impact-quantification

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

1. 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).
2. Gather inputs — collect baseline metrics, affected population size, expected lift/reduction, time horizon, and confidence level.
3. Build the point estimate — use scripts/revenue_impact.py for revenue/growth scenarios or scripts/cost_savings.py for cost/efficiency scenarios.
4. Add uncertainty bounds — use scripts/confidence_interval.py to produce low/base/high estimates. Never deliver a single number without a range.
5. 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.
6. 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