Graph 4-2: Age distribution company A
The figure above summarises the percentage of the age groups that participated in the survey for company A. The largest age group falls in the 30–39 years bracket and consists of 39% of the
59%
1%
40%
Feedback percentage company A
Completed Spoiled Not Completed
14%
39%
19%
20%
8%
Age distribution company A
20 - 29 30 - 39 40 - 49 50 - 59 60 and older
results, with the age group 40–49 covering 20% of the survey results. The new (young) engineers joining the company falls in the age group 20–29, making up only 14% of the total. The ageing workforce in the company may be a disadvantage, and the company needs to adapt to make Generation Z, also known as Zoomers, feel more welcome in the company.
Graph 4-3: Gender distribution company A
In total, 62 people participated in the survey with five spoiled questionnaires. The survey consists of 84% male and 16% female participants. However, only one female survey was spoiled, and all the females are employed by company A. Therefore, the gender distribution for company A consists of 82% male and 18% female. These numbers might be an indication that gender is an issue to be addressed by the company and that automation engineering must be promoted as a viable career option for females.
82%
18%
Gender distribution company A
Male Female
Graph 4-4: Years working in engineering industry company A
The average work experience of engineers working for company A is 31% in the category 0–9 years. This number which makes up nearly one third of the total indicates that younger people are moving into the industry. A contributory factor for this phenomenon may be that the automation industry is technology-driven. Given the worldwide situation that young people are very competent in using technology related to the fourth industrial revolution may provide an explanation for this trend.
Graph 4-5: Highest qualification level company A
31%
27%
16%
18%
8%
Years working exsperiance company A
0 - 9 Years 10 - 19 Years 20 - 29 Years 30 - 39 Years 40 Years and More
5
17
9
3
11
4
0
2 0
2 4 6 8 10 12 14 16 18
National Certificate
(Matric)
National Diploma
B-Tech DegreePost-Graduate Diploma
Honour’s Degree
Master’s Degree / MEng
PhD Other
Higest qualification level company A
More than 50% of the participants in company A have obtained NQF level six and seven qualifications. In addition to that one must obtain a national diploma to work as an engineer at company A.
It is possible to divide the biographical data into two groups, one with order and one without order.
The age group, years of work experience, and qualification represent order. Take the age factor, for example: the age group 20–29 carries a weight of 1, and 60 years and older a weight of 5. On the other hand, gender falls in the group without order, meaning that one is not more important or carries more weight than the other. The items in the order category can be used to require correlation. There must be normality and order in the items. If one wants to do a Spearmen correlation, order is important. The Spearman rank-order was used, so there is no need to prove normalisation. The Spearman test is used for ordinal variables or continuous data that are insufficient to conduct a Pearson’s product-moment correlation. Spearman’s rank-order correlation calculation does not measure linear connection but is used to find a monotonic relationship. A monotonic relationship is when something tends to move in the same direction but not at a constant rate (Leard Statistics, 2018).
The small sample group only had 51 feedbacks indicating few statistically significant correlations.
Considering the table below, when looking at the correlation, it is evident that the correlation coefficient is very low. This means that the biographical data do not have a big, if any, impact on the work-life balance, quality of work, and occupational stress. For this reason, the biographical data will be ignored in the rest of the discussion. There is no statistical value in the biographical values because it is so low. This result is acceptable because it indicates that nothing else is acting on the facts, e.g. age does not play a role in work-life balance. More work experience does not determine one's quality of work.
Correlations can vary between -1 and +1. Both values -1 and +1 are perfect correlations and compare with themselves. A correlation equal to 0 is not a correlation. One is all very much after string correlation, for instance, a value of -0.6.
Table 4-1: Group statistics with biographical information
What is your
age group?
How many years are you working
in the engineering
industry?
Highest qualification
level.
WLB_WIPL Correlation
Coefficient
-0.115 -0.069 -0.003
Sig. (2-tailed) 0.421 0.633 0.984
N 51 51 49
WLB_PLIW Correlation
Coefficient
-0.164 -0.162 -0.055
Sig. (2-tailed) 0.249 0.256 0.710
N 51 51 49
WLB_WEPL Correlation
Coefficient
0.113 0.230 0.121
Sig. (2-tailed) 0.431 0.105 0.407
N 51 51 49
WLB_PLEW Correlation
Coefficient
0.027 0.102 0.183
Sig. (2-tailed) 0.852 0.476 0.208
N 51 51 49
QWS_Satisfaction Correlation Coefficient
0.089 0.041 -0.002
Sig. (2-tailed) 0.536 0.776 0.989
N 51 51 49
QWS_Mobbing Correlation
Coefficient
0.012 0.000 0.055
Sig. (2-tailed) 0.936 0.999 0.708
N 51 51 49
QWS_Mental_Strain Correlation Coefficient
0.104 0.139 -0.047
Sig. (2-tailed) 0.466 0.331 0.750
N 51 51 49
QWS_Communication Correlation Coefficient
0.081 0.118 -0.137
Sig. (2-tailed) 0.571 0.408 0.346
N 51 51 49
QWS_Cooperation Correlation Coefficient
0.047 0.097 -0.127
Sig. (2-tailed) 0.744 0.497 0.383
N 51 51 49
What is your age group?
How many years are you working
in the engineering
industry?
Highest qualification
level.
Do you consider your work to be important?
Correlation Coefficient
0.033 0.089 0.185
Sig. (2-tailed) 0.816 0.534 0.204
N 51 51 49
Is your work appreciated by your company?
Correlation Coefficient
0.009 -0.018 -0.017
Sig. (2-tailed) 0.951 0.898 0.906
N 51 51 49
WS_Influence Correlation
Coefficient
-0.132 -0.151 -0.119
Sig. (2-tailed) 0.357 0.291 0.415
N 51 51 49
WS_Stress_conflicts Correlation Coefficient
-0.230 -0.152 -0.067
Sig. (2-tailed) 0.104 0.287 0.646
N 51 51 49
WS_Stress_commitments Correlation Coefficient
-0.116 -0.044 0.040
Sig. (2-tailed) 0.416 0.761 0.784
N 51 51 49
WS_Work_Leisure Correlation Coefficient
0.130 0.031 -0.162
Sig. (2-tailed) 0.365 0.827 0.265
N 51 51 49