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| Criterion | ![]() Operations PDCA Cycle | ![]() Product Strategy DIBB | ![]() Operations Root Cause Tree Analysis | ![]() Operations Root Cause Analysis |
|---|---|---|---|---|
Purposedifferent | For an improvement that still has to prove itself in everyday work, the method runs it through small learning loops. It connects planning, checking, and standardization into a repeatable learning mode. | DIBB helps clarify target groups, value, goals, and priorities by making the logic behind a decision explicit. It captures results as a DIBB document, belief list, bet list, and learning report. | 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. | When a problem keeps recurring and the cause stays unclear, the method exposes the underlying mechanism. It separates symptom, guess, and robust explanation from one another. |
Complexitydifferent | Low | Low | Medium | Medium |
Timedifferent | 1 h bis mehrere Wochen | 1-2 h | 1-3 h | 1-4 h |
Participantsdifferent | 1-8 | 2-8 | 2-8 | 3-8 |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Workshop + async |
Outputdifferent | PDCA Log, Experiment Plan, Learning Outcome, Standard Change | DIBB document, Belief list, Bet list, Learning report | Cause Tree, Evidence Notes, Countermeasures | Problem Statement, Cause Hypotheses, Confirmed Causes, Action Plan |
Tagsno overlap | Continuous improvementLeanExperiments | StrategyDecisionAssumptionsHypothesis | Root causeTreeIncidentQuality | Root causeProblem solvingQualityIncident |



