When you put a benchmark in front of a client, you are vouching for it. "Your deductible sits at the 70th percentile for your peer group" is only as credible as the data behind that percentile. If a client, or a client's CFO, asks where that number comes from, you want an answer you can stand behind in the room.
Not every benchmark can give you that answer. Many are assembled by blending several different kinds of data and filling the gaps with a model. The result looks precise on the page, but it is an estimate of the market, not a record of real plans. Here is the difference, and six questions to ask any benchmarking provider before you rely on their numbers.
Every benchmark is only as good as its inputs
There are two fundamentally different ways to build a benefits benchmark.
Blend many sources, then fill the gaps
Combine inputs such as employer surveys, broker-shared plans, self-submissions, claims clearinghouses, public government filings (for example DOL Form 5500), and association aggregations. Because no single source is complete or consistent, the data is refined with proprietary modeling, and when a peer cohort is too thin, it is expanded by size or region, or replaced with national numbers.
Broad coverage is the selling point. The cost is traceability.
One validated source
Build the benchmark from a single, consistent source: actual plan designs, shared by brokers, and validated before they enter the dataset. No surveys, no claims inference, no filing scrapes, and no modeling to paper over gaps. Every data point traces back to a real plan that a real employer runs, checked for accuracy on the way in.
This is the model Bnchmrk is built on: a number you can defend, line by line.
What the blended approach quietly costs you
Blending sources buys breadth, which is a real benefit. But it carries problems a careful advisor should weigh before quoting the result to a client.
Survey self-report is not verified.
Employers answering a survey may misremember or round their own plan details. Nothing confirms the figure against the actual plan document.
Claims data is not plan design.
You can infer rough cost-sharing from claims, but you cannot read an actual deductible, coinsurance schedule, or out-of-pocket maximum from a claims feed.
Government filings lag and lack design detail.
Public filings like DOL Form 5500 are useful for some retirement metrics, but they run months to years behind and say little about medical or ancillary plan design.
Modeling fills gaps you cannot see.
When sources disagree or data is sparse, a model decides the answer. You are shown a clean number with no way to tell which inputs produced it.
Thin cohorts quietly become national.
When your peer group is small, the cohort figure may actually be a national average, or a group expanded by size or region until it was large enough. The label still says it is yours.
Six questions to ask any benchmarking provider
Use these with any vendor, including us. The answers tell you what you are actually quoting to your clients.
- 1
Where does each data point come from?
If the answer is "a blend of sources," ask which ones, and ask them to separate verified plan data from survey responses, claims inference, and public filings.
- 2
Is the plan data validated against real plan documents, or self-reported?
Validation is the difference between a record and a guess.
- 3
When my cohort is small, what am I actually seeing?
Ask directly whether thin cohorts are modeled, expanded by size or region, or replaced with national figures, and whether the report tells you when that happens.
- 4
How much of the report is the provider's own data versus public or partner data?
Much of what looks impressive in market reports (high-cost claims trends, carrier market share, utilization studies, employer-reputation scores) is public or licensed from a partner. You may be paying for data you could get for free.
- 5
Does the report score my client's actual plan, or just describe the market?
A market average tells you what others do. It does not tell you whether this client's plan is competitive, or by how much.
- 6
Can I trace any single number back to its source?
If you cannot, neither can your client's CFO.
What a "market report" often really contains
A knowledgeable advisor should not pay a premium for repackaged public content. Behind the glossier pages of a typical benchmarking report, you often find:
High-cost claims and injectable-drug trends
Frequently drawn from a stop-loss carrier's publicly released annual book-of-business report, which reflects national claims, not your client's cohort.
Carrier market-share figures
Typically licensed from a third-party analytics firm.
Employer-reputation and ratings data
Pulled from publicly available sources.
Retirement metrics
Often originate in public DOL Form 5500 filings.
None of this is wrong to include. The point is simpler: these are not proprietary insights about your client, and they are not a reason to trust the benchmark at the center of the report.
Where Bnchmrk stands
Bnchmrk is built on one source: validated, broker-shared plan designs, currently 95,000+ verified plans across roughly 13,000+ employers. That choice drives two things that matter when you are advising a client.
Data you can defend
Every percentile comes from real plans your peers actually run, validated before inclusion. When a client asks where a number comes from, the answer is clean: real plans, not a model.
Your client's plan, scored
Bnchmrk does not stop at market averages. It scores the client's actual plan against the cohort, field by field, with a percentile rank and an overall competitiveness score, so the conversation moves from "here is the market" to "here is exactly where you stand and what to improve."
The bottom line
Breadth is easy to advertise. Trust is harder to earn. A benchmark assembled from many sources and smoothed with a model will always be able to show you a number. Whether you can stand behind that number is a different question. Before you put a benchmark in front of a client, ask the six questions above, and make sure the answer to "where does this come from?" is one you are comfortable saying out loud.
Frequently asked questions
How are employee benefits benchmarks calculated?
There are two fundamentally different approaches. The first blends many inputs (employer surveys, broker-shared plans, self-submissions, claims clearinghouses, public filings, and association aggregations), then refines them with proprietary modeling and expands thin peer groups by size, region, or national averages. The second builds the benchmark from a single validated source: actual plan documents, verified before they enter the dataset, with no modeling to fill gaps. The first approach is broader; the second is more defensible. Bnchmrk uses the second.
Are benefits benchmarking surveys accurate?
Surveys are good for directional prevalence (what share of employers offer a perk, wellness program, or policy), but they rely on employers self-reporting their own plan details, usually once a year. That makes them inconsistent on hard plan economics like deductibles, coinsurance, and employer contribution splits, because nothing confirms the answer against the actual plan document. For those numbers, verified plan data is more reliable.
What questions should I ask a benefits benchmarking provider?
Six are enough to tell you what you are really quoting: Where does each data point come from? Is the plan data validated or self-reported? When my cohort is small, what am I actually seeing? How much of the report is the provider's own data versus public or partner data? Does the report score my client's plan or just describe the market? Can I trace any single number back to its source? If a provider cannot answer these cleanly, neither can you when a client's CFO asks.
What is usually inside a benefits "market report"?
Much of what looks impressive is repackaged public or partner content: high-cost claims trends from a carrier's publicly released book-of-business report, carrier market share licensed from an analytics firm, employer-reputation data from public ratings sites, and retirement metrics from public DOL Form 5500 filings. None of it is wrong to include, but it is not proprietary insight about your client, and it is not a reason to trust the benchmark at the center of the report.
Can you trace a benchmark number back to its source?
It depends on how the benchmark was built. With a blended-and-modeled dataset you are shown a clean number with no way to tell which inputs produced it. With verified plan data, every figure traces back to a real plan document that was validated before inclusion, so you can stand behind it line by line. Bnchmrk is built so you can trace any number to real plans.
What makes Bnchmrk's benchmarks different?
Bnchmrk is built on one source: validated, broker-shared plan designs, currently 95,000+ verified plans across roughly 13,000+ employers. There are no surveys, no claims inference, and no modeling to paper over thin cohorts. It also does not stop at market averages: Bnchmrk scores your client's actual plan against its peer cohort, field by field, with a percentile rank and an overall competitiveness score.
Benchmark on data you can defend
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