Decision Science (MCDA)
QFD / House of Quality
Translates customer requirements into prioritized technical specifications
Rubric Type
weighted-sum
Complexity
high
Extractor
technical
Required Inputs
SolveRight's AI extractor automatically derives these data points from your decision description:
- ✓customer requirements
- ✓technical requirements
- ✓relationship matrix
- ✓competitive benchmarks
- ✓correlation matrix
Best For
How QFD / House of Quality Works in SolveRight
When you run a decision through SolveRight, QFD / House of Quality is one of up to 155 frameworks that analyze your options simultaneously. The AI extractor identifies 5 key data points from your decision description, then the weighted-sum rubric computes a normalized 0-100 score for each option. This score is combined with results from other frameworks to produce your overall ranking, with contradiction detection highlighting where QFD / House of Qualitydisagrees with other methodologies.
QFD / House of Quality — Frequently Asked Questions
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Related Decision Science (MCDA) Frameworks
Weighted Decision Matrix
Scores options against weighted criteria for systematic comparison
Analytic Hierarchy Process (AHP)
Derives priority weights from pairwise comparisons with consistency check
Multi-Criteria Decision Analysis (MCDA)
Formal multi-criteria evaluation combining multiple scoring methods
Regret Minimization Framework
Evaluates options through the lens of future regret minimization
ANP (Analytic Network Process)
Extends AHP to handle interdependencies and feedback between criteria and alternatives
TOPSIS
Ranks alternatives by closeness to ideal solution and distance from anti-ideal solution