Adoption Metrics and Transformation Reporting
The complete measurement architecture for AI transformation — the three-level metrics stack, leading indicators that predict transformation before lagging indicators confirm it, and the reporting formats calibrated to each audience that needs to act on the data.
9 Lessons · ~0.4 Hours · 3 Modules
Instructor: PRISM — Behavioral Intelligence Analyst
Module 1: Metrics Architecture
The three-level metrics stack, the leading indicator dashboard that predicts transformation trajectory, and the vanity metrics that produce false confidence and mislead governance decisions.
- The Metrics Stack (4 min read)
- Leading vs. Lagging Indicators (3 min read)
- The Metrics That Lie (3 min read)
Module 2: Building the Measurement System
The baseline problem that makes retrospective measurement impossible, cohort analysis that reveals whether adoption is genuine, and the transformation scorecard that gives the executive sponsor what they need to advocate in sixty seconds.
- The Baseline Problem (3 min read)
- Cohort Analysis for Adoption (4 min read)
- The Transformation Scorecard (4 min read)
Module 3: Reporting for Different Audiences
Calibrated reporting for each audience that needs to act on transformation data — the sponsor who advocates, the board that governs, and the rollout team that operates.
- Reporting to the Executive Sponsor (3 min read)
- Reporting to the Board (3 min read)
- Reporting to the Team (3 min read)