Berkshire Blog

The Case for Objective Performance Management: Practical Steps to Reduce Risk and Improve Decisions

Written by Berkshire | June 5 2026

Performance management is often treated as an HR routine - an annual cycle of forms, ratings, and approvals. But as discussed in the webinar The Case for Objective Performance Management Processes: Pay Equity, Promotions, and Terminations (RIF), performance reviews are far more than just an annual feedback loop. They directly influence pay, promotions, and terminations, and they frequently become central evidence when an employer needs to defend decisions during internal investigations, government inquiries, or litigation.

The panel’s message was clear: performance management systems can protect an organization or create challenges, depending on how thoughtfully they are designed, implemented, and audited.

Why performance management is under a brighter spotlight

Performance management has always mattered, but it has become even more relevant in the current environment, where organizations may be asked to demonstrate how employment outcomes connect to merit-based performance. Employers, particularly federal contractors, can face questions like: How are you making pay and promotion decisions? and Can you show that performance connects to outcomes? That makes performance rating data, documentation quality, and consistency more important than ever. Also, more and more organizations are using AI to check whether documentation supports scores that are being given and this creates additional scrutiny due to it rarely being checked for consistency or what it is “learning.”

The biggest recurring issue: systems that exist, but don’t run as intended

Some organizations invest heavily in performance management systems yet struggle to proactively check whether managers are applying them consistently and as designed. When organizations assume the process is “running smoothly” without auditing it, problems can persist unnoticed until a dispute arises.

The panel also stressed that uniform practices aren’t enough on paper; uniform implementation matters. Employees should not be subjected to different standards simply because their manager treats the rating scale differently or puts in dramatically less effort than others.

Subjectivity creates risk—especially when it becomes a story others can fill in

Performance evaluations often contain unavoidable subjectivity. But the panel argued that subjectivity is also where employers face the most claims of bias, because inconsistent or unclear ratings can be interpreted as unfair, even if unfairness wasn’t intended. And when decisions aren’t explainable in concrete terms, it becomes easier for others to assume a non-performance explanation.

The practical recommendation: focus on what can be made tangible. For instance, instead of vague statements like “writing skills aren’t where we expect them to be,” document specific examples such as errors found in a report, inaccuracies, or missed expectations with clear detail.

Common rater biases HR should train and design around

The panel highlighted multiple rater biases that commonly distort ratings:

  • Halo/Horns: One standout positive or negative event overshadows the full year.

  • Leniency/Severity: Some managers inflate ratings; others are unusually strict.

  • Central tendency: Managers avoid the ends of the scale and cluster ratings in the middle.

  • Primacy/Recency: Early impressions or recent events drive the entire rating.

  • “Similar to me” effect: Managers rate people more favorably when they identify with them.

  • Compare/contrast: Employees are rated against each other instead of against defined standards.

  • Stereotypes: Heuristics and assumptions can influence perceptions of performance.

Training helps, but the panel emphasized that training alone is not enough; the system must be structurally designed to reduce discretion and inconsistency.

The “ski slope” problem: when almost everyone is rated at the top

A common pattern that the speakers see: performance rating distributions with little variation, such as 97% of employees receiving the top rating. That typically doesn’t mean 97% are exceptional. More often, managers avoid giving lower ratings because they don't want to impact raises or because they want to avoid difficult conversations.

This becomes a business and risk problem. From an analytics perspective, when nearly everyone has the same rating, the lack of variation in the data makes performance less useful as an explanatory factor in pay analyses. That leaves more unexplained pay variation and creates avoidable questions about why pay differs among similarly situated employees

Why this matters most in terminations and reductions in force (RIF)

Terminations and RIF decisions are among the highest-risk personnel actions. In those moments, performance ratings often become the key input, and organizations may have to explain their decision process, especially for employees age 40+ where specific disclosures are required in group termination situations.

A frequent defensibility problem arises when leaders describe an employee as a poor performer, but the person’s performance reviews are “stellar”. This mismatch undermines credibility and increases risk.

What “more objective” really looks like

“Objectivity” is not a gimmick, but the product of transparency, structure, documentation, and consistency. Key methods discussed included:

  • Transparency in what earns each rating: Employees should not be guessing how to achieve top ratings
  • Documentation that matches scores: Narrative and rating should align; inconsistencies can be flagged and scrutinized
  • Ongoing documentation and feedback: Don’t cram everything into a two-week year-end scramble; keep documentation open year-round and enable timely feedback
  • Behaviorally anchored rating scales (BARS): Tie rating levels to job-specific behavioral examples, leveraging job analysis and defined job dimensions
  • Calibration panels: Having multiple leaders review ratings increases consistency and improves defensibility, especially because decisions can be attributed to a group, not a single supervisor

Top takeaways

  1. Performance management is core evidence in disputes about pay, promotions, and terminations. For these reasons, performance management systems must be defensible, not just functional
  2. Reduce subjectivity through system design, not just manager training
  3. Avoid inflated ratings and low-variation distributions; they reduce the usefulness of performance data and can increase risk
  4. Make standards transparent and anchored to job realities through job analysis and behavior-based criteria
  5. Use calibration and auditing to ensure consistent implementation and catch problems early, preferably with appropriate confidentiality and legal guidance
  6. Be cautious in the use of AI to ensure that it isn’t relied upon without checks and scrutiny