Data strategies for policymaking
Identifying international good practice: Final report
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With the move towards evidence-based policymaking, the need for high-quality data — which can include statistical and qualitative data, but also existing research — has increased for policy makers and public sector organisations. Against this background DG SANCO asked RAND Europe to explore international good practice of using data in policymaking. Based on previous research in this field, this report develops a conceptual framework for characterising and classifying the different elements of a data strategy for public sector organisations. This framework comprises the key questions of how to identify and define data needs, how to collect data, how to analysis and how to use data.
This framework is then applied to the analysis of thirteen cases studies. These thirteen case studies illustrate how different organisations in the fields of health, consumer, food and feed safety and animal welfare policy handle their data needs in policy making. The report concludes by identifying the key choices that need to be made in developing and implementing a data strategy for policymaking.
Table of Contents
Chapter One
Introduction
Chapter Two
A conceptual framework of data strategies
Chapter Three
Identifying and prioritising data needs
Chapter Four
Data collection
Chapter Five
Data management
Chapter Six
Data analysis
Chapter Seven
Data use
Chapter Eight
Revising the linear model
Chapter Nine
Conclusions and recommendations
Appendix A
Methodology
Research conducted by
The research described in this report was prepared for the European Commission Directorate General for Health and Consumers (DG SANCO) by RAND Europe.
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