Free Lesson
Accuracy Is Not an Outcome: The Dashboard Lie
Part of The Five Dysfuntions of AI Transformation
30 min
Oct 7, 2026 2:00 PM
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What you'll learn
Tell Output Metrics From Outcome Metrics
Separate model accuracy from revenue lift, cost reduction, and decision quality — and know which ones to manage.
Build an Outcome-First Dashboard
Design a review rhythm where business KPIs come before any technical metric — and what to do when they disagree.
Write Kill Criteria That Actually Kill
Define shutdown conditions upfront ('we stop if X doesn't move by Y') so failing initiatives die before draining budget.
Why this topic matters
Run AI as a project and success is measured in delivery dates, accuracy, and feature completeness. A 94% accurate model that moves no business metric is a failed investment in a success costume. This is Dysfunction 5: Inattention to Outcomes, fed by every layer below. Teams celebrate green dashboards while the P&L stays flat, because nobody defined 'working' upfront. You leave with rituals that measure what matters — and kill what doesn't.
