CONTENTS
Executive Summary ...........................................................................................................1
Findings................................................................................................................1
1. Jobs Distributions………………………………………………………………………………………………………….3
1.1 Three categories of jobs ………........................................................................................3
1.2 Levels of jobs distributed to Mechanics ........................................................................ 3
2. Mechanics Performance..................................................................................................4
2.1 Time and difficulty levels.................................................................................................4
2.2 Correlation of time and difficulty ....................................................................................5
2.3 Efficiency of 4 Mechanics…………. ....................................................................................5
3. Customers’ Satisfaction Level ..........................................................................................6
4. Hypothesis Testing on Satisfaction Level..........................................................................6-7
5. Conclusions…………………………………………………………………………………………………………………….7
FIGURES
Figure 1 Distributions of Job Difficulty Levels
Figure 2 Distributions of Jobs
Figure 3 – 6 Frequency of time taken with job levels
Figure 7 Correlation between time and difficulty levels
Figure 8 Efficiency of Mechanics
Figure 9 Customers’ satisfaction levels
Figure 10 Customers’ satisfaction levels without no response
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1. Jobs Distributions
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Mechanics Performance
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Correlation of Time and Difficulty
According to figure 7, for easy task with difficulty 1, the time range is narrow ranged from 10 to 30 minutes. For Harder task ( difficulty 3 ), time range is more wider from 10 to 90 minutes. In addition, the trend line shown as upward sloping, indicating that there is a positive correlation between time and difficulty levels, the correlation coefficient is approximately equal to 0.6 which is closed to 1, thus indicate that time taken to undertake jobs increase with the associated difficulty level.
Efficiency of 4 Mechanics
From Figure 8, it shows that the trends of time taken to perform easy and standard jobs are very similar. Reason behind are that easy and standard tasks require less ability, experience and time to deal with assigned tasks, for example, less time and skills used to deal with refrigerator fixing or replacement. While for harder jobs, Mechanic 4 has a higher trend of time taken to complete harder jobs, reasons maybe that Mechanics 4 has little experience ( 2 years ) and has been assigned the least amount of hard jobs (3%), which has assigned only 2 hard jobs which took 69 and 88 minutes, as compared to others. While Mechanics 3 has the least amount used to seal with hard jobs regardless of experience in AllRepairs, this may due to that only 6 hard jobs were assigned to Mechanics 3, which it is an inadequate representation of actual overall performance. Moreover, Mechanics may have prior experience of repairs before entering AllRepairs, therefore further investigation should be carried out.
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Customers’ Satisfaction Level
According to figure 9, customers which have no response equal to 5%, with 18% in either dissatisfied or very dissatisfied. While, customers which are satisfied or very satisfied equal to 77% which is less than the agreed target of 80%, this result may only suitable to describe in sample but may not represent the total population of customers associated with Allrepairs. With regard to figure 10, however, the target of 80% has been reached ( 81% ) when customers with no response are excluded. As a result, a hypothesis testing on this statement should be carried out afterwards.
Hypothesis Testing
In order to ensure the attainment of target in each of the service branches in the company, a hypothesis testing need to be carried out to test on the condition that whether 80% of customers should be either ‘satisfied’ or ‘very satisfied’ with the service provided.
According to the statistical data given, there are some missing response from customers about the satisfaction level of services provided which represented by a number‘9’. Assume that the missing response is randomly and the data is a normally distributed, such as some survey forms are accidentally missed out or customers do not have a pen when conducting survey,
By using the critical value method: H0 = 0.8 (null hypothesis)
H1 < 0.8 (alternative hypothesis)
σ(p*) = √(pq/n)
= √(0.8x0.2/(293-13))
= 0.0239
∴ Z = (p* -p) / (pq/n) = (0.8071-0.8)/ 0.0239
= 0.2988 (Z-test score)
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For large sample size, numbers of customers with very satisfied and satisfied approximately normal irrespective of total population distribution which are customers associated with AllRepairs, thus sample proportion is also approximately normal for large number using Central Limit Theorem ( CLT ). CLT could be applied as the sample data is larger than 30 ( 293 in total ). By setting the observed significance level of 5% (the probability of Type I error), the lower class level is – 1.645 which associated is shown as the rejection region from the t- distribution table, thus the Z – score calculated is 0.2988 which does not fall in the rejection region, therefore we accept the null hypothesis that at least 80% of customers were satisfied or very satisfied for the services provided and AllRepairs has been successfully achieved its agreed target.
Conclusions
To conclude, the efficiency of 4 Mechanics are similar to each other in easy and standard jobs, while for harder jobs, there is a significant upward trend of time taken for mechanics 4 compared to mechanics 1, 2 and 3 with gradually increase and the least of increase in time taken respectively. In addition, AllRepairs has been achieved its agreed target whereas 80% of customers should be either satisfied or very satisfied with services provided. However, there are some limitations consist in with the result. Firstly, the data provided only consists of refrigerating repairing services which the results analyzed cannot respresent all employees in different branches in AllRepairs, and cannot be used to adequately evaluate the efficiency of repair staffs. Secondly, Mechanics 3 and 4 has only assigned for 6 and 2 hard jobs respectively which lead to inadequate result of efficiency of jobs performance regard to different Mechanics. Also, mechanics prior experience in repairing services before entering AllRepairs are not provided, therefore more accurate investigation and further analyze needed to be performed instead.
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