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PART 1. Overview

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Chapter Summaries

  • Chapter 1. Introduction to The Government Analytics Handbook
    Chapter 1. Introduction to The Government Analytics Handbook

    Daniel Rogger and Christian Schuster


    Government analytics involves collecting, analyzing, and utilizing data to enhance the administration of government, enabling a realistic view of how government functions in practice. By providing an evidence-based platform for action, it highlights areas in need of improvement, and those that can be emulated. Whether repurposing existing government records or developing new measures, analytics can shed light on stark contrasts in how government operates, from prices paid for the same goods to the qualities of individual managers as perceived by their staff. Addressing these disparities can result in significant savings and improved working conditions for staff. In today's economy and society, where digitization and data analysis dominate other fields, government analytics has the potential to revolutionize the quality of government administration. This chapter showcases what the insights outlined in the Government Analytics Handbook mean for officials, managers, agency heads, and government leaders. While the public service presents unique challenges and requires a distinctive framework for measurement and analysis, the potential benefits are immense. With the aid of analytics, government organizations can improve their efficiency, effectiveness, and accountability, delivering better services to the public. Investments in measurement, data, and analytics have already revolutionized productivity in other sectors. It is time to turn the lens on public administration and revolutionize government.

  • Chapter 2. How to Do Government Analytics
    Chapter 2. How to Do Government Analytics
    Lessons from the Handbook

    Daniel Rogger and Christian Schuster


    How can practitioners and researchers undertake government analytics effectively? This chapter summarizes lessons from ‘The Government Analytics Handbook’. To structure these lessons, the chapter begins by introducing a public administration production function. The production function illustrates how different data sources – such as procurement data or civil service survey data – shed light on different parts of the machinery of government. Before turning to how specific data and analysis can inform an understanding of government, the chapter highlights lessons that should be kept in mind when undertaking any measurement and analysis of government administration. The core of the chapter then summarizes the lessons the Handbook contains for how to undertake government analytics. Our focus is on a core set of data sources that can be used to understand how government is functioning. These are administrative data, such as payroll data, procurement data, budget data, case data or text-as-data; survey data from surveys of public servants; and external assessments of government, for instance household or citizen surveys. The chapter concludes by showcasing how different data sources can be integrated to understand core challenges in the administration of government – from corruption to personnel management.

  • Chapter 3. Government Analytics of the Future
    Chapter 3. Government Analytics of the Future

    Daniel Rogger and Christian Schuster


    The investments governments make in measurement today will determine what they know tomorrow. Building an analytics system in government has long-term benefits for our ability to manage scarce public resources and detect unforeseen risks. The Handbook has outlined the motivation for such investments and provided guidance on how to direct them effectively. This chapter provides complementary guidance on the transition process implicit in the rest of the book: what can public organizations do today to become more analytical tomorrow? Government institutions themselves require reshaping: through enhanced structures for planning; by equipping public sector managers with a greater ability to consume and interpret analytics; and, through the development of a new architecture of analytical units. Facilitating each public sector organization to develop an analytics agenda of its own induces cultural change and targets those analytics to the requirements of its specific mission. Rewarding experimentation with novel data sources that are not yet a recognized analytical tool yields service-wide benefits. Each of these changes helps build an environment for analytical insights from across government, and charts a course to the government analytics of the future.

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    A collaboration between the Development Impact Evaluation Department, Office of the Chief Economist of Equitable Growth, Finance and Institutions.