Executive Summary An internal pay-equity review is how you (1) establish whether people are being paid fairly for comparable work, (2) identify misalignments caused by hiring-time and market swings, and (3) create a clear, defensible remediation plan. The goal is not to “make everyone equal,” but to ensure differences are explainable by job-related factors (role level, skills, performance, tenure where relevant, scope, location, market, etc.) and are consistently applied.

Key Recommendations

1. Define the scope and pay-equity standard

• Scope: choose what you will review (base salary only vs. total cash; include allowances/bonuses if they materially affect pay).
• Geography: if you operate across locations, decide whether to normalize by location or run separate reviews.
• Equity lens (important): decide whether you’re assessing:
• Internal equity (people in similar roles should be paid similarly), and/or
• External equity (your pay vs. market—separate from pay equity, but often reviewed together).
• Standard of defensibility: document that differences must be explainable by job-related criteria (not by historical timing or inconsistent offers).

1. Create a “job architecture” baseline (this is where most pay-equity reviews succeed or fail)

You need a consistent way to compare jobs:

• Use (or build) a job leveling framework:
• Job families + levels (e.g., Engineering L2/L3/L4) based on scope, complexity, autonomy, decision-making, and required expertise.
• Group employees into comparable clusters:
• Same job/level, or same leveling band (where titles differ).
• Decide on comparators:
• “Same role/level” and “closely related roles” (e.g., within a level band) are typically used first; expand only if necessary.

1. Build the dataset and control for confounders

Collect HR + payroll data per employee:

• Pay components: base salary, guaranteed allowances, commissions/variable targets (if relevant)
• Job data: title, department, job level, location, manager/grade boundaries
• Business drivers: employment status (full-time/part-time), start date, employment type, hours, probation status
• Performance rating (if you will use it), tenure (only if your policy uses it meaningfully)
• Any formal pay exception approvals (if your org tracks them)

Then define the key “control variables” you will use during analysis, for example:

• Job level/band
• Location (if market differs)
• Performance rating (if used consistently)
• Employment type/hours
• Hard-to-control factors (rare cases): document and exclude or treat separately

1. Run pay-equity analytics (the practical approach)

Use a staged analysis so you don’t drown in complexity:

Stage A: Descriptive mapping (find where differences exist)

• For each job/level band:
• Count incumbents
• Minimum/median/maximum base salary
• Salary distribution (e.g., quartiles)
• Compare by location and manager where relevant

Stage B: Statistical / normalization view (find “unexplained gaps”) Two common methods (you can use either, or both):

• Regression approach (preferred when you have enough headcount per group):
• Pay ~ job level + location + performance + etc.
• Flags employees or groups whose pay is materially above/below predicted ranges
• “Range vs. target” approach:
• If you have salary bands/market ranges:
• Compare actual pay to midpoints and ranges by level/location
• Flag outliers outside policy

Stage C: “Equity exceptions ledger”

• Create a list of every outlier with its documented reason:
• Market emergency hire
• Scarce skill premium
• Retention exception approved by HR/Finance
• Promotion/acting role adjustment
• One-off adjustment due to role expansion
• If no reason exists, treat it as an issue to remediate.

1. Validate with qualitative review (don’t rely on math alone)

Pay equity analysis should be paired with manager and HR validation:

• Are roles truly comparable? (title ≠ role)
• Are level assignments correct?
• Were performance ratings applied consistently across teams/years?
• Are there undocumented comp practices (e.g., “informal supplements,” off-cycle adjustments)?
• Any “policy drift” since salary bands were last updated?

Deliverable: For each job band where gaps exist, produce a 1-page explanation:

• What’s the observed gap?
• Is it explained by controls (level/location/performance)?
• If not, what is the likely cause (legacy hires, inconsistent negotiation, outdated bands, manager practice)?

1. Decide remediation approach (you need a playbook)

Common remediation options—choose based on root cause and budget:

• “Within-band alignment” (most common):
• Bring employees toward the midpoint or within the band, prioritizing largest unexplained gaps first.
• “Targeted increases for underpaid, funded by freezes elsewhere”:
• Avoid blanket increases; focus on fairness and business-critical roles.
• “Correct job leveling first”:
• If mis-leveling is the driver, fix levels and reprice (often more defensible than adjusting pay arbitrarily).
• “Overpayment correction” (use carefully):
• In many organizations and many jurisdictions, taking pay away is sensitive and may be impractical legally/ethically. If you do consider it, do it only with legal/HR governance and a strong policy rationale.
• “Policy and governance fixes”:
• Even if you remediate pay now, you must fix the decision process so it doesn’t recur.

1. Put governance around decision-making (so it’s defensible)

Establish a Pay Equity Review Committee or working group:

• HR (Compensation lead + HRBP)
• Finance/Payroll representative
• Optional: Legal/Compliance review for sensitive remediation approaches
• Ensure documentation: each adjustment needs a rationale tied to the job-related factors.

1. Communicate appropriately

• Don’t publish raw salary differences.
• Communicate the “principles and outcomes”:
• What you reviewed, how you ensured comparability, and what happens next.
• Focus on fairness and consistency. For impacted employees, provide a clear explanation of what changed and why.

Business Impact

• Reduces legal and reputational risk associated with unfair or inconsistent pay practices (by making decisions transparent and job-based).
• Improves retention and reduces “quiet attrition” from perceived inequity.
• Strengthens hiring credibility: future offers will be anchored to policy rather than individual negotiation history.
• Creates a foundation for performance management credibility (so pay progression feels logical).

Risks (and how to manage them)

• Risk: Mis-leveling disguised as pay inequity
• Mitigation: verify job leveling and role comparability before adjusting pay.
• Risk: “Over-correcting” legacy pay
• Mitigation: use controls + exceptions ledger; prioritize unexplained gaps.
• Risk: Employee distrust due to unclear process
• Mitigation: document methodology and provide empathetic, principle-based communication.
• Risk: Budget shock
• Mitigation: phase remediation (e.g., 1-year plan), prioritize highest-impact outliers.

Immediate Next Steps (practical 30–45 day plan) Week 1–2: Prepare

• Confirm scope (base vs total cash), geographies, time frame
• Freeze and validate the HR/pay dataset
• Confirm or build job level bands and employee clustering

Week 2–3: Analyze

• Produce pay distributions by level/location
• Identify outliers and calculate “unexplained gap” indicators
• Build the exceptions ledger (document reasons, or flag missing reasons)

Week 4: Validate and decide

• Manager/HR validation workshops for the bands with the largest gaps
• Compensation committee reviews root causes and selects remediation options

Week 5–6: Remediate plan + governance

• Draft an implementation budget and phasing plan
• Set policy/process updates:
• Offer guidelines
• Approval thresholds for exceptions
• Required documentation for off-cycle adjustments
• Create a communication plan for affected employees

Three concise questions (optional, to tailor your approach)

1. Are you reviewing base salary only, or base + allowances/variable pay?
2. Do you already have job levels and salary bands (or are you starting from titles)?
3. How many employees fall into each job level band (roughly)—are there enough numbers for meaningful analysis?

If you need help implementing these recommendations or would like expert guidance tailored to your organization, the team at Zunavish would be happy to assist.