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| Criterion |  Decision Making Decision Tree |  Architecture C4 Model |  Operations Scatter Diagram |  Operations Root Cause Tree Analysis |
|---|---|---|---|---|
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. | The C4 Model makes a system legible across several resolution levels, from context down to code. It suits situations where different audiences need to understand the same architecture from different altitudes. | When the question is whether two measures are related, the method makes patterns in the data picture visible. It separates felt correlations from relationships that actually show up in the data. | For a problem with several suspected causes, the method builds a causal structure instead of a mere list. It makes visible how causes connect and where the strongest points of leverage lie. |
Complexitydifferent | Medium | Low | Low | Medium |
Timedifferent | 30-90 min | 1-4 h | 30-90 min | 1-3 h |
Participantsdifferent | 1-6 | 1-5 | 1-4 | 2-8 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Workshop |
Outputdifferent | Decision Tree, Option Map, Assumption List | Context Diagram, Container Diagram, Component Diagram | Scatter Plot, Korrelationsnotiz, Hypothesenliste | Cause Tree, Evidence Notes, Countermeasures |
Tagsno overlap | DecisionTreeOptions | ArchitectureCommunicationVisualization | Root causeQualityVisualization | Root causeTreeIncidentQuality |