Agency benchmarks — the unified reference.

Insurance-agency benchmarking is a literature, not a number. Four independent datasets — produced by four different organizations on four different cadences with four different participant universes — supply the empirical basis on which valuations are anchored, operational deficits are diagnosed, producer-compensation grids are designed, and Silver Tsunami sizing claims are made. Each dataset answers a question the other three cannot. None of the four substitutes for any of the others.

The Pillar that follows orients the reader to the four datasets, the questions each one answers, and the analytical errors that surface when an analyst reaches for the wrong source. The four pages in this category — GPS, BPS, Producer Compensation, Future One — provide the depth treatment for each individual source. The most common workflow is to read this Pillar, then route to the page that matches the question.

§ 01 · Why four datasetsFour sources, four questions.

Industry benchmarks for independent insurance agencies fall into four distinct lineages, each producing a non-overlapping kind of data. The four lineages are not historical accidents — each emerged because the question its dataset answers is genuinely different from the others.

The GPS lineage originates with the National Alliance Research Academy. It publishes Growth, Profit, and Stability benchmarks based on a participant universe that has stabilized in recent vintages at approximately 153 agencies. GPS reports pre-tax profit including depreciation and amortization. It uses revenue tiers from Under $500K through $3M+ and segments by metro size and business focus. GPS is the operational-variance reference — the dataset against which an analyst diagnoses why a specific agency's expense ratios, productivity metrics, or balance-sheet ratios diverge from peers.

The BPS lineage originates with Reagan Consulting in partnership with the Independent Insurance Agents and Brokers of America (IIABA). It publishes the Best Practices Study at a vintage cadence (2022, 2024, with year-paired strategic-context companion data) covering 250–280+ agencies in any given year. BPS reports Pro-Forma EBITDA — owner-compensation normalized to market, perks and non-recurring items removed, the resulting earnings stream comparable across deals. BPS also publishes top-quartile data alongside average data. BPS is the M&A-valuation standard. A multiple applied to a BPS-derived Pro-Forma EBITDA is the canonical agency valuation; a multiple applied to anything else is not.

The Producer Compensation lineage originates with the CIC-designated producer survey published as the Insurance Producer Profile, now in its sixth edition. The participant universe is 80% CIC-designated producers — a quality skew the analyst must account for when reading the data. Producer Compensation publishes producer-level (not agency-level) data: compensation by method (commission only, salary plus commission, salary only), by experience cohort (years in role), by agency size, and the post-M&A producer-compensation impact patterns. Producer Compensation answers questions GPS and BPS cannot — there is no producer-level data anywhere else in the agency-benchmark literature.

The Future One lineage originates with Future One in partnership with IIABA. It publishes the Agency Universe Study on a biennial cadence, most recently with a 2024 wave covering 1,269 respondents. Future One is a breadth-first whole-universe dataset — it sizes the U.S. independent-agency universe, tracks demographic trends, and surveys sentiment on perpetuation, technology adoption, and carrier relationships. Future One is the source for any claim about agency-universe count, the Silver Tsunami demographic wave, or aggregated industry sentiment.

§ 02 · GPSOperational variance, diagnostic.

GPS is the dataset an analyst reaches for when diagnosing why a specific agency's operations diverge from peers. The diagnostic value comes from three properties of the dataset: granular revenue-tier coverage including the small end (Under $500K, $500K–$1M), metro-size and business-focus segmentation (Big City, Medium City, Rural/Small Town; CL-Focused, PL-Focused), and operational-metric breadth across revenue per employee, revenue per producer, expense-line composition, and balance-sheet ratios.

The pre-tax profit basis matters for interpretation. GPS reports pre-tax profit including depreciation and amortization — not EBITDA. The implication for M&A work: a buyer comparing the target's earnings to GPS data is not comparing apples to the BPS Pro-Forma EBITDA that the deal will be priced against. The right use of GPS in an M&A workflow is operational diagnosis (why is this agency's revenue-per-employee 30% below the GPS Big-City tier average?), not direct valuation.

The granular small-tier coverage is GPS's defining structural advantage. BPS begins at Under $1.25M; GPS begins at Under $500K. For a buyer evaluating a tuck-in target below the BPS coverage band, GPS is the only structured operational reference. The dedicated page on GPS benchmarks covers the dataset in depth.

§ 03 · BPSThe M&A-valuation standard.

BPS is the dataset that anchors agency M&A valuation in North America. Three properties make BPS the standard: Pro-Forma EBITDA as the profit basis, top-quartile data published alongside average data, and a revenue-tier band that extends to Over $25M.

Pro-Forma EBITDA is the M&A-canonical earnings metric. BPS reports the agency-level EBITDA after owner-compensation normalization (the owner's W-2 is replaced with a market-rate manager salary), after non-recurring add-backs are removed, and after perks (vehicles, club memberships, family-employee payroll) are stripped. The resulting EBITDA is comparable across agencies in a way that pre-tax profit, including D&A, is not. When an M&A multiple is quoted in agency literature — 8× EBITDA, 10× EBITDA, the kill-zone bands at 12–14× EBITDA — the EBITDA almost always refers to BPS-shape Pro-Forma EBITDA. The discipline matters because misapplied multiples produce systematic mispricing.

Top-quartile data is BPS's second defining feature. The dataset reports both average and top-quartile performance for each revenue tier across every meaningful operational and financial dimension — EBITDA margin, organic growth rate, retention rate, revenue per employee, producer productivity. The top-quartile data is what a competitive seller benchmarks against (the multiple band a top-quartile agency commands is materially higher than the average band) and what a strategic buyer aspires to engineer through post-close operational discipline. The top-quartile reference does not exist in GPS, Producer Comp, or Future One.

The vintage cadence — 2022, 2024, with companion strategic-context data — supports cross-year longitudinal analysis. Five-to-seven-year trend lines on EBITDA margin, organic growth, and carrier-mix composition give the analyst the through-cycle perspective that single-year data cannot. The dedicated page on BPS benchmarks covers the dataset in depth, including the year-paired strategic context for 2022, 2023, and 2024.

§ 04 · Producer CompensationProducer-level data.

The Producer Compensation dataset is the only producer-level benchmark in the agency-benchmark literature. GPS and BPS report agency-level data (revenue per producer aggregated to the agency, not individual producer compensation). Producer Compensation reports individual producer-level data — compensation method, compensation level by experience cohort, compensation level by agency size, and the patterns that emerge from post-M&A producer-compensation impact.

The 80% CIC-designated participant universe is the dataset's defining methodological caveat. CIC-designated producers are a quality skew — they have completed a certification program and are not a random cross-section of all producers. The implication: the data overstates compensation, productivity, and experience-cohort sophistication relative to the broader independent-producer population. Analysts use Producer Compensation as a top-quartile reference, not a population average.

The post-M&A producer-compensation impact data is particularly valuable for the buyer's HR-DD workstream. The dataset captures patterns in producer compensation pre-acquisition vs. post-acquisition — including the proportion of producers whose compensation grids changed materially in the integration window, the direction of change, and the correlation with producer retention. The dedicated page on producer compensation benchmarks covers the dataset in depth.

§ 05 · Future OneUniverse sizing, perpetuation sentiment.

Future One is the breadth-first dataset. Where GPS and BPS sample ~150–280 agencies for depth-first operational and financial data, Future One sampled 1,269 agency respondents in the 2024 wave for breadth-first universe and sentiment data. The two design choices are complementary, not competitive.

Three Future One outputs are load-bearing in market-intelligence work. First, the U.S. independent-agency universe count — Future One sizes the universe at approximately 39,000 agencies in the 2024 wave (down from 40,000 in 2022 and a 1996 peak near 44,000; the figure varies by methodology footnote across waves). Any analyst claiming "there are X thousand U.S. independent agencies" is citing Future One or a derivative dataset. Second, the perpetuation-readiness data — Future One captures principal-age demographics and self-reported perpetuation plans, which feeds the Silver Tsunami narrative that drives M&A supply-side analysis. Third, the carrier-relationship and technology-adoption sentiment — the survey captures aggregated agency views on hard-market dynamics, AMS adoption, direct-purchase competition, and other dynamics that the depth-first datasets do not measure.

The biennial cadence (2018, 2020, 2022, 2024) gives Future One trend depth across the demographic and sentiment dimensions. The dedicated page on Future One agency universe covers the 2024 wave in depth, including universe size, perpetuation outlook, and the technology and carrier-relationship sentiment.

§ 06 · Source-aware cross-readingCite source, vintage, methodology.

The analytical discipline that prevents the most common benchmark errors is source-aware citation. Every benchmark claim — whether in a valuation memo, a buyer-side IC presentation, a seller-side CIM, or a market-intelligence research note — should cite the specific source, the specific vintage, and the specific methodology footnote. The three-part citation pattern looks like: "BPS 2024, Average column, $5M–$10M tier" or "GPS 2024, CL-Focused segment, Medium City metro." Without the three-part citation, the claim is unauditable and the consumer of the analysis cannot judge whether the right benchmark was used.

The most common analytical error in agency-benchmark work is reaching for a single dataset to answer a question the dataset was not designed to answer. GPS does not price M&A. BPS does not size the universe. Future One does not diagnose operational variance. Producer Compensation does not measure agency-level economics. Source-aware reading prevents the error.

A second discipline supports the citation pattern: cross-source triangulation when a metric appears in more than one dataset. Revenue per employee, for example, appears in GPS (operational measurement), BPS (M&A benchmark), and Future One (sentiment context). The three sources will disagree by 5–15% on any given vintage — the disagreement reflects participant-universe differences and methodology variations, not data quality problems. The analyst's job is to pick the source whose methodology best fits the question being asked, not to "average" the three.

§ 07 · Which benchmark for which questionThe routing map.

The routing decision is the load-bearing analytical step. The map below catalogs the question, the right source, and the analytical caveat for each common agency-benchmark workflow.

For variance analysis on a target agency — diagnosing why a specific agency's expense lines, productivity metrics, or balance-sheet ratios diverge from peers — start with GPS. Pair with BPS for the M&A valuation overlay if the target sits in BPS coverage range (above $1.25M revenue). GPS's metro-size and business-focus segmentation makes it the diagnostic-first reference; BPS's Pro-Forma EBITDA gives the valuation-adjacent overlay.

For valuation work, M&A diligence, and Rule-of-20 scoring — anchoring a price, defending a multiple, or scoring deal-readiness — start with BPS. The Pro-Forma EBITDA basis and the top-quartile reference are what make BPS the M&A standard. Pair with GPS for operational color when the target is under $1.25M (below BPS coverage). Always cite the BPS vintage explicitly; multiples shift materially across vintages.

For producer hiring, compensation design, and talent-cost benchmarks — designing a compensation grid, evaluating producer productivity, or modeling post-M&A producer-cost impact — start with Producer Compensation. Cross-reference the BPS year-paired producer-sourcing data and GPS revenue-per-producer for context. The 80% CIC-designated participant universe is the methodological caveat to track.

For sizing the universe, perpetuation narrative, or Silver Tsunami claims — making any aggregate statement about the U.S. independent-agency population — start with Future One. Cross-reference M&A market intelligence for the consolidation-narrative overlay. Future One is the only structured whole-universe dataset; any other source making universe-size claims is either derivative or unreliable.

The source-aware-reading checklist for any benchmark claim:

• Source named explicitly (GPS, BPS, Producer Compensation, or Future One).
• Vintage cited (e.g., BPS 2024 vs. BPS 2022 — multiples and metrics shift across vintages).
• Methodology footnote checked — profit basis (pre-tax profit vs. Pro-Forma EBITDA), participant universe, segmentation scheme.
• Cross-source triangulation noted when the same metric appears in two datasets — and the methodology difference explained.
• The question being asked matched to the source designed to answer it — operational variance to GPS, valuation to BPS, producer-level to Producer Compensation, universe to Future One.

The four pages that follow this Pillar — GPS, BPS, Producer Compensation, Future One — provide the depth on each source. The deeper analyst can also navigate to the cross-source comparison work in the GPS methodology page, which catalogs the benchmark-selection decision framework, the unified glossary across GPS and BPS terminology, and the variance-analysis guide for using multiple sources in a single diligence workflow.

The market category landings — agency benchmarks foremost, but also M&A market intelligence and friction points — are the structured entry points for the four datasets covered here. The seller-side cluster critical factors of agency value consumes BPS and GPS benchmarks as inputs to the seller's valuation defense. The buyer-side cluster financial due diligence consumes the same benchmarks for the forensic-investigation workflow. The market theme is the upstream source; the seller and buyer themes are the operationalizing consumers.