1 Prof. Indrajit Mukherjee, School of Management, IIT Bombay QUALITY MANAGEMENT Kano’s Model of (Non- Linear) Customer Satisfaction Customer Satisfied Customer Not Satisfied Requirement Fulfilled Requirement Not Fulfilled Delighter (D) Linear Satisfier (L) or Performance Indifferent (I) Time Must Have (M) or basic Needs

2 Prof. Indrajit Mukherjee, School of Management, IIT Bombay QUALITY MANAGEMENT Market Dynamics and the Kano Model “Delighters” move to “Must Be” features over time! COMMODITY Customer Satisfaction Execution Excellence Standard performance INNOVATIVE Leadership performance Competitive performance

3 Prof. Indrajit Mukherjee, School of Management, IIT Bombay QUALITY MANAGEMENT Quality Function Deployment Voice of the Engineer “House of the Quality” Voice of the customer correlations Competitive Analysis Technical Comparison

4 Prof. Indrajit Mukherjee, School of Management, IIT Bombay QUALITY MANAGEMENT Designing for the Customer: The House of Quality Car door Design Easy to close7 Can open on a hill5 Easy to open3 Doesn’t leak in rain3 No road noise2 Importance Weighting Target Values Customer Requirements Engineering Characteristics X=Us A=Comp. A B=Comp. B (5 is Best) xAB xB x x x x x x xAB A AB Technical Evaluation (5 is Best) A A A A B B BB BA X X X X XX X Correlation: ∆ Strong Positive o Positive X Negative * Strong Negative Relationships: ∆ Strong=9 o Medium=3 * Small=1 Customer requirements information forms the basis for this matrix, used to translate them into operating or engineering goals

5 Prof. Indrajit Mukherjee, School of Management, IIT Bombay QUALITY MANAGEMENT Customer-Driven Quality cycle Identification of customer needs Translation into product/service specifications (design Quality ) Performance/Output (actual quality) Customer perceptions (Perceived quality) Customer needs and expectations (expected Quality) PERCEIVED QUALITY = ACTUAL - EXPECTED Measurement and feedback

6 Prof. Indrajit Mukherjee, School of Management, IIT Bombay QUALITY MANAGEMENT The Engineering Method and Statistical Thinking Develop a dear description Conduct experime nts Conclusion and recommendations Identify the important factors Propose or refine a model Manipulat e the model Confirm the solution

7 Prof. Indrajit Mukherjee, School of Management, IIT Bombay QUALITY MANAGEMENT Median = 3 Median Not affected by extreme values In an ordered array, the median is the “middle” number – If n or N is odd, the median is the middle number – If n or N is even, the median is the average of the two middle numbers

8 Prof. Indrajit Mukherjee, School of Management, IIT Bombay QUALITY MANAGEMENT Variation Measures of variation give information on the spread or variability of the data values. Same center, different variation

9 Prof. Indrajit Mukherjee, School of Management, IIT Bombay QUALITY MANAGEMENT Data Summary and Display How Does the Sample Variance Measure Variability? x1 x2 x3 x4x5 x6x7 x8 Figure How the sample Variance measures variability through the deviations