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HR13·Promotion Calibration

Promotion / Calibration Panels

Extract promotion evidence, compare cases against shared criteria, and produce calibration narratives for panel review.

Before you start

What you’ll need

  • Completed performance review packs for all promotion candidates
  • Agreed promotion criteria framework approved by leadership
  • Access to an approved enterprise GenAI tool for evidence extraction
  • Promotion Criteria Framework
  • Panel Governance Guidelines

Who’s involved

  • HR Business PartnerFacilitates the calibration process, verifies extracted evidence, and ensures consistent criteria application across cases.
  • Panel ChairReviews comparative analysis and calibration narratives, approves final promotion panel outcomes.

Safe use

  • Data HandlingThis workflow processes sensitive performance data (review ratings, manager commentary, development notes) and promotion candidacy details. Do not paste these inputs into public or unapproved GenAI tools.
  • VerificationGenAI may fabricate evidence, misattribute performance achievements across candidates, or inflate justification strength. Verify every extracted citation against the original review pack before presenting to the panel.

Execution steps

Hybrid

Inputs

  • Confirm all promotion candidates have completed performance review packs
  • Verify the promotion criteria framework is current and approved
  • Check that panel governance guidelines are available and distributed

Data Handling: Do not include candidate personal contact details or compensation data in the prompt — use candidate identifiers only.

Prompt

Extract criterion-linked promotion evidence per candidate

CONTEXT
You will be provided with the following source documents:
1. Performance Review Pack
2. Promotion Criteria Framework
3. Panel Governance Guidelines

TASK
For each candidate, extract specific, verbatim quotes or concrete facts from their performance review pack that relate to each promotion criterion. Produce a Promotion Evidence Matrix mapping every candidate to every criterion.

OUTPUT FORMAT
Use a markdown table with the following columns:
- **Candidate** — candidate identifier
- **Criterion** — the promotion criterion being assessed
- **Evidence** — verbatim quote or specific fact from the review pack
- **Source** — which section of the review pack the evidence comes from (self-assessment, manager narrative, peer feedback, goals summary)
- **Strength** — [Strong / Partial / No Evidence]

Include one row per candidate-criterion pair. If no evidence exists for a criterion, enter "No evidence found" in the Evidence column and "No Evidence" in the Strength column.

CONSTRAINTS
Do not infer or assume achievements not explicitly stated in the review pack. Do not paraphrase — use verbatim quotes where possible. Do not include personally identifiable contact details or compensation data in the output.

Outputs

  • Promotion Evidence Matrix

Verification: Verify that every evidence citation maps to an actual passage in the candidate’s review pack — GenAI may fabricate quotes or conflate candidates.

Hybrid

Inputs

Prompt

Flag misattributed or fabricated evidence entries

CONTEXT
You will be provided with a Promotion Evidence Matrix and the original performance review packs it was derived from.

TASK
Compare each evidence entry in the matrix against the original source document. Flag any entry where the quoted evidence cannot be found in the source, is materially paraphrased, or is attributed to the wrong candidate.

OUTPUT FORMAT
Return a markdown table with columns:
- **Candidate** — candidate identifier
- **Criterion** — the criterion in question
- **Status** — [Confirmed / Corrected / Removed]
- **Note** — explanation of any correction or removal

CONSTRAINTS
Do not add new evidence that was not in the original extraction. Only confirm, correct, or remove existing entries.

Outputs

  • Verified Evidence Matrix
  • Confirm every Strong-rated entry has a traceable verbatim quote
  • Verify no evidence is attributed to the wrong candidate
GenAI

Inputs

  • Verified Evidence Matrix
  • Confirm the Verified Evidence Matrix reflects all corrections from the verification step

Prompt

Compare promotion candidates consistently across criteria

CONTEXT
You will be provided with a Verified Evidence Matrix mapping multiple promotion candidates to the same set of promotion criteria, each with strength ratings.

TASK
Produce a Comparative Case Analysis that places all candidates side by side for each promotion criterion. For each criterion, summarize the relative strength of evidence across candidates so the panel can see where cases diverge.

OUTPUT FORMAT
Structure the output as follows:

For each criterion, use a section header and a markdown table:

### [Criterion Name]
| Candidate | Strength | Key Evidence Summary |
|---|---|---|
| [Candidate A] | [Strong/Partial/No Evidence] | One-sentence summary of evidence |

After all criteria sections, include a **Summary Heat Map** — a single table with candidates as rows and criteria as columns, each cell showing [S / P / N] for Strong, Partial, or No Evidence.

CONSTRAINTS
Do not rank or recommend candidates — this step is purely comparative. Do not introduce evidence not present in the Verified Evidence Matrix. Do not editorialize about candidate potential.

Outputs

Verification: Verify the heat map ratings match the Verified Evidence Matrix — GenAI may inadvertently upgrade Partial ratings to Strong in the summary.

GenAI

Inputs

  • Verified Evidence Matrix
  • Comparative Case Analysis

Prompt

Identify cases with weak or inconsistent promotion evidence

CONTEXT
You will be provided with a Verified Evidence Matrix and a Comparative Case Analysis for promotion candidates being reviewed by a calibration panel.

TASK
Produce a Justification Strength Report that flags every candidate-criterion pair where the evidence is Partial or No Evidence, and identifies candidates whose overall case relies on fewer than half the criteria having Strong evidence. Highlight inconsistencies where a candidate is Strong on one criterion but has No Evidence on a closely related criterion.

OUTPUT FORMAT
Structure the output in three sections:

**1. Weak Evidence Flags**
A markdown table with columns:
- **Candidate** — candidate identifier
- **Criterion** — the weak criterion
- **Current Strength** — [Partial / No Evidence]
- **Risk Note** — one sentence describing why this gap matters for the promotion case

**2. Below-Threshold Cases**
List each candidate where fewer than half the criteria are rated Strong, with a count summary (e.g., "2 of 6 criteria rated Strong").

**3. Inconsistency Alerts**
List candidate-criterion pairs where strength ratings on related criteria are contradictory, with a brief explanation.

CONSTRAINTS
Do not recommend whether a candidate should be promoted. Do not fabricate risk notes — each must trace to specific evidence gaps. Do not include candidates with Strong ratings across all criteria.
GenAI

Inputs

  • Comparative Case Analysis
  • Justification Strength Report

Prompt

Draft evidence-based calibration narrative per candidate

CONTEXT
You will be provided with a Comparative Case Analysis and a Justification Strength Report for promotion candidates under panel review.

TASK
For each candidate, draft a calibration narrative that explains how their evidence compares to the promotion criteria and to other candidates reviewed in the same cycle. Each narrative should state the evidence basis, note any gaps flagged in the Justification Strength Report, and provide a clear recommendation category.

OUTPUT FORMAT
For each candidate, use this structure:

### [Candidate Identifier]
- **Recommendation**: [Promote / Defer with Development Plan / Do Not Promote]
- **Evidence Summary**: 2–3 sentences consolidating the strongest criterion-evidence pairs
- **Gaps Acknowledged**: 1–2 sentences noting criteria with Partial or No Evidence
- **Comparative Position**: One sentence stating how this case compares to other candidates on the shared criteria
- **Panel Discussion Point**: One question or concern the panel should address before finalizing

EXAMPLE
### Candidate A
- **Recommendation**: Promote
- **Evidence Summary**: Candidate A demonstrated Strong evidence on leadership impact ("led cross-functional initiative reducing cycle time by 30%") and technical depth ("redesigned data pipeline serving 200+ users").
- **Gaps Acknowledged**: No direct evidence of external stakeholder management, rated Partial on that criterion.
- **Comparative Position**: Strongest overall case in this cycle, with the highest count of Strong-rated criteria.
- **Panel Discussion Point**: Should the stakeholder management gap be addressed through a development plan post-promotion?

CONSTRAINTS
Do not fabricate evidence or achievements. Every claim must trace to the Comparative Case Analysis or Justification Strength Report. Do not use vague language like "shows promise" — cite specific evidence. Do not include compensation or personal details.

Outputs

  • Draft Calibration Narratives

Verification: Verify that recommendation categories are consistent with the justification strength — GenAI may recommend Promote for candidates flagged as below-threshold.

Hybrid

Inputs

  • Draft Calibration Narratives
  • Justification Strength Report
  • Comparative Case Analysis

Prompt

Incorporate panel feedback into final promotion outcomes

CONTEXT
You will be provided with Draft Calibration Narratives and specific feedback from the calibration panel on recommendation changes, additional discussion points, or evidence reassessments.

TASK
Update the calibration narratives based on panel feedback to produce the final Promotion Panel Outcomes document. Adjust recommendation categories, evidence summaries, and discussion points as directed. Add a decision rationale for any changes made from the draft.

OUTPUT FORMAT
For each candidate, use this structure:

### [Candidate Identifier]
- **Final Decision**: [Promote / Defer with Development Plan / Do Not Promote]
- **Evidence Summary**: 2–3 sentences consolidating the evidence basis
- **Gaps Acknowledged**: 1–2 sentences noting unresolved criteria gaps
- **Panel Rationale**: 1–2 sentences explaining the panel reasoning, especially where the final decision differs from the draft recommendation
- **Next Steps**: One sentence stating the immediate action

At the end, include a **Decisions Summary Table**:
| Candidate | Final Decision | Changed from Draft? | Key Rationale |
|---|---|---|---|

CONSTRAINTS
Do not change recommendations unless explicitly directed by panel feedback. Do not remove candidates from the document. Preserve the evidence trail from prior steps.

Outputs

  • Confirm every candidate has exactly one final decision category
  • Verify each decision rationale cites specific evidence from the review
  • Check that all panel feedback has been incorporated and documented
  • Confirm the Decisions Summary Table matches the individual candidate sections

Reference

Guardrails

  • Evidence-Linked Decisions OnlyEvery promotion recommendation must cite specific evidence from the Verified Evidence Matrix — no decisions based on reputation or tenure alone.
  • Consistent Criteria ApplicationApply the same promotion criteria to every candidate in the cycle — do not adjust thresholds or weighting between cases.
  • Separate Extraction From RecommendationComplete evidence extraction and verification before generating comparative analysis or narratives to prevent confirmation bias.

Pitfalls

  • Pasting unredacted performance ratings or sensitive manager commentary into a public or unapproved GenAI tool.
  • Accepting AI-extracted evidence without verifying quotes against the original performance review pack.
  • Allowing the AI to infer achievements or competencies not explicitly documented in the review materials.
  • Skipping the justification strength check and presenting under-evidenced cases as ready for promotion.

Definition of Done

  • Every candidate calibration narrative cites specific verbatim evidence from the verified review packs.
  • The Comparative Case Analysis covers every candidate against every promotion criterion in a single consistent view.
  • The Justification Strength Report flags all candidates with fewer than half their criteria rated Strong.
  • The Promotion Panel Outcomes document assigns a final decision to every candidate with a panel-approved rationale.

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AGASI AiOS · HR13 v1.0 · Apr 8, 2026