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5.4 The Kano Model and Quality Function Deployment

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ASQ Certified Six Sigma Black Belt CSSBB

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1 Chapter 1: Introduction & CSSBB Exam Strategy

1.1 CSSBB Exam Format, Scoring, and Testing Windows 1.2 Eligibility, Project Affidavits, Application, and Recertification 1.3 Open-Book Strategy, Reference Materials, and a 16-Week Study Plan

2 Chapter 2: Organization-Wide Planning and Deployment

2.1 Fundamentals of Six Sigma and Lean Methodologies 2.2 Selecting the Right Methodology: DMAIC, DFSS, and Lean 2.3 Business Systems, Processes, and Stakeholder Relationships 2.4 Strategic Planning and Deployment of Six Sigma Initiatives 2.5 Six Sigma Roles and Responsibilities 2.6 Organizational Barriers and Common Causes of Six Sigma Failure 2.7 Change Management: Stakeholder Analysis, Readiness, and Communication

3 Chapter 3: Organizational Process Management and Measures

3.1 Impact of Six Sigma Projects on Customers, Suppliers, and Stakeholders 3.2 Benchmarking Types and Performance Goal Setting 3.3 Performance Measures: Balanced Scorecard, KPIs, KBIs, OKRs, and Line of Sight 3.4 Leading and Lagging Indicators and Performance Dashboards 3.5 Financial Measures: Revenue Growth, Margin, NPV, ROI, and Cost-Benefit Analysis 3.6 Cost of Poor Quality and Hard versus Soft Savings

4 Chapter 4: Team Management

4.1 Team Types and Constraints 4.2 Team Roles, Responsibilities, and Member Selection 4.3 Team Success Factors and Ground Rules 4.4 Motivational Techniques and Overcoming Demotivators 4.5 Stages of Team Development and Conflict Resolution 4.6 Team Communication Plans 4.7 Team Leadership Models: Direct, Coach, Support, and Delegate 4.8 Group Behaviors, Conflict Resolution, and Meeting Management 4.9 Facilitation Techniques and Team Decision-Making Methods 4.10 Team Training: Needs Assessment, Delivery, and Evaluation

5 Chapter 5: Define Phase

5.1 Customer Identification and Segmentation 5.2 Customer Data Collection: Methods, Validity, and Reliability 5.3 Customer Requirements: CTX, CTQ Trees, and Operational Definitions 5.4 The Kano Model and Quality Function Deployment 5.5 SIPOC and Process Mapping 5.6 Business Case Justification 5.7 The Project Charter and the Problem Statement 5.8 Project Scope and Boundaries 5.9 SMART Goals and Project Performance Measurements 5.10 Project Charter Reviews and Toll-Gate Governance 5.11 Project Management Tools: Gantt Charts, Toll-Gate Reviews, WBS, and RACI 5.12 Analytical Tools Used Throughout the DMAIC Cycle

6 Chapter 6: Measure Phase

6.1 Process Flow Metrics and the Hidden Factory 6.2 Process Analysis Tools and Value Stream Mapping 6.3 Types of Data and Measurement Scales 6.4 Sampling Concepts, Methods, and Sample Size for Estimation 6.5 Data Collection Plans and Common Pitfalls 6.6 Gage R&R for Variable Measurement Systems 6.7 Attribute Agreement Analysis and Audit MSA 6.8 Measurement Systems Across the Organization, and Metrology 6.9 Population Parameters, Sample Statistics, and Valid Statistical Conclusions 6.10 Descriptive Statistics: Central Tendency, Dispersion, and Shape 6.11 Graphical Methods for Exploratory Data Analysis 6.12 Probability Concepts, Common Distributions, and the Central Limit Theorem 6.13 Additional Distributions: Hypergeometric, Exponential, Lognormal, Weibull, and Bivariate 6.14 Process Capability and Performance Indices 6.15 Capability Studies, Attributes Capability, Yield Metrics, and Long-Term Capability

7 Chapter 7: Analyze Phase

7.1 The Correlation Coefficient, Its Confidence Interval, and Causation 7.2 Linear Regression and Residual Analysis 7.3 Multivariate Tools: Factor Analysis, Discriminant Analysis, and MANOVA 7.4 Hypothesis Testing Terminology, Errors, and Single-Sample Tests 7.5 Statistical Versus Practical Significance 7.6 Sample Size for Hypothesis Tests 7.7 Point Estimates, Confidence, Prediction, and Tolerance Intervals 7.8 Tests for Means, Variances, and Proportions 7.9 Analysis of Variance 7.10 Chi-Square Goodness-of-Fit and Tests of Independence 7.11 Types of Risk and Failure Mode and Effects Analysis 7.12 Gap Analysis and Root Cause Analysis 7.13 Waste Analysis: The Seven Classic Wastes and Resource Under-Utilization

8 Chapter 8: Improve Phase

8.1 Design of Experiments: Objectives, Terminology, and Effects 8.2 DOE Design Principles: Randomization, Blocking, Replication, and Resolution 8.3 Planning and Evaluating Designed Experiments 8.4 One-Factor Experiments: Completely Randomized, Randomized Block, and Latin Square Designs 8.5 Full Factorial Experiments and Design Selection 8.6 Two-Level Fractional Factorial Experiments and Confounding 8.7 Response Surface Methodology and Optimization 8.8 Waste Elimination: Pull Systems, Kanban, 5S, and Poka-Yoke 8.9 Cycle-Time Reduction: Continuous Flow, SMED, and Heijunka 8.10 Kaizen, Kaizen Blitz, Theory of Constraints, and OEE 8.11 Implementation Planning, Piloting, and Solution Selection

9 Chapter 9: Control Phase

9.1 SPC Objectives, Variable Selection, and Rational Subgrouping 9.2 Control Charts for Variables Data 9.3 Control Charts for Attributes Data 9.4 Short-Run SPC and Moving Average Charts 9.5 Control Chart Analysis: Common Cause, Special Cause, and Run Rules 9.6 Total Productive Maintenance and Visual Controls 9.7 Measurement System Reanalysis 9.8 Control Plan Development and Process Owner Handoff 9.9 Lessons Learned, Documentation, and Training for Sustainment 9.10 Ongoing Evaluation of the Improved Process

10 Chapter 10: Design for Six Sigma (DFSS)

10.1 DFSS Frameworks: DMADV, DMADOV, and Design Transfer 10.2 Design for X (DFX) 10.3 Robust Design, Parameter Design, and Verification 10.4 Tolerance Design and Statistical Tolerancing

5.4 The Kano Model and Quality Function Deployment

Key Takeaways Explain This Topic AI

Kano categories are must-be, one-dimensional, attractive, indifferent, and reverse.

Must-be requirements cause dissatisfaction when absent but produce no satisfaction when present, so improving them beyond the threshold wastes resources.

Attractive requirements decay over time into one-dimensional and eventually must-be requirements as customer expectations rise.

The house of quality relates weighted customer whats to technical hows, and the roof matrix records correlations among the technical requirements.

A technical importance score is the sum over customer requirements of customer weight times relationship strength.

Last updated: August 2026

  • The Kano model
  • Noriaki Kano's insight is that the relationship between how well a requirement is met and how

satisfied the customer feels is not the same for every requirement . Five categories result.

Category Behaviour Example Project implication

Must-be (basic, dissatisfier) Absence causes strong dissatisfaction; presence produces no satisfaction Brakes work; the invoice arithmetic is right Meet the threshold reliably; do not over-invest beyond it

One-dimensional (performance, satisfier) Satisfaction rises roughly linearly with performance Fuel economy; delivery lead time This is where competitive differentiation and most DMAIC value lives

Attractive (delighter, exciter) Absence causes no dissatisfaction; presence produces disproportionate satisfaction Unexpected proactive status update Source of differentiation; usually a DFSS rather than DMAIC target

Indifferent Customer does not care either way Internal documentation format Candidate for cost reduction

Reverse More of it makes the customer less satisfied Excessive feature complexity; over-frequent notifications Reduce deliberately

Two consequences dominate the exam:

  • Over-investing in must-be requirements produces no satisfaction gain. Taking on-time delivery
  • from 99.2% to 99.6% in a market where anything above 99% is assumed buys nothing. The same effort

spent on a one-dimensional attribute would move the customer.

Failing a must-be requirement cannot be compensated by excellence elsewhere. A delightful

interface on a system that loses transactions is an unhappy customer.

  • Attribute decay
  • Categories are not permanent. An attractive attribute becomes one-dimensional as competitors copy it,
  • then must-be as customers come to assume it. Wi-Fi in hotels moved through all three in about a
  • decade. The implication for a Black Belt is that Kano classification has a shelf life and should

be refreshed rather than inherited from an old study.

  • Classifying requirements
  • Kano classification uses a paired-question survey. For each attribute, ask the functional form
  • ("how would you feel if the order arrived within 24 hours?") and the dysfunctional form ("how
  • would you feel if it did not?"). Both use the same five-point scale: I like it, I expect it, I am
  • neutral, I can tolerate it, I dislike it. The pair of answers maps to a category through a standard
  • evaluation table -- for example, like on the functional question plus dislike on the dysfunctional

question indicates one-dimensional, while expect plus dislike indicates must-be.

  • Quality function deployment
  • QFD is the structured method for translating the voice of the customer into technical requirements

and carrying that translation through design. Its central artifact is the house of quality .

The rooms

Room Contents Question answered

Left wall Customer requirements (the whats ) with importance weights What does the customer want?

Ceiling Technical requirements or design characteristics (the hows ) What can we measure and control?

Body / relationship matrix Strength of each what-how relationship, typically 9 / 3 / 1 Which technical characteristics affect which needs?

Right wall Competitive assessment from the customer's perspective How do we compare on each need?

Roof Correlations among technical requirements Which design choices conflict with each other?

Basement Technical importance scores, targets, and technical benchmarks Where do we set the specifications?

Computing technical importance

For technical characteristic j j j : T I j = ∑ i w i × r i j TI_j = \sum_{i} w_i \times r_{ij} T I j ​ = i ∑ ​ w i ​ × r ij ​

where w i w_i w i ​ is the importance weight of customer requirement i i i and r i j r_{ij} r ij ​ is the relationship

strength between requirement i i i and characteristic j j j (9 strong, 3 moderate, 1 weak, blank none).

Worked example for a delivery service:

  • Customer requirement (what) Weight Route density Dispatch cycle time Vehicle reliability
  • Arrives when promised 5 3 9 9
  • Short lead time 4 9 9 1
  • Undamaged goods 3 1 0 3

Technical importance 5 ( 3 ) + 4 ( 9 ) + 3 ( 1 ) = 54 5(3)+4(9)+3(1) = 54 5 ( 3 ) + 4 ( 9 ) + 3 ( 1 ) = 54 5 ( 9 ) + 4 ( 9 ) = 81 5(9)+4(9) = 81 5 ( 9 ) + 4 ( 9 ) = 81 5 ( 9 ) + 4 ( 1 ) + 3 ( 3 ) = 58 5(9)+4(1)+3(3) = 58 5 ( 9 ) + 4 ( 1 ) + 3 ( 3 ) = 58

Dispatch cycle time carries the highest technical importance, so it is where specification effort and

project resources should go first.

  • Reading the roof
  • The roof records whether improving one technical characteristic helps or hurts another: strong
  • positive, positive, negative, strong negative. A negative correlation is a design conflict that
  • must be resolved by trade-off or by innovation rather than by wishing. Increasing route density
  • improves lead time but may reduce vehicle reliability through higher duty cycles -- that conflict is

exactly what the roof is for.

The four-phase cascade

QFD does not stop at one house. The outputs of each house become the inputs of the next:

House 1 : customer requirements to technical requirements.

House 2 : technical requirements to part or component characteristics.

House 3 : part characteristics to process parameters.

House 4 : process parameters to production and control requirements.

  • House 4 is where QFD connects to the Control phase, because production requirements become control
  • plan entries. This cascade is what makes the link from a customer statement to a control chart on a

specific process parameter traceable.

  • Using Kano and QFD together
  • Kano supplies the weights for the left wall. Requirements are not equally important, and Kano

category tells you how importance behaves:

Must-be requirements get a threshold target rather than a maximization target. Meet them and

stop.

One-dimensional requirements carry the highest improvement weight, because satisfaction scales

with performance.

Attractive requirements are weighted for differentiation value but should not displace unmet

must-be requirements.

Indifferent requirements are candidates for cost removal.

A house of quality built with unweighted customer requirements, or with weights that ignore Kano

category, will systematically over-specify basics and under-specify differentiators.