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| Criterion |  Product Discovery Opportunity Scoring |  Agile Bucket System |  Agile Affinity Estimation |  Product Discovery Opportunity Solution Tree |
|---|---|---|---|---|
Purposedifferent | When opportunities need ranking by their effect, it makes importance and satisfaction directly comparable. It separates problem, assumption, solution, and evidence. The result is captured as an opportunity-score table and top outcomes. | 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 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. |
Complexitysame | Medium | Medium | Medium | Medium |
Timedifferent | 60-120 min | 30-90 min | 30-90 min | 1-2 h Setup, laufend |
Participantsdifferent | 3-6 | 3-12 | 3-12 | 2-6 |
Formatdifferent | Workshop + async | Workshop | Workshop | Workshop + async |
Outputdifferent | Opportunity Score Table, Top Outcomes | Bucketed Backlog, Relative Estimates, Split Candidates | Affinity Size Map, Grouped Estimates, Unclear Items | Opportunity Solution Tree, Experiment Backlog, Learning Log |
Tagsno overlap | PrioritizationDiscoveryOutcomesNeeds | EstimationBacklogRelative sizing | EstimationBacklogRelative sizing | DiscoveryOutcomesExperimentsOpportunity |