Why benchmarking matters for FP&A
Compensation is typically the largest line item on the P&L. Yet many businesses set pay based on gut feel, individual negotiation, or reactive matching of counteroffers. The result is an inconsistent compensation structure that overpays in some areas, underpays in others, and creates internal equity issues that eventually surface as retention problems.
Structured benchmarking gives the finance team confidence that headcount budgets are calibrated to market reality and that the business is investing its people spend where it matters most.
Data sources
Salary surveys (paid). The gold standard. Providers like Willis Towers Watson, Mercer, Radford, and Korn Ferry publish detailed compensation data by role, level, industry, and geography. These surveys have large sample sizes and rigorous methodology. The cost (typically £5,000-£20,000 per year) is justified for businesses with 50+ employees.
Recruitment agency data. Specialist recruiters publish annual salary guides (Hays, Robert Half, Michael Page). These are free, directionally useful, and cover a wide range of roles. The data is based on placements and candidate expectations, so it tends to reflect current market rates rather than installed base compensation.
Government data. The Office for National Statistics (ONS) publishes the Annual Survey of Hours and Earnings (ASHE), which provides median and percentile pay data by occupation, industry, and region. Free and comprehensive, though the data is 12-18 months old by the time it is published.
Startup and tech-specific data. For technology companies, resources like Glassdoor, Levels.fyi, and Payscale provide crowd-sourced compensation data. Useful for benchmarking technology roles where traditional surveys may have smaller samples. Treat with caution -- self-reported data has inherent biases.
Your own offer and attrition data. Track every offer you make and whether it was accepted or rejected. Track every departure and whether compensation was cited as a factor. Over time, this internal data becomes your most reliable benchmark because it reflects your specific market position.
The benchmarking process
Step 1: Define your comparator group. Who are you competing with for talent? A 50-person SaaS company in Manchester competes with different employers than a 500-person financial services firm in London. Define your peer group by industry, size, location, and funding stage.
Step 2: Map roles to benchmark data. Match your internal roles to the survey definitions. Job titles vary widely -- focus on the responsibilities and level, not the title. A "Senior Engineer" at one company may be equivalent to a "Staff Engineer" at another.
Step 3: Choose your target percentile. Most businesses target the 50th percentile (median) for base salary and use variable pay or equity to push total compensation higher for critical roles. Some target the 60th or 75th percentile for hard-to-fill roles. The target should align with your talent strategy and budget constraints.
Step 4: Analyse the gaps. Compare current compensation to benchmark data for each role. Identify roles that are significantly below market (retention risk) and roles that are significantly above market (potential over-investment).
Step 5: Build the adjustment plan. Address critical gaps in the next compensation review cycle. Prioritise adjustments for roles where the retention risk is highest or the market gap is largest.
Integrating with the headcount budget
Once you have benchmark data, use it to set salary bands for each role level. The headcount plan should use the midpoint of the relevant band for budgeting new hires. This ensures the budget reflects market reality and provides a consistent basis for workforce planning.
Review benchmark data annually. Compensation markets shift, and a benchmark that was current twelve months ago may already be stale for in-demand roles.