Module 6: Analysis: Making sense of data and drawing conclusions about
impact
Good impact research needs good designs, selection of methods,
operationalization of concepts, and approaches to ensure validity and reliability.
However, one of the most frequent weaknesses of monitoring and evaluation is
the lack of a strategy, approach, or just a structured game plan for how you will
analyze all the data. Of course, this question needs to be asked early in the
design process itself.
The collection of resources below will help you design analytical approaches and
strategies for your data.
Analyzing Qualitative Data: Technical note for lead impact assessment
researchers. This two-page paper provides an outline of the basics of good
qualitative data analysis, including defining ‘analysis’, some analytic strategies
and common approaches, and specific techniques. It is a reminder to those who
already know something about analysis, rather than a comprehensive training
tool for novices.
→Full document
Social Analysis. This manual leads you through the full process of conducting
social analysis, including how to analyze the data.
 Full document
Secondary Data Analysis. Sometimes, we do not need to go out and collect our
own primary data. Instead, we can analyze existing data sets. This brief note
tells you how.
 Full Document
Data Analysis Technical Note. This brief how-to leads you through a primer on
causation and then walks you through three common analytical strategies. It
then covers a handful of common qualitative analytical techniques.
Full Document
CARE Bangladesh’ SII on Women’s Empowerment: A Discussion on Methods.
This has a section on methods used to analyze causality, establish validity and
reduce bias by researchers, including triangulation of the information through
discussions with elites, elected representatives and NGOs working in the area.
Another section describes how the researchers distilled and discussed the
findings of the research, including the shortcomings of the project.
→Summary
→Full document
What is triangulation? This is one-page that explains a technique for assuring
the reliability and credibility of qualitative research.
→ Full document
Changes from the Heart: Unlocking the Potential. Report on the Chhattisgarh
Reflective Practice Exercise. The methodology described in this short paper is
meant to produce rich discussions among participants about a program’s major
achievements, failures, lessons learned, and learning challenges for the future. It
is based on the principles of appreciative inquiry in that the focus is not on fault
finding, but reaching consensus on changes needed and how to achieve them.
Triangulation is achieved by repeating the same questions in different groups at
different levels.
→Summary
→Full document
Metaevaluation Analytical Guide. This document walks you through a step-bystep process for analyzing evaluation documents through a women’s
empowerment lens.
Full document
Promising Practices Inquiry on Women’s Empowerment: A practical guide to the
process. A PPI workshop is designed for country offices or project staff to
collectively identify, assess and gather evidence of promising practices for
promoting women’s empowerment. It has two parts, which complement and
reinforce each other. The first involves staff sharing their views about their work
on women’s empowerment and production of a short document describing best
practices and promising approaches. The second component is a peer review
process, in which two country offices exchange their documents and critique
what each has done toward promoting women’s empowerment.
→Summary
→Full document
La Piste. This document – in French – describes CARE Burundi’s innovative use
of the appreciative inquiry methodology to both better understand local context
and to alter relations of power between participants and CARE staff.
 Full document
And remember: please send in your own ideas about data analysis so we can
update this collection. You can send them to the PQDL librarian
(PQlibrarian@care.org ) or to pshift@care.org
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