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Criterion
Paper illustration for Causal Factor Analysis.
Operations
Causal Factor Analysis
A hypothetical failure makes concrete risks, signals, and fitting mitigations visible.
Decision Making
Pre-Mortem
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Purposedifferent
For an event with a complicated course, the method breaks down the contributing factors along the timeline. It shows how conditions, decisions, and reactions together produce a course of events.In early initiatives with many uncertainties, planning quickly turns too optimistic. A pre-mortem makes the expected failure visible in advance and sharpens the view of causes, gaps, and countermeasures.When two variants compete, discussions quickly decide by taste rather than effect. A/B Testing checks behavior under controlled conditions and separates real improvement from chance or expectation effects.
Complexitydifferent
HighLowHigh
Timedifferent
2-6 h20–45 min1-4 Wochen
Participantsdifferent
3-10Small cross-functional group1-6
Formatdifferent
Workshop + asyncWorkshopAsync
Outputdifferent
Event Timeline, Causal Factor Chart, Cause List, Corrective ActionsRisk list, Mitigation plan, Assumption logExperiment results, Decision log, Learning summary
Tagsno overlap
CausalityIncidentRoot causeTimeline
RiskDecisionFailurePlanning
ExperimentsGrowthAnalyticsValidation
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Paper illustration of a calm four-quadrant Assumption Map with hypothesis cards and emphasis on important assumptions with little evidence.
Product Discovery
Assumption Mapping
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
Paper illustration of an assumption matrix with prioritized test cards
Decision Making
Assumption Surfacing