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Criterion
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
Paper illustration for NoEstimates.
Agile
NoEstimates
Paper matrix with six colored hat cards for information, feeling, value, caution, ideas and process control.
Facilitation
Six Thinking Hats
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Purposedifferent
For decisions with follow-on paths and dependencies, a linear comparison is often not enough. A Decision Tree shows how options branch under conditions and which consequences hang on each branch.When estimating slows a team down more than it helps, it shifts the focus to flow, small slices, and real lead time. It sorts work by value, risk, and delivery ability. The result is captured as Throughput Data, Flow Forecast, and Slicing Rules.When a topic gets stuck too quickly in the same thinking mode, Six Thinking Hats deliberately separates the perspectives. This means facts, risks, creativity, and emotional signals get worked through one after another instead of mixed together.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.
Complexitydifferent
MediumMediumMediumHigh
Timedifferent
30-90 minlaufend45-90 min30-90 min Setup, danach laufend
Participantsdifferent
1-62-124-121-8
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshopWorkshop + async
Outputdifferent
Decision Tree, Option Map, Assumption ListThroughput Data, Flow Forecast, Slicing RulesPerspective Notes, Decision Inputs, Action ItemsForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
DecisionTreeOptions
EstimationForecastingFlow
FacilitationOptionsDecision
ForecastingFlowDelivery
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