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Criterion
Design Thinking as a learning loop: an observation notebook, a focused problem statement, different idea sketches, a cardboard prototype and user-test notes. Feedback leads to new understanding.
Innovation
Design Thinking
Paper illustration for Failure Scenario Analysis.
Engineering
Failure Scenario Analysis
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Purposedifferent
For complex user problems with an uncertain cause, the method connects observation, interpretation, and experiment into a learning cycle. It keeps the focus on real needs and avoids premature solution language. This produces robust decisions for product and service.In critical processes, it is not enough to plan only for the normal case. Failure Scenario Analysis looks at the path into failure and shows which failures, chains, and control gaps cause the most damage.When demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all.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
HighMediumLowHigh
Timedifferent
1 Tag bis mehrere Wochen1-3 h1-5 Tage1-4 Wochen
Participantsdifferent
4-103-8Nutzertraffic1-6
Formatdifferent
WorkshopWorkshopAsyncAsync
Outputdifferent
Problem Statement, Prototype, Test LearningsFailure Scenarios, Risk Notes, Control Gaps, Test and Response ActionsInterest Metrics, Conversion Signal, Learning NoteExperiment results, Decision log, Learning summary
Tagsno overlap
InnovationPrototypeResearch
FailureResilienceRisk
ValidationExperimentsDemandGrowth
ExperimentsGrowthAnalyticsValidation
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