Analyzing and Interpreting Data Essay
Analyzing and Interpreting Data
BIMS management team has been facing a major dilemma of high turnover and extremely low employee morale. BIMS management team has asked Team B to help identify the main cause of the high turnover and low morale and propose an acceptable solution that will result in a decrease of both.
Data Collection Conclusion
In the past few months we at BIMS have learned, thru the drop in employees that the company’s employee morale was dwindling. So, to help the company boosts the employees’ morale and company image, we decided as a whole in management by collecting data from those that are directly responsible for or affected by the issues, the research should lead them to some resolution to fix the problems we are facing with the turnover in employees. We gave surveys to 449 staff members. The survey collected information on attitudes, opinions, and levels of satisfaction from the staff. We used the levels used nominal, ordinal, and interval levels of measurement for the questions. 449 employees were given surveys, and only 78 turned in the survey, which was less than 18% of the employees. The surveys had flaws and they were biased, causing them to not contain enough input to implement any changes.
Summarizing and presenting conclusion
Based on the conclusions represented in the collected data of the survey used by management, the findings conclude the overwhelming dissatisfaction of a majority of the employees surveyed. This survey is based on a smaller sample of the entire employee base and represents only those that took part in the process and cannot conclude the entire impact of how all employees feel regarding their employer and how they are ultimately treated in their own minds of fairness. The data gives the management team a look into how their employees feel, what is causing them to consider leaving the company and offers an insight into what the management team can do in order to help change the perceptions of those that feel negative about any portion of the company. Most employee satisfaction surveys lend the company a well-constructed look into the pulse of their workplace and record proof of dissatisfaction throughout the company, allowing the owners or managers to fix the problems and institute productive changes in the area of concern (T. Englander, Employee Surveys, Sept. 1988). Another survey with questions as to why employees are leaving is suggested.
Upon the reviews the company has submitted another test asking employees why they are leaving. This survey allows the company to come up with a hypothesis statement and testing. A hypothesis is a statement about a population (Lind, & Marchal, 2011). The company wants to decrease turnover and improve morale. This makes our hypothesis statement if the employee turnover is decreased than the employee morale will increase. Data from the company is then used to check the reasonableness of this statement (Lind, & Marchal, 2011). The survey can identify the areas of greatest concern to the resigning employees. If we look at question 11 that asks employees the primary reason that led them to decide to quit, this could create a hypothesis statement of employees who resigned, did so because they did not like their supervisor.
Five Step Hypothesis test
The hypothesis test was performed on question 11. Question 11 asks what the primary reason for leaving the organization is. After all the responses were collected 78 out of 78 responses were gathered. Of the 78 responses the two reasons that scored the highest explaining why BIMS employees were leaving the organization was 45% answered their supervisor while 24% were not satisfied with their pay. The null hypothesis would be Ho: = 45 and the alternate would be Hα: ≠ 45. Testing mean with known variance
Type I error
P value (1tail)
P value (2tail)
The decision was to perform a hypothesis test on question 11 because this gave us the best insight as to why BIMS employees were choosing to leave the organization or had low morale. We decided to use a percentage test to calculate the responses given by BIMS employees for leaving the organization. Below you can see that each question was broken down by percentage of how each employee responded. We took the responses from each question totaled them and then divided them by the number of employees that responded which was 78. The percentages can then be put into a pie chart to create a visual impact. With the attached pie chart it gives BIMS management a clear picture of their employees feelings towards the specific questions asked. For example, most of the employees who answered the survey did not like their supervisor.
The results show patterns of dislike toward the management in place and financial incentive paid to employees. With 45% of all employees surveyed stating their immediate supervisor is not liked, Team B believes it best to introduce management training in an effort to ease the unfavorable tension from the almost half surveyed employees. With limited participation from the employee population, the group cannot strongly encourage change, because of an inconclusive response and varying degrees of discrepancies.
Team B used the statistical data obtained from the employee survey results to rule out certain attributes as to why the employees are leaving the company at a faster rate recently. The data points to dissatisfaction in pay and leadership quality. The group believes the decisions made by management have led to a higher quitting rate than ever before, while shift times were ranked very low as a reason for leaving. The survey supports evidence that suggests changes do need to be made in management, and employee departure is relevant to the decisions that have been being made over the past few months. The results also report pay structures need to be addressed, and the company must recognize and be willing to conform to industry standards as far as pay is concerned.
After processing the small amount of returned surveys completed, the analysis team concludes the returns are far too small to positively make concrete adjustments to many of the possible problems that may be causing employees to quit the company. The team recommends management training with a focus on supervisor’s morale boasting methods in order to help identify those that are not happy with the current management process that takes place. The analyst also reports a need to look into pay increases at the entry levels of the company and make adjustments in an effort to increase productivity and company morale. The team encourages the company to insert a new independent anonymous survey into every employee’s paycheck in hopes of a greater return of data needed to positively make the right changes and implement the changes to keep a happier and healthier work environment.
Lind, D., & Marchal, W. (2011). Basic statistics for business & economics (Revised/Expanded ed.). Boston. McGraw-Hill. Englander, Todd, Employee
Surveys, Incentive 1988, Sept. pg. 150