Research design & methodology
Define answerable questions and align study design, measurement, sampling, data collection and analysis with the intended use of the findings.
Research & Evaluation
Rigorous research and evaluation designed around the question, evidence need and decisions the work must support.
From a research question to evidence that can be interpreted and used
Support is shaped around the problem—not a fixed package of methods or an unnecessarily complex model.
Researchers, programme teams and organisations may need to clarify a question, select a defensible design, analyse structured or mixed evidence, evaluate performance or outcomes, and communicate what the findings reasonably mean.
An engagement can cover one stage or connect several stages. It does not need to include the entire research workflow.
Research and evaluation support matched to the evidence need
Quantitative research
Support descriptive, exploratory and inferential analysis of structured data, with assumptions and uncertainty reported clearly.
Mixed-methods research
Integrate quantitative and qualitative evidence when the question benefits from complementary measurement and contextual enquiry.
Programme evaluation
Assess implementation, performance and outcomes using designs suited to the programme, context and available evidence.
Impact evaluation
Examine attribution only where the design, comparison strategy and data can support causal inference.
Secondary-data analysis
Develop focused questions from existing datasets and produce interpretable analyses, reporting and evidence-informed recommendations.
A connected path from question to decision support
Stages are selected and adapted to the scope; the sequence is a guide rather than a requirement for every engagement.
Research question
Design
Data
Analysis
Interpretation
Decision support
Methods should fit the question, data and level of inference
Rigour comes from alignment, transparency and proportionate choices—not from applying the most advanced method available.
Observational associations do not by themselves establish causality, and programme evaluation does not automatically constitute causal impact evaluation. Attribution claims require an appropriate design and evidence.
Statistical significance is considered alongside effect size, uncertainty and substantive importance. Mixed methods are used where integration adds value; a well-designed single-method study may be more appropriate. Simpler analyses are preferred when they answer the question adequately and more transparently.
Research across organisational and programme contexts
- Public health and health research
- Development and humanitarian programmes
- Socioeconomic and financial-inclusion research
- University and institutional research
Deliverables aligned with scope and audience
- Research protocols and analysis plans
- Study and measurement frameworks
- Statistical analyses and research tables
- Evaluation and analytical reports
- Interpretive evidence summaries
- Evidence-informed recommendations
Connect the question with deeper analytics and the research record
Explore advanced analysis in Data Science & Analytics, relevant scholarly work, or selected project contexts.
Have a research question, dataset or evaluation need to discuss?
Share the question, available evidence and reporting requirement to explore an appropriate scope.