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Criterion
Paper illustration for Diary Study.
UX Research
Diary Study
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
Purposedifferent
When experiences build up over days or weeks and a single session cannot capture them, Diary Study records the course of everyday life. Recurring triggers, moods, and habits become visible this way, beyond the sharpness of memory.Helps clarify scope, sequence, and delivery flow in concrete terms. It makes work, boundaries, and order steerable. The result is captured as Forecast Percentiles, Throughput Dataset, and Risk Communication.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 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
MediumHighLowHigh
Timedifferent
1-4 Wochen30-90 min Setup, danach laufend1-2 h1-4 Wochen
Participantsdifferent
5-201-82-86-30 Experten
Formatdifferent
AsyncWorkshop + asyncWorkshop + asyncAsync
Outputdifferent
Diary Entries, Longitudinal Patterns, Experience TimelineForecast Percentiles, Throughput Dataset, Risk CommunicationDIBB document, Belief list, Bet list, Learning reportExpert Forecast, Consensus Range, Assumption Notes
Tagsno overlap
UX researchTrackingBehavior
ForecastingFlowDelivery
StrategyDecisionAssumptionsHypothesis
ForecastingExpertsDecisionStrategy
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