Quality : A Parameter of Customer Satisfaction

Quality:  when a product surpasses our expectation we consider that quality. Thus, it is somewhat of an intangible based on perception. Quality can be quantified as follows

  Q= P/E

Where Q= quality

P= Performance

E= Expectations

If Q is greater than 1 , this means the performance of the product is higher than the expectation of the customer, then the customer perception about the product is of extraordinary quality as the customer get ‘extraordinary satisfaction’.

There is trend in modern day competition among Japanese companies to give you rather more in order to ‘delight’ you. So when buy a lamp bulb which has a ‘mean time between failure’ of 1000 hrs , the Japanese manufacturer will try their best to ensure that you can get at least 20% more. Likewise when you buy a Japanese brand video tape specifying 180 minutes, it can normally record up to 190 minutes. When you buy a mink coat from a department store in Japan, they would invite you to store the fur coat in their temperature –control room during the hot summer season free of charge. They call these extra little things as ‘extra – ordinary customer satisfaction’ or ‘delighting the customers’.

So in second case if Q=1, this means the performance of the product is equal to the expectation of the customer, and quality of the product is at par for the customer. The customer is just satisfied about the quality of the product he is not getting any extraordinary satisfaction.

In third case if Q is less than 1, i.e. the performance of the product is less than the expectation of the customer, and the quality of the product is poor in the perception of the customer. The customer will never satisfy form the product quality.

 

The Dimensions of Quality

Quality has nine different dimensions. These dimensions are somewhat independent ; therefore a product can be excellent in one dimension and average or poor in another. Very few , if any product excel in all nine dimensions . For example, the Japanese were cited for high –quality cars in the 1970s based only on the dimensions of reliability, conformance and aesthetics. Therefore , quality products can be determined by using a few of the dimensions of quality.

Nine Dimensions of Quality
Dimensions	Meaning and Example
Performance	Primary product characteristics, such as the brightness of the picture
Feature	Secondary characteristics , added features, such as remote control
Conformance	Meeting specifications or industry standards, workmanship
Reliability	Consistency of performance over time, average time for the unit to fail
Durability	Useful life, includes repair
Service	Resolution of problems and complaints, ease of repair
Response	Human to Human interface, such as the courtesy of the dealer
Aesthetics	Sensory characteristics, such as exterior finish
Reputation	Past performance and other intangibles, such as being ranked first

   Adapted from David A. Garvin, Managing Quality: The strategic and Competitive Edge (New York : Free Press, 1988)

Skewness-Lack of symmetry in frequency distribution

Meaning of Skewness:

The term skewness means lack of symmetry in a frequency distribution. Skewness denotes the degree of departure of a distribution from symmetry and reveals the direction of scatterness of the items. It gives us an idea about the shape of the frequency curve. When a distribution is not symmetrical , It is called a skewed distribution. Skewness tells us about the asymmetry of the frequency distribution.

Definition of Skewness:

1. Skewness is the degree of asymmetry or departure from symmetry of a distribution --------  M. R. Speigal.
2. When a series is not symmetrical , it is said to be asymmetrical or skewed-------------Croxten and Cowden.
3. By skewness of a frequency distribution , we mean degree of its departure from symmetry----------Simpson and kafka.

Skewness and frequency Distribution:

1.  Symmetrical Distribution:
   In a symmetrical distribution or symmetrical curve , skewness is not present. The values of mean , median and mode coincide i.e. Mean=Meadian=Mode. The spread of the frequencies is the same on both sides of the central point curve.
   
2. Skewed Distribution:
   A distribution which is not symmetrical is called skewed distribution or asymmetrical distribution . 
   A skewed distribution may be either positively skewed or negatively skewed.
   1. Positively skewed: If the longer tail of the frequency curve of distribution lies to the right of the central point, it is called a positively skewed distribution.In Positively skewed distribution , the  value of the  mean will be greater than median and median will be greater than mode.
   2. Negatively skewed.: If the longer tail of the frequency curve of the distribution lies to the left of the central point , it is called a negatively skewed distribution. In the negatively skewed distribution , the value of the mean will be less then median be less than mode.
   Formula for calculating Skewness is given in below fig.