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| Criterion |  Operations PDCA Cycle |  Systems Thinking Leverage Points |  Decision Making Delphi Method |  Product Strategy DIBB |
|---|---|---|---|---|
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. | Leverage Points show exactly where interventions in a system produce a disproportionate effect. It draws relationships, patterns, and feedback loops. The result is captured as a leverage map and action strategy. | 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. | 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. |
Complexitydifferent | Low | High | High | Low |
Timedifferent | 1 h bis mehrere Wochen | Half day | 1-4 Wochen | 1-2 h |
Participantsdifferent | 1-8 | 3-12 | 6-30 Experten | 2-8 |
Formatdifferent | Workshop + async | Workshop | Async | Workshop + async |
Outputdifferent | PDCA Log, Experiment Plan, Learning Outcome, Standard Change | Leverage Map, Action Strategy | Expert Forecast, Consensus Range, Assumption Notes | DIBB document, Belief list, Bet list, Learning report |
Tagsno overlap | Continuous improvementLeanExperiments | Systems thinkingChangeStrategy | ForecastingExpertsDecisionStrategy | StrategyDecisionAssumptionsHypothesis |