PI - Reviews
Cohort-level analysis of a review cycle — talent grid, manager calibration, benchmarking, and lenses for performance, development, risk, culture, and collaboration.
11 articles
- Reviews OverviewThe cohort-level read on a single review cycle — performance distribution, sentiment, perspective alignment, top themes.
- Collab Points (lens)The recognition leaderboard — who’s being recognised, how broadly, and whether recognition aligns with performance.
- Culture (lens)People-investment evidence from review narratives — who’s mentoring, building teams, developing talent.
- Collaboration (lens)Cross-department collaboration patterns extracted from review narratives — strongest connections, silos, networks, evidence.
- Development (lens)The cohort-level read on development needs — top areas, top strengths, and a department × capability skills matrix.
- Calibration (lens)Rating distribution, per-manager calibration, and self-vs-manager perspective gaps for any rating dimension in the review.
- People (lens)An employee-by-employee table for the selected review cycle — AI performance level, development area, sentiment, perspective alignment.
- BenchmarkA scatter plot that lets you correlate any two numeric fields — typically financial metrics against AI performance signals.
- ManagersManager effectiveness across the cycle — review quality, sentiment, team performance distribution, and calibration consistency.
- Talent GridA 9-box matrix placing every employee on configurable X and Y axes — the classic talent map, populated automatically from AI signals.
- Risk (lens)Retention, burnout, and disengagement signals extracted from reviews — by department, by performance level, with outlier detection.