W2 _Said Alamri_ Car Selection using Decision Matrix Analysis


1. Problem Recognition

It is important to carefully select a car that fits your expectations and needs. In this post I will use a technique might help customers to choose the best car that satisfy their passions and needs, after reading this blogs you will be surprised that the car that might impress you is not really fits you.

2. Development the Feasible Alternative

Short listed of cars that can be considered to be purchased:

  • TOYOTA LAND CRUISER
  • RANG ROVER VOUGE
  • CHEVROLETE TAHEO
  • NISSAN SAFFARI
  • LEXUS 570

3. Development of the Outcome for Alternative

The needs and expectations for a car which can be considered have the following criteria:

  • Design, Engineering and Value: The Car Engineering must illustrate cost-effective technologies, as well as a decent overall package. Value is another factor when choosing the Car If a car is designed and made well, but costs a lot more than other cars in its class, it’s not going to fit well.
  • Safety: Because of the potential for serious accidents on the road, safety is critical when choosing a Car. Including advanced airbags, etc
  • Function: The car must be good at what it’s intended to do. For example, if it’s an off road car, it should deliver durability on rough road — and do it well.
  • Price: car price can be afforded by costomer or not?
  • Maintenance cost
  • Salvage value

4. Selection of Criteria

Decision Matrix Analysis (Grid Analysis) technique used for making the decision to choose best car fit the customer expectation.

5. Analysis and Comparison of the Alternative

List down as in Table-1 option for each of the factors in your decision. Score each option from 0 (poor) to 5 (very good):

Price: 4=Cheapest, 3=Cheap, 2=Expensive, 1=Most Expensive

Design, Engineering and Value: 4= High, 3= Medium, 2= Low, 1= Very Low

Safety: 4=Very high, 3=High, 2=Good, 1=Poor

Function: 4=Very high, 3=High, 2=Good, 1=Poor

Maintenance cost: 4=1000, 3=2000, 2=4000, 1=5000

Salvage value: 4=8000, 3=6000, 2=4000, 1=3000

In Table-2 put scores for the relative importance of the factors in your decision. Show these as numbers from, say, 0 to 4, where 0 means that the factor is absolutely unimportant in the final decision, and 4 means that it is very important. As an example High=4, Medium=3, Low=2, Very Low=1

Now multiply each of your scores from Table-2 by the values for relative importance of the factor that you calculated in Table-1. This will give you weighted scores for each option/factor combination in Table-3

 

Table-1 Un- weighted grid *(all values are based on personal assumptions)

Table-1 Un- weighted grid *(all values are based on personal assumptions)

Table-2 weighted as per importance for the customer*(all values are based on personal assumptions)

Table-2 weighted as per importance for the customer*(all values are based on personal assumptions)

Table-3 weighted scores

Table-3 weighted scores

 

6. Selection of the Preferred Alternative

It can be seen from Decision Matrix Analysis (Grid Analysis) technique that LEXUS 570 is the best option fits customer needs and satisfaction for the earlier specified criteria  in section 3.

7. Performance Monitoring and the Post Evaluation of Result

From the calculation it can be observed that the nearest second choice was  TOYOTA LAND CRUISER. If the customer wants to save some amount of money although can have almost the same features in a car.

8. References:

 

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One thought on “W2 _Said Alamri_ Car Selection using Decision Matrix Analysis

  1. EXCELLENT case study and you did a good job on your analysis, Said!!

    What you might want to consider would be to look at some of the more sophisticated multi-attribute decision making models? http://topazsmartd.wordpress.com/2014/06/12/w7-0_sb_softwaretools-selection-by-compensatory-model-additive-weighting-technique/comment-page-1/#comment-151.

    For your W3 blog, if you take the same case study, but use either the additive weighting technique or one of the other COMPENSATORY methods. These are very powerful and useful decision making tools to master.

    BR,
    Dr. PDG, Pensaola, Florida

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