Support staff and efficiency.

Support staff compensation is the second-largest variable line item in most agency P&Ls. It's also the line item buyers diligence most aggressively for what it reveals about operating efficiency — because the comp ratio alone doesn't tell the story. Two agencies at the same 21.8% support-staff comp ratio can have wildly different operating efficiency, and the diagnostic that surfaces the difference is the spread metric.

21.8%, and what it doesn't tell you.

The 21.8% GPS benchmark for support-staff comp as a percentage of total agency revenue is a useful sanity check. Significantly above it: overstaffed, under-leveraging technology, or running an unusually high-touch service model. Significantly below: at risk of service failure, burnout, or single-point dependencies.

But the percentage is line-mix and geography dependent. Commercial-heavy books legitimately run higher because complex placements require richer support coverage. Personal-lines-heavy books with strong AMS automation can run materially lower. A book in a high-cost MSA legitimately runs higher because the cost-of-labor is structurally elevated; a book in a lower-cost market runs lower.

Sellers should benchmark against three calibrations before declaring a ratio "healthy":

1. Line-mix calibration — adjust the 21.8% for the agency's specific commercial/personal/specialty mix.
2. Geographic calibration — use BLS regional data or industry geographic comp surveys.
3. Tech-leverage calibration — agencies with documented AMS automation, workflow tools, and CSR efficiency multipliers legitimately run leaner.

Revenue per support FTE, the productivity view.

Spread is the metric that converts the comp ratio into operational meaning. It's calculated as total agency revenue divided by the number of support-staff full-time-equivalents (CSRs, account managers, admin):

The spread metric is independent of the comp percentage. A book at 21.8% support-staff comp with $250K spread is overstaffed at market wages; a book at the same 21.8% with $450K spread is running efficiently. Buyers underwrite the spread metric explicitly because it's a leading indicator of post-close operating leverage.

The broader efficiency proxy.

Revenue per employee — total revenue divided by total headcount (producers + support staff) — is the broader efficiency benchmark. GPS standards:

• Below $150K per employee: overstaffed or stalled growth; structural concern.
• $150K–$200K: baseline operating profile; market-band candidate.
• $200K+: premium-band agencies; multiple expansion possible.
• $250K+: high-performing books; competitive-band candidates.

Falling revenue per employee is one of the most reliable early-warning signals of operating issues. Sellers tracking this metric quarterly catch problems before they show up in EBITDA.

Improve spread without distressed signals.

For sellers facing low spread or revenue-per-employee in the pre-sale window, three improvement paths are available — all of which work without triggering distressed-pre-sale signals:

1. AMS workflow investment. Automating routine renewal, certificate, and endorsement workflows raises spread per support FTE without headcount reduction. The investment compounds at the multiple — every dollar of EBITDA improvement is worth the multiple at sale.
2. Cross-training for redundant coverage. Cross-trained staff allows lean staffing without single-point dependency. The seller who can document that any account has secondary coverage runs leaner without service-failure risk.
3. Attrition through non-replacement. Natural staff turnover in the runway window can be used to right-size without layoffs. Each natural departure that doesn't get replaced raises spread by ~$150–250K per FTE; over 24 months, two or three non-replacements meaningfully shift the metric.

The path NOT to take is layoffs in the 12 months before sale. Workforce reductions in the immediate pre-sale window read as distress and depress the multiple more than the EBITDA improvement adds. The Pillar — Compensation & Personnel Cost Management — walks the full comp framework; this Explainer is the support-staff and efficiency-metrics layer.