AI/AIZENME
⚖️ WRITING · Copy & Docs Level: Beginner ⏱ 20 MIN Free & Open Source

Design Job Grading Ladders, Competency Matrices & Salary Bands with AI

Growing past 20–100 employees and realizing ad-hoc salary negotiation has created toxic pay inversions and vague promotion rules? Use AI to build a clear dual-track Job Grading ladder (IC vs Management), observable behavioral rubrics, and overlapping salary bands.

CORE TOOLS DeepSeek / Claude, Excel / Lark Sheets
BEST FOR Startup founders, HR Directors, People Ops leads, Department Heads
REQUIREMENTS List of core roles and approximate market pay anchors
✦ WHY THIS WORKFLOW

HR consultancies charge tens of thousands for bloated job-level manuals startups never use. This workflow builds a transparent, anti-pay-inversion career ladder and salary band table in 20 minutes.

✦ Interactive Workflow Animation Preview

Step-by-Step Action Checklist

0 / 4 Completed
READY-TO-USE PROMPT TEMPLATE
Open Official Tool / Repo ↗
Act as a Principal Organizational Development (OD) and Total Rewards (C&B) Consultant.
We are a [size, e.g., 60-person] company in [industry], with key roles in [Engineering, Product, Marketing/Ops].
Build a pragmatic, zero-bloat **Job Grading & Salary Band Framework**:
1) [5-Level Competency & Scope Matrix (L1–L5)]: Contrast each level across Problem Complexity, Autonomy, Business Impact, and Mentorship using concrete, verifiable deliverables;
2) [Broadband Salary Table]: Using market midpoint anchors of [insert approximate role midpoints], calculate Min, Midpoint, Max, Range Spread %, and Midpoint Progression % for L1–L5;
3) [Compa-Ratio × Performance Merit Increase Matrix]: Plus a practical playbook for fixing existing pay inversions between loyal tenured staff and new hires.
Use Cases & Tags:
Building IC (Professional) and Management dual-track career laddersReplacing vague traits with observable behavioral & delivery rubrics per levelDesigning overlapping salary bands (Min / Midpoint / Max & Compa-Ratio)Creating a Merit Increase Matrix (Performance Rating × Compa-Ratio)