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| Criterion | ![]() Agile Planning Poker | ![]() Product Strategy DIBB | ![]() Agile Bucket System | ![]() Decision Making Delphi Method |
|---|---|---|---|---|
Purposedifferent | When estimates within the team diverge too much, it puts differing expectations on a common test bench. It separates rough complexity from unspoken assumptions. | 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. | 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 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. |
Complexitydifferent | Low | Low | Medium | High |
Timedifferent | 2-5 min je Item | 1-2 h | 30-90 min | 1-4 Wochen |
Participantsdifferent | 3-9 | 2-8 | 3-12 | 6-30 Experten |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Async |
Outputdifferent | Relative Estimates, Assumption Notes, Split Candidates | DIBB document, Belief list, Bet list, Learning report | Bucketed Backlog, Relative Estimates, Split Candidates | Expert Forecast, Consensus Range, Assumption Notes |
Tagsno overlap | EstimationAgileRelative sizingTeam | StrategyDecisionAssumptionsHypothesis | EstimationBacklogRelative sizing | ForecastingExpertsDecisionStrategy |



