Value Proof, Portfolio Decisions & Misdiagnosis Risks

Value Proof, Portfolio Decisions & Misdiagnosis Risks governs the strength of a value claim. Claims progress through claimed, operational, measured, attributed and sustained evidence. Reviews test blind spots, incentives and alternative explanations before recommending Kill, Pivot, Persevere, Scale or Sunset.

Use value evidence to decide whether AI initiatives should continue, change, scale or stop. Separate weak proof from problems in strategy, data or delivery.

Why this matters

Large forecasts and enthusiastic anecdotes can outrun proof; early setbacks can also prompt an unjustified rejection. Commitment and claim language should reflect the current evidence and its limits.

Questions to bring to the work

• What is the strongest claim the evidence currently supports?
• Could another change, an omitted group or a flawed denominator reverse our conclusion?

Explore this chapter

Classify claims as claimed, operational, measured, attributed or sustained; keep evidence confidence separate from forecast size and close explicit proof gaps.

Inspect missing cases, denominators, counter-metrics and incentives to detect gaming, displaced burden or apparent improvement without outcome improvement.

Test alternative explanations and distinguish model, process, data, adoption and transition effects before crediting or rejecting the human–AI configuration.

Use evidence to recommend Kill, Pivot, Persevere, Scale or Sunset, with criteria set before review and closure obligations preserved.

State for whom, where, against what comparison and at what cost the effect occurred; revise claims as contrary evidence or context changes.

What useful evidence looks like

• A claim-to-evidence register with scope, comparator, costs, uncertainty and proof gaps.
• Gate records showing the criteria, confidence, downside, recommendation and resulting resource decision.

Move from understanding to practice

Framework source

Editorial adaptation from the supplied AIDIVE Version 1 master documents.

• AIDIVE Impact Dimension Version-1.docx · I.6 Value Proof, Portfolio Decisions & Misdiagnosis Risks; AIDIVE Impact - Practices & Playbook Version-1.docx · AR-IM16, AR-IM21, AR-IM25

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