1Prof. 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

2Prof. Indrajit Mukherjee, School of Management, IIT Bombay

QUALITY MANAGEMENT

Market Dynamics and the Kano Model

“Delighters”move to “MustBe” featuresover time!

COMMODITY

Customer Satisfaction

Execution Excellence

Stan

dard

per

form

ance

INNOVATI

VE

Lead

ersh

ip p

erfo

rman

ce

Compe

titiv

e pe

rform

ance

3Prof. Indrajit Mukherjee, School of Management, IIT Bombay

QUALITY MANAGEMENT

QualityFunctionDeployment

Voice of the Engineer

“House of the Quality”

Voice of the customer correlations

Competitive Analysis

Technical Comparison

4Prof. Indrajit Mukherjee, School of Management, IIT Bombay

QUALITY MANAGEMENT

Designing for the Customer:The House of QualityCar door Design

Easy to close 7

Can open on a hill 5

Easy to open 3

Doesn’t leak in rain 3

No road noise 2

Importance Weighting 10 6 6 9 2 3

Target Values

Customer Requirements

Engineering Characteristics

X=UsA=Comp. AB=Comp. B(5 is Best)1 2 3 4 5

x AB

AB

xB

x

x

x

x

xx

x AB

A

A B

Technical Evaluation(5 is Best)

54321

AA

AA

BB

BBBA

XBAX

X

XX X

X

Correlation:∆ Strong Positiveo PositiveX Negative* Strong Negative

Relationships:∆ Strong=9o Medium=3* Small=1

Customer requirements information forms the basis for this matrix, used to translate them into operating or engineering goals

5Prof. 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

6Prof. Indrajit Mukherjee, School of Management, IIT Bombay

QUALITY MANAGEMENT

The Engineering Method and Statistical Thinking

Develop a dear

description

Conduct experime

nts

Conclusion and recommendation

s

Identify the important

factors

Propose or refine a

model

Manipulate the model

Confirm the

solution

7Prof. Indrajit Mukherjee, School of Management, IIT Bombay

QUALITY MANAGEMENT13X 13X

0 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 6 7 8 9 10

Median = 3 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

8Prof. Indrajit Mukherjee, School of Management, IIT Bombay

QUALITY MANAGEMENT

Variation

13X 13X

Measures of variation give informationon the spread or variability of the data values.

Same center,different variation

9Prof. Indrajit Mukherjee, School of Management, IIT Bombay

QUALITY MANAGEMENT13X 13X

Data Summary and DisplayHow Does the Sample Variance Measure Variability?

12 13 14 15

x1

x2

x3

x4 x5

x6x7

x8

ix x

Figure How the sample Variance measures variability through the deviations

x