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Criterion
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Blameless Postmortem workspace showing the question, observations, and next decision.
DevOps
Blameless Postmortem
Paper illustration for Current Reality Tree
Systems Thinking
Current Reality Tree
Paper illustration for Causal Factor Analysis.
Operations
Causal Factor Analysis
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.After an incident with damage or a near miss, the method creates a sober field for learning without assigning blame. It directs attention to the course of events, conditions, and effective countermeasures.A Current Reality Tree condenses many symptoms into a few causal chains. The method makes visible which core problems drive several negative effects at once.For an event with a complicated course, the method breaks down the contributing factors along the timeline. It shows how conditions, decisions, and reactions together produce a course of events.
Complexitydifferent
HighMediumHighHigh
Timedifferent
30-90 min Setup, danach laufend30-90 min2-6 h2-6 h
Participantsdifferent
1-83-123-83-10
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshopWorkshop + async
Outputdifferent
Forecast Percentiles, Throughput Dataset, Risk CommunicationPostmortem Doc, Action Items, TimelineCurrent Reality Tree, Core Problems, Intervention IdeasEvent Timeline, Causal Factor Chart, Cause List, Corrective Actions
Tagsno overlap
ForecastingFlowDelivery
Site Reliability EngineeringIncidentLearningReliability
Systems thinkingRoot causeConstraintsCausality
CausalityIncidentRoot causeTimeline
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