Human Resource Management

Finding and discussion

This study involved a total of 200 employees from both the Federal Reserve and other government agencies. These employees filled out the questionnaires and were also involved in the survey. Out the 200 questionnaires given out a total of 162 questionnaires were returned with a response rate of 91%. Each of these questionaries after being collected back from the respondents were them corrected and cleaned before being fed to the SPSS database (Ponta et al., 2020). The most obstructive omissions were corrected by inspecting the inaccuracies. 2 questionnaires were dropped because they had not been completed which indicated either lack of interest or inadequate time. Therefore, the data from questionnaires that was used was from 160 employees.

Analysis and discussion findings

Data was analyzed with the help of the SPSS. Descriptive statistical methods were used to analyze descriptive data where cross -tabulation was used to represent the findings in the frequency distribution tables. Other tests that were also employed include the Chi-square fit test which tested the hypothesis to give out conclusions that are meaningful. Data analysis included combination of many analysis tools to help the researcher to come up with the best results. The tools also were used depending on the type of data that needed to be analyzed. For descriptive data descriptive tools were used and for the non-descriptive data non descriptive tools were used.

Profile of the respondents

Some personal information about the respondents were collected by the researcher. Personal information was important to be collected because it helped the researcher to define the characteristics of the demographic the researcher was working on. Understanding demographics is important because it can explain why a person gave a certain answer and what the person values according to their age or gender. The four main pillars of the definition of demographics that the researcher focused on are age, gender, work experience and education. Profiling the respondents also helps the researcher to know how to handle different respondents during the interviews and the questionnaire. It also guides the researcher to choose the correct vocabulary to use around the respondents. For instance, how the researcher will address a 60-year-old female is not the same with how a 20-year-old female will be addressed.

Staff category

The finding on gender showed that out of supporting employees 9 (21%) were female while 8 (14%) were male. Out of the 66 employees 29 (67%) were females while 37 (65%) were male. Out of 17 employees 12 (21%) were male and 5 (12%) were females. This study in general involved almost an equal number of females and males. This showed that the government of the United States is a good employer who gives equal opportunity to all of its people. The study therefore will have little or no bias or prejudice which is caused by gender inequality in the workplace.

Age distribution and staff category

Out of the 17 employees 16 (94%) were aged between 36-45 while one (6%) was below the age of 35. Out of the 66 employees in the federal staff 48 (73%) were aged between 36-45 years while 15 (23%) were below 35 years old. The other 17 employees 2 (12%) were above the age of 55 years while 15 (88%) were between 36-55 years old. Majority of the employees who were involved in this study were aged between 36-55 years old. This study represents a group of matured and working-class people who are capable of providing information that is relevant to the study. These people also have enough experience in their work, and they are likely to give information that is accurate about the matters of the job such as incentives and motivation. In addition, this is a group with families and responsibilities therefore they have high motives for work.

Educational level and staff category

On the educational levels of the employees out of the 17 employees 2 (125) gad graduate degrees, while 14 (82%) had no degrees the other one had either master’s degree or a postgraduate degree. 51 of the other employees which is (77%) had masters or postgraduate degree. 1 (2%) had no degree and 14 (21%) had undergraduate degree. The employees at the topmost positions 16 (94%) had masters and post graduate degrees while 1 which is (6%) had undergraduate degree. These employees are based on their level of education and therefore this shows that the United States compensates individuals depending on their level of education. The people that earn the title of professionals are only the ones with degrees either undergraduate, masters or postgraduate those with no degrees are supporting staff. It can be concluded that the employees with the highest qualifications are likely to get the highest positions withing the government agencies and also in the federal reserve.

Working experience

The employees involved in this study had work experience of more than three years. Even the employees with less qualifications and those who are considered supporting staff have an experience of more than three years. However, there are other top employees who were involved in the study who had much experience to even 10 years (Hale et al., 2019). These employees included the managers and the leaders. These employees are very reliable in the study because they are likely to give correct information due to their experience and many years they have spent on the job. Since the employees have enough experience on different things concerning their jobs, they are more suited to give their view on the issue of incentives and motivation.

Most significant indicators of motivation

The main objectives aimed at determining the indicators of motivation are analyzed by the researcher. The respondents are therefore asked to rank the attributes of motivation. Several attributes were chosen, and the researchers were asked to rank them indicating which was of more importance to them. The questions guiding both the researcher and the respondents included which is the most significant attribute of motivation? Using the five points Likert scale to rate the statements used there was 1 which was strongly disagree, 2-disagree.3-neitral, 4-agree and 5- strongly agree. The respondents gave their answers using the Likert scale to show which of the motivational attributes were more significant to them.

Salary as an indicator of motivation

29% of the employees concurred that salary was a basic indicator of motivation. 74% of the employees who are professionals with qualifications agreed that salary is an indicator of motivation and 20% of the topmost employees agreed that salary was an indicator of motivation. In this study 60% of the respondents either agreed or strongly agreed that salary was an indicator of motivation. Therefore, it can be concluded that salary is a basic indicator of motivation. Some people go to work with the sole purpose of getting salary. They are motivated by salaries and increment of salaries can even motivate them more.

However, there are those employees who were neutral they did not agree or disagree whether salaries were indicator for motivation (Fallatah et al., 2018). 57% of the supporting staff were neutral, 25% of the professionals were neutral and 20% of the topmost employees were neutral.

There is also the issue of overtime as an indicator for motivation. 60% of the support staff disagreed that overtime was an indicator of motivation, 40% of the professionals disagreed that overtime was an indicator of motivation and 70% of the topmost employees disagreed that overtime was an indicator for motivation. Therefore, overtime is not considered an indicator for motivation.

Bonus pay as an indicator of motivation

On the issue of bonus pay as an indicator of motivation 30% of employees who are considered support staff disagreed that bonus was an indicator of motivation. 60% of the employees considered professionals disagreed that bonus is an indicator of motivation and 23% of the topmost employees disagreed that bonus is an indicator for motivation. There were groups that reserved their comments too (Daniel, 2019). They did not agree or disagree whether bonuses are an indicator for motivation. 70% of the professional support staff reserved their comments on the issue while indicating that this group of employees do not regard bonuses as a factor of motivation. Mangers also indicated that bonuses are not applicable to most of these employees.

Car loans as motivation indicator

The results of the employees and how they felt about car loans as an indicator of motivation are as follows. 61% of the professionals agreed that they are motivated by car loans,27% of the topmost employee agreed that car loans were an indicator to motivation and 12% of the support staff agreed that car loans were an indicator for motivation. 32 employees were not sure about car loans being an indicator to motivation. These people did not agree or disagree about car loans being an indicator to employee motivation. 68% of the professionals reserved their comment on the issue, 18% of the support staff reserved their comments on the issue and 14% of the topmost employees reserved their comment on the issue. This indicates that to professionals and top-ranking employees mostly car loans are an indicator of motivation. This is because of the reasons that are accrued when one problematic a private means of transportation.

House allowances as an indicator for motivation

The researcher also considered house allowances as incentives and aimed at establishing their relationship with motivation. 54 % of employees strongly agreed that house allowances were indicators of motivation. The 45% of the employees strongly disagreed that house allowances were indicator for motivation. The number that disagreed strongly was lower to the supporting staff and very high on the professionals. This shows that professionals do not consider house allowances an indicator for motivation. House allowances are necessary for the employees because it saves their money which they would have spent in seeking for good shelter which is a basic necessity.

Staff loans as an indicator for motivation

61% of the employees agreed and others agreed strongly that staff loans were an indicator for motivation. 11 people who agreed were support staff, 41 people were professionals and 9 people were topmost employees. They agreed that they were motivated by the staff loans. They even revealed in the comment sections of the questionnaire as well as in the interviews that staff loans helped them carry out projects which required large amounts of capital they did not have. This shows that staff loans are an important indicator of motivation to employees because it helps them in fostering their personal goals and promoting the work morale of the employees. There are things that their salary cannot fulfil and hence these loans are used to fulfil such things.

The following bar graph summarizes the indicators of motivation as explained above. The four most important factors were salaries, staff loans, car loans and house allowance. Things like bonus pay, overtime allowances were not an indicator for motivation in this case. These factors that are not considered to be an indicator of motivation had lowest responses of people agreeing if they were an indicator or not. This helped the researcher to conclude on the factors that were indicators of motivation and those which were not indicators of motivation.

The most important indicators of motivation

The employee motivation in this study involved extrinsic rewards which results from the attainment of the rewards that are eternally administered which include material possession, pay, prestige, and the positive evaluations from others. The study realized the four major significant indicators of employee motivation and these included car loans, salary, staff loans and house allowances. In commenting on these significant indicators of motivation the respondents agreed or strongly agreed. However, on the other factors that have been ruled out as not significant indicators of motivation many respondents would withhold their comments or disagree.

These findings supported the study of Novianty, (Novianty,2018) which suggested that there is a good relationship between the performance and the productivity of employees in an organization and compensation and incentives offered to these employees. There is a good relationship that exists between the remuneration and the performance of not only the employees but also the organization in whole. Employees are likely to perform better in an organization due to the incentives offered to them. This is because these incentives make their lives easier, and they are able to focus on their work. For instance, when the organization offers the employees car loans, they lift the burden of the employee using public means of transport which are stressful and less reliable. It also increases the quality of the life of the worker this increases their job morale and hence their productivity. Some of these incentives also helps to boost the self-esteem of the workers. The Maslow’s hierarchy of needs places the self-actualization needs at the top and the basic needs at the bottom this means that lacking basic needs can make a person lack self-esteem. Therefore, helping the employees achieve the basic needs will help them acquire self-esteem. Employees with good attitude towards themselves also have good attitude towards their jobs.

The motivation hygiene factor states that ‘treat people as best as you can so that they have minimum dissatisfaction’. This theory suggests that people should be treated in a way that they are helped to grow and become better in their work for this improves their achievements and their motivation. Therefore, for the employees to be entirely satisfied they must be properly compensated. The pay must be in decent so that it meets the needs of the employees. However, most of the times compensating employees properly does not necessarily mean success of the organization, it is the responsibility of the leaders in the organization to use these incentives properly to increase morale. The incentives therefore in order to benefit the organization should be given strategically.

Significant and non-significant incentives

The researcher also determined the impact of non-salary incentives on the motivation of the employees. These non-salary incentives include medical insurance, this is the most significant financial and non-salary incentive. Employees are motivated by this kind of incentive because it caters for their most important factor their health. Others include the retirements benefits which are the benefits given by the company to the employee after they have retired. These benefits ensure a smoot life for the employee whether in sickness or in old age after retirement. In this study 85% of all employees acknowledged that they were motivated by these health insurance benefits or the retirement benefits. The study dived further to establish the difference that exists in incentives between the private sector and the public sector. The study aimed at coming up with the incentives that were more appropriate for the public sector since it was dealing with the federal reserve and government agencies. The study therefore showed that it was more problematic to use pay related incentives in the public sector. This is because in the public sector many problems are created by difficulties in measuring outputs, multi-tasking, and multiple principals.

You have taken a quantitative (questionnaire) study, and this should be interpreted in graphs. The last paragraph of staff loans as indicators for motivation talked about graph but with no evidence of it.