Job Satisfaction Analysis For Valero Energy Corporation Employees

Problem Definition and Analysis Method

Valero Energy Corporation is a global manufacturer and market leader of transportation fuels and other petroleum products. It is an independent petroleum refiner and producer of ethanol. The headquarter of the organization is based in San Antonio, Texas and is served by a population of approximately ten thousand employees. The refinery plants are situated in the United States, Canada and United Kingdom while the ethanol plants are situated in the mid-continent region of the United States.

Problem Definition and Analysis Method

Over the recent couple of months, Valero Energy has been faced by a major problem of deterioration among its employees. The deterioration is depicted by the low profit margins achieved by the organization, continued absenteeism among employees, high rate of resignation and inability of available workers to meet set deadlines and hence the company’s objectives. To determine the root cause and reach an amicable solution for the same, the human resource officer decided to conduct a survey to identify the satisfaction levels of the employees. Three hundred employees of the company were interviewed and their job satisfaction level measured before and after training.

The data is analyzed using statistical measures such as measures of central location (Mean, median, mode) and measures of variation (range, standard deviation, variance) to determine how factors such as age, gender, training and salary among others affect employees of job satisfaction (Hinton, 2014). To develop a better, detailed and insightful analysis, the results obtained from the data analysis are presented using tables, graphs and pie-charts (Evans and Basu, 2013).

Data Description

The data was collected from a sample of three hundred employees working globally for the organization. The data consists of thirteen variables each of which plays a crucial role in describing the employees job satisfaction. The table below shows the variables, their data types and levels of measurement.

Variable	Data Type	Level of Measurement
ID	Discrete Numeric	Nominal
Gender	Discrete Numeric (1 male, 2 female)	Nominal
Marital Status	Categorical	Nominal
Age	Numeric	Interval
Years of Experience	Numeric	Interval
City Area	Discrete Numeric	Nominal
Region	Categorical	Nominal
Department	Discrete Numeric	Nominal
Salary	Continuous numeric	Ratio
Job satisfaction before and after training	Discrete Numeric	Ordinal
Life Happiness	Discrete Numeric	Ordinal
Promoted	Categorical	Nominal

Descriptive Statistics

Measures of Location

This are single values that describe data sets by identifying the central position. They are the arithmetic mean, median and the mode (Foster, Barkus and Yavorsky, 2006). The measures of location can only be applied to numeric variables. In the dataset provided, they are applied to the variables; age, years of experience, salary, job satisfaction and life happiness score. The table below presents the measures of central tendency for the various numeric variables within the dataset.

Measures of Variation

Measures of variation describe the spread or variation of the distribution, the commonly used measures of variation are range, quartiles, variance and standard deviation (Freund, 2014). Measures of variation are also determined for the numeric variables in the dataset. The table below summarizes the measures of variation for the numeric variables in the dataset.

Data Summarizing and Presentation

The count or the frequency of single and married male individuals as well as the count of single and married female individuals sampled and working within the organization are summarized in the table below. 1 represents male while 2 represents female.

The bar chart below visualizes the distribution of single and married male and female employees respectively.

Data Description

It is evident that in the organization, there were more married female, followed by married male, single female and the least population of employees was composed of single male.

The average age, average salary and average years of experience for single and married individuals is summarized in the table below:

The married proportion of individuals had the highest average age, salary and experience when compared to the single proportion. This is visualized in the bar plot below:

The average age, average salary and average years of experience for male and female individuals is summarized in the table below:

The male proportion of individuals had the highest average age, salary and experience when compared to the female proportion. This is visualized in the bar plot below:The average job satisfaction before and after training and the score of life happiness for single and married individuals is summarized in the table below:

The married proportion of individuals had the highest average job satisfaction before and after the training as well as the average score of life happiness when compared to the single proportion. This is visualized in the bar plot below:

The average job satisfaction before and after training and the average score of life happiness for male and female individuals is summarized in the table below:The average job satisfaction before training for male is higher than that of female. However, the contrary is happens after the training. The average life happiness score for male is much higher than that of female. The results are visualized in the bar plot below:

The table below shows the satisfaction levels and the average life scores for individuals who are either promoted or not promoted.

The averages of job satisfaction before and after training and the average score of life happiness are higher for individuals who are not promoted than for the individuals who are promoted. The results are visualized in the bar plot below.

The frequency of married couples and single individuals is shown in the table below:

Using the table above and the pie chart below, it is evident that the largest proportion of individuals who are promoted are the married couples rather than the single individuals.

The frequency of male and female individuals is shown in the table below:

Using the table above and the pie chart below, it is evident that the largest proportion of individuals who are promoted are female compared to the male individuals.

Results and Recommendations

From the data analysis above, we can conclude that the biggest proportion of organization employees is composed of married couples than single individuals. Despite their large proportion, the married couples have the highest average salary, average age and average working experience.

In terms of gender, the organization is composed of more female than male. However, on average the male earn more average salary, have the highest average age and have the highest average experience compared to females. Married couples have got the highest job satisfaction before and after training and have the highest score for happiness in life. In terms of gender, male individuals have on average the highest level of job satisfaction before and after training as well as the score of happiness life. Moreover, it is clear that when an individual is trained, his/her level of job satisfaction increases significantly.

The root cause of the organization can therefore be attributed to its hiring of high number of married couples and paying them more than the single individuals. Despite their high average working experience, married couples are known of being committed in other aspects of life and therefore lack concentration for work. Additionally, the high average age associated with this highly hired proportion of individuals is a limiting factor to the organization ability to meet its objectives since high or old age is associated with low productivity and vice versa.

Another cause of the organization’s deterioration in job is promotion; the organization promotes more married couples than single individuals and more females than male. This lowers the enthusiasm of the affected group of individuals leading to their inability to be passionate about their jobs.

To counter the impact of the above problems and therefore meet the organizations objects, the organization can consider employing more single individuals with less “away from work” responsibilities, hire more youthful population since they are energetic, train the employees so that their levels of job satisfaction can be raised, devise mean to improve employees score of happiness on life, and devise new methods of job promotions that promote equality and transparency. 

References

Evans, J. R., and Basu, A. 2013. Statistics, data analysis, and decision modeling. 5^th ed. Boston: Pearson.

Foster, J. J., Barkus, E., and Yavorsky, C. 2006. Understanding and using advanced statistics. 2^nd ed. London: SAGE.

Freund, J. E. 2014. Modern elementary statistics. 12^th ed. Boston: Pearson.

Hinton, P. R. 2014. Statistics explained. 3^rd ed. London: Routledge, Taylor & Francis Group.