Every plan sponsor believes their census is accurate. It’s one of those quiet assumptions that never gets challenged—until it has to be. And when it does, the result is rarely pretty.
The problems aren’t obvious. They’re subtle and cumulative. Rehires coded as new employees. Terminated participants lingering as active. Excluded classes that drift over time as job titles evolve. Compensation definitions applied differently depending on who is running payroll that week. None of it looks catastrophic in isolation. Together, it’s a compliance problem waiting to surface.
“Close enough” doesn’t work in retirement plans. Coverage testing under §410(b), nondiscrimination testing, and contribution allocations all rely on accurate data. If your inputs are flawed, your outputs are unreliable—even if the reports say you passed. That’s the danger. Errors can sit quietly for months, even years, before they’re discovered during an audit, a plan conversion, or a correction exercise.
By then, you’re not fixing a small issue. You’re reconstructing history—who should have been eligible, what compensation should have been counted, what contributions should have been made. That’s where correction costs escalate and confidence erodes.
No one catches it early because everyone assumes someone else is checking. HR assumes payroll has it right. Payroll assumes the TPA will flag issues. The TPA assumes the data they receive is correct.
A clean census isn’t a given. It’s a process. Regular audits, clear definitions, and accountability across departments. Without that, you don’t have reliable data—you just have a well-formatted guess.
