Measuring Success of AI Team

Can replicate similar style dashboards to measure effectiveness of different teams / organizations

Cost Savings by AI Product

Capacity Agent

Incorporates bottom-up activities and processes of roles and departments to achieve work. Differential created between current processes and new processes with AI products delivered to determine an impact to FTE change per activity and scaled up for total cost savings (Activities × Occurrences).

High Level Example

"TLF Agent" turns SAP/table shells into spec-as-code, auto-generates and QC's SAS/R TLFs with review-by-exception, cutting Oncology Biometrics per-cut effort from ~8 to ~3 FTE-weeks (~60%) while staying audit-ready.

Efficacy

Evaluation Set Scores by AI Product

Product Evaluation Standards

Each AI product maintains a curated evaluation set developed collaboratively between the AI team and oncology biometrics SMEs. Department leadership defines pass/fail thresholds for production deployment.

Evaluation Framework

Scores improve from 70% to 92% as agents learn from production feedback and model updates are deployed.

Team Performance

Performance Analytics

Track team velocity, product quality, and development efficiency as AI agents are integrated into workflows. Measures innovation speed (POCs), delivery acceleration (time to launch), adoption patterns (tool usage), and quality trends (bugs reported).

Current Performance

Team velocity improved from 3 to 13 POCs/month (+333%), while time-to-launch decreased from 45 to 21 days (53% faster) and bugs reduced by 75%.

Function Upskilling

Upskilling & Engagement

Track function growth, collaboration, and contribution patterns as employees develop AI/ML skills and participate in agent development. Measures expanding contributor base, innovation outputs, code contributions, and cross-functional collaboration through working groups.

Growth Overview

Contributor base grew from 8 to 26 people (+225%), with prototype submissions increasing 5.4x and working groups expanding from 2 to 7 active teams.

User Satisfaction

No metrics matter if stakeholders aren't happy with the products and methodologies.

4.7
Overall Rating
92%
Would Recommend
87%
Satisfaction Score

Details

Continuous feedback collection through surveys, interviews, and usage patterns.

Survey Responses: 156

NPS Score: +68

Response Rate: 73%

[Set up satisfaction surveys]