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Criterion
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
Paper illustration of a four-column Kanban board with limited ongoing work, a visible blocker and a review loop.
Engineering
Kanban
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
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 work sits in too many parallel streams, throughput suffers and no one sees the bottlenecks. Kanban makes the flow of work visible and limits overload so a system becomes calmer and more predictable.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.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
MediumMediumHighHigh
Timedifferent
30-90 minOngoing1-4 Wochen30-90 min Setup, danach laufend
Participantsdifferent
1-62-126-30 Experten1-8
Formatdifferent
Workshop + asyncWorkshop + asyncAsyncWorkshop + async
Outputdifferent
Decision Tree, Option Map, Assumption ListKanban board, WIP policies, Flow metricsExpert Forecast, Consensus Range, Assumption NotesForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
DecisionTreeOptions
FlowVisual managementDelivery
ForecastingExpertsDecisionStrategy
ForecastingFlowDelivery
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