Portrait of Nilesh KasimahantiNilesh KasimahantiQA Lead, Electronic Arts
← Back to work

01 · Performance system

A weighted rating model that replaced subjective QA reviews

Before this existed, performance reviews on the team were a lead’s judgment call, applied inconsistently across testers at different levels. I designed a scoring system that replaces that judgment call with a formula anyone can audit.

The model scores every tester on two independent axes. Performance (60% of the score) is built entirely from objective data pulled out of Jira, QMetry, and attendance systems: bug quality and volume, test-case execution (volume, schedule accuracy, and cases-per-hour efficiency), and attendance. Potential (40% of the score) is four lead-assessed dimensions: impact and mentorship, communication, escalation handling, and process mindfulness. Each is scored 1 to 10 against a documented three-tier evidence rubric, so “exceeds expectations” means the same thing for every rater.

Neither axis uses one flat bar. Scores are role-adjusted: a QA Tester, a Senior QA Tester, and a Quality Analyst are held to different Low/Medium/High thresholds on the Performance axis, because a junior tester and a lead shouldn’t be judged against the same number. The two scores place every tester on a 9-box grid automatically, and the workbook includes a “how it works” reference tab so the model is replicable by someone else, not dependent on me to interpret it.

The model is implemented and in use. It's what team performance decisions are now made against, so those calls rest on conclusive data rather than a lead's recollection. I've run a full rating cycle on it for a 20-person team (1 lead, 2 quality analysts, 17 testers), and the tracker covered 37 people at the team's peak. It's the artifact I'd point to first if you're hiring for the "manager" half of QA Lead / Manager. This is what fair, defensible performance measurement looks like when nobody's watching.
Live demo: try the sliders

9-Box Scoring Simulator

The weighted formula behind the performance model. Adjust the inputs and watch the placement change.

Performance (hard score)

Potential (soft score)

Potential ↑

Performance →

Lower bandMid bandHigher band

Weights match the real model's structure. Role band thresholds shown are illustrative for this demo, not the calibrated production values.