association (SBA), worked with technology specialists on the federal government’s 18F team to find uses for the new data system. In the process, they found mislabeled data, made several data quality improvements, and even discovered discretionary funds that they had thought were already committed.7 Agencies like the SBA, which experienced significant improvements, could evangelize the benefits of clean, transparent data for decision-making to the larger public sector community. Further, more can be done to invest in the upskilling of managers. This could help managers to develop a vision for how data can be used and begin to provide the resources needed to get there.
For all its laudable intent, the DATA Act may fail to deliver its full potential unless it is effectively executed. Some steps for the federal government to consider include:
Establish a permanent governance structure. Currently, OMB and Treasury are responsible for managing data standards for spending data. While this fulfills the basic mandates of the DATA Act, experts acknowledge that, with their current resources, these two agencies can’t do the work indefinitely.8 To ensure DAIMS’s flexibility and stability, a permanent management structure should oversee it for the long term.
Extract information directly from source systems. Currently, when a government agency awards a contract, it reports the contract data using several old reporting systems, many of which have well-documented accuracy problems.9 Currently, DAIMS extracts financial information from these inconsistent sources. The first major revision to DAIMS should require agencies to extract contract information directly from their source award systems. Going straight to the source for both financial and award data should lead to more efficient processing, boost data quality, and could save agencies time and effort.
Adopt a numbering system that anyone can use. Everyone, from local governments to American businesses, should be encouraged to integrate their own budgeting data with the federal government’s. Instead of using a proprietary numbering system that excludes participants, the government could consider adopting an open-source or freely available numbering system.
Expand the DAIMS to reflect the full budget life cycle. The federal budget follows a life cycle, from the president’s proposed budget to congressional appropriations to payments. To properly track the flow of funds through this life cycle, the spending data in DAIMS should reflect the budget as something that evolves over time from the beginning, with the receipt of tax revenues to final payments to grantees and contractors.
CDOs will likely recognize both the potential benefits of enhancing an organization’s ability to leverage data, and the challenges of changing the way public organizations manage data. CDOs would have to thoughtfully manage through the barriers to realize the potential benefits of readily available, transparent data. Leaders would be wise to prepare their own organizations for change even as the DATA Act takes hold at the federal level.