benchmarking-analyst
Benchmarking study skill for internal, competitive, and best-in-class performance comparison
Best use case
benchmarking-analyst is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Benchmarking study skill for internal, competitive, and best-in-class performance comparison
Teams using benchmarking-analyst should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/benchmarking-analyst/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How benchmarking-analyst Compares
| Feature / Agent | benchmarking-analyst | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Benchmarking study skill for internal, competitive, and best-in-class performance comparison
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Benchmarking Analyst
## Overview
The Benchmarking Analyst skill provides comprehensive capabilities for conducting benchmarking studies. It supports internal, competitive, and best-in-class benchmarking, KPI normalization, best practice identification, and adaptation planning.
## Capabilities
- Benchmark partner identification
- KPI selection and normalization
- Data collection methodology
- Performance gap analysis
- Best practice identification
- Adaptation planning
- Progress tracking
- Benchmarking database maintenance
## Used By Processes
- CI-003: Benchmarking Program
- CI-001: Operational Excellence Program Design
- QMS-002: TQM Program Development
## Tools and Libraries
- APQC benchmarking database
- Industry consortiums
- Survey tools
- Data analysis platforms
## Usage
```yaml
skill: benchmarking-analyst
inputs:
benchmarking_type: "best_in_class" # internal | competitive | functional | best_in_class
focus_area: "Order fulfillment cycle time"
current_performance:
metric: "order_to_ship_days"
value: 5
benchmark_sources:
- type: "industry_database"
source: "APQC"
- type: "consortium"
source: "Supply Chain Council"
target_percentile: 90 # aim for top 10%
outputs:
- benchmark_study
- performance_gaps
- best_practices
- adaptation_plan
- implementation_roadmap
- tracking_metrics
```
## Benchmarking Types
| Type | Description | Use Case |
|------|-------------|----------|
| Internal | Compare across own sites/units | Identify internal best practices |
| Competitive | Compare to direct competitors | Understand competitive position |
| Functional | Compare to same function in other industries | Learn from leaders |
| Best-in-Class | Compare to world leaders | Achieve breakthrough performance |
## Benchmarking Process
### Phase 1: Planning
1. Identify what to benchmark
2. Form benchmarking team
3. Identify benchmark partners
4. Determine data collection method
### Phase 2: Analysis
1. Collect performance data
2. Determine performance gaps
3. Identify enablers of superior performance
4. Project future performance
### Phase 3: Integration
1. Communicate findings
2. Establish improvement goals
3. Develop action plans
4. Gain commitment
### Phase 4: Action
1. Implement plans
2. Monitor progress
3. Recalibrate benchmarks
4. Achieve maturity
## KPI Normalization
Normalize metrics for fair comparison:
- Per employee
- Per revenue dollar
- Per unit produced
- Per square foot
- Percent of total
### Example
```
Raw metric: Inventory value = $10M
Normalized: Days of inventory = 45 days
Industry benchmark: 30 days
Gap: 15 days (50% improvement opportunity)
```
## Performance Gap Analysis
| Performance Level | % of Benchmark | Action |
|-------------------|----------------|--------|
| Leading | >110% | Share best practices |
| Parity | 90-110% | Monitor and improve |
| Lagging | 70-90% | Targeted improvement |
| Poor | <70% | Major initiative needed |
## Best Practice Categories
1. **Process Design** - How work flows
2. **Technology** - Tools and systems used
3. **Organization** - Structure and roles
4. **People** - Skills and culture
5. **Metrics** - What is measured
## Integration Points
- Industry databases (APQC, Gartner)
- Consortium networks
- Performance management systems
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