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| Criterion |  Agile Affinity Estimation |  Product Discovery Opportunity Solution Tree |  Agile Bucket System |  Product Discovery Hypothesis Prioritization Canvas |
|---|---|---|---|---|
Purposedifferent | When many tasks need to be classified quickly, it sorts them by perceived effort and similarity. It reduces the effort of fine-grained estimation for large volumes. | 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 a large batch of work needs a fast, rough estimate, it sorts items into predefined size buckets. It sorts work by value, risk, and delivery ability. The result is captured as a Bucketed Backlog, Relative Estimates, and Split Candidates. | 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. |
Complexitysame | Medium | Medium | Medium | Medium |
Timedifferent | 30-90 min | 1-2 h Setup, laufend | 30-90 min | 60-90 min |
Participantsdifferent | 3-12 | 2-6 | 3-12 | 3-8 |
Formatdifferent | Workshop | Workshop + async | Workshop | Workshop |
Outputdifferent | Affinity Size Map, Grouped Estimates, Unclear Items | Opportunity Solution Tree, Experiment Backlog, Learning Log | Bucketed Backlog, Relative Estimates, Split Candidates | Prioritization Canvas, Hypothesis Backlog |
Tagsno overlap | EstimationBacklogRelative sizing | DiscoveryOutcomesExperimentsOpportunity | EstimationBacklogRelative sizing | ExperimentsPrioritizationDiscoveryHypothesis |