Evidence-Informed Policy Analysis for Government Policy Analysts Training Course

Course overview

Government policy analysts are expected to turn incomplete administrative data, programme evidence, research findings and stakeholder views into advice that can withstand ministerial scrutiny. In development and humanitarian settings, the challenge is intensified by uncertain baselines, political constraints, urgent delivery timelines and competing claims about what works. Poorly framed evidence can lead to weak problem definitions, untestable policy options, unrecognised distributional effects and decisions that cannot be defended in a briefing, business case or parliamentary response.

This course equips participants to build a disciplined evidence chain from policy problem to recommendation. Participants learn to define policy questions, develop theories of change, assess evidence quality, interpret descriptive and causal findings, commission proportionate analysis, and compare options using multi-criteria analysis, cost-effectiveness and distributional assessment. They practise distinguishing correlation from causation, identifying bias and uncertainty, integrating quantitative evidence with qualitative insight, and presenting findings through concise policy submissions, evidence matrices and decision-ready visualisations.

Teaching combines instructor-led technical sessions with government and humanitarian case work on issues such as social protection targeting, displacement response and public health programme design. Participants work with realistic evidence packs, administrative datasets and conflicting stakeholder evidence, using Excel and Power BI to test claims and communicate results. By the final day, each participant produces an evidence-informed policy analysis pack: a problem statement, theory of change, evidence assessment, options appraisal, recommendation and implementation learning plan that can be adapted for use in their own organisation.

The course is designed for analysts who already contribute to policy development and need stronger methods for judging evidence and advising decision-makers under uncertainty. It is equally relevant to staff preparing ministerial briefings, programme redesign proposals, spending submissions or humanitarian response policies.

Course objectives

By the end of this course, participants will be able to:

• Frame a policy problem using a problem tree, stakeholder analysis and decision-focused policy questions
• Construct a theory of change with explicit assumptions, causal pathways, indicators and evidence gaps
• Appraise research and evaluation evidence using relevance, methodological quality, bias and applicability criteria
• Interpret descriptive statistics, confidence intervals, effect sizes and causal claims for policy advice
• Build an evidence matrix that grades sources and links findings to policy options
• Compare policy options using multi-criteria analysis, cost-effectiveness and distributional impact criteria
• Create decision-ready charts and evidence summaries in Excel and Power BI
• Draft a policy recommendation pack containing an options appraisal, uncertainty statement and implementation learning plan

Benefits of attending

Target competencies

Who should attend

• Government Policy Analysts — who must develop defensible options and recommendations for senior decision-makers
• Development Programme Officers — who need to translate programme evidence into policy and funding decisions
• Humanitarian Policy Advisers — who assess intervention evidence under time, data and access constraints
• Monitoring, Evaluation and Learning Specialists — who need to connect evaluation findings to policy choices
• Economic and Social Researchers — who must communicate analytical findings in a usable policy format
• Public Sector Strategy Managers — who oversee policy portfolios and need consistent evidence standards across teams

Requirements and prerequisites

Participants should have practical experience contributing to policy papers, programme design, research, monitoring or evaluation in government, development or humanitarian organisations. They should be comfortable reading tables and charts, working with percentages and rates, and using spreadsheets for basic sorting, filtering and formulas. Familiarity with policy cycles, logical frameworks, theories of change or appraisal processes is helpful but not essential. Participants should bring a laptop with Microsoft Excel and, where possible, Power BI Desktop access. Advanced econometrics, coding, statistical software and prior impact-evaluation training are not required; causal concepts are taught from first principles.

Training methodology

The course uses short instructor-led inputs followed by applied analysis of a running government and humanitarian policy case. Participants interrogate evidence packs containing administrative data, evaluation summaries, survey findings and stakeholder testimony; then work individually and in small groups to assess quality, construct causal arguments and compare options. Facilitated peer review mirrors a policy clearance process, with participants testing whether claims are decision-relevant and defensible. Excel and Power BI workshops support practical analysis and communication. The final session converts learning into an individual policy analysis pack and workplace application plan.

Course outline

Day 1: Defining policy problems and decisions

• Decision-focused policy questions and analytical boundaries
• Problem trees, root causes and symptoms
• Stakeholder mapping and political-economy considerations
• Policy objectives, constraints and decision criteria
• Theories of change and causal pathway mapping
• Assumptions, risks and evidence gaps
• OECD DAC criteria as a policy evidence lens

Workshop: Participants develop a problem tree and theory of change for a social protection or humanitarian response policy case, producing a scoped evidence plan.

Day 2: Assessing evidence quality and causal claims

• Evidence hierarchies and their limitations
• Research relevance, transferability and applicability
• Selection bias, confounding and reverse causality
• Experimental and quasi-experimental evaluation designs
• Qualitative evidence, triangulation and lived-experience data
• Systematic reviews, rapid evidence assessments and evidence gap maps
• Evidence matrices and source-quality grading

Workshop: Participants appraise a mixed evidence pack on displacement assistance and produce a graded evidence matrix with limitations and implications.

Day 3: Analysing data for policy advice

• Administrative data quality, completeness and comparability
• Descriptive statistics, rates, ratios and disaggregation
• Confidence intervals, statistical significance and practical significance
• Effect sizes, counterfactuals and uncertainty statements
• Equity analysis by gender, geography, income and vulnerability
• Excel pivot tables, lookup functions and sensitivity tables
• Power BI dashboards and decision-focused visualisation

Workshop: Participants analyse a programme dataset in Excel and Power BI, producing a disaggregated findings dashboard and three evidence-backed messages.

Day 4: Designing and comparing policy options

• Generating a credible long list of policy options
• Do-nothing and baseline scenarios
• Multi-criteria decision analysis scoring models
• Cost-effectiveness, cost-benefit and value-for-money distinctions
• Distributional impacts and unintended consequences
• Sensitivity analysis and treatment of uncertainty
• HM Treasury Green Book appraisal principles

Workshop: Teams build an options appraisal for alternative targeting approaches, producing a weighted multi-criteria matrix and recommended option.

Day 5: Writing defensible recommendations and learning plans

• Structuring evidence-informed policy submissions
• Recommendation logic and ministerial decision points
• Writing clear caveats, confidence statements and limitations
• Evidence visualisation for briefing notes and slide decks
• Implementation indicators and adaptive management triggers
• Monitoring, evaluation and learning plans
• Peer review against an evidence-to-decision checklist

Workshop: Participants complete and peer-review an evidence-informed policy analysis pack containing a recommendation, options appraisal and implementation learning plan.

Tools & standards covered

Microsoft Excel, Microsoft Power BI, OECD DAC Evaluation Criteria, HM Treasury Green Book

A typical training day

Live online deliveries follow the same structure in the East Africa Time zone, with shorter screen blocks and longer breaks.

What the fee includes

How you can take this course

Certification

Participants who complete the full five days receive the Skillset Development Certificate of Completion, stating the course title, course code, dates and delivery format — suitable for professional-development records and employer reimbursement.

Frequently asked questions