Data Collection

QNT/351

July 10, 2014

There are many times when companies have to collect data to come to a conclusion about an issue. The data may be collected from their employers, their competition or their consumers. BIMS saw that there had been an average turnover that was larger then what the company had seen in the past. Human Resources decided that they would conduct a survey to see what had changed in the company from the employee’s point of view. They attached each survey to the pay checks to ensure that each person received one, and waited for the response. Overview of the Situation The issue presented by BIMS employee turnover was a problem because when a company has a high turnover they put more money into the hiring and training process of new employees. The purpose was to understand what had happened in the last four months that had causes the increase in turnovers. The research questions were based on employee satisfaction within their departments. The data collected was going to be used to aide in the hypothesis that the turnover rate had increased because employee’s morals had decreased ("Develop A Research Proposal", 2014).
The Types of Data and How They Were Collected

The data that was conducted in the BIMS, Inc. was an employee evaluation, which consisted of both quantitative and qualitative statistics. By giving employees self-assessment will help them provide the necessary information that BIMS is observing for about the staffs of their organization. The survey entails ten questions which the answers can be replied in quantitative method. There are also four extra questions that are offered in qualitative form. Those questions ask things such as gender, employee rank, work division, and length of employment. The data that was collected will allow BIMS to see how their employees are from either a quantitative or qualitative stand point. BIMS will collect the data and show the percentage of what employee score was on each individual survey.
The Instrument Used for Data Collection

The instrument that was used for data collection for Ballard Integrated Managed Systems is that the Human Resource manager Debbie Horner has established an employee assessment instrument that can help the business find their core cause of their problem. The questions will consist of a variety of things that is correlated to working environments, job safety, training superiority and shift hours. Another part of the analysis is composed of various inquiries that is linked to department worked in, length of time employed at BIMS, the job title of the employee and gender. The data that is gathered on the employee survey is both qualitative and quantitative.

Clean Data

In order to provide the leaders of BIMS with accurate results; the data must be cleaned to eliminate the data input errors made. Any error that is identified within the data are for people whose response had unsuccessful results to a question within the survey. The decision to enter in a zero for the questions that were left blank was an internal decision. There are quite a few of these errors within the sample data. The areas these errors can be found in would be the demographics in which there were five zeros. Also in questions one through ten; seventeen zeros can be found. In addition to these errors, another error in the data that resulted from a keystroke error which caused an invalid value of six that is shown in questions one through ten. The appropriate survey response for questions one through ten should show a value of 1,2,3,4,5 with ‘1’ representing ‘Very Negative’ and ‘5’ representing ‘Very Positive’—there are six occurrences of this error (University of Phoenix, 2011, BIMS, Inc. Part I).

Final Analysis

The appropriateness of the data to meet the purpose of the study was to present BIMS leadership with a voluntary survey to all four hundred and forty nine employees. They were concerned about the morality of their employees and needed a statistical analysis they would be able to rely on. In order to filter appropriately there were minor amounts of demographics included. Overall, the survey method was not as effective and yielded below average result with just 78 responses out of the 449 employee population—17.3% overall response rate (University of Phoenix, 2011, BIMS, Inc. Part I).

Level of measurement for each of the variables

As a result of ten questions possessing a one to five scale, they can be identified as an ordinal level of measurement. This should not be mistaken as a solution, instead recognized as a degree of significance. It should be noted, that various levels of measurement require diversified method of measuring statistically data.

Levels of measurement for questions A., C., and D., fall in the category of nominal. This particular set of questions is qualitative and has potential to be posed in any sequence. The inquiry of the employees is to acknowledge whether they are male or female, supervisor, manager, and the department they report to. Implemented in Question B; this is a question that involves a zero value. It wants to know the length of time one was employed with BIMS. The question holds a present value of zero, but it is not possible for time of employment to be recorded with a negative integer it is a ratio level. It was found that the company adjusted every employee’s services into strictly months.

Data Coding

The data collected in the survey is numerically coded on the ordinal level, nominal level, and ratio level. The first column displays a total of 78 participants in numerical order and the second column has ten questions in the survey. The response rate of the survey was not good and shared qualitative and quantitative data.

The question rating scales are quantitative and the department and gender related questions represent qualitative data (Roberts, 1998). The questions regarding gender and department are qualitative. Question B wanted to know length of time employed at BIMS which makes it on a ratio level since it has numerical characters and zero is used if the if response is not marked. The company was attempting to assess why morale was low amongst employees.

In Conclusion, BIMS did not receive enough surveys back to come to an accurate conclusion. With only 17.3% of the employees returning their surveys, BIMS hypothesis is inconclusive. It can be said that if the 17.3% is satisfied then all employees are satisfied because only the percent received can be used in the research. However, the other percentage of employees who did not participate are equally important because they still count in the overall findings of employee turnovers. Unfortunately BIMS may need to come up with another way to get 100% employee involvement so that they may come to a complete conclusion about the moral of their employees.

References

Develop a Research Proposal. (2014). Retrieved from http://bcps.org

Roberts, D. (1998). Qualitative vs Quantitative Data. Retrieved from http://regentsprep.org

University of Phoenix. (2014). Ballard Integrated Managed Services, Inc., Part 1. Retrieved from University of Phoenix, QNT/351 website.