Alignment - Self & Manager

The Alignment - Self & Manager report page presents the visuals listed below. Each row gives the on-screen name, its underlying metric, and a short description; see the metric glossary for the full formula and interpretation.

Visuals:

Name	Measure	Description
Total reviews	Count of review IDs (one per performance review)	Total number of performance reviews in scope. It's the base against which the review-status, alignment, and rating measures are read, so every review share on the page is relative to it. It counts reviews, not people, though typically each worker has one review per cycle. Read the completion and alignment percentages relative to this total.
Self-review rating distribution	Count of reviews with this worker self-rating÷ count of all reviews (in the current selection)	How workers' self-ratings spread across the rating scale, showing what share of reviews land at each self-rating value. It reveals self-assessment tendencies: a skew toward the top means workers rate themselves generously, a spread or lower cluster means more critical self-views. Because it's a share of the total in the selection, filtering re-bases the percentages. Read against the manager rating distribution to compare how workers rate themselves versus how managers rate them.
Initial manager/worker alignment	Count of reviews, by initial alignment (Yes / No / Not Available)	How many reviews had the worker's self-rating agree with the manager's rating at the initial stage, split into Yes (they matched), No (they differed), and Not Available (no worker rating to compare). It gauges how aligned self-assessment and manager assessment are before any final calibration; a large No slice signals gaps between how workers and managers see performance. It counts reviews, not people.
Manager rating distribution	Count of reviews with this manager rating÷ count of all reviews (in the current selection)	How managers' ratings spread across the rating scale, showing what share of reviews land at each manager-given value. It reveals rating tendencies on the manager side: a skew toward the top means lenient rating, a wider or lower spread means more differentiated assessment. Because it's a share of the total in the selection, filtering re-bases the percentages. Read against the self-review rating distribution to compare how managers rate versus how workers rate themselves.
Final manager/worker alignment	Count of reviews, by final alignment (Yes / No / Not Available)	How many reviews had the worker's self-rating agree with the review's final rating, split into Yes (matched), No (differed), and Not Available (no final rating yet). Unlike the initial version, which compares against the manager's own rating, this compares against the calibrated final rating, so it shows alignment after the process concludes. A large No slice means workers' self-view often diverges from where reviews land. It counts reviews, not people.
Final review rating distribution	Count of reviews with this final rating÷ count of all reviews (in the current selection)	How the calibrated final ratings spread across the rating scale, showing what share of reviews land at each final value. It's the outcome distribution after the review process, so it reflects where performance actually settles once self and manager inputs are reconciled. Because it's a share of the total in the selection, filtering re-bases the percentages. Read against the self-review and manager rating distributions to see how the final outcome differs from either input.

This is a tip message.

For more information about the visuals and metrics used in Analytics Hub, refer toVisuals in Analytics hub and Metric dictionary, respectively.