View methods side by side.
Choose up to four methods. Add them using the search and share the comparison by copying its link.
| Criterion |  Decision Making Delphi Method |  Product Discovery Opportunity Solution Tree |  Product Discovery Hypothesis Prioritization Canvas |  Product Strategy DIBB |
|---|---|---|---|---|
Purposedifferent | 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 discovery keeps swinging between goals, ideas, and learning loops, it creates clear steering logic. It connects the desired outcome, opportunities, and experiments into a legible structure. | 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. | DIBB helps clarify target groups, value, goals, and priorities by making the logic behind a decision explicit. It captures results as a DIBB document, belief list, bet list, and learning report. |
Complexitydifferent | High | Medium | Medium | Low |
Timedifferent | 1-4 Wochen | 1-2 h Setup, laufend | 60-90 min | 1-2 h |
Participantsdifferent | 6-30 Experten | 2-6 | 3-8 | 2-8 |
Formatdifferent | Async | Workshop + async | Workshop | Workshop + async |
Outputdifferent | Expert Forecast, Consensus Range, Assumption Notes | Opportunity Solution Tree, Experiment Backlog, Learning Log | Prioritization Canvas, Hypothesis Backlog | DIBB document, Belief list, Bet list, Learning report |
Tagsno overlap | ForecastingExpertsDecisionStrategy | DiscoveryOutcomesExperimentsOpportunity | ExperimentsPrioritizationDiscoveryHypothesis | StrategyDecisionAssumptionsHypothesis |