Presently Finding Himself In A Situation †Myassignmenthelp.Com

Question: Discuss About The Presently Finding Himself In A Situation? Answer: Introduction The manager of TripleA Company is presently finding himself in a situation where he is unable to develop a growth strategy for his company. He is facing many difficulties in running the company smoothly and this is mainly due to a particular issue that he has noticed regarding the working attitude of his employees. He is of the opinion that if the situation is not handled and the problems are not redressed, then the company might just go into liquidation in the coming years. Now, the main issue in any research design is the issue of problem identification. Similarly in the case of TripleA Company, the basic problem lies in the proper identification of the cause of the working attitude problem among the employees. There might be many reasons due to which the company employees do not wear the right attitude to work, namely, issues in management, unsuitable work environment, poor promotion or incentive strategies, etc. The task at hand, or in other words, the main objective of this paper is to design a research methodology whereby the main causes behind the working attitude problem of the employees can be identified and the areas where the company can improve so as to enhance the engagement and the performance of the employees can be highlighted or brought to the notice of the top management of the company. Another thing to note is that the working attitude of the employees might look like the real issue to the manager on the face of it. But in reality the problem that the company is facing whereby the overall performance of the employees and with it the performance of the company is failing, might lie elsewhere. So the main objectives of the research design are the following: To identify the causes due to which the company performance is being hampered. To identify the level or area at which the problem is arising. To highlight the areas in which the company management is going wrong and the improvements that can be made by the company to enhance employee engagement and performance. To provide an easy and feasible solution to the problems that will be established from the results of the data analysis. It is a common observation that employees who are dissatisfied with their job, be it for any reason, end up having an undesirable attitude or a negative behavior that can result in the employees underperformance and can hamper the profitability of the company (Meyer, 1997). The study is conducted to ascertain the right method whereby the manager can address the issue at hand. The main objective is to devise the right strategy, the right plan so as to choose the correct method of sampling and the right instrument of data collection which can pin point to the main cause of underperformance and bad working attitude of the employees. Sampling Design Now, since we are dealing with a company that is facing different problems, as stated earlier, first we need to identify the basic areas of problem. In order to do that, we have to devise a sampling method whereby all the different levels of hierarchy in the organization are properly represented so as to study the different levels of management and see wherein the problem lies. The issue might be in the way the top level management works, the middle management works, the bottom management, or a mix or the above. It might be due to lack of communication or trust between the different levels of authority. The flexibility that an employee enjoys in his/her work is found to have a direct effect on their job performance (Richardson, 2014). For this purpose, the right sampling method is the method of Stratified Sampling. Now, stratified sampling is used as a sampling method for populations that do not consist of homogeneous units. In such cases, the population is divided into sub-populations that are more-or-less homogeneous. These sub-populations are known as strata. Then from each stratum, selections are made that form the sample. This type of sampling ensures more accurate estimates where heterogeneous populations are involved (Kothari, 2004). For the purpose of our research, we differentiate between the different stratums based on the level of management that the employee belongs to in order to capture the relationship between the different hierarchies. This sort of stratification will help in making the sample much more representative of the whole company workers. Also, based on these stratums, different issues can be targeted which are more relevant in their own level of management. For example, the communication between the top level management, the directors and managers of the company and the bottom level management, the new recruits or the helping staff might be almost negligible. The higher authorities might be unaware of the distress among the employees. The new recruits and the trainees might be dissatisfied with the work environment or maybe their mentors attitude towards them. There might be problems of different kind all of which together impede the profit making capacity of the company. (Miller, 2014). Theref ore, studying all the different groups is very important in getting an overall picture of what is really going wrong in the company. And this is made possible only with stratified sampling as the method of sampling design. The sample size depends on the workforce of the company. But whatever be the workforce, at least 50% of the workforce should comprise the sample. Since we are talking about a companys performance here and the issue is really crucial since the manager fears the possibility of liquidation in the coming years, we should try to keep the sample size as large as possible and include the opinion of most in order to get more precise estimates and results. For example, lets say TripleA has 3000 employees. These employees are divided according to their levels in the following way: Top level management 50 Middle level management 1000 Bottom level management 1750 Helping staff - 200 So the sampling can be done by considering the different categories as different stratums. And from each of these stratums, we take a certain proportion that forms the sample. Let the proportion be 50. Then from each stratum we take the following numbers: Top level management 25 Middle level management 500 Bottom level management 875 Helping staff 100 So we get a sample of 25 + 500 + 875 + 100 = 1500. If the proportion was taken as 25, then we would get the following numbers: Top level management 13 (rounding off) Middle level management 250 Bottom level management 437 Helping staff 50 So then the sample size would be 13 + 250 + 437 + 50 = 750 Depending on the situation at hand, you might choose different sample sizes. Given, the issue at hand is one of working attitude; a large sample size is more useful. Therefore one should choose a sample which represents the whole workforce proportionally and has a sample size half the size of the population size. Instrument of data collection Data collection is the next step and a very important component of research. The main goal of collecting data is to gather information on certain issues that form the crux of the research study. Based on this information, the data is analyzed and results are drawn. There are many instruments or tools for data collection. Building questionnaires, holding interviews, or simple observation and reading can all be considered as different tools whereby data can be collected for research. Any instrument should been chosen based on how reliable it is as a tool of data collection and how valid it is in providing accurate estimates. For the case at hand, questionnaire seems like an appropriate tool for data collection. There are mainly two forms of questionnaires, structured and unstructured. Structured questionnaires are the restricted ones with a closed form. They are said to be structured in the sense they provide the respondent with questions and a multiple choice for the answers and the r espondent is to check that item which is closest to his/her opinion. Unstructured questionnaires are the open ended type of questionnaires in which the respondents have the liberty to express their opinion and answer in their own words. For the case of the TripleA Company, using structured questionnaire is the most appropriate tool of data collection. Following are the reasons that other tools are not appropriate for the case at hand: Interview: Holding face to face interviews for a large sample size is very time consuming. Also, responses might be biased when questions are asked face to face. In order to capture genuine response, such a method might not always be a good idea. Observation: It will be highly unlikely to get any result out of just observing the situation in the company affairs. A structured questionnaire will be able to bring out the main problem areas among the employees. Knowing their opinion about the company management, the benefits and the incentives provided by the company, and their level of job satisfaction will go a long way in addressing the work attitude problem among them and enhancing their proficiency and productivity. The questionnaire should consist of at least 50 questions on the overall experience of the employees. In this case, a detailed survey is required and so a minimum of 60 questions based on different themes should be framed. After preparing the questions, the questionnaire should be reviewed by a trustworthy and reliable source. An expert opinion should be taken in order to test for the effectiveness and the appropriateness of the survey. The next step should be to conduct a pre-test of the instrument where the sample questionnaire is given to potential respondents so as to improve the quality of the survey, to do away with the errors and the improper wordings and make all the necessary changes based on the opinion of the ones on whom the pre-test is done. Survey Method Sincewe are using a structured questionnaire which allows the respondents to give their opinion in a predetermined construction, it allows for the responses to be converted into statistical data that can be used for proper data analysis. The task at hand is therefore to undertake a quantitative research using survey questionnaire. The selected participants that comprise the sample can be made to take the survey, a questionnaire that includes questions on different themes. The survey will help the manager of the company to focus on the immediate needs of the company and will throw light on the areas for improvement. The questions should be structured in such a way that their answer can be used to draw information on the employees attitude towards work, their assessment of their own performance, their commitment to the company goals, the level of flexibility they have in their work, the overall work environment, the kind of relationship and trust they enjoy with their peers and their s eniors and the level of independence in decision making that they possess and the effect that has on their efforts in work, etc. The main themes that should definitely be featured in the questionnaire are as follows: The work environment/ corporate culture of the company Job satisfaction/ benefits and incentives The stress level of work The work-life balance Training and teamwork Flexibility at work, opportunity for self-improvement and self- development Employee relations Management structure, hierarchy and transparency Pay/Rewards/Recognition Human Resource Communication There are different ways or different scales that can be used to measure and report the responses of the respondents. Based on the question posed, one may use different measures like the measure of agreement or the measure of satisfaction for measuring the response of the participants. Using a 5 point Likert scale is most appropriate in this case. An example of a question using the measure of agreement and a 5 point Likert scale is: Do the managers involve you in the decisions affecting your work? Strongly Disagree Disagree 3. Neutral 4. Agree 5. Strongly Agree Similarly, a measure of satisfaction can also be used depending on the type of question posed and its structure. An example of a question using the measure of satisfaction and a 5 point Likert scale is: Are you happy with the level of efficiency shown by your team members? Very Dissatisfied Dissatisfied 3. Neutral 4. Satisfied 5. Very Satisfied Along with the survey question, there should be a list of items on which general comments can be taken from the participants of the survey. The items should mainly concentrate on the following: Areas that the company feels more efforts can be taken for improvement New initiates that the company has taken for the benefit of its customers or employees and would like an opinion of the employees on the same New initiatives that the company can take for the benefit of the employee While making the survey questions it should be kept in mind that the company has people from different backgrounds who are working at different levels. So, there is a need to have few common questions for all the employees and a section of questions that are particular to the level of post held by the employee. For example, the question given in an above example, as to whether the managers involve the employees in the decisions affecting their work is not appropriate for the top level managers but the employees working under the managers in any project. Similarly the question as to whether the employee is satisfied with the level of efficiency shown by the team members is not meant for the unskilled helping staff. But the question as to whether the employee is happy with the work environment applies to employees of all levels. So a note should be made on the same and separate questionnaires should be made for the employees of different levels. Data Analysis Once the survey is conducted and the participants fill in their responses, the scores got from the Likert scale can be used to conduct statistical tests and data analysis. We can use Microsoft Excel to tabulate the information got from the survey. All the responses got from the employees can be put in a structured format in the excel file. Then you can import the (.xls or .xlsx) file into the software package SPSS for conducting statistical analysis. Once imported to SPSS, we will have a database having the number of variables equal to the number of questions plus two (for the ID of the employee and the gender of the employee). The different tools or methods that can be used for data analysis in this case are as follows: Descriptive Statistics Simple relative frequency tables / Contingency tables Inferential Statistics Hypothesis testing using t-test and ANOVA Regression Analysis Descriptive Statistics The data got from the survey is mainly ordinal data. And hence, the first thing that should be done is create simple relative frequency tables or contingency tables for each of the questions posed or you might just choose the important questions. Based on the frequency tables, we will get an idea of the relative frequency of the different scores on the scale. For example, lets say there were 500 respondents to the question, The Human Resource staff is approachable and responsive when I need any kind of assistance and they responded to the question in the following way: Strongly disagree (1) Disagree (2) Neutral (3) Agree (4) Strongly Agree (5) 42 106 72 41 39 14% 35.33% 24% 13.66% 13% So, we can conclude that 14% of the employee respondents strongly disagree, 35.55% of the employee respondents disagree, 24% of the employee respondents is neutral, 13.66% of the employee respondents agree and 13% of the employee respondents strongly agree to the fact that the Human Resource staff is accessible, approachable and responsive to the needs of the employees. These numbers are random and have been used just for the sake of providing an example. But these percentages give just an overall picture but for more detailed analysis we have to move on to inferential statistics next. In order to make a visual comparison we can use bar graphs. Bar graphs provide an easy way of checking the height of the scores, which basically means seeing the percentage of people choosing different score as their response. Since, the questionnaire was designed to collect ordinal data, using summary measures like mean, median, mode, range and standard deviation will not be an appropriate method for running proper analysis of the data. SPSS commands: Analyze = Descriptive Statistics = Frequencies Graphs = Chart Builder = Bar = Simple bar chart Inferential Statistics In order to draw more meaningful insights and extend the analysis beyond the simple summary measures, we have to use inferential statistics. Inferential Statistics is just a means of inferring information about the population from the sample data at hand. Inferential statistics mainly involves the General Linear Model, which is a family of statistical tests involving the t-test, Analysis of Variance (ANOVA), Analysis of Covariance (ANCOVA), regression analysis and others. We can run many hypothesis tests using the above statistical models in order to draw better insights from the data collected from the survey responses. Now, there are different types of t-tests, each used for a different purpose. These are as follows: One Sample t-test: It is generally used to test whether the population mean is equal to a target value. Now, different hypothesis can be framed for using the one sample t-test. Few examples have been listed below. Null Hypothesis: The average job satisfaction level score is equal to 4 (where 4 = satisfied). Alternate Hypothesis: The average job satisfaction level score is not equal to 4 (where 4 = satisfied). Null Hypothesis: The average agreement score regarding team spirit among the employees is equal to 4 (where 4 = agree) Alternate Hypothesis: The average agreement score regarding team spirit among the employees is not equal to 4 (where 4 = agree) Two Sample t-tests: This type of test is used to test whether the difference between the means of two independent populations is equal to a target value. Few examples are given below. Null Hypothesis: The average job satisfaction level is the same between the male and the female employees Alternate Hypothesis: The average job satisfaction level is not the same between the male and the female employees Null Hypothesis: The average work-life balance satisfaction score is the same between the male and the female employees Alternate Hypothesis: The average work-life balance satisfaction score is not the same between the male and the female employees Paired t test: This type of t-test is used to test whether the mean of the differences between paired or dependent observations is equal to a target value. An example is given below. Now, paired t test is useful when you try to find out the effect of some measure taken on a given population. For example, you want to measure the effect of a drug for cholesterol maybe. So you test the difference in the mean cholesterol level before and after the drug use for the same population. So in the case of the TripleA Company, what can be done is the survey can be conducted twice with a time interval of a month, where within the month, based n the conclusions drawn from the reports on the survey results, few measures are taken to address the problems being faced by the employees and improvements are made in some distress areas. Based on these two survey reports, we can try to see whether there has been a change in the working attitude of the employees. Null Hypothesis: There has been a significant change in the attitude towards work of the employees before and after the new measures. Alternate Hypothesis: There has been no significant change in the attitude towards work of the employees before and after the new measures. SPSS Commands: Analyze = Compare Means = One sample t-test Analyze = Compare Means = Independent samples t-test Analyze = Compare Means = Paired samples t-test Analysis of Variance (ANOVA) ANOVA is used as a statistical model in order to capture variations among and between groups. If you want to check whether there is any difference in the average satisfaction levels between the employees of different levels, then ANOVA is the appropriate method. Null Hypothesis: The mean level of satisfaction or agreement is the same for all the groups Alternate Hypothesis: The mean level of satisfaction or agreement is not the same for all the groups You can test for the difference in the mean scores or the mean responses across the different groups for any of the relevant questions that are deemed to be important. SPSS Command: Analyze = Compare Means = One way ANOV Regression Analysis In case you want to test for causation, then regression analysis is a form of inferential statistical tool that can come of great help. If you want to see whether two or more items on the questionnaire are linked and whether one causes the other, using the method of simple linear regression can help answer all your questions. For example, if you want to know whether the level of satisfaction with the pay or incentives program offered to the employee has an effect on the work engagement of the employee, you can test for such causation using regression analysis. Our main objective of this study is to identify the reasons or the causes for the inappropriate working attitude among the employees. In order to do that, we can take the results found from the above tests that are run, on what are the key areas of dissatisfaction and try to see whether those factors have an overall effect on the work commitment, the work performance and the work engagement of the employee. You can also test fo r multi-colinearity in the model, whereby you can find out whether two factors are correlated to each other. Looking at correlation between the different variables can also help in finding out the underlying problem. SPSS Command: Analyze = Regression = Linear All the above analyses are done using the software, SPSS which provides a very convenient way of running t-tests, ANOVA tests and also regression analysis. After running these series of tests, you can draw meaningful insights from the responses collected and form a proper report on the survey data. The report will then help in trying to find out wherein lies the real problem with the employee and what are the ways the performance of the employees and with it that of the company can be improved, so as to avoid the impending liquidation. Summary Now, we summarize the whole study to see the research design that has been proposed in a nutshell. We shall go over the things point wise. Problem Statement: The problem being faced by the manager of TripleA Company was with its employees. Things were not running smoothly in the company and he feared that the company would be liquidated soon. The manager felt that the issue lied in the working attitude of the employees and wanted to address the same. Objective of Study: Now, the objective of the study as stated earlier is to chalk out a research design for the manager so that he can address the above issue regarding his company. So, the main motive is to identify the problem areas of the company and the issues being faced by the employees so that once the problems can be looked into and a solution can be provided, the overall performance of the company will improve. Sampling Design: The method of sampling chosen for running this research was the stratified sampling method. The reason for choosing this method of sampling is because the company employees form a heterogeneous group with people coming from different backgrounds, holding different positions and working at different levels in the company hierarchy. Instrument for Data Collection: The tool chosen the purpose of data collection is questionnaire. It is the appropriate tool for the kind of research at hand. Depending on the quality of the questionnaire, a lot of important information can be collected from the employees which in turn can help pin point to the underlying problems of the company which is hampering its performance. Research Method: The method that can be used for conducting research for this particular case study is survey. Survey is a very popular and convenient way data is collected and the responses got from the survey are a good means of doing research in any field. Data Analysis: For the purpose of data analysis, both descriptive statistics and inferential statistics have been used. In the case of descriptive statistics, we have confined to simple relative frequency tables and bar graphs to get an overall picture of the data collected from the responses. When moving on to the inferential statistics portion, different statistical models like the t-tests, one-way ANOVA, linear regression model can be used. Few things should always be kept in mind while conducting a survey. These are: The problem areas that are highlighted from the survey response should be acted upon by the senior managers. The language of the questionnaire should be simple, clear and precise. No technical and fancy jargon should be used unless really necessary. The anonymity of the participants should be ensured in order to get genuine responses. The questionnaire should be pilot tested. Instructions regarding the questionnaire should be clearly communicated to the participants. The survey can be conducted for a second time in order to see whether attitudes change among the employees in the way of change in responses. References Ahmad, H., Ahmad, K., Syah, I. (2010). Relationship between job satisfaction, job performance attitude towards work and organizational commitment. European Journal of Social Sciences , 18 (2), 257-267. Dawn, L. (2010, November 2). Handling Employee "Attitude" Problems| A Step-by-Step Guide. Retrieved from toolbox.com: https://hr.toolbox.com/blogs/business-fitness/handling-employee-attitude-problems-a-stepbystep-guide-42263 Employee Survey Checklist . (2017). 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