KPI's (that I generally follow) to build High

Evidence based research that I generally use: SPACE study for Developer Productivity, Developer Wishlist, Leveraging Ai to drive Developer Sat, Scalability & Sustainability

Operational Excellence: Engineering Velocity / Sprint Velocity v/s. Burnout risks, Bus Factor (Enabler) (Tech Infra: Uplevel, Code Climate, Jira, Confluence)
Performance Management metric: % of High Performers, Medium Performers, Low Performers (Goal based); % of High Potential, Medium Potential (Critical Behaviors based)
Performance Management metric: Movement across buckets (especially, Medium to High Potential, High Performance)
Performance Management metrics: % of critical roles aligned to career paths, % of development paths alignment & progress on monthly basis
Engagement metric: eNPS, mNPS (RAG for Critical functions, High Performers - High Potentials bucket, High Performers bucket, Overall Org)
Alignment metrics: % of OKR deployment in Critical teams (Product, Engineering, Growth & CX) at Function & Team level
Alignment metrics: Overall OKR deployment %, OKR weekly checkins %, OKR scores, Displacement efforts %
Culture metric: % of overall alignment with Critical Behaviors, mNPS
Talent Management metric: Talent pipeline for middle management & leadership + % of succession planning for all critical roles
Utilization %, Absenteeism rate (Planned, Unplanned), Productivity Leaks
Compensation metric: % of team around 80th percentile of market rate, % of critical roles around 80th percentile, Any strong anomalies/disparity to market benchmarks
Talent Acquisition metric: Referral rate, Quality of Hire score (Critical Behaviors + Skill proficiency), Onboarding Score, P0 - Critical roles ETA, Pipeline conversions %, Fulfillment estimation v/s. Actual timelines