Benefits Reconciliation Savings Calculator

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1 I reconcile benefits for...

2 Company Profile

Estimated annual turnover: Annual total separations rate derived from BLS JOLTS Table 20 (2024).
Compounded from monthly rates: 1−(1−r)12, where r is the monthly separation rate.

Source: U.S. Bureau of Labor Statistics,
Job Openings & Labor Turnover Survey

3 Current Benefits Spend

Estimated Annual Total Premium

4 Current Reconciliation Efforts

Benefits Reconciliation ROI Analysis

Potential Annual Savings
$0
$0 / month
Potential Overpayment Recovery
$0
0% of annual spend
Potential Labor Cost Savings
$0
0 hours/year recoverable

Savings Breakdown

Want to understand why these errors happen?

Read how billing variances accumulate — breakdown in NAPEO PEO Insider Magazine

Read Article
Key Assumptions Applied
Methodology & Sources

Overpayment Recovery

Tabulera client analysis shows employers overpay 0.79–1.3% of total premium when reconciling monthly. This comes from two sources:

Rate differentials — the invoice doesn't match what it should be. Wrong rates, tier mismatches, ineligible dependents, wrong plan assignments, missed life events.

Missed terminations — terminated employees who remain on carrier invoices until someone catches it. More turnover and less frequent reconciliation = more exposure.

Turnover rates are sourced from BLS JOLTS Table 20 (2024 annual average monthly separation rates). Since JOLTS reports monthly rates, we annualize using compound probability: Annual rate = 1 − (1 − r)12, where r is the monthly separation rate. This accounts for the fact that employees who leave in one month cannot leave again, avoiding the overstatement that simple multiplication (r × 12) would produce.

Both scale with how often you reconcile. Less frequent = more errors accumulate. More invoices and (for outsourcers) more client companies add a small complexity uplift.

How Reconciliation Frequency Affects Exposure

The less often you reconcile, the longer errors go undetected on carrier invoices. Based on Tabulera client data, the average detection lag by frequency is:

Monthly: ~0.4 months — errors are caught within the current billing cycle, but some slip to the next month.

Quarterly: ~1.0 month — errors accumulate for several weeks before the next review.

Never / Ad-Hoc: ~2.0 months — without a regular process, errors persist until someone happens to notice them.

Error rates also increase with less frequent reconciliation, as billing discrepancies and eligibility mismatches compound over time without correction.

For outsourcers managing multiple client companies, there is an additional delay factor of 1.5× because terminations must flow from the client's HR team to the outsourcer before reaching the carrier.

Labor Cost Savings

We take your state's median HR/Benefits specialist wage, add 35% for payroll taxes and benefits, then multiply by reconciliation hours. We calculate with 33% as a conservative floor — Tabulera clients typically report a 75% increase in reconciliation speed.

Data Sources

Data PointSourceDate
HR/Benefits specialist wages by state BLS OEWS — SOC 13-1141 2023
Health premiums & enrollment by tier AHRQ MEPS-IC 2024 2024
Turnover rates by industry (compounded from monthly: 1−(1−r)12) BLS JOLTS Table 20 2024
Loaded labor cost multiplier BLS ECEC 2024
Overpayment baseline & automation efficiency Tabulera client analysis 2024–25

This is an estimate. Actual savings depend on your plan design, carrier relationships, data quality, and process maturity.