Performance Scorecard System with Weighted Rankings

Overview: This project showcases a complete individual performance scorecard system, designed to rank and visualize key contributors across multiple KPIs. Using Python and Power BI, I created a backend scoring engine that transforms raw operational data into a full ranked scoring dataset—optimized for performance visibility and leadership clarity.

How It Works: • Raw agent or technician data is pulled and pre-processed • A Python script calculates rankings for each key metric across all individuals • Each metric is weighted based on its impact (metric driver analysis) • Final scores are computed using a composite weighted formula • The output is exported to Power BI as a clean, ranked dataset for interactive visualization

Key Features: • Custom score weighting based on what drives performance • Built-in flexibility to update weights, add/remove KPIs, or adjust logic • Full output includes stack rankings, top/worst performer views, and team-level averages • Output designed for leaders to identify strengths, gaps, and coaching priorities

Tools Used: Python • Power BI

Impact: This system eliminates guesswork by turning subjective evaluations into data-backed performance clarity. Leaders get a clear view of who’s excelling and where there are growth opportunities.