| name | impact-quantification |
| description | Estimate and communicate business impact of insights. Use when sizing opportunities discovered in analysis, calculating ROI of recommended actions, or prioritizing initiatives by potential impact. |
When to use
After an analytical finding surfaces a potential action, change, or opportunity. Use to produce a defensible numeric estimate that stakeholders can act on. Also use when prioritizing a backlog of initiatives — quantified impact is the primary ranking signal.
Process
- Classify the impact type — revenue growth, cost reduction, risk reduction, or efficiency gain. Each type has a different formula family (see
references/impact_quantification_framework.md).
- Gather inputs — collect baseline metrics, affected population size, expected lift/reduction, time horizon, and confidence level.
- Build the point estimate — use
scripts/revenue_impact.py for revenue/growth scenarios or scripts/cost_savings.py for cost/efficiency scenarios.
- Add uncertainty bounds — use
scripts/confidence_interval.py to produce low/base/high estimates. Never deliver a single number without a range.
- Document assumptions — fill in
references/assumption_documentation.md for every input that is estimated rather than directly measured; note the sensitivity of the output to each.
- Package the estimate — complete
assets/impact_estimate_template.md with the range, assumptions, confidence, and recommended action; optionally build the full assets/business_case_template.md for larger decisions.
Inputs the skill needs
- Baseline metric value (current state)
- Affected population or volume
- Expected change (lift %, absolute, or rate change)
- Time horizon (monthly / annual)
- Confidence level in inputs (high / medium / low)
Output
- Impact estimate with low/base/high range
- Assumption log (source and sensitivity for each input)
- Completed
impact_estimate_template.md or business_case_template.md
