A Study of the Correlation between High Employee Satisfaction and Low Employee Absenteeism
Introduction
Employee satisfaction is both a quantitative and qualitative measure of the happiness and content of employees towards their working environment and job. This satisfaction and resultant happiness influence productivity, morale, loyalty and absenteeism. Whereas, on the other hand; absenteeism is termed as a pattern of the habit of being absent from obligations and duties at work. Satisfaction of employees tends to relate to absenteeism, and thus; has led to the study of their correlation. This is done in a bid to identify the extent of the relation between the two factors.
The study of the correlation between employee satisfaction and absenteeism
The study of employee satisfaction and absenteeism would consider several variables that seem to bear significance on their correlation. These variables would include age, gender, level of activity, position at work, the number of days that an employee is absent and the turn-over of employees at the work place. Other variables may include the amount of pay and satisfaction percentage based on the number of yes and no responses to the questionnaires’ questions that rate satisfaction. The analysis of the data obtained from these variables bears significance on the correlation. Thus, the obtained results from the analysis of this data will be used to draw a conclusion about the correlation. The variables involved in this research may contain uncontrolled variables other than the independent variables involved (extraneous variables). These may bear significance on the results to be obtained in the final analysis because they affect the behavior of the subjects under study. These extraneous variables may include subject variables (gender, mood, age and health status), experimental variables (language, gender and race) and situational variables (time of day and level of activity)-just to mention but a few. In order to control the effect of these extraneous variables, I would use a two-pronged approach that would eliminate the effect they may have on the results of the study. The first approach would ensure all highly influential extraneous variables are kept similar for all involved subjects under the research.
The can be done, for example, by ensuring all subjects under a group are of the same gender and age. The second approach would ensure that extraneous variables that occur under different experimental units are balanced. This will serve to nullify any unbalanced effect that they my have in various constituent groups. The design I would choose to employ in this research would be the quasi-experimental design, widely used in the fields of psychology and social sciences. Though seemingly unreliable and unscientific to physical and biological sciences; the method has an advantage. This is because it combines both qualitative and quantitative experimental design elements. In turn, this will be essential for this scenario because the study involves elements of data that have both qualitative and quantitative significance to the experiment’s research (Shuttleworth, 2008). Data collection for this would involve methods that include administering of questionnaires, interviews and the use of collected available data in the work records. Queries and questionnaires will be directly administered to employees, whereas, available information can be solicited from the labor or human resource offices. The administration of questionnaires and interviews will be used because the researcher can determine and measure other extraneous variables that may not be obvious without direct involvement (Shuttleworth, 2008). These methods also help the researcher ascertain the quality of data collected because he/she will be directly involved. The use of available data is equally important because it will reduce the amount of time required to generate data for the research.
The correlation coefficient generated after analysis of the data will portray the extent and type of relation between the two factors under consideration in the hypothesis. The correlation coefficient normally used is referred to as the Pearson’s correlation coefficient. If the result of the coeffient’s calculation is zero, then the variables can be termed independent. The value of the coefficient of correlation lies in the range of +1 to -1. A value of +1 indicates a positive, perfect, increasing relationship that is linear in nature. On the other hand, a -1 figure indicates negative, perfect, decreasing relationship that is linear in nature. Values in between the range of -1 to +1 indicate the linear dependence degree. Thus, as the value nears zero correlation diminishes, whereas; a value closer to +1 or -1 indicates a correlation between variables that is stronger. Therefore, according to the given value of -0.7; I would conclude that there is indeed a strong correlation between high employee satisfaction and absenteeism. The direction of the relation is negative and indicates that as satisfaction goes low absenteeism tends to increase (Kendall, 1955).Potential problems in this research may include language barrier, unwillingness of interviewees to acts as subjects of research and obtaining of false information (IDRC, 2010). These problems would be minimized by acquiring an interpreter for cases where there is a language barrier. In the second case as the interviewer would have to highlight the importance of the research and improve on my communication skills and approach to win the confidence of the employees. This will in turn, make them speak freely and willingly. Finally, in order to avoid acquiring wrong data, I would have to counter-check with the authorities at the work place to ensure the data is genuine and up-to-date.
References
Kendall, M. G. (1955). Rank Correlation Methods, fourth edition. Chicago, IL: Charles Griffin and Company.
Shuttleworth, M. (2008). Types of Research Designs: Quasi-experimental Design. Retrieved from, http://www.experiment-resources.com/research-designs.html, on 20th May 2010.
The International Development Research center (IDRC), (2010). Overview of Data Collection Techniques. Retrieved from, http://www.idrc.ca/en/ev-56606-201-1-DO_TOPIC.html, on 20th May 2010.
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