Selecting Techniques
Cross-Cutting Methods
Identifying and gathering data
Library search methods
Interviewing for policy data
Quick surveys
Assessing information quality
Basic data analysis
Communicating the analysis


Selecting the appropriate techniques to use in policy analysis depends on a variety of factors:
what the client wants to know
the time available
knowledge of the decision criteria
complexity of the issue
available data
Some techniques commonly used in various stages of policy analysis include:
1. Verifying, Defining, and Detailing the Problem
Back-of-the-envelope calculations
Quick decision analysis
Creation of valid operational definitions
Political analysis
Issue paper/first cut analysis
2. Establishing Evaluation Criteria
Technical feasibility studies
Economic and financial feasibility studies
Political viability studies
Administrative operability studies
3. Identifying Alternatives
Researched analysis
No-action analysis
Quick surveys
Literature reviews
Comparison of real-world experiences
Passive collection and classification
Development of typologies
Analogy, metaphor, and synectics
Comparison with an ideal
Feasible manipulations
Modifying existing solutions
4. Assessing Alternative Policies
Theoretical forecasting
Intuitive forecasting
Cost/Benefit analysis
Sensitivity analysis
Allocation formulas
Quick decision analysis
Political feasibility analysis
Implementation analysis
Scenario writing
5. Displaying Alternatives and Distinguishing Among Them
Paired comparisons
Lexicographic ordering
Non-dominated alternatives method
Equivalent alternatives method
Standard-alternative method
Matrix display systems
Scenario writing
6. Implementing, Monitoring, and Evaluating Policies
Before-and-after comparisons
With-and-without comparisons
Actual-versus-planned performance
Experimental models
Quasi-experimental models
Cost-oriented approaches
7. Cross-Cutting Methods
Identifying and gathering data
Library search methods
Interviewing for policy data
Quick surveys
Basic data analysis
Assessing information quality
Communicating the analysis


Cross-cutting methods are techniques of policy analysis that can be used at nearly any stage in the analysis. They are useful tools for the policy analyst to know how to use. They include:
Identifying and gathering data
Library search methods
Interviewing for policy data
Quick surveys
Assessing information quality
Basic data analysis
Communicating the analysis


Policy analysts need to know how to search for existing information, such as
academic journal articles
census records
legislative history
news media reports
past policy analyses
public agency reports
public records
People are also good sources of information, including
advocacy groups
issue networks
personal contacts
professional colleagues
    Even personal observation can be a source of data. Personal observation can furnish data on usage patterns, compliance patterns, insights into the problem, anecdotes, and innovative suggestions. However, observation is time consuming and may suffer from problems with accuracy, bias, limited samples, and difficult to quantify data. Observational methods include "sidewalk surveys," mechanical counting devices, measures of erosion, satellite images, etc.
Other sources of information include:
federal agencies
local agencies
non-profit agencies
private organizations
research institutes
state agencies
think tanks
    Policy analysts should seek information from multiple sources ("triangulation"), especially on controversial data. Problems with sources of data include:
outdated statistics
irrelevant data
misleading data
poor quality data
biased data
    Looking for documents that may be helpful in doing the policy analysis is important. But three questions that must be asked are:
1) do such documents exist?
2) can they be obtained in a reasonable time?
3) when is additional searching no longer worthwhile?


    Libraries are excellent sources of policy-related information. To make the most of library resources, follow these strategies:
1) look up basic policy-related terms and definitions in encyclopedias, dictionaries, or a subject-related thesaurus; each policy issue area has its own terms and jargon
2) develop a list of search terms for searching computerized bibliographic data bases, electronic guides to library holdings, and Internet access;
3) identify key journals in the field and skim their table of contents for the past 1-2 years;
4) check guides to current periodicals, newspapers, news magazines, trade journals, and guides to the literature
5) check annual reviews in the policy subject area; conference proceedings on the subject; government hearings on the subject, etc.
The federal government offers a wide variety of sources:
Congressional Directory
Government Yearbooks
Guide to Federal Statistics
International Statistics
Population Reports
Statistical Abstract of the U.S.
U.S. Census
U.S. Government Printing Office catalogues
U.S. Government Manual
Many sources of legal information have bearing on policy issues:
Adjudication and case law
Agency regulations
Code of Federal Regulations
Federal and State statutes
Federal Register
Legal Periodicals
Municipal ordinances
Nexus-Lexis (on-line system)
Supreme Court decisions


    Interviewing is typically conducted with either mass, elite, intensive, or focus group methodologies. Interviewing is typically used:
to gather historical background, context, and evolution of the policy
to gather basic facts about the problem
to assess political attitudes and resources of major players
to gather ideas about the future, trends, and forecasts
to generate additional contacts and materials (snowball technique)
Elite (specialist) interviewing is most typically used when:
it is a short-term policy project
it is on a new topic
there is a lack of existing literature
informants are reluctant to put information into writing
no quantitative data are available
it is not feasible to use hired interviewers
To set up interviews, the policy analyst usually:
arranges appointments in advance
makes formal or informal requests (letterhead, telephone)
sends a reminder letter and follows up with a phone call
gives the name of a mutual friend or influential person as a reference
collects background information prior to the interview
will conduct a telephone interview if a face-to-face interview is not possible
When conducting the actual interview, it is usually accepted behavior to:
ask before using any recording device
promise anonymity and/or confidentiality of information
take notes during the interview
keep to the allotted time
thank the person for the interview
send a follow-up letter


    Surveys can be conducted by mail, in person, or by telephone. Survey methodology is described in many standard research texts. Cross-sectional interviews are conducted at one point in time across a wide sample of the population. Longitudinal interviews are conducted repeatedly over many time intervals (months, years, decades) with the same individuals. A comparison of the advantages and disadvantages of the most typical surveys is displayed below.
Type of 
Response Rate Sample Concerns Staffing Other concerns
Mail 15% May not be representative Least staff time required Response rate improves with gifts
Telephone 50% Limited to those with telephones Moderate staff time required Short and simple questions
In-Person 75% May be needed for less-educated Most intensive; most supervisors Can cover complex issues


    When collecting information and data for policy analysis, the analyst must assess the quality of the information and data collected.
Document Analysis:
When was the document generated?
What was the original purpose of the document?
Is there an obvious bias in the document?
What is the pattern of word usage?
Does the document omit important information?
Are there errors in the document?
Assessing Interviews:
Was the information plausible?
Was the information consistent?
Does the information diverge from accepted facts?
Did the respondent report direct experience?
Did the respondent have ulterior motives?
Did the respondent operate under some constraints?
Was the respondent candid?
Did the respondent acknowledge areas of ignorance?
Was the respondent self-critical?
Data quality:
Are multiple sources of information consistent?
Were data collected independently, from separate sources?
Is the data original or re-organized?
Do the data pertain to a particular geographic locale?
Were the data collection methods systematic?
For what purpose were the data originally collected?
How old are the data? Were they affected by timing?
Was there bias or special motivation in the collection of the data?


    Data are not generally useful in their raw form. Instead, they must be analyzed. Data are most often analyzed using descriptive and/or inferential statistics. Descriptive statistics search for patterns in the data and look for relationships to gain insight into the problem. Inferential statistics attempt to estimate a characteristic of a population from data gathered from a sample.

    Descriptive univariate statistics look for patterns in the data. They are best presented in graphical form, using frequency distributions, cumulative distributions, bar charts, histograms, pie charts, and frequency polygons. Statistics include the mean, median, and mode, as well as the range, stnadard deviation, and variance.

    Descriptive bivariate statistics look for relationships in the data. They are best presented in tables, plots, scattergrams, and time series graphs. Measures of association include Lambda, Gamma, and Pearson's r.

    Inferential statistics make probabilistic statements (or inferences) about a whole population based on the results obtained from a partial sample. Measures of statistical significance are used to estimate whether two groups differ from one another, or whether there is a chance that a relationship observed in a sample also exists in a population. These measures include Chi Square, Z-scores, t-tests, and F-tests.


Written Communication:
Work from an outline--keep separate folders for each section of the analysis
Work from goals and deadlines--generate a complete draft and then fill in the holes
Get help--with editing of rough drafts; revise for clarity; incorporate new ideas
Include a Table of Contents--sections include Executive Summary; Problem Definition; Decision Criteria; Alternatives; Comparison of Alternatives; Conclusions and Recommendations;
Use graphics--charts, graphs, flow charts, tables, maps, pictures, diagrams, drawings, etc.
Use geographic information systems (GIS)--to generate maps of data distributions
Simplicity--use the active voice for verbs
Accuracy--verify facts; triangulate; check all calculations
Documentation--note all formulas used and assumptions made
Fairness--use references and give credit to your sources of data
Neatness--use good grammar, spelling, punctuation, syntax, etc.
Oral Presentations
Know your audience
Keep it short and simple
Use visual aids and handouts
Allow time for questions, comments and criticisms