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Criterion
Paper illustration for Ideal Days.
Agile
Ideal Days
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
Paper illustration for Planning Poker.
Agile
Planning Poker
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
Purposedifferent
When effort needs to be thought of as real working time, it offers a simple common denominator for comparison. It sorts work by value, risk, and delivery ability. The result is captured as Ideal Day Estimates, Assumption Notes, and Capacity Caveats.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 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.
Complexitydifferent
LowHighLowLow
Timedifferent
15-60 min1-4 Wochen2-5 min je Item1-2 h
Participantsdifferent
2-96-30 Experten3-92-8
Formatdifferent
Workshop + asyncAsyncWorkshop + asyncWorkshop + async
Outputdifferent
Ideal Day Estimates, Assumption Notes, Capacity CaveatsExpert Forecast, Consensus Range, Assumption NotesRelative Estimates, Assumption Notes, Split CandidatesDIBB document, Belief list, Bet list, Learning report
Tagsno overlap
EstimationEffortAgile
ForecastingExpertsDecisionStrategy
EstimationAgileRelative sizingTeam
StrategyDecisionAssumptionsHypothesis
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