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Criterion
Game Day workspace showing the question, observations, and next decision.
DevOps
Game Day
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Funnel Analysis workspace showing the question, observations, and next decision.
Growth
Funnel Analysis
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
Purposedifferent
In preparing for rare incidents, the method tests response capability under controlled conditions. It shows where assumptions about stability, roles, and recovery are too optimistic.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.When many visitors or users drop off along the way, the reason behind the number often stays hidden. Funnel Analysis exposes these transitions and makes visible exactly where the path collapses.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.
Complexitydifferent
HighHighMediumLow
Timedifferent
Halber Tag1-4 Wochen1-3 h30-60 min
Participantsdifferent
5-201-61-51-5
Formatdifferent
WorkshopAsyncAsyncWorkshop + async
Outputdifferent
Simulation Notes, Gaps List, Updated RunbooksExperiment results, Decision log, Learning summaryFunnel report, Drop-off analysis, Optimization hypothesesCompleted Experiment Canvas, Success Metric
Tagsno overlap
ResilienceOperationsIncident
ExperimentsGrowthAnalyticsValidation
AnalyticsConversionGrowth
ExperimentsValidationDiscoveryHypothesis
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