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Criterion
Paper illustration for OODA Loop.
Decision Making
OODA Loop
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
In dynamic situations, decisions become outdated faster than they can be prepared.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 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
15-60 min je ZyklusOngoing1-4 Wochen30-90 min Setup, danach laufend
Participantsdifferent
1-82-126-30 Experten1-8
Formatdifferent
Workshop + asyncWorkshop + asyncAsyncWorkshop + async
Outputdifferent
Situation Assessment, Decision Loop, Action UpdatesKanban board, WIP policies, Flow metricsExpert Forecast, Consensus Range, Assumption NotesForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
DecisionChangeLearningStrategy
FlowVisual managementDelivery
ForecastingExpertsDecisionStrategy
ForecastingFlowDelivery
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