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Performance
Merit Cycle Decision Support
Decision support surfaces performance evidence, compa-ratio, and equity flags.
The problem
Compensation reviewers lack unified performance context during merit decisions.
The opportunity
AI can reduce repetitive effort and surface options humans still decide — when grounded in the right data and oversight.
What the solution does
Decision support surfaces performance evidence, compa-ratio, and equity flags.
How it works
Performance, compensation, and tenure data are combined in reviewer workflows.
Who uses it
- Managers
- Employees
- HRBPs
Data required
- Relevant HRIS / ATS records
- Role or policy context
- Access and consent rules
AI / technology patterns
- Automation
- LLM
Reported impact
No independently reported impact recorded for this item yet.
Impact categories
- Decision support
- Quality
Limitations and risks
Bias inheritance, stale data, privacy obligations and over-automation of people decisions. Keep humans accountable for outcomes that affect careers.
What implementation requires
Start narrow, define evaluation criteria, involve legal/HR governance early, and measure adoption plus quality — not only model accuracy.
Updated 2026-08-09