Nonprofit Results-Based Management (RBM) Logic Model
Goal
Produce a complete, donor-ready Results-Based Management (RBM) logic model that clearly links resources to long-term change and includes measurable indicators and monitoring guidance.
Workflow
- Gather core context before drafting:
- Program problem and intervention summary
- Target population and inclusion priorities
- Geography and implementation scope
- Time horizon (for example, 1 year outcomes vs 3-5 year impact)
- Donor/reporting constraints (United States Agency for International Development (USAID), United Nations (UN), European Union (EU), internal template)
- Baseline availability and data constraints
Ask up to five high-leverage clarifying questions when critical context is missing. If details remain unknown, proceed with explicit assumptions.
Build a five-level logic model:
- Inputs
- Activities
- Outputs
- Outcomes (short/medium term changes)
- Impact (long-term societal/system change)
- Keep causal logic explicit and testable:
- Avoid listing activities as outcomes
- Avoid describing deliverables as impact
- Use concrete, time-bound outcome statements where possible
- Define indicators for each outcome:
- Provide 3-5 Specific-Measurable-Achievable-Relevant-Time-bound (SMART) indicators per outcome
- Include definition/formula, baseline, target, frequency, and data source
- Include disaggregation guidance (for example sex, age, location) when relevant
Map outcomes and impact to relevant Sustainable Development Goals (SDG) goals and targets only when there is a defensible link.
Propose a practical data collection plan:
- Baseline and endline timing
- Routine monitoring frequency
- Follow-up windows (for example 3/6/12 months)
- Data quality checks and accountability owner
- Return output in the required format.
Output Format
- Theory of Change (if/then statement plus causal pathway and key assumptions)
- Executive Summary (2-3 sentences)
- Logic Model Table (Inputs to Impact)
- Outcome Indicators (group by outcome)
- Sustainable Development Goals (SDG) Alignment (goal and target references)
- Data Collection Plan (method, frequency, owner)
- Assumptions and Risks (recommended when uncertainty exists)
Quality Rules
- Prefer numeric targets and time bounds over vague language.
- Distinguish outputs from outcomes:
- Outputs are products/services delivered.
- Outcomes are changes in behavior, conditions, or systems.
- Keep impact long-term unless user requests a shorter horizon.
- State assumptions explicitly for any inferred values.
- Flag missing baseline data and suggest how to collect it.
Reference Usage
Use references/rbm-framework.md when you need:
- Indicator templates
- Sector-specific indicator ideas
- Sustainable Development Goals (SDG) mapping shortcuts
- A complete worked example