Why Survey Data Isn't Enough Anymore

Every year, benefits professionals wait for the same surveys to come out. Kaiser. SHRM. Mercer. The reports land, get passed around, and inform millions of dollars in benefits decisions.

There's just one problem: by the time you're reading them, the data is already old.

The Survey Problem

Traditional benefits surveys have a fundamental flaw built into their methodology. Here's how they typically work:

1. Survey goes out in Q1
2. Responses trickle in through Q2
3. Data gets cleaned, analyzed, and packaged in Q3
4. Report publishes in Q4

By the time you're using that data to inform your client's renewal strategy, you're looking at information that's 9-12 months old. In a market where healthcare costs are shifting constantly, that lag matters.

Beyond Timing: The Accuracy Question

Age isn't the only issue. Survey data has structural limitations that affect accuracy:

Self-reported data — Respondents fill out surveys from memory or incomplete records. Deductible fields get rounded. Contribution amounts get estimated. Small errors compound across thousands of responses.

Selection bias — Who responds to surveys? Usually larger employers with dedicated HR staff who have time for voluntary questionnaires. Small and mid-size employers—the majority of the market—are chronically underrepresented.

Aggregation masks variation — National averages tell you very little about what employers in your specific industry and geography are actually doing. A manufacturing company in Ohio has different competitive dynamics than a tech startup in San Francisco.

What's the Alternative?

We started Bnchmrk because we believed there had to be a better way. Instead of surveys, we built a platform powered by actual plan documents—SPDs, SBCs, and benefit guides submitted by consultants and validated through our compliance engine.

The difference:

• Real plans, not survey responses — Every data point traces back to an actual employer's benefit offering
• Continuous updates — Data flows in throughout the year, not once annually
• Granular filtering — Benchmark against your actual peer group, not national averages
• Validated accuracy — Our compliance engine flags inconsistencies before they enter the dataset

The Bottom Line

Survey data served the industry well for decades. It was the best option available. But the market has evolved, and benefits professionals deserve tools that have evolved with it.

The question isn't whether surveys are useful—they are, for directional trends and year-over-year comparisons. The question is whether they're sufficient for the high-stakes decisions you're making on behalf of employers and their employees.

We don't think they are. And we built Bnchmrk to prove there's a better way.