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Criterion
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Paper illustration for Future Reality Tree.
Systems Thinking
Future Reality Tree
Paper illustration for OODA Loop.
Decision Making
OODA Loop
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
Purposedifferent
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.A Future Reality Tree shows how desired actions are meant to lead to a better system state. The method checks whether a path of change holds together logically before time flows into implementation.In dynamic situations, decisions become outdated faster than they can be prepared. The OODA Loop holds observing, orienting, deciding, and acting together as a recurring rhythm so reaction does not slide into inertia.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
HighHighMediumHigh
Timedifferent
30-90 min Setup, danach laufend2-4 h15-60 min je Zyklus1-4 Wochen
Participantsdifferent
1-83-81-86-30 Experten
Formatdifferent
Workshop + asyncWorkshopWorkshop + asyncAsync
Outputdifferent
Forecast Percentiles, Throughput Dataset, Risk CommunicationFuture Reality Tree, Negative Branches, Assumption List, Improved InjectionsSituation Assessment, Decision Loop, Action UpdatesExpert Forecast, Consensus Range, Assumption Notes
Tagsno overlap
ForecastingFlowDelivery
Theory of ConstraintsSystems thinkingChange
DecisionChangeLearningStrategy
ForecastingExpertsDecisionStrategy
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