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Criterion
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Paper illustration for OODA Loop.
Decision Making
OODA Loop
Paper illustration of a review with planned work, actual event sequence, comparison, and assigned improvement actions.
Operations
After-Action Review
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is captured as Forecast Percentiles, Throughput Dataset, and Risk Communication.In dynamic situations, decisions become outdated faster than they can be prepared.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.After missions or project phases with unclear outcomes, the method makes visible what actually happened and what can be learned from it. It separates course, effect, and causes so experience turns into solid improvement.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
HighMediumLowHigh
Timedifferent
30-90 min Setup, danach laufend15-60 min je Zyklus20-45 min1-4 Wochen
Participantsdifferent
1-81-83-126-30 Experten
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshop + asyncAsync
Outputdifferent
Forecast Percentiles, Throughput Dataset, Risk CommunicationSituation Assessment, Decision Loop, Action UpdatesLessons learned, Action items, Event summaryExpert Forecast, Consensus Range, Assumption Notes
Tagsno overlap
ForecastingFlowDelivery
DecisionChangeLearningStrategy
LearningOperationsImprovement
ForecastingExpertsDecisionStrategy
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