1) Define expectations
- Objectives — Set in the platform; linked to evidence sources
- Scorecards — Templates that combine Delivery, Skills, and Behaviors checklists
- Talent Bar — Minimum expectations by seniority; used to interpret performance
2) Capture evidence automatically
- Connectors pull from project management, docs, and communication tools
- Evidence is attached to objectives and performance dimensions
- AI can recommend or populate context from connected systems
- Reduces admin and “only loud work gets noticed”
3) Support manager evaluation
- Managers complete reviews using checklists of observable statements
- Reviews cover Delivery, Skills, and Behaviors — same structure for everyone
- Evidence is surfaced so managers evaluate with context, not memory alone
- AI assist can help summarise and structure feedback
4) Calibrate results
- The Performance Team runs calibration: A-player cap, missing data, outliers
- Leadership reviews and approves final grades
- Ensures fairness and consistency across teams
5) Deliver outcomes
- Outcomes: promotions, compensation, equity, development, PIPs, exits
- Results are communicated; managers deliver feedback in one-to-ones
End-to-end in the platform
| Stage | In the platform |
|---|---|
| Define | Objectives, scorecard templates, Talent Bar by level |
| Capture | Connectors + AI |
| Evaluate | Checklist-driven reviews with evidence in context |
| Calibrate | Grade calculation, calibration checks, leadership approval (process; platform supports data and workflows) |
| Deliver | Outcome decisions; manager-led feedback |