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| Criterion |  Product Strategy KPI Tree |  Product Discovery Experiment Canvas |  Product Strategy DIBB |
|---|---|---|---|
Purposedifferent | When metrics across the organization drift apart, it arranges drivers and effects under one shared logic. It connects customer value, product logic, and decision priorities. The result is captured as a KPI tree and owner list. | When experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric. | DIBB helps clarify target groups, value, goals, and priorities by making the logic behind a decision explicit. It captures results as a DIBB document, belief list, bet list, and learning report. |
Complexitydifferent | Medium | Low | Low |
Timedifferent | 90-180 min initial, dann laufend | 30-60 min | 1-2 h |
Participantsdifferent | 3-8 | 1-5 | 2-8 |
Formatsame | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | KPI Tree, Owner List | Completed Experiment Canvas, Success Metric | DIBB document, Belief list, Bet list, Learning report |
Tagsno overlap | MetricsStrategyAlignmentMeasurement | ExperimentsValidationDiscoveryHypothesis | StrategyDecisionAssumptionsHypothesis |
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