Evidence-Informed Policy and Development Planning Training Course

Participants can construct a results logic that connects problems, interventions, assumptions and intended outcomes.

• Problem trees trace immediate causes, structural drivers and observable consequences
• Baseline statements specify population, condition, location, period and magnitude
• SMART policy objectives distinguish outcomes from activities, outputs and targets
• Theory of Change maps causal pathways, assumptions, risks and interventions
• Logical Framework matrices align goal, outcomes, outputs, indicators and assumptions
• Results chains expose attribution limits and external contribution factors

Participants can formulate evidence questions and organise relevant sources for a policy decision.

• OECD evidence-informed policy principles distinguish evidence use from political judgement
• Evidence questions framed using population, intervention, comparator and outcome criteria
• Systematic review protocols define search terms, inclusion criteria and synthesis methods
• Administrative data assessed for coverage, completeness, timeliness and definitional consistency
• Qualitative evidence appraised through sampling, triangulation, reflexivity and transferability
• Evidence maps reveal gaps, concentration and relevance to policy questions

Participants can judge evidence quality, interpret uncertainty and identify limits on causal claims.

• Internal validity threats include selection bias, confounding, attrition and measurement error
• Randomised trials, quasi-experiments and observational studies compared for causal inference
• GRADE certainty ratings assess risk of bias, precision, consistency and applicability
• Confidence intervals, effect sizes and statistical significance interpreted for decisions
• Cost-effectiveness evidence separates average costs, incremental costs and distributional consequences
• Source appraisal records authorship, methods, limitations, funding and relevance

Participants can develop policy alternatives and recommend an option using explicit decision criteria.

• Longlist development combines regulatory, fiscal, service, behavioural and information instruments
• Multi-criteria decision analysis weights effectiveness, equity, feasibility, cost and acceptability
• UK Green Book options appraisal tests additionality, optimism bias and value for money
• Distributional analysis identifies winners, losers, mitigations and compensatory measures
• Scenario planning tests options against uncertainty, shocks and implementation conditions
• Recommendation papers state trade-offs, evidence strength and residual risks

Participants can specify measurable results, credible indicators and proportionate data arrangements.

• Indicator reference sheets define numerator, denominator, frequency, source and disaggregation
• Results frameworks connect objectives, indicators, baselines, targets and reporting responsibilities
• Data collection plans assign methods, sampling frames, safeguards and quality checks
• Disaggregated data exposes unequal access, outcomes and unintended exclusion
• Dashboard design prioritises decision thresholds, trend comparisons and action owners
• Data governance addresses consent, confidentiality, access controls and retention

Participants can estimate policy costs, test affordability and present value-for-money considerations.

• Fiscal impact analysis estimates recurrent costs, capital costs and revenue implications
• Unit-cost models separate volume assumptions, fixed costs and variable costs
• Budget envelopes test affordability across medium-term expenditure framework periods
• Sensitivity analysis examines cost drivers, uptake rates and inflation assumptions
• Procurement and delivery constraints inform realistic implementation sequencing
• Value-for-money narratives link costs to outcomes, equity and strategic priorities

Participants can prepare an implementation plan that addresses ownership, risks, capability and political constraints.

• Implementation plans specify workstreams, milestones, owners, dependencies and decision points
• RACI matrices clarify accountable authorities, delivery roles and consultation responsibilities
• Risk registers score likelihood, impact, controls, triggers and contingency actions
• Political economy analysis examines incentives, power, institutions and reform coalitions
• Change readiness assessments identify capability gaps, communications needs and resistance
• Pilot design sets learning questions, selection criteria, metrics and scale decisions

Participants can establish monitoring and evaluation arrangements that support timely management decisions.

• Monitoring plans establish indicator cadence, data owners, review forums and escalation
• Evaluation questions distinguish process, outcome, impact, efficiency and equity
• OECD DAC criteria structure relevance, coherence, effectiveness, efficiency, impact and sustainability
• Contribution analysis tests causal claims where experimental designs are infeasible
• Before-and-after comparisons recognise secular trends, regression effects and selection
• Adaptive management records decisions, evidence updates, course corrections and accountability

Participants can communicate evidence and recommendations clearly and prepare an application plan for a live assignment.

• Policy briefs structure problem, evidence, options, recommendation, costs and implementation
• Evidence grading communicates confidence, limitations and decision implications without false certainty
• Executive summaries use message hierarchy, quantified findings and clear calls
• Data visualisations select charts matching comparisons, trends, distributions and uncertainty
• Ministerial submissions distinguish decisions sought, key risks and clearance requirements
• Application plans assign a live policy question, evidence tasks and milestones