Essential Statistics for Public Managers and Policy Analysts

Evan M. Berman, XiaoHu Wang

• Verlag: CQ Press
• Jahr: 2016
• ISBN:
  9781506364292
• Auflage: 4
• Thema: Politics & International Relations
• Thema: Public Affairs & Administration

Known for its brevity and student-friendly approach, Essential Statistics for Public Managers and Policy Analysts remains one of the most popular introductory books on statistics for public policy and public administration students, using carefully selected examples tailored specifically for them. The Fourth Edition continues to offer a conceptual understanding of statistics that can be applied readily to the real-life challenges of public administrators and policy analysts. The book provides examples from the areas of human resources management, organizational behavior, budgeting, and public policy to illustrate how public administrators interact with and analyze data.

Chapter 1 Why Statistics for Public Managers and Policy Analysts?

Chapter Objectives

After reading this chapter, you should be able to

• Appreciate the importance of using data in public management and policy analysis
• Identify levels of competency and proficiency in data analysis
• Describe strategies for increasing proficiency in data analysis
• Understand the importance of ethical principles in data analysis

Role of Data in Public Management

Why research? Why statistics? The ethos of public management is to “go out and make a difference,” not to sit behind a desk and crunch numbers. Public managers often join agencies because they seek to serve and help their communities and country. Not surprisingly, some managers are puzzled by the suggestion of engaging in research and statistics: research appears boring in comparison with developing and implementing new programs, and statistics seems, well, impossibly challenging with little payoff in sight.

In fact, analytical techniques involving research and statistics are increasingly in demand. Many decisions that public and nonprofit managers make involve data and analysis, one way or another. Consider the following common uses of analysis and data.

First, data and objective analysis often are used to describe and analyze problems, such as the magnitude of environmental disasters (for example, oil spills), the extent of social and public health problems (such as homelessness or the AIDS epidemic), the extent of lawlessness, the level of economic prosperity or stagnation, or the impact of weather-related problems such as brought on by hurricanes and snowstorms. For example, it matters whether the illiteracy rate among 12-year-olds is 3 percent or 30 percent, or somewhere in between. By describing the extent of these problems and their underlying causes accurately, managers are able to better formulate effective strategies for dealing with them. Policy analysis often begins by describing the extent and characteristics of problems and the factors associated with them.

Second, data are used to describe policies and programs. What are programs and policies expected to achieve? How many services are programs expected to provide? What are some milestones of achievement? How much will a program cost? These questions involve quantifiable answers, such as the number of national guardsmen brought in to assist with search and rescue efforts after a major hurricane, or the number of evacuees for whom officials expect to provide refuge. Analysis helps think about policies and programs in detailed ways, linking resources to efforts to outputs and final outcomes, and a need exists to attach numbers to these elements, such as the level of resources committed to literacy programs and their results, and so on. Policies and programs can be described in quite detailed ways, involving distinct program activities, the duration and geographic scope of activities, and staffing levels and area program budget data.

Third, policies and programs produce much routine, administrative data that are used to monitor progress and prevent fraud. For example, hospitals produce a large amount of data about patient visits, who attended them, their diagnoses, billing codes, and so on. Regulatory programs produce data about inspections and compliance. In many states, gaming devices (such as slot machines) are monitored electronically to ensure that taxes are collected and that they are not tampered with. Administrative data assist in monitoring policies and programs, and managers are expected to be familiar with these data, and provide careful tracking of them.

Fourth, analysis is used to guide and improve program operations. Data can be brought to bear on problems that help managers choose among competing strategies. Some examples are the “big data” uses by large city policy departments, and increasingly broader “Citistat” programs that track a broad number of services to citizens. But examples are found at all levels, including in departments that lack expensive data systems. A modest amount of data and a spreadsheet can be sufficient for a “what-if” analysis that assesses the cost-effectiveness of alternative courses of action. In addition, systematic surveys provide valid and objective assessments of citizen and client needs, priorities, and perceptions of programs and services that are also used to improve programs.

Fifth, data are used to evaluate outcomes. Legislatures and citizens want to know what return they are getting from their tax dollars. Did programs and policies achieve their aims? Did they produce any unexpected results? Most grant applications require public managers to be accountable for program outcomes. Public managers must demonstrate that their programs are producing effective outcomes and that they are doing so in cost-effective ways. This demand for outcome evaluation and monitoring far exceeds any requirement of proper funds management; it requires a comprehensive framework. Analysis can also be used to determine the impact of different conditions on program effectiveness, leading to suggestions for improving programs.

Data and analysis are thus omnipresent in programs and policies. They are there at every stage, from the inception of programs and policies to their very end. Of course, decisions are also based on personal observations, political consensus, anecdotal and impressionistic descriptions, and the ideologies of leaders. Yet analysis and data often are present, too, one way or another. Specifically, quantitative analysis aids in providing an objective, factual underpinning of situations and responses. Even more, analysis is more than data analysis; it is grounded in research methods that provide a rigorous way of understanding policies and programs, and about asking certain questions about them. Analysis helps examine and quantify the extent of problems, solutions, and likely impact of proposed strategies in ways that other information seldom can. At the very least, a focus on facts and objective analysis might reduce judgment errors stemming from overly impressionistic or subjective perceptions that are factually incorrect. Managers are expected to bring data and analysis to the decision-making table.

Getting Started

How are these uses of data and analysis present in your field?

Competency and Proficiency

Competencies. Analysis requires competency and proficiency. The accrediting organization, the Network of Schools of Public Policy, Affairs, and Administration (NASPAA), requires that such programs in public policy and administration provide evidence of their graduates’ abilities in five “universal required competencies,” and most (if nearly all) programs require statistics to help meet this. Students must have skills to participate in and contribute to the policy process; lead and manage in public governance; communicate and interact productively with a diverse and changing workforce and citizenry; analyze, synthesize, think critically, solve problems, and make decisions; and articulate and apply a public service perspective.¹ As Henry notes, “empirical data and analysis are important forms of currency in the policy process . . . and one must be aware of the potential misuse of statistical analysis,”² hence requiring foundation in research methods and the ability to produce valid conclusions from data, generate data in valid ways, and communicate these effectively to diverse stakeholders and leaders. Statistics are obviously also involved in managing organizations, analyzing performance, workforce issues, financial management, and more, while applying a public service perspective further shapes the content (what is analyzed) and the communication of analysis. Thus, consensus exists that the statistics course contributes in many ways to meeting NASPAA accreditation standards.

Other accreditation bodies also recognize the role of quantitative skills. The relatively new International Commission on Accreditation of Public Administration Education and Training Programs (ICAPA) drafted its standards in cooperation with a United Nations task force. It states that curriculum components should include the “application of quantitative and qualitative techniques of analysis” in such areas as “institutional and developmental economics,” “policy and program formulation, analysis, implementation and evaluation,” and “decision-making and problem-solving.”³ The European Association for Public Administration Accreditation (EAPAA) follows a similar, “mission-based” accreditation approach as NASPAA, but without identifying five specific competencies. Rather, it states that programs must provide evidence that “curriculum components . . . produce professionals capable of intelligent, creative analysis and communication, and action in the public sector,” that “courses taken to fulfil the core curriculum components provide research methods,” and that the program includes “adequate training of practical skills.” Having some level of quantitative ability is surely consistent with this, too, of course.⁴

In short, the overwhelming consensus is that public managers and policy analysts need a firm grasp on analyzing data and their uses in policy and managerial processes, though programs have much leeway to define the way they bring statistics and analysis to furthering this. This capacity for leading policy and management implies the need for six competencies for analysis. First, managers and analysts should be familiar with data sources in their lines of business. They will need to know what data are available and to what uses they are commonly put. For example, are they used for monitoring? For estimating service needs? For determining program efficiency? For describing community conditions? Managers will also need to assess the validity of these data, and know the criteria by which validity is judged, including the processes and purposes for which they have been collected. Indeed, managers will need to know what sources of intelligence exist in their area, and data sources are an important and necessary part of that.

Second, managers and analysts need competencies to gather their own data. Simply, existing data do not always address important issues at hand. For example, they may not be adequate to determine client needs or evaluate programs. The ability to collect new data implies familiarity with and competencies in conducting different types of research, such as archival research, or in conducting scientific population or program client surveys. Many managers value the ability of their staff to conduct these types of research. Client and citizen surveys are increasingly a staple of public management. Sometimes, data are assembled from ongoing operations or large, “big data” sets in ways that provide analysts with the datasets they need.

Third, public managers and analysts need to be able to analyze the data. Without analysis, it is not possible to generate meaningful information about program efficiency and effectiveness, for assessing whether a program is on track, and for determining and identifying new client needs. Analysis requires competency in statistics. Analysis must be done in ways that shine light on important problems. It must also be done in ways that are sound, defensible, objective, and consistent with current practice. Policy analysts are often called upon to put existing data to new uses; this requires the development of creative skills and insight.

Fourth, public managers and analysts should be able to communicate their results. Communication requires the ability to explain complex or abstract concepts in ways that are suited to very different audiences—both those with very little understanding of statistics as well as those with deep professional skills. Results should be explained in simple ways that are easy to understand without oversimplifying. Communication also involves effective writing and presentation skills; yes, analysts must also be able to produce clear, professional-looking graphs and charts tha...