Executive Summary Of Technomart Employee’s Job Satisfaction

Working Hours analysis

Executive summary of Technomart employee’s job satisfaction

The main aim of this report was to present the findings and analysis of TechnoMart employee survey. A total of 400 employees to part in the survey where the participants were randomly selected into the study. Both descriptive and inferential statistics were used to analyze the dataset. The following key findings were noted from the survey;

• Average working hours for the TechnoMart employees was about 45.43 hours
• The union and non-union member employees did not significantly differ in terms of their working hours
• There seemed to be a bias in terms of positions held by the non-unionized employees and unionized employees. The non-unionized employees seemed to be somehow favored.
• The job satisfaction levels slightly differed between the unionized employees and non-unionized employees. A large percentage of non-unionized employees seemed to be more satisfied as compared to unionized employees.

The first test we sought to analyze is the summary statistics for the overall working hours. We give the measures of central tendency such mean, mode, median. We also provide the measures of dispersion such as standard deviation as well as the range. Results showed that the mean working hours for all the sampled employees was found to be 45.43 with a standard deviation of 10.05. The highest number of hours worked by the employees was found to be 89 hours while the lowest number of hours was found to be 28 hours. Looking at the highest number of hours we can see that it is very much deviated from the measures of central tendency (mean, median and mode). This suggests that the value is an unusual value which can be treated as an outlier. The range is 61 which further shows a very huge difference. The skewness value is greater than 1 which shows that the data is not normally distributed but is rather skewed (positively skewed).

There was also an interest to determine whether we have numerous workers that are working over 40 hours. So far as that is concerned, we give an exact gauge of the aggregate number of workers over the entire organization who might work over 40 hours. We found that an aggregate of 178 representatives over the entire association worked for over 40 hours speaking to 44.5%. On the other hand, a total of 26 employees across the whole organization worked for more than 60 hours representing 6.5%.

How does the union employees compare with non-union employees?

The interest in this section is to try and compare how the union member employees compare with non-union member employees. The focus is placed on the following; number of hours of work, occupation of the employees and the job satisfaction of the employees.

The first interest was on the number of hours worked by the employees in the company comparing the non-union member employees and union member employees. Results showed that on average the union member employees worked for an average of 45.14 while their counterparts who are non-unionized members worked for 45.49 hours. These results shows that there is no significant difference in terms of the working hours for the union and non-union members.

Comparison of union and non-union employees

Next the focus was on occupation of the union and non-union members. It was established that a big percentage of the non-unionized member employees were mostly in management (18%, n = 61) against the small percentage of unionized employees (5.8%, n = 4). The union and non-union members had an almost equal percentage when it comes to professional occupation of the employees; 17% (n = 12) of the union member employees worked as professionals while 16% (n = 54) of the non-unionized member employees said to work a professional.  Large percentage for the union member employees when compared to non-union member employees was observed in laborer and production. 19% (n = 13) of the union member employees were production against 12% of the non-union member employees (n = 41). 29% (n = 30) of the union member employees said to work as laborers against 13% (n = 44) of the non-unionized member employees.

Low percentages for the union member employees was observed in regard to tech/sale jobs, administration jobs and service jobs.  For instance, in the case of administrative job, the unionized member employees were represented by 13% (n = 9) against 16% (n = 51) for the non-unionized employees. In the tech/sales category, the non-unionized member employees were represented by 15% (n = 50) while the unionized member employees were represented by 10% (n = 7).  In relation to the service jobs, 6% (n = 4) were from the union employees and 8% (n = 25) were from the non-unionized member employees.

Results showed that satisfaction levels differed among the unionized member employees and non-unionized member employees. A slightly big proportion of non-unionized member employees said to be satisfied (that is, they were either moderately satisfied or very satisfied). 91% (n = 300) of the non-unionized member employees were satisfied against 81% (n = 56) for the unionized member employees. For the all employees, 89% (n = 356) of the employees said to be satisfied (either moderately or very satisfied).

Only 9% (n = 31) of the non-unionized employees admitted that they were either little dissatisfied or very dissatisfied while 19% (n = 13) of unionized employees said to be dissatisfied.

In this section, the study sought to identify whether there is a predictor variable that is outstanding. A multiple regression test was performed to check on how the various predictor variables affect the dependent variable (pre-tax income).

We tested whether there are predictors that would significantly predict the pre-tax income. The following predictor variables were tested to check on how they affect the dependent variable. The predictor variables are age, education years, earners, working years, employment years, number promotions, whether a member is a union member, dummy variable for male.

Multiple Regression test results

Results showed that the following predictors were significant in the model; education years, working years, employment years and being a male. Out of these variables the dummy variable for male stood out since it is the significant predictor variable with the largest standard error. We found the coefficient for the dummy variable to be 9.04. The coefficient value implies that a male employee has a chance of having about 9.04 higher pre-tax income as compared to the female employee. 

Some portion of the worry of the senior administration is that throughout the following couple of years the organization should attempt a huge enlistment drive since the organization’s workforce is maturing and a significant number of workers will have to retire creating room for new employees. We looked to give evaluations to the accompanying:

• Average age of TechnoMart employees
• Average time our employees have been working at TechnoMart 

1. Average age of TechnoMart employees

The mean age of the TechnoMart employees was found to be 39.41 yrs. old with the highest age of the employees being 69 years old. The youngest employee was aged 18 years old while the median and the mode for the employees were 38 years old and 33 years old respectively. The standard deviation was found to be 10.61.

On average the employees of technoMart have worked for about 8.67 years with the longest serving employee having worked for about 52.25 years and the shortest serving employee having served for nearly 0.08 years (close to a month). The median and the mode for the working length for the TechnoMart employees was found to be 5.25 years and 1 year respectively. The standard deviation was found to be 8.38. 

In this section we sought to verify the claims that the union made.

First the union made a claim that their workers are extremely faithful to the organization and that the union trusted that the normal length of work at TechnoMart would surpass the business normal of 7.5 years. We along these lines checked this claim is valid for all workers, for just male representatives and for female workers.

We conducted a one-sample t-test to test this claim for all the employees at TechnoMart. The results showed that the average employment length for all the union member employees was indeed significantly larger than the industry mean of 7.5 years. The average employment length for all the union member employees was found to be 10.74 years. This therefore confirms the claim made that the union workers are faithful to the organization and that they would exceed the industry average of 7.5 years.

Male employees only

We also conducted a one-sample t-test to test the claim for the male employees at TechnoMart only. The results showed that the average employment length for all the union member employees was indeed significantly larger than the industry mean of 7.5 years. The average employment length for all the union member employees was found to be 11.21 years. This therefore confirms the claim made that the union workers are faithful to the organization and that they would exceed the industry average of 7.5 years.

Lastly, we also conducted a one-sample t-test to test the claim for the female employees at TechnoMart only. For the female employees only, the results showed that the mean employment length stay is not significantly larger than the industry length of 7.5 years.

There were some kind of whispers that the union members work at least 45 hours in a week. Using one-sample test, we verified this claim at 5% level of significance. The results showed that the average working hours was approximately 45.14 hours. Also we found the p-value to be0.459 (a value greater than 5% level of significance), we thus fail to reject the null hypothesis and conclude that the average working hours for all the union employees is not significantly different from 45 hours.

The management is concerned as to whether the sample of only 400 workers was not enough compared to the size of the population which is about 9800. We provide a rationale and ideal sample size by providing the right procedure. An ideal sample size is calculated based on the margin of error and the level of significance. The formula for computing the sample size is given as follows; 

So ideally a good sample size would have been; 

So with a sample size of 400 employees we can say we have an ideal sample size. 

1. Of specificinterest to the management is being capable of accurately estimate the scale of the trouble we’ve with group of workers running immoderate hours (i.e. extra than 60 hours per week). In different phrases, with a view to correctly estimate the size of our overtime problem, do I have enough quantity of staff in my pattern who work more than 60 hours? If no longer, how many have to be sampled?

First we had to compute the required sample size as follows; 

From the computation, it is clear that there is no sufficient number of staff in my sample who work more than 60 hours and as such an additional 68 employees who work more than 60 hours should be added to the sample.