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Criterion
A hypothetical failure makes concrete risks, signals, and fitting mitigations visible.
Decision Making
Pre-Mortem
Paper illustration for Causal Factor Analysis.
Operations
Causal Factor Analysis
Paper illustration of a calm four-quadrant Assumption Map with hypothesis cards and emphasis on important assumptions with little evidence.
Product Discovery
Assumption Mapping
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Purposedifferent
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.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.When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first.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
LowHighMediumHigh
Timedifferent
20–45 min2-6 h45-60 min1-4 Wochen
Participantsdifferent
Small cross-functional group3-102-81-6
Formatdifferent
WorkshopWorkshop + asyncWorkshop + asyncAsync
Outputdifferent
Risk list, Mitigation plan, Assumption logEvent Timeline, Causal Factor Chart, Cause List, Corrective ActionsAssumption map, Test backlog, Risk rankingExperiment results, Decision log, Learning summary
Tagsno overlap
RiskDecisionFailurePlanning
CausalityIncidentRoot causeTimeline
AssumptionsRiskExperimentsValidation
ExperimentsGrowthAnalyticsValidation
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