Date of Award


Document Type

Campus Access Dissertation

Degree Name

Doctor of Philosophy (PhD)


Public Policy

First Advisor

Heather MacIndoe

Second Advisor

Michael Johnson

Third Advisor

Amy Smith


Data-driven decision-making is a well-established management strategy in the private sector (Liberatore & Luo, 2010). Under pressure to adapt similar techniques to the public sector, many public organizations have adopted “performance management” (PM) programs to measure, track and report their performance. Major components of PM typically include strategic planning, identification of performance measures, systematic data collection and routine monitoring of performance. While private firms have used similar techniques to increase profits, the public sector faces unique challenges when attempting to identify how PM can lead to more effective and responsive government (Van Dooren, 2011). Public organizations often face challenges when attempting to establish clear goals, quantify their progress and demonstrate outcomes. A wide range of scholarship on public sector PM has examined the social and political movement behind PM, the strengths and weaknesses of PM as a public administration technique and the implications of performance management for public organizations (Obsorne & Gaebler, 1992; Wholey, 1999; Kellough, 1998). Despite gains in our understanding about the adoption of performance management programs, more research is needed to understand how performance data is used to inform decision-making in the public sector. This dissertation helps fill this void by examining: What factors influence the adoption of PM for decision-making in state agencies? How do state agencies use PM data to inform decision-making? A case study design examines PM in Massachusetts state executive agencies through in-depth semi-structured interviews of public employees and consultants and an analysis of secondary data from Massachusetts. Results suggest that strong leadership, staff that are aligned around organizational goals and the availability of reliable and timely data help drive PM use in state agencies. More importantly, results suggest that successfully using PM for decision-making is a complex challenge that requires extensive coordination of resources such as staff, technical expertise, data, technology and consultants.


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