Free Ensuring Pay Increases For Staff And Attorneys To Increase Employee Morale Essay Example
Type of paper: Essay
Topic: Workplace, Employee, Staff, Human Resource Management, Salary, Employment, Satisfaction, Criminal Justice
Employee morale is influenced by many factors, some exclusive and others as a result of a combined effect. Ensuring high employee morale is vital for any organization as it has a profound effect in the productivity and the bottom lines of the organization. The organization for which I work has been experiencing reduced employee morale. This is attributable to the changes within the organization that have seen massive layoffs of employees and the transfer of employees to other departments. Additionally, this is reduced job security, causing worries for the security of tenure for the employees.
There is also an issue with remuneration and benefits where two conspicuous cohorts with regards to remuneration are evident within the organization. One cohort consists of the staff who receive a lesser basic pay compared to the attorneys in the organization. Additionally, the staff has to pay for their health benefits while the attorneys enjoy the benefits in the organizations bill. These disparities have resulted in decreased morale, especially for the staff. This research paper is intended to find out whether an alteration in the variables can lead to an increase in the employee morale.
Although the data collection process did not sample many respondents owing to the massive layoffs, describing the data reiterates the rationale on which the research paper was based.
With regard to remuneration, the mean of staff salaries was at 1383.022 dollars. This shows that the average biweekly staff salary before tax was at 1383.022 dollars. In this dataset, the range between the highest paid employee who got 1483.57 dollars and the least paid employee who earned 1275.26 dollars was 208.31 dollars.
In order to give further meaning to this data, it is important to compare the attorney salaries in the same organization. The average biweekly attorney salary before tax for the dataset was 2176.924 dollars. The range between the highest paid attorney who earned 2423.08 dollars and the least paid attorney who earned 1923.08 dollars was 500 dollars.
Comparing the two means
In order to determine whether there is a statistically significant difference between the staff salaries and those of the attorneys in the same organization, a comparison of the two means was performed. In performing this analysis, a t-test for the two samples assuming that there were equal variances was performed. The output of the analysis showed that the p-values for the one-tailed t-test and the two-tailed t-test were small (Cobb, Scheaffer, Watkins & Watkins, 2011). The implication of this is that there was a statistically significant difference between the mean of the staff salaries and the attorney salaries.
When a t-test for the two samples assuming that there were equal variances was performed, the output of the analysis showed that the p-values for the one tailed t-test and the two tailed t-test were small. The implication of this is that there was a statistically significant difference between the mean of the staff salaries and the attorney salaries. The statistically significant difference between the salaries of the staff and the attorneys in the organization can be one of the reasons why the employees are not sufficiently motivated.
The premise of this research paper is to understand the strength relationship between the dependent and independent variable of study. There are a number of independent variables in this research paper. They include the staff salaries, attorney salaries, holiday bonuses and the medical benefits. The independent variable in this research paper is employee satisfaction. It is important for the research paper to establish the correlation between all the independent variables and the dependent variable. For instance, establishing the strength of the relationship between staff salaries and attorney salaries and employee satisfaction, one can make inferences on the effect altering the independent variable positively and negatively has on the dependent variable. Additionally, by establishing the strength of the relationship between each of the independent variable and the dependent variable, the organization hierarchy can determine the areas to focus on in order to increase the morale of their employees (Sharma, 2005).
Regression Analysis for Staff Salaries and Employee Satisfaction
When the independent variable (staff salaries) is computed against the dependent variable (employee satisfaction) for the regression coefficient, the value acquired is 0.864542544. From this correlation coefficient, it is possible to make inferences on the strength of the linear relationship between the dependent and the independent variable. Normally, a correlation coefficient of 1 signifies a positive relationship where an increase in one variable results in an increase in the other variable. A correlation coefficient of 0 indicates that there does not exist a linear relationship between the independent and the dependent variable (Ratner, n.d.). In this instance, there is a strong relationship (r=0.864542544) between staff salaries and employee satisfaction. The inference that can be made is that an increase in the staff salaries will result in an increase in the employee satisfaction.
Regression Analysis for Attorney Salaries and Employee Satisfaction
When the independent variable (attorney salaries) is computed against the dependent variable (employee satisfaction) for the regression coefficient, the value acquired is 0.618247. From this value, it is possible to make inferences on the strength of the relationship between attorney salaries and employee satisfaction and the effect on the dependent variable when the independent variable is manipulated. When r = 0.618247, it can be inferred that the strength of the relationship between attorney salaries and employee satisfaction is mild. This implies that an increase in attorney salaries would result in an increase in employee satisfaction, although the magnitude of this increase would be mild compared to that of the staff.
When the correlation coefficient for the relationships between the remuneration for the staff and the attorney and their corresponding employee satisfaction is compared, it is evident the correlation coefficient for the staff (r=0.864542544) is higher compared to that of the attorneys (r = 0.618247). This implies that remuneration has a bigger effect on employee satisfaction for the staff compared to the attorneys. This could be attributed to the fact that the attorneys are paid significantly more (2176.924 dollars) compared to the staff (1383.022 dollars).
Regression Analysis for Holiday Bonuses and Employee Satisfaction for Attorneys compared to the Staff
The analysis of the data as presented above shows that the attorneys are paid significantly more than the other staff. While this is in regard to their salaries, their other benefits are also better compared to those of other staff. For instance, the attorneys are not charged for the insurance cover unless they want to include dependants, in which case they only pay for the dependants. When a regression analysis is carried out between the two independent variables and the dependent variable, a trend is established. In this trend, the strength of the relationship between the two independent variables (salaries and bonuses) and the dependent variable (employee satisfaction) is less for the attorneys when it is compared to that of the other staff. This means that any improvements in the working conditions of the attorneys should focus on other aspects, and that an improvement. It also implies that any improvement in the employee morale for the staff will be achieved when their remuneration package is restructured.
Cobb, G. W., Scheaffer, R. L., Watkins, A. E., & Watkins, A. E. (2011). Statistics: From data to decision. Hoboken, N.J: Wiley.
Ratner, B. (n.d.). The correlation coefficient: Definition. Retrieved 21 Jan. 2015 from http://www.dmstat1.com/res/TheCorrelationCoefficientDefined.html
Sharma, K. (2005). Text book of correlations and regression. New Delhi. Discovery Publishing House.