Single criterion preference measurement of a group

As mentioned before in Section 5.1, a reputable construction company used to address their customers with a yearly inquiry to measure their perception of the quality of the firm. Respondents were requested to give a grade for the performance of the company in regard to various criteria that were considered to be relevant. On all criteria the company scored well above seven, so everything seemed to be in order. In this section we will show that this is misleading and how proper use of preference measurement and statistical analysis can improve the probability that the construction firm will be selected in future bidding procedures.

To this end, first a (correct) single criterion preference measurement of a group of customers is conducted to grade the company's performance. Next a criteria ranking on relevance using the enquiry results of the same group of customers is peformed to assess the relative relevance of the various criteria as perceived by the customers. The procedure generates feedback from customers which is essential for a learning organisation.

An example of the old and improved scaling is given in Table 5.1 and 5.2 respectively.

In short, to measure preference correctly, you need at least three scores per criterion. Measuring with only one score, on an arbitrary scale, is meaningless. The simple change in the enquiry as indicated in Table 5.2 made it possible to measure how the firm scored in comparison to the competition.

Table 5.2 Part of the improved enquiry on the criterion Reliability

Subcriterion Reliability

Grade

Firm 1

2

3

4

5 6

7

8

9

10

Skill of office workers

Best competitor 1

2

3

4

5 6

7

8

9

10

Worst competitor 1

2

3

4

56

7

8

9

10

Table 5.3 Results new enquiry

Criterion

Best

Firm's

Worst

%

%

score

score

score

higher

lower

Communication

8.55

7.19

4.45

25.99%

74.01%

Reliability

8.27

7.30

4.35

15.78%

84.22%

Delivery times

8.29

7.24

7.34

18.08%

81.92%

Eye for customer's interests

8.48

7.03

4.13

27.47%

72.53%

Quality control

8.06

6.88

4.06

21.99%

78.01%

Image

8.17

7.41

4.30

12.12%

87.88%

Statistical analysis

By having three scores from the group of customers on every (sub)criterion, it becomes possible to establish if the company achieves its objective score in all criteria at least in the top quartile. With the assumption that performances of competitors follow a normal distribution, the relative position of the firm on each criterion can be assessed (Fig. 5.1). A confidence level (meaning that the probability that the conclusion from the statistical analysis is true) of 97.5% was chosen. Figure 5.2 shows how the construction firm scores in relation to the competition on the criterion 'Communication'.

Table 5.3 shows the results of the analysis. It shows that on two criteria the firm scores just below the top quartile, namely 'Communication' and 'Eye for customer's interests', which could warrant managerial measures in those areas.

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