Value Attribution and Evidence Maturity
Use generic terminology and preserve the status of every material statement: observed fact, proposal, ratified decision, rejected decision, unresolved question, measured result, estimate, or causal claim.
Workflow
- List each value claim with population, period, unit, owner, and decision use.
- Classify its evidence as hypothesis, estimate, modeled projection, observed association, supported contribution, or causal evidence.
- Trace inputs, formulas, baselines, counterfactuals, uncertainty, sensitivity, and data lineage.
- Identify double counting, selection bias, displacement, cost omission, timing, and benefit persistence.
- Separate gross benefit, incremental benefit, cost, risk, and realized versus forecast value.
- State what design or additional evidence would strengthen or falsify the claim.
- Recommend language proportionate to the current evidence maturity.
Boundaries
- Do not turn a simulation, projection, correlation, or stakeholder report into causal proof.
- Do not hide uncertainty or negative outcomes in a single net figure.
- Do not publish financial or performance claims without separate review and authority.
Output
Return Claim register, Evidence maturity, Calculation and lineage, Attribution limits, Sensitivity, Supported language, and Next evidence.
1---2name: value-attribution-evidence-maturity3description: Assess claimed value, benefit, savings, risk reduction, or outcome contribution against an explicit evidence-maturity model. Use when stakeholders need to distinguish observed results, estimates, attribution, contribution, and causal claims.4license: MIT5---67# Value Attribution and Evidence Maturity89Use generic terminology and preserve the status of every material statement: observed fact, proposal, ratified decision, rejected decision, unresolved question, measured result, estimate, or causal claim.1011## Workflow12131. List each value claim with population, period, unit, owner, and decision use.142. Classify its evidence as hypothesis, estimate, modeled projection, observed association, supported contribution, or causal evidence.153. Trace inputs, formulas, baselines, counterfactuals, uncertainty, sensitivity, and data lineage.164. Identify double counting, selection bias, displacement, cost omission, timing, and benefit persistence.175. Separate gross benefit, incremental benefit, cost, risk, and realized versus forecast value.186. State what design or additional evidence would strengthen or falsify the claim.197. Recommend language proportionate to the current evidence maturity.2021## Boundaries2223- Do not turn a simulation, projection, correlation, or stakeholder report into causal proof.24- Do not hide uncertainty or negative outcomes in a single net figure.25- Do not publish financial or performance claims without separate review and authority.2627## Output2829Return Claim register, Evidence maturity, Calculation and lineage, Attribution limits, Sensitivity, Supported language, and Next evidence.30
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