Comp benchmarking

Compensation Benchmarking Skill

Overview

The Compensation Benchmarking skill provides capabilities for analyzing market compensation data and establishing competitive pay structures. This skill enables market percentile positioning, salary range development, and compensation competitiveness monitoring.

Capabilities

Survey Data Analysis

• Import and analyze salary survey data
• Blend multiple survey sources
• Age and trend data appropriately
• Handle different data cuts
• Validate data quality

Market Positioning

• Calculate market percentiles and positioning
• Determine competitive positioning strategy
• Analyze positioning by job family
• Track positioning trends
• Compare against target percentile

Salary Range Development

• Build salary range structures
• Calculate range spread and midpoint
• Design grade structures
• Create multiple range types (broad, narrow)
• Support geographic differentials

Scenario Modeling

• Model compensation scenarios and costs
• Project budget impacts
• Analyze merit increase scenarios
• Model structure adjustments
• Calculate cost of living impacts

Reporting

• Generate market pricing reports
• Create competitiveness summaries
• Build survey participation reports
• Document market data sources
• Track year-over-year trends

Geographic Analysis

• Create geographic pay differentials
• Analyze location-based pay
• Support remote work pay strategies
• Map cost of labor differences
• Handle multi-location structures

Usage

Market Analysis

const marketAnalysis = {
  surveys: [
    { source: 'Radford', weight: 40, year: 2026 },
    { source: 'Mercer', weight: 35, year: 2026 },
    { source: 'Compensation Surveys Inc', weight: 25, year: 2025 }
  ],
  aging: {
    rate: 3.5,
    targetDate: '2026-07-01'
  },
  cuts: {
    industry: 'Technology',
    companySize: '1000-5000',
    geography: 'US National'
  },
  jobs: [
    {
      internal: 'Senior Software Engineer',
      surveyMatch: 'Software Engineer IV',
      matchQuality: 'strong'
    }
  ],
  positioning: {
    targetPercentile: 50,
    hotJobs: ['Machine Learning Engineer', 'Security Engineer'],
    hotJobTarget: 75
  }
};

Range Structure Design

const rangeStructure = {
  type: 'traditional',
  grades: 10,
  midpointProgression: 12,
  rangeSpread: {
    byGrade: {
      '1-3': 40,
      '4-6': 45,
      '7-10': 50
    }
  },
  overlap: 35,
  anchoring: {
    method: 'market-midpoint',
    targetPercentile: 50
  },
  differentials: {
    geographic: {
      enabled: true,
      tiers: ['Tier 1', 'Tier 2', 'Tier 3']
    }
  }
};

Process Integration

This skill integrates with the following HR processes:

Process	Integration Points
salary-benchmarking.js	Full market pricing workflow
job-evaluation-leveling.js	Job matching
pay-equity-analysis.js	Market data input

Best Practices

1. Multiple Sources: Use at least 2-3 survey sources
2. Quality Matching: Ensure strong job matches to market data
3. Regular Updates: Refresh market data at least annually
4. Consistent Methodology: Apply aging and cuts consistently
5. Documentation: Document all assumptions and methodology
6. Stakeholder Communication: Explain positioning philosophy

Metrics and KPIs

Metric	Description	Target
Compa-Ratio	Employee pay vs. range midpoint	95-105%
Market Position	Actual percentile vs. target	Within 5 points
Range Penetration	Distribution within ranges	Normal distribution
External Competitiveness	Offer acceptance rate	>85%
Survey Participation	Surveys participated in	>3 annually

Related Skills

• SK-012: Job Evaluation (job matching)
• SK-014: Pay Equity (equity analysis)