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Criterion
Design sheets and interface cards connect to jointly written pseudocode with highlighted unresolved questions.
Architecture
ARID (Active Reviews for Intermediate Designs)
Paper illustration of Outcome-Driven Innovation with its method-specific working model.
Product Discovery
Outcome-Driven Innovation
Paper illustration of a branching tree with an outcome at its root, customer opportunities, solution options and small experiment cards.
Product Discovery
Opportunity Solution Tree
Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
Purposedifferent
ARID examines how well developers can work with a technical design. It focuses on a part of the system that can still be revised, between the architecture overview and the detailed specification.Outcome-Driven Innovation clarifies customer problems, solution opportunities, and evidence. It separates jobs, desired outcomes, importance, satisfaction, and opportunity, and captures results as desired outcome statements, an opportunity landscape, and segments by underserved needs.When discovery keeps swinging between goals, ideas, and learning loops, it creates clear steering logic. It connects the desired outcome, opportunities, and experiments into a legible structure.When demand is still unclear, it measures interest in a feature before it is built. It separates real behavior from polite agreement and deliberately keeps build effort small.
Complexitydifferent
MediumHighMediumMedium
Timedifferent
2–4 h review as a planning range; preparation and evaluation additionalMehrere Wochen1-2 h Setup, laufend1-5 Tage
Participantsdifferent
Designers, developers as users, and facilitation2-6 researchers plus sample2-6Nutzertraffic
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshop + asyncAsync
Outputdifferent
Prioritized development tasks, Jointly produced code or pseudocode, Observed difficulties and open design questions, Proposed design revisionsDesired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypothesesOpportunity Solution Tree, Experiment Backlog, Learning LogClick Data, Interest Signal, Learning Decision
Tagsno overlap
ArchitectureEngineeringFeedbackValidationTasks
OutcomesInnovationResearchQuantitative
DiscoveryOutcomesExperimentsOpportunity
ValidationExperimentsDemandDiscovery
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