Percentile
- Compensation Components
- Career Structure & Progression
- Benchmarking & Market Data
- Job Architecture & Leveling
- Pay Structures & Ranges
- Performance & Incentives
- Lines of Business & Consulting Specialisms
- Geographic & Market Adjustments
- Governance, Fairness & Transparency
- Workforce Planning & Analytics
A percentile is a statistical measure that indicates the position of a data point within a distribution. In compensation benchmarking, a percentile shows the pay level below which a specified percentage of the surveyed market falls. For example:
- P25 (25th percentile) — 25% of comparable firms pay at or below this level. This is a below-market position, sometimes used by firms in lower-cost markets or with very strong non-cash benefits.
- P50 (50th percentile / median) — The midpoint of the distribution. Half of comparable firms pay at or below this level. Often used as a default positioning target, though not always appropriate.
- P75 (75th percentile) — 75% of comparable firms pay at or below this level. A firm targeting P75 is paying above most of its direct competitors, typically to attract or retain scarce talent.
- P90 (90th percentile) — A high-market position. Used selectively for critical roles or in exceptionally competitive talent markets.
Vencon Research's benchmarking surveys present compensation data as percentile distributions rather than simple averages. This approach is explained in detail in Percentiles for Accuracy and Privacy in Compensation Benchmarking.
Why Percentiles Matter More Than Averages
A simple average (mean) is sensitive to outliers — one firm paying exceptionally high or low will shift the average, producing a misleading reference point. Percentiles are more robust because they describe the actual distribution of market practice across all firms surveyed.
In consulting, where pay can vary significantly across firm size, line of business and geography, percentile data gives a much more accurate picture of where any individual firm sits relative to the market — and whether that position is intentional and appropriate.
How Percentiles Are Used in Practice
- Setting pay positioning targets — A firm might decide to target the P50 for base salary and the P75 for total cash, reflecting a philosophy that prioritises variable pay as a retention tool.
- Identifying outliers — Roles or individuals significantly below P25 or above P75 may require immediate attention in salary reviews.
- Salary band design — Salary bands are often anchored to percentile benchmarks, with the band minimum, midpoint and maximum set at P25, P50 and P75 respectively.
- Compa-ratio calculation — A compa-ratio compares an individual's salary to a market reference point (typically the P50). A compa-ratio of 1.0 means the employee is paid exactly at the median; below 1.0 means below market. Vencon Research surveys include compa-ratio tools — see our video tutorial on percentile analysis and the compa-ratio tool.
- Budget simulation — Firms use percentile data to model the cost of moving from their current market position to a target position across the full workforce.
Percentile Positioning in Consulting
Consulting firms do not all target the same percentile, and that is deliberate. The right target depends on a firm's talent strategy, competitive context and compensation philosophy. A boutique strategy firm competing for the same talent as MBB may need to target P75+ to attract candidates. A large IT consultancy with strong career development and brand appeal may find P50 sufficient.
What matters is that the positioning choice is intentional — made with full awareness of where the firm sits relative to the market — rather than the result of benchmarking inertia or incomplete data.
Percentile Data and Privacy
One important practical virtue of percentile reporting is that it preserves confidentiality. Rather than disclosing any individual firm's pay data, Vencon Research presents the distribution of the surveyed group, allowing each participant to see where they fall without exposing competitor-specific figures. This is a core principle of our methodology, discussed further in Percentiles for Accuracy and Privacy in Compensation Benchmarking.