industry-benchmarking

Industry Benchmarking

You perform autonomous industry benchmarking analysis. You research benchmark data yourself — do not ask the user for data they would need to look up. If the user provides their own performance metrics, compare them against researched benchmarks. Only ask the user for decisions and confirmations.

Input handling

Follow shared foundation §7 — interview mode. When input is missing or insufficient, interview to gather at minimum:

Dimension	Required	Default
Subject (company, product, or business unit)	Yes	—
Industry/market	Yes	—
Company size/stage	No	Inferred from subject
Geographic scope	No	Global
Domains to benchmark (financial, operational, etc.)	No	Auto-selected by industry
Own performance metrics	No	Benchmark standards only
Known peers	No	Will be researched

Exit interview when: Subject, industry, and size/stage are clear.

Phase 1 — Setup

1. Collect input

Accept one of:

• A company, product, or business unit name/description
• A file path to a business case document
• Pasted business case content with optional own metrics
• No input or vague input → enter interview mode (§7)

2. Detect scope

From the input (or interview results), identify:

• Subject: The company, product, or business unit
• Industry/market: Sector and segment
• Size/stage: Revenue band, employee count, maturity (startup/growth/mature)
• Geographic scope: Region or global
• Domains: Which metric domains to benchmark
• Own metrics: Any performance data the user provided

3. Confirm scope

Present detected scope:

**Subject**: [name]
**Industry**: [industry/segment]
**Size/stage**: [size band / maturity]
**Geographic scope**: [scope]
**Benchmark domains**: [listed or "auto-selected"]
**Own metrics provided**: [yes — listed / no — benchmark standards only]

Ask the user to confirm or adjust.

Ask diagram render mode and output path per the diagram-rendering and autonomous-research mixins.

Phase 2 — Research

Use WebSearch and WebFetch per the autonomous-research mixin.

2a. Industry benchmark data

Research:

• Industry reports with performance benchmarks (Gartner, McKinsey, Deloitte, PwC, APQC)
• Public company financials and filings (SEC EDGAR, annual reports)
• Sector-specific benchmark databases (OpenView for SaaS, Damodaran for financials)
• Professional association benchmarks (ASQ, APQC PCF)
• Government statistics (BLS, Census, Eurostat)

2b. Peer identification

Identify 8-15 comparable organizations based on:

• Size: Revenue band within 0.5x-2x of subject
• Geography: Same regulatory/cost environment
• Business model: Subscription vs transactional, product vs services
• Maturity stage: Startup vs growth vs mature

Present peer group for user confirmation.

2c. Data freshness

Flag any data older than 18 months with [Dated: YYYY]. Prefer recent sources.

Phase 3 — Metric Selection

Select 8-12 key metrics based on industry and business model. Use domain-specific metric sets:

SaaS/Tech

Metric	Good	Great	Elite	Source
ARR Growth	40%+	80%+	100%+	OpenView/KeyBanc
Gross Churn (monthly)	<2%	<1%	<0.5%	Industry benchmark
CAC:LTV Ratio	>3:1	>5:1	>7:1	Industry benchmark
CAC Payback	<18 mo	<12 mo	<6 mo	Industry benchmark
Rule of 40	40+	60+	80+	Bessemer
Net Dollar Retention	>100%	>120%	>140%	Industry benchmark

Financial (general)

Metric	What it measures
Gross Margin	Production efficiency
EBITDA Margin	Operating profitability
Net Margin	Bottom-line profitability
Revenue per Employee	Labor efficiency
ROIC	Capital efficiency
Current Ratio	Liquidity
Debt-to-Equity	Leverage

Operational

Metric	What it measures
Cycle Time	Process speed
Defect Rate	Quality
Capacity Utilization	Resource efficiency
On-time Delivery	Reliability

Marketing

Metric	What it measures
Customer Acquisition Cost (CAC)	Acquisition efficiency
Lifetime Value (LTV)	Customer value
Conversion Rate	Funnel efficiency
Cost per Lead	Lead generation efficiency

Product

Metric	What it measures
Net Promoter Score (NPS)	Customer satisfaction
Churn Rate	Retention
Feature Adoption Rate	Product-market fit
Time-to-Value	Onboarding efficiency

HR

Metric	What it measures
Turnover Rate	Retention
Revenue per Employee	Productivity
Cost-per-Hire	Recruitment efficiency
Engagement Score	Culture health

Technology

Metric	What it measures
Uptime / Availability	Reliability
Deployment Frequency	Delivery speed
MTTR	Incident recovery
Change Failure Rate	Delivery quality

Select domains most relevant to the subject. Document why each metric was chosen.

Phase 4 — Benchmark Data Collection

For each selected metric, gather:

Metric	P25	P50 (median)	P75	Best-in-class	Source	Year
[metric]	[value]	[value]	[value]	[value]	[source]	[year]

Where quartile data is unavailable, use available data points and label confidence:

• [Full distribution] — P25/P50/P75 available
• [Median only] — only median found
• [Estimated] — derived from limited data points
• [Proxy] — from adjacent industry

Phase 5 — Gap Analysis

If the user provided their own metrics, calculate gaps:

Metric	Subject	P50 (median)	Best-in-class	Absolute gap	Relative gap	Percentile
[metric]	[value]	[value]	[value]	[diff]	[%]	[est. Pxx]

Absolute gap: Benchmark - Current value Relative gap: (Benchmark - Current) / Benchmark × 100% Percentile: Estimated position in the distribution

If the user did NOT provide their own metrics, present the benchmark ranges as reference standards with guidance on how to self-assess.

Severity classification (per assessment extension)

Percentile	Severity	Meaning
Below P25	Critical	Significantly underperforming — immediate attention needed
P25 to P50	Warning	Below average — improvement opportunity
P50 to P75	Info	Average to good — optimize selectively
Above P75	—	Strong performance — maintain and leverage

Phase 6 — Composite Scoring

Create a weighted composite score:

Domain weights

Select weights based on strategic relevance (must sum to 100%):

Domain	Weight	Rationale
Financial	[X%]	[why]
Operational	[X%]	[why]
Marketing	[X%]	[why]
Product	[X%]	[why]
...	...	...

Scoring method

1. For each metric, normalize to 0-100 using min-max: score = (value - P25) / (P75 - P25) × 100 (capped at 0 and 100)
2. Average scores within each domain
3. Apply domain weights for composite score

Present as scorecard:

Domain	Score (0-100)	Grade	Key insight
Financial	[score]	[A/B/C/D]	[one-line insight]
Operational	[score]	[A/B/C/D]	[one-line insight]
Overall	[score]	[grade]

Grade mapping: A = 75-100, B = 50-74, C = 25-49, D = 0-24.

Phase 7 — Maturity Assessment (optional)

If relevant, assess organizational maturity across key dimensions:

Dimension	Level (1-5)	Description
[dimension]	[1-5]	[what this level means]

Maturity levels:

1. Initial — Ad hoc, reactive
2. Developing — Some structure, inconsistent
3. Defined — Standardized processes
4. Managed — Measured and controlled
5. Optimizing — Continuous improvement, industry-leading

Phase 8 — Prioritization

Plot gaps on an impact-vs-effort matrix:

Gap	Impact (1-5)	Effort (1-5)	Category
[gap]	[score]	[score]	Quick Win / Strategic Investment / Fill In / Deprioritize

• Quick wins: High impact, low effort — do first
• Strategic investments: High impact, high effort — plan and resource
• Fill ins: Low impact, low effort — do when convenient
• Deprioritize: Low impact, high effort — skip or defer

Phase 9 — Action Plan

For each priority gap:

#	Gap	Current	Target	Initiative	Owner	Timeline	Priority
1	[metric gap]	[current]	[target]	[what to do]	[role]	[timeframe]	Critical/High/Medium

Targets should be specific: "Close 50% of gap to P50 within 12 months" or "Reach P75 within 18 months."

Phase 10 — Diagrams

Generate 5 Mermaid diagrams:

1. Performance radar (comparison)

xychart-beta
    title "Performance vs Industry Benchmark"
    x-axis ["Metric 1", "Metric 2", "Metric 3", "Metric 4", "Metric 5"]
    y-axis "Score (0-100)" 0 --> 100
    bar [subject_scores]
    line [p50_scores]
    line [p75_scores]

2. Gap analysis bars

xychart-beta
    title "Gap Analysis — Current vs P50 Benchmark"
    x-axis ["Metric 1", "Metric 2", "Metric 3", "Metric 4"]
    y-axis "Value" 0 --> [max]
    bar [current_values]
    bar [benchmark_values]

3. Percentile ranking

xychart-beta
    title "Percentile Ranking by Metric"
    x-axis ["Metric 1", "Metric 2", "Metric 3", "Metric 4"]
    y-axis "Percentile" 0 --> 100
    bar [percentile_values]
    line [50, 50, 50, 50]

4. Prioritization matrix

quadrantChart
    title Gap Prioritization
    x-axis Low Effort --> High Effort
    y-axis Low Impact --> High Impact
    quadrant-1 Strategic Investments
    quadrant-2 Quick Wins
    quadrant-3 Fill Ins
    quadrant-4 Deprioritize
    [Gap 1]: [x, y]
    [Gap 2]: [x, y]

5. Maturity heatmap

xychart-beta
    title "Maturity Assessment"
    x-axis ["Strategy", "Operations", "Technology", "Culture", "Data"]
    y-axis "Maturity Level" 0 --> 5
    bar [level_scores]
    line [3, 3, 3, 3, 3]

The line at 3 represents "Defined" level — the industry-standard baseline.

Phase 11 — Diagram Rendering

Render diagrams per the diagram-rendering mixin.

File naming:

• performance-radar.mmd / .png
• gap-analysis.mmd / .png
• percentile-ranking.mmd / .png
• prioritization-matrix.mmd / .png
• maturity-heatmap.mmd / .png

Phase 12 — Report Assembly and Approval

Assemble the complete report:

# Industry Benchmarking: [Subject]

**Date**: [date]
**Industry**: [industry]
**Size/stage**: [size band / maturity]
**Geographic scope**: [scope]
**Metrics benchmarked**: [count]
**Peer group**: [count] peers

## Executive Summary
[3-5 sentences: overall score/grade, top strengths, critical gaps, key recommendation]

## Peer Group
[Peer table with selection rationale]

## Benchmark Metrics
[Metric selection rationale]
[Benchmark data table with P25/P50/P75/best-in-class]

## Gap Analysis
[Gap analysis table with absolute/relative gaps and percentile rankings]
[Performance radar diagram]
[Gap analysis diagram]
[Percentile ranking diagram]

## Composite Scorecard
[Domain scores, grades, weights, overall score]

## Maturity Assessment
[Maturity table and heatmap diagram]

## Prioritization
[Impact-effort table]
[Prioritization matrix diagram]

## Improvement Roadmap
[Action plan table with targets, initiatives, timelines]

## Sources
[Numbered list with publication dates]

## Assumptions & Limitations
[Explicit list]

Present for user approval. Save only after explicit confirmation.

Generation rules

Per the autonomous-research mixin, plus:

• Benchmarks: Always show distribution (P25/P50/P75), not just single values
• Normalization: Metrics must be normalized for fair comparison (per employee, per revenue, percentages)
• Peer group: Must be explicitly defined with selection criteria
• Gaps: Present with context (root cause, severity) not just numbers
• Targets: Must be specific and time-bound, not vague
• Weights: Composite score weights must be documented with rationale
• Sources: Every benchmark value must reference its source with publication date
• Data freshness: Use data from last 18-24 months. Flag older data with [Dated: YYYY]
• Language: Respond and generate in the user's language unless specified otherwise

Failure behavior

Situation	Behavior
No subject provided	Enter interview mode (§7) — ask what company/product to benchmark
Subject too vague	Enter interview mode (§7) — ask targeted questions
No benchmark data found for industry	Use adjacent industry benchmarks, label as [Proxy: adjacent industry]
User provides own metrics	Compare against researched benchmarks, show gaps
User provides no own metrics	Present benchmark ranges as reference standards
Insufficient data for percentile ranking	Use available data, label confidence level
Data older than 18 months	Flag with [Dated: YYYY], proceed with caveat
Peer group too small (<5)	Expand criteria, explain trade-off
mmdc / web search failures	See diagram-rendering and autonomous-research mixins
Out-of-scope request	"This skill performs industry benchmarking. [Request] is outside scope."

Self-check

Before presenting output, verify:

[] 8-12 metrics selected and justified
[] Benchmark data shows P25/P50/P75 distribution (not just averages)
[] Peer group defined with 8-15 peers and selection rationale
[] Metrics normalized for fair comparison
[] Gap analysis includes absolute gap, relative gap, and percentile ranking
[] Composite score shows weights, methodology, and domain breakdown
[] Severity classification applied (Critical/Warning/Info per percentile band)
[] Every gap has root-cause context and actionable recommendation
[] Action plan has specific, time-bound targets
[] All 5 Mermaid diagrams included and render valid syntax
[] Every benchmark value sourced with publication date
[] Assumptions explicitly labeled
[] No fabricated data