# CTC Smart Tech — Performance Review · People Development Cycle

Updated 09.2026
A design case study from the AI HR capability: employees update evidence, managers review, HR coordinates calibration and employees respond to results.

An AI HR landing and Performance Analytics direction exist; the review system, assistant and apps in this kit are proposed prototypes using no real HR data.

## Business flow
- **Goals**: Publish criteria, weights and permissions before the cycle.
- **Evidence**: Employees update work and self-review.
- **Review**: Managers check against the rubric and write evidence-based comments.
- **Calibration**: HR checks consistency, coordinates and publishes within rights.
- **Development**: Employees respond; actions and coaching milestones are agreed.

## People Development workspace
Prototype dashboard with simulated records; states and process follow the solution design.
![Proposed prototype](https://solutions.smarttechctc.io/solutions/performance-review/screens/workspace.webp)

## People Development assistant
How do I draft a review from evidence? Sourced simulated scenario; no LLM call.
![Proposed prototype](https://solutions.smarttechctc.io/solutions/performance-review/screens/assistant.webp)

## App Employee
Work fully recorded.
- View the goals and criteria for the cycle.
- Submit evidence and the self-review.
- Respond to results once published.

Module: Goals → Evidence → Self-review → Response
Permissions: Own file only; cannot view colleagues’ reviews.
![App](https://solutions.smarttechctc.io/solutions/performance-review/screens/employee.webp)
![App](https://solutions.smarttechctc.io/solutions/performance-review/screens/employee-detail.webp)
Try it: https://solutions.smarttechctc.io/demo/solutions/performance-review/employee/

## App Line manager
Evidence-based comments and a development direction.
- Read employee evidence within the managed scope.
- Check against the rubric, write comments and development suggestions.
- Send the file to calibration.

Module: Evidence → Review → Development plan
Permissions: Assigned employees only; cannot publish results that skipped required steps.
![App](https://solutions.smarttechctc.io/solutions/performance-review/screens/manager.webp)
![App](https://solutions.smarttechctc.io/solutions/performance-review/screens/manager-detail.webp)
Try it: https://solutions.smarttechctc.io/demo/solutions/performance-review/manager/

## App HR / Calibration committee
Consistent criteria. Clear right to respond.
- Check process completeness and the basis for comments.
- Coordinate calibration and record reasons for any change.
- Publish within scope and receive responses.

Module: Progress → Calibration → Publish → Response
Permissions: Per review-cycle policy; admin rights are not used to disclose data beyond scope.
![App](https://solutions.smarttechctc.io/solutions/performance-review/screens/hr.webp)
![App](https://solutions.smarttechctc.io/solutions/performance-review/screens/hr-detail.webp)
Try it: https://solutions.smarttechctc.io/demo/solutions/performance-review/hr/

## Sourced assistant
The draft should list the available evidence, what is missing and questions for the conversation. This sample lacks the data to conclude on performance. The manager checks and decides the content; the AI does not score or make HR decisions.
- EVIDENCE-DEMO v1: Simulated work-completion documents with no real employee names or results.
- RUBRIC-DEMO v1: Reviews based on goals, output quality and collaboration; the manager is accountable for comments.
- POLICY-DEMO-HR: Employees may respond. No biometrics, inferred emotion or AI decides the final score.

## Pilot roadmap
- Choose one position group; agree the rubric and access policy.
- Build a cleared evidence set and the review forms.
- Run a trial cycle with three roles, calibration and responses.
- Accept access rights, review basis and development actions.

## Acceptance
- Submission only when the self-review has evidence and a complete checklist.
- Reviews are evidence-based before HR publishes.
- Employees can respond within their own file.
- No automated decisions on scores, pay or discipline.

## Boundary & production conditions
No automatic scoring, no pay/discipline decisions, no inference of emotion or personality.
The prototype stores data in one browser; there is no backend, multi-user authentication, cross-device sync or real LLM. APIs, backend permissions, audit and integration must be accepted separately.
Source: CTC Smart Tech AI HR & Performance Analytics direction
Case study: https://solutions.smarttechctc.io/case-study/performance-review-cycle/

## Problem
- Unaligned goals and scattered evidence force manual synthesis at period end.
- Managers apply different standards and are swayed by the most recent events.
- Reviews stop at a score, with no coaching plan or follow-up after the cycle.

## Input data
- Org structure, roles and reporting lines from the HRIS.
- Competency framework per position, goals, rating scale and review policy.
- Work evidence cleared for use; retention policy and feedback visibility rights.

## Deliverables
- Review-cycle process, KPI/OKR forms and rubrics per position group.
- Permission matrix for employee, manager, HR and calibration committee.
- Review workflow, sourced drafts, calibration minutes and development-plan template.
- Case study with screenshots, a workspace and sample apps for three roles; module/permission matrix and handover flow.

## Governance
- No faces, voices or EEG are used to infer emotion, personality or to score employee performance.
- AI never decides final scores, pay rises, discipline or termination.
- Employees can respond or request a re-check; every score change has an owner and a reason.
- 360 feedback is disclosed only per policy; groups too small to stay anonymous are avoided.