A final rule from the Office of Personnel Management took effect September 2, rewriting the formula federal agencies use to decide which employees survive a staff cut. The rule, published in the Federal Register as document 2026-15665, replaces the decades-old system built around tenure groups with a numeric scale that puts job-performance ratings ahead of seniority when a reduction in force begins. Veterans’ preference still adds points to an employee’s score, but length of service now works mainly as a tiebreaker rather than a primary factor. The change reshapes retention odds for a federal civilian workforce that numbers well over two million people, many of them long-tenured and approaching retirement.
OPM’s New Performance-Credit Formula Replaces Tenure Groups
Under the finalized regulation, agencies score each employee using the three most recent ratings of record drawn from the preceding four years. A Level 5 rating, the top tier on the federal five-level appraisal scale, earns seven points; Level 4 earns five points; Level 3 earns three points; and a rating of Level 1 or Level 2 earns zero. Agencies total those points into a performance credit that becomes the primary sorting factor once a reduction in force forces a ranking of who stays and who is separated, with special provisions covering employees who are missing a rating or who were appraised under a different agency’s scale.
That performance-credit formula replaces the current structure of competitive-service Groups I, II, and III. In its place, the final rule creates separate retention registers for competitive-service and excepted-service employees, each divided into two tenure subgroups, with performance credit ranking employees within those registers before tenure or length of service ever comes into play. OPM said the redesign responds to complaints that the old tenure-first system let long-serving but poorly rated employees outlast higher-performing colleagues during a layoff.
The docket behind the rule, OPM-2025-0107, drew 721 unique public comments during a 60-day comment period, according to OPM’s published response to those submissions, filed as an amendment to 5 CFR parts 316, 330, 351, 353, 359, 362, and 430. Federal employee unions and several professional associations argued the new formula would functionally erase the value of tenure and length of service. OPM disagreed, writing that nothing in the reduction-in-force statute requires the agency to preserve the current tenure-group hierarchy as a fixed category, and that Congress required only that tenure receive due effect, not primacy, in a layoff.
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Veterans’ Preference Shifts From a Tenure-Group Perk to Point Credit
Veterans’ preference survives the overhaul, but its mechanics change substantially. A preference-eligible employee with a compensable service-connected disability of 30 percent or more now receives five additional points on top of a performance-credit score; other preference-eligible employees receive three additional points; employees without preference status receive none. Those points are added directly to the seven-point performance scale rather than layered on top of a separate tenure ranking, the structure the current regulations still use.
The math can change outcomes that a straight performance comparison would not. A 30-percent-or-more disabled veteran with three consecutive Level 4 ratings collects a raw performance credit of 15, then rises to an augmented score of 20 once the disability preference is applied. A non-preference employee with two Level 5 ratings and one Level 4 rating lands at a raw score of 19, still below the veteran’s augmented total. OPM cited that kind of calculation in the final rule to answer commenters who argued preference would become largely illusory under the new point system.
That represents a real change from the prior regulation. Under the tenure-group system in effect through September 1, veterans’ preference operated only within a tenure group, meaning a veteran ranked in Group II could still fall behind a non-veteran ranked in Group I. The reduction-in-force statute requires OPM to give due effect to both military preference and tenure without mandating any specific order between them, and the new rule folds preference points directly into a single performance-based score instead of subordinating them to a tenure hierarchy that could outweigh a veteran’s status entirely.
Assignment Rights Narrow as Bump-and-Retreat Disappears
The rule also eliminates the long-standing bump-and-retreat process, under which a released employee could displace a lower-ranked worker in a different position or grade elsewhere in the agency. In its place, a released competitive-service employee now receives assignment rights only to a position held by a lower-ranked employee within the same tenure group, generally limited to three grades below the released employee’s own position, or five grades for certain veterans with a disability rating of 30 percent or more.
Timing determines which version of the rules applies to a given layoff. An agency that issued a reduction-in-force notice before September 2 must complete that action under the regulations in effect when the notice went out. Any notice issued on or after the effective date must follow the amended rules, meaning agencies currently planning workforce reductions are already operating under the performance-first formula rather than the tenure system it replaces.
OPM’s own record shows how contested the change was before it took effect. The agency’s 721 public comments raised a recurring objection: that numeric performance ratings carry more subjectivity than tenure or length of service, and that a supervisor’s rating can be shaped by factors that have nothing to do with actual job performance. OPM rejected that argument in the final rule, calling greater weight for performance consistent with federal merit-system principles. Whether that holds up in practice depends on something the rule itself cannot settle: how consistently agencies score employees once a reduction in force actually begins.
This article was drafted with AI assistance and reviewed for accuracy against primary sourcing.
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