#metrics
Measuring what matters, and resisting the numbers that flatter.
Tagged articles (8)

Governing the Redeployment Dividend: Turning Saved Hours Into Value
AI is saving time almost everywhere. The organisations that gain from it are the ones whose Boards decide what the recovered capacity becomes.

The Appreciating Ledger: When AI Capital Outgrows the CFO's Rulebook
AI capital appreciates, accumulates, and crosses functions. The four indicator types let CFOs see what conventional project-ROI models structurally cannot.

Maximum Fidelity: How Four Indicator Types Strengthen Board Decisions
Four indicator types give boards progressively higher decision fidelity: lagging, leading, predictive, and reasoned. Together they represent the most accountable governance instrument available.

The AI Maturity Mirage: Diagnosing the Gap Between Investment and Readiness
Boards overestimate AI maturity by counting tools and pilots rather than capability. Three patterns create the illusion, and each can be diagnosed before it misleads.

AI’s Hidden ROI: Measuring Second and Third-Order Effects for Board Decisions
AI's largest returns arrive late, as second- and third-order effects on capability and business model. Boards need leading and predictive indicators to see them.

Rethinking Business Cases in the Age of AI: Building Your AI Business Case
A disciplined AI business case balances financial rigour with AI's unusual value patterns: the step-by-step construction, from opportunity to a case a Board can sign.

Rethinking Business Cases in the Age of AI: Creating the Foundation
AI's parallel, multi-speed adoption breaks the sequential logic of traditional business cases. These are the building blocks an evaluation needs before any number is written.

Measuring AI value: A strategic framework for Boards and business leaders
Measuring AI value needs more than total cost of ownership. A strategic framework for Boards, built on what the cloud business case taught me.
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