Analyze compensation data, create salary bands, and ensure pay equity. Use this skill when benchmarking salaries, building compensation structures, or analyzing pay equity. Activate when: compensation, salary, pay equity, salary bands, compensation analysis, total rewards, salary benchmark.
Build fair, competitive compensation structures.
## Band Structure
| Level | Title Examples | Band Width | Typical Range |
|-------|---------------|------------|---------------|
| L1 | Associate, Junior | 20% | Entry level |
| L2 | Mid-level, Specialist | 25% | 2-4 years exp |
| L3 | Senior, Lead | 30% | 5-8 years exp |
| L4 | Staff, Principal | 35% | 8-12 years exp |
| L5 | Director, Senior Staff | 40% | 12+ years exp |
## Band Positioning
| Position | % of Midpoint | When to Use |
|----------|--------------|-------------|
| Below Min | <80% | Rarely, new to role |
| Min | 80% | New to level |
| Target | 90-100% | Fully competent |
| Midpoint | 100% | Market rate |
| Above Mid | 100-120% | High performer |
| Max | 120% | Exceptional, at cap |
## Step 1: Market Data
- Gather salary data from 3+ sources
- Sources: Radford, Mercer, Levels.fyi, Glassdoor, Payscale
- Match to job families and levels
## Step 2: Determine Positioning
| Strategy | Market Position | When to Use |
|----------|----------------|-------------|
| Lead | 75th percentile | Talent-competitive roles |
| Match | 50th percentile | Standard roles |
| Lag | 25th percentile | Budget constraints |
## Step 3: Set Band Width
- Narrower bands (20%): Entry-level, structured roles
- Wider bands (40%): Senior, variable roles
## Step 4: Calculate Ranges
Midpoint = Market rate at target percentile
Min = Midpoint × (1 - Band Width/2)
Max = Midpoint × (1 + Band Width/2)
Example (30% band, $100K midpoint):
- Min: $100K × 0.85 = $85,000
- Max: $100K × 1.15 = $115,000
## Step 1: Data Collection
Required fields:
- Base salary
- Job level/band
- Department
- Location
- Tenure
- Gender
- Race/ethnicity (where legally collected)
- Performance rating
## Step 2: Group Comparison
Compare pay within:
- Same job level
- Same department
- Same location
- Similar tenure
## Step 3: Statistical Analysis
- Calculate pay gap percentages
- Run regression analysis controlling for:
- Job level
- Experience
- Performance
- Location
- Education (if relevant)
## Step 4: Identify Outliers
Flag individuals who are:
- >5% below expected pay
- >10% above expected pay
- Unexplained by legitimate factors
## Raw Pay Gap
(Avg Male Salary - Avg Female Salary) / Avg Male Salary × 100
## Adjusted Pay Gap
Difference after controlling for:
- Job level
- Department
- Location
- Experience
- Performance
## Compa-Ratio
Individual Salary / Band Midpoint × 100
Target: 90-110%
## Base Salary
- Fixed annual pay
- Typically 60-80% of total comp
## Variable Pay
### Bonus
- Target %: [X]% of base
- Performance multiplier: 0-200%
- Payout timing: Annual/Quarterly
### Commission (Sales)
- On-target earnings (OTE)
- Split: [X]% base / [X]% variable
- Accelerators above quota
## Equity
### Stock Options
- Grant value at hire
- Vesting: Typically 4 years, 1-year cliff
- Refresh grants
### RSUs
- Restricted Stock Units
- Same vesting as options
- Value = shares × stock price
## Benefits Value
- Health insurance: $[X]/year
- 401(k) match: [X]% up to $[X]
- Other benefits: $[X]/year
## Total Rewards Statement
Base Salary: $XXX,XXX
Target Bonus: $XX,XXX
Equity (annual): $XX,XXX
Benefits: $XX,XXX
Total Compensation: $XXX,XXX
## Annual Review Cycle
### Timeline
| Month | Activity |
|-------|----------|
| Q3 | Budget planning, market data refresh |
| Q4 | Manager recommendations |
| Jan | Calibration sessions |
| Feb | Final approvals |
| Mar | Communication to employees |
| Apr | New compensation effective |
### Manager Worksheet
For each employee, consider:
1. Current compa-ratio
2. Performance rating
3. Time since last increase
4. Retention risk
5. Market movement
6. Budget constraints
### Calibration Questions
- Are increases proportional to performance?
- Are there pay equity concerns?
- Are high performers above midpoint?
- Are retention risks addressed?
## Location-Based Adjustments
| Tier | Example Locations | % of Base |
|------|-------------------|-----------|
| Tier 1 | SF, NYC, Seattle | 100% |
| Tier 2 | LA, Boston, Denver | 90-95% |
| Tier 3 | Austin, Chicago, Atlanta | 85-90% |
| Tier 4 | Other metro areas | 80-85% |
| Tier 5 | Rural / low COL | 75-80% |
## Relocation Considerations
- Moving to higher tier: May increase
- Moving to lower tier: Typically maintain (grandfathered)
- New hires: Paid at location rate