The Integrated Data System Approach: A Vehicle to More Effective and Efficient Data-Driven Solutions in Government
Introduction: America’s Crisis in Public Trust
Public confidence and trust in government’s administration of public services in the United States is at an all-time low. Only 20 percent of Americans describe government programs as well run and say that they trust the federal government most of the time (Pew Research Center, 2017a). This crisis in confidence comes at a time when the U.S. population is larger and more diverse than ever (U.S. Census Bureau, 2017), and while the U.S. is shouldering a post-recession national debt of over $19 trillion. There is tremendous pressure on our government human service agencies to address complex social problems with less. So why are our government agencies perceived as so ineffective by the public?
Major policy analysts have identified outmoded and dysfunctional features of the American public problem-solving process that are not suited to addressing the complexity of our contemporary national problems (Kettl, 2002, 2009, 2012; Lindblom & Cohen, 1979). Government effectiveness is often thwarted by top-down, one-way, hierarchical leadership; compartmentalized bureaucracies with rigid boundaries; and no disciplined knowledge development-to-practice cycle that utilizes existing administrative data in an ongoing process to understand and solve problems. These barriers thwart effective, efficient, and ethical governance and undermine public trust in government’s ability to solve pressing problems.
Approaches to Public Administration Reform
Ineffective public administration management structures have led to a proliferation of responses. Most recently, the Office of Management and Budget (OMB) and the United States Congress have called for the cross-sector use of government collected administrative data to inform social problem-solving processes that lead to evidence-based policy. This resulted in the passage of H.R. 1831 in March of 2016, establishing the Commission on Evidence-Based Policy. The goal of the Commission is to identify and encourage innovative approaches that show how existing administrative data can be integrated and made available to facilitate “program evaluation, continuous improvement, policy-relevant research, and cost-benefit analyses,” and to identify concrete “infrastructures” to support these objectives while maintaining high “data security” (Evidence-based Policymaking Commission Act, 2016).
This most recent effort to transform American public administration reflects the core tenets of three key reform movements: (1) Performance Management (PM); (2) Evidence-Based Policy (EBP); and (3) Continuous Quality Improvement (CQI). Performance Management emanates from the public administration sector and it primarily seeks to bolster government accountability. PM requires goal setting toward the attainment of important, visible outcomes, strategic planning to identify the steps necessary to achieve those goals, and measurement of progress toward these ends (Moynihan, 2008). Based on the performance information generated, public administrators are held accountable for the agencies they oversee and their agencies’ ability to meet goals for public service through sanctions or rewards. The main focus of Evidence-Based Policy, which comes from the university research sector, is the incorporation of high-quality research into the policy-making process. This movement relies upon an accumulated body of rigorous scientific knowledge to inform the adoption of certain policies based on their demonstrated record of success. It also calls for independent program evaluations to ensure that policies are producing the expected results. Finally, Continuous Quality Improvement has emerged from the private business sector. This movement began as a response from critics of assembly-line production and regimented factory management and seeks to refocus business on the merits of more dynamic and innovative processes to create and build better products. Additionally, it emphasizes the necessity of creating a culture that encourages employees to make active contributions to improving those processes from their unique perspectives. Continuously improving upon an organization’s process will eventually produce a higher quality product, which is the ultimate goal of this movement. This requires attention to incremental improvements derived through a trial-and-error process.
Despite the useful core concepts upon which these movements are based, each has faced a unique set of challenges when applied to government and has remained in and of itself insufficient to reform American public administration. Performance Management has suffered, first and foremost, from its emphasis on performance outcomes and the corresponding sanctions and rewards associated with those outcomes. Because of this strict accountability focus, many public administrators have come to view the movement as a means of forced compliance reporting or a mechanism for public shaming (Waitt, 2010). In addition, the accountability-driven nature of PM has also led to data manipulation and gaming in this high-stakes environment, a side effect that ultimately undermines the entire improvement process by distorting the data through which outcomes are assessed (Heinrich, 2002). While accountability is undeniably important, especially in government, a single-minded focus on high-stakes accountability can distort a well-intended PM system. In contrast, Evidence-Based Policy maintains a dominant focus on research studies as the primary vehicle to effective public policies. While government is responsible to a diverse set of stakeholders and must engage in the policymaking process amid complex political sensitivities and competing interests, EBP demands that only high-quality science be considered in making important program and policy decisions—a demand that is unrealistic within the context of public administration (Jennings & Hall, 2012). Furthermore, there is often a presumption that all high-quality research is beneficial to policymakers when, in fact, much of the research generated is highly contextualized, precluding any generalizations or broad applications across contexts. Often, research that is directly relevant to the specific needs of policymakers and public administrators simply does not exist. Finally, adapting Continuous Quality Improvement from the private business sector to the public service sector has proven challenging due to a number of salient differences between these two realms. In comparison to private enterprise, the public sector lacks a defined customer, is not unified across departmental agencies, is beholden to a variety of stakeholders, tends to lack a singular strategic vision, and is often tasked with too many performance targets (Vinni, 2007). This movement requires an emphasis on processes over outcomes, an emphasis which is fundamentally incompatible with the public sector need for government scrutiny, accountability, and a focus on policy and program outcomes (Swiss, 1992). Thus, while Performance Management, Evidence-Based Policy, and Continuous Quality Improvement have singularly struggled to revolutionize the organizational management of public administration, all three of these movements have merit and their core tenets should be considered as we seek innovative approaches to improve public administration.
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