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Selected:Hypothesis-Driven Troubleshooting Pretotyping Experiment Canvas Hypothesis Prioritization Canvas

Criterion	Engineering Hypothesis-Driven Troubleshooting	Product Discovery Pretotyping	Product Discovery Experiment Canvas	Product Discovery Hypothesis Prioritization Canvas
Purposedifferent	When systems fail unexpectedly, spontaneous attempts often produce more noise than insight. Hypothesis-driven Troubleshooting translates symptoms into testable assumptions and makes troubleshooting learnable.	Pretotyping clarifies whether a customer problem and solution idea create enough real demand. It separates problem, assumption, solution, and evidence, and captures the result as a pretotyping sketch, test setup, and conversion data.	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.	When many hypotheses compete for attention, it brings order to their learning sequence and importance. It separates problem, assumption, solution, and evidence. The result is captured as a prioritization canvas and a hypothesis backlog.
Complexitydifferent	Medium	Low	Low	Medium
Timedifferent	30-240 min	Stunden bis wenige Tage	30-60 min	60-90 min
Participantsdifferent	1-6	1-4	1-5	3-8
Formatdifferent	Workshop + async	Workshop + async	Workshop + async	Workshop
Outputdifferent	Hypothesis Log, Test Plan, Evidence Notes, Diagnosis Summary	Pretotyping sketch, Test setup, Conversion data, Go or no-go decision	Completed Experiment Canvas, Success Metric	Prioritization Canvas, Hypothesis Backlog
Tagsno overlap	TroubleshootingProblem solvingDiagnosis	ValidationDemandMVP	ExperimentsValidationDiscoveryHypothesis	ExperimentsPrioritizationDiscoveryHypothesis

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