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| Criterion |  Delivery Monte Carlo Forecasting |  Product Discovery Hypothesis Prioritization Canvas |  Decision Making Delphi Method |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
Purposedifferent | Helps clarify scope, sequence, and delivery flow in concrete terms. It makes work, boundaries, and order steerable. The result is captured as Forecast Percentiles, Throughput Dataset, and Risk Communication. | 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. | When knowledge is distributed and direct dominance should be avoided, groups quickly fall under the sway of their opinion leaders. The Delphi Method gathers assessments iteratively and gradually brings expert judgments closer together. | 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 | High | Medium | High | Low |
Timedifferent | 30-90 min Setup, danach laufend | 60-90 min | 1-4 Wochen | 30-60 min |
Participantsdifferent | 1-8 | 3-8 | 6-30 Experten | 1-5 |
Formatdifferent | Workshop + async | Workshop | Async | Workshop + async |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Prioritization Canvas, Hypothesis Backlog | Expert Forecast, Consensus Range, Assumption Notes | Completed Experiment Canvas, Success Metric |
Tagsno overlap | ForecastingFlowDelivery | ExperimentsPrioritizationDiscoveryHypothesis | ForecastingExpertsDecisionStrategy | ExperimentsValidationDiscoveryHypothesis |