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Criterion
Design Thinking as a learning loop: an observation notebook, a focused problem statement, different idea sketches, a cardboard prototype and user-test notes. Feedback leads to new understanding.
Innovation
Design Thinking
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
Paper illustration for Trade-off Analysis.
Decision Making
Trade-off Analysis
Paper illustration of a decision table with criteria rows, weighted ratings, and a narrowly leading alternative.
Decision Making
Decision Matrix
Purposedifferent
For complex user problems with an uncertain cause, the method connects observation, interpretation, and experiment into a learning cycle. It keeps the focus on real needs and avoids premature solution language. This produces robust decisions for product and service.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.With limited resources, quality, speed, cost, and risk almost always compete with each other. Trade-off Analysis makes these tensions explicit and prevents decisions from producing hidden side effects.When several options collide with several criteria, comparison quickly becomes subjective. A Decision Matrix makes the trade-off visible and brings weighting, criteria, and options into a shared logic.
Complexitydifferent
HighMediumMediumMedium
Timedifferent
1 Tag bis mehrere Wochen30-90 min45-120 min45-90 min
Participantsdifferent
4-101-62-82-8
Formatdifferent
WorkshopWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Problem Statement, Prototype, Test LearningsDecision Tree, Option Map, Assumption ListTrade-off Matrix, Criteria List, Decision Rationale, Accepted DownsidesDecision Matrix, Scoring Rationale, Selected Option
Tagsno overlap
InnovationPrototypeResearch
DecisionTreeOptions
TradeoffsDecisionCriteriaOptions
DecisionCriteriaScoringTradeoffs
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