Institutionalizing Big Data in the Federal Government: Key Issues
*Names in bold indicate Presenter
The emergence of “big data” offers a rich opportunity to observe the emergence and institutionalization over time and in political and economic context of a potentially disruptive innovation in government. The Obama Administration open data initiative overlaps with “big data” develops but only partially and problematically. Legal and regulatory frameworks to guide the collection, use, storage and transparency of big data currently are emergent. Big data offers potential to address policy problems but also poses challenges to fundamental understanding of the relationship between citizens and their government, specifically, in terms of privacy and security.
The Big Data Research and Development Initiative of the U.S. Office of Science and Technology Policy includes $200 million in new research and development investments by six federal departments and agencies. The initiative has as its goal development of tools and techniques to better collect, organization, analyze, and manage data to advance “scientific discovery, environmental and biomedical research, education and national security” (John Holdren). Moreover, the initiative will fund a series of new graduate programs to build human capital in data analytics.
On the other hand, federal bureaucracies face the daunting task of modifying performance programs and routines to encompass big data. For example, the Government Data Sharing Community of Practice, formed by the General Accountability Office initially to use data analytics as a tool to reduce waste, fraud and abuse has focused primarily on within-agency analytical processes. The first task of the group was to determine what data exist in the federal government and where. Initial meetings revealed that little cross-agency awareness has been developed in the federal bureaucracy regarding data. Moreover, incentives are lacking for agencies to build analytical information systems largely due to the institutional separation of program mission from oversight and control. Further bureaucratic challenges include the need to examine carefully the legal implications for agencies of data ownership and stewardship taking into account severe resource constraints on agencies as well as the requirements of FOIA and FISMA. Finally, government officials have been challenged by the ascendancy of performance measures in the Government Performance and Results Act Modernization Act (GPRAMA). Data analytics are often successful as preventative efforts. Yet measuring the success of preventative efforts is difficult under GPRAMA.
Ironically, most big data government projects currently lie within federal departments; few are cross-agency. Yet cases of failure that could be ameliorated through positive use of big data include food safety, energy efficiency, international trade, and federal statistics.
In sum, the U.S. federal bureaucracy is designed for fragmentation and inter-agency competition, institutional features that mitigate against use of big data.