Methodology

How We Validate Data

Our methodology for collecting, validating, and maintaining the accuracy of benchmarking data. Because your decisions are only as good as the data behind them.

Most benchmarking data comes from self-reported surveys. Someone in HR fills out a form, often from memory, often rushed. The result? Inconsistent definitions, outdated figures, and data you can't fully trust.

We take a different approach. Our data comes directly from plan sponsors and benefits consultants who submit detailed plan and cost information from actual plan documents—no third-party aggregators, no scraped data. Here's how we ensure quality.

Where Our Data Comes From

We collect data directly from the people who know it best:

Plan Sponsors

Employers submit their own benefits data directly. They have access to the actual plan documents, rate sheets, and contribution schedules—the real numbers, not estimates.

Brokers & Consultants

Benefits consultants submit data on behalf of their clients. They work with plan documents daily and understand the details—deductibles, contributions, plan structures.

Form & API Submission

Data comes in through our web forms or directly via API integration. Both methods apply the same rigorous validation before data enters our system.

No Third Parties

We don't aggregate from other databases, scrape public filings, or buy data from vendors. Every record comes directly from plan sponsors or their advisors, sourced from actual plan documents.

Our Validation Process

Every submission—whether via form or API—passes through multiple validation checks before entering our database. Submissions that fail validation are rejected and must be corrected.

Mathematical Checks

Numbers have to add up. We validate calculations and relationships between fields automatically.

Examples: Contribution percentages must equal 100%. Premium amounts must align with contribution splits. Per-pay-period amounts must reconcile to annual figures.

Healthcare Law Compliance

Benefits plans must comply with ACA and other regulations. We check that submitted data falls within legal parameters.

Examples: Out-of-pocket maximums can't exceed ACA limits. HSA-eligible plans must meet minimum deductible requirements. Preventive care cost-sharing rules.

Cross-Field Validation

Fields don't exist in isolation. We check that related values make sense together.

Examples: Family deductible must be ≥ single deductible. Out-of-pocket max must be ≥ deductible. Family premium must be > single premium.

Logic & Range Checks

We catch obvious errors—typos, misplaced decimals, and values that fall outside reasonable ranges.

Examples: A $50,000 deductible gets flagged. A $10/month family premium gets flagged. 500% employer contribution gets flagged.

Periodic Human Review

Automated checks catch most issues, but we also conduct periodic human reviews to identify patterns, edge cases, and data quality trends that algorithms might miss.

Real-Time Updates

Our database updates in real time. When a submission passes validation, it's immediately available in benchmarks—no waiting for quarterly releases or annual publications.

Instant

Validated data appears in benchmarks immediately

Continuous

New data flows in constantly from active users

Current

Benchmarks reflect the latest available data

Why This Matters

The difference between validated and unvalidated data isn't academic. It affects real decisions:

❌ Typical Survey Data

  • • Respondent may not know exact figures
  • • No validation of submitted values
  • • Typos and errors go undetected
  • • Often 6-12 months stale by publication
  • • Aggregated from unknown sources

✓ Validated Direct Data

  • • Sourced from plan documents
  • • Multiple validation checks required
  • • Errors rejected before entry
  • • Real-time updates
  • • Direct from sponsors and advisors

Our Commitment to Transparency

We believe you should be able to trust your data source. That means being transparent about our methodology:

Sample Sizes Shown

Every benchmark shows the number of plans included. You'll never see a benchmark based on just a handful of data points presented as authoritative.

Filter Criteria Clear

When you filter by industry, size, or region, you see exactly what's included. No black boxes.

Methodology Published

This page exists because we believe you should know exactly how we collect and validate data. No proprietary mystery sauce.

What We Cover

Our database includes comprehensive benefits data across:

Plan Types

  • Medical / Health Insurance
  • Dental
  • Vision
  • Life & AD&D
  • Short-Term Disability
  • Long-Term Disability
  • Stop Loss

Filters Available

  • 54 Industries (NAICS-based)
  • All 50 States + DC
  • Company Size Bands
  • Plan Type (PPO, HDHP, HMO, etc.)
  • Funding Type (Self-insured, Fully-insured)

Questions About Our Data?

We're happy to discuss our methodology in more detail. If you have questions about how we validate data, what's included in a specific benchmark, or how we handle edge cases, reach out.

We'll tell you:

  • • Exactly how many plans are in your peer group
  • • What validation checks your data passes through
  • • How we handle unusual plan structures
  • • What filters are available for your analysis

See the Data for Yourself

Explore our benchmarking data and see the difference validated, direct-source data makes. Filter by your industry, size, and region.

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