QNT/351 University of Phoenix Material: Ballard Integrated Managed Services WEEK 3 CHART

BIMS Data Collection

QNT/351

October 27, 2013

University of Phoenix

BIMS Data Collection

Introduction

Upper management at BIMS has been attempting to understand the high rate of turnover the company has been experiencing from its employees recently. Though they were able to conduct a survey of their employees, the first attempt led to inaccurate data. By conducting the survey again, with a different structure, the management team at BIMS will be able to get the answers from their employees more accurately.

BIMS

Ballard Integrated Managed Services, Inc. (BIMS) primary purpose is to provide larger entities such as corporations and institutions with food and hospitality services. BIMS has undergone an integrative study as a way to determine the root cause of the company’s high turnover rate of employees. The management team at BIMS was unsuccessful when trying to find out the reason for the higher than usual turnover of their staff members. The first study contained multiple flaws due to data coding, entry problems and the construction of the questionnaire itself. The flaws of the questionnaire compromised the integrity of the data and therefore the results were disappointing. Although the results were disappointing, the data from the quantitative analysis provided useful tips that helped the organization to undergo a more solid subsequent quantitative analysis

The second quantitative study proved to be much more successful than the first as the database had improved. The data base consisted of descriptive and inferential statistics that was used to determine various relationships between the antecedent variables. The purpose in developing a predictive model was to allow BIMS to have a better understanding of the cause and effect relationships with regards to reasons employees were quitting. The results from the second quantitative study proved to be substantive, however, it was determined that more specific information was needed in order to correct the high turnover of employees. Due to failed attempts, a third study was conducted. The company used the qualitative approach as a part of the company’s internal employee development program. This information was more useful as it gathered data from their unsatisfied departing employees and also employees still employed by BIMS.

Types of Data Collected

Two types of data were collected: qualitative and quantitative. Quantitative data can be defined as variables measured by number. Qualitative data is information gathered that is strictly categorical (Lind, et al, 2012). BIMS collected qualitative data to address their concerns about employee morale in the workplace. This information was measured on a numerical scale of one to five. Although the data is measured on a numerical scale, the data is still considered qualitative because the numerical values are codes and cannot be meaningfully added, subtracted, multiplied, or divided. Management scaled that data into a data set (Exhibit B) to outline and pinpoint the specific areas that needed improvement. BIMS also implemented qualitative data when inquiring division being worked, gender, and position. Quantitative data included length of employment (University of Phoenix, 2012).

Level of Measurement for Each Variable

In the first 10 questions, a numerical value has been assigned to gauge the level of satisfaction from very negative (number 1) to very positive (number 5). It is assumed that if an employee chooses number two it is negative, number three is neither positive nor negative and number four is positive. These are considered ordinal levels of data and are ranked according to satisfaction. The final four questions identify nominal levels of data concerning the division that an employee works, the length of service with BIMS, gender, and whether or not the employee is a manager or supervisor.

BIMS – Coding

According to the University of Phoenix (2012), HR manager Debbie Horner used descriptive statistics to create a survey that coded qualitative data numerically, making it easier to assess. The data collected, with the exception of question 4 and letters A- D, was answered based on a scale that rated the employee’s viewpoint on the topic. One was “very negative” and progressed to numeral five for “very positive”. The data has been given a numerical value of 0 for no response. Question number 4 asked the employee how many sick days they had used in the last month. This question should have been listed separately, as it does not fall under the 1-5 emotional rating scale that applies to questions 1 through 10. Questions A-D clarify the variables for the data set. The data set has been corrected to remove any typographical errors made by Sally, the support staff member who created the data set from the survey responses. It is attached to this report. And labeled as Appendix A.

Conclusion

By completing the survey again with the new, corrected structure, upper management at BIMS was able to gather the more accurate information, and move forward towards fixing the issues causing the high employee turnover. Though the central theme remained the same, there were errors in their data collection methods that prevented the information from being accurate.

References:

Lind, D., Marchal, W., & Wathan, S. (2011). Basic statistics for business and economics (7th ed.). New York, NY: McGraw-Hill/Irwin.

University of Phoenix. (2012) University of Phoenix Material: Ballard Integrated Managed Services, Inc., Part 1. Retrieved from:

https://portal.phoenix.edu/classroom/coursematerials/qnt_351/20120110

Appendix A

Corrected Survey A Data Set

No. Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 A B C D

1 3 4 0 1 5 1 3 0 3 2 3 37 2 2

2 5 5 5 5 5 3 5 5 2 5 1 12 1 2

3 1 2 1 5 5 1 1 1 1 1 2 76 1 2

4 2 5 3 3 2 4 5 1 3 4 2 3 2 1

5 4 4 5 1 4 1 3 3 2 4 2 16 1 2

6 5 2 5 4 3 3 2 1 2 1 1 52 1 2

7 0 1 4 5 3 2 5 4 2 1 1 8 2 2

8 1 3 2 2 5 2 4 5 3 2 2 28 0 2

9 3 3 1 4 4 2 2 2 2 4 3 15 2 1

10 5 1 3 2 2 2 1 4 1 1 1 83 2 2

11 5 4 3 3 1 3 3 2 2 1 2 21 1 1

12 4 5 1 3 3 2 3 3 3 2 1 216 2 2

13 2 2 4 0 3 3 1 3 3 3 1 27 1 1

14 1 4 5 5 1 3 4 0 2 1 2 5 1 2

15 3 2 2 4 4 0 5 5 3 4 3 27 2 2

16 3 3 4 1 5 2 2 4 4 5 2 16 2 2

17 1 3 2 1 2 3 4 1 2 2 1 4 1 2

18 4 0 3 2 4 1 2 1 1 4 2 58 2 2

19 5 5 3 5 2 1 3 2 3 2 1 108 0 1

20 2 4 2 1 3 2 3 5 3 3 2 82 2 2

21 4 1 5 5 4 3 5 2 1 3 1 43 2 2

22 2 1 4 2 2 1 5 4 3 0 0 14 1 0

23 3 2 1 3 5 4 4 2 2 5 2 96 1 2

24 3 5 1 2 4 2 1 3 2 4 2 251 2 2

25 2 1 2 2 1 3 1 2 4 1 3 87 1 1

26 5 4 5 3 1 2 2 2 2 1 1 15 1 2

27 4 2 1 5 2 2 5 3 3 2 2 7 2 2

28 1 3 4 4 5 3 1 5 3 5 2 36 2 2

29 1 2 2 4 1 2 4 4 2 1 1 139 1 2

30 2 2 3 2 4 1 2 4 1 4 1 47 2 0

31 5 3 2 2 2 4 3 2 4 2 2 14 2 2

32 1 5 2 3 3 2 2 2 1 3 1 9 2 2

33 4 4 3 1 2 2 2 3 1 2 3 7 1 2

34 2 4 5 1 2 3 3 1 2 2 2 116 2 2

35 3 2 4 2 3 1 5 1 3 3 1 73 2 1

36 2 2 4 5 5 1 4 2 1 5 1 157 1 2

37 2 3 2 4 4 2 4 5 3 4 2 14 2 2

38 3 1 2 2 4 1 2 4 2 4 1 2 1 2

39 5 1 3 1 2 3 2 2 3 2 2 69 2 2

40 4 2 1 0 2 2 3 1 2 2 1 14 2 1

41 4 5 1 3 3 1 1 0 2 3 2 67 2 2

42 2 4 2 2 1 0 1 3 3 1 2 44 1 2

43 2 2 5 1 1 3 2 2 2 1 1 60 2 2

44 3 1 4 4 2 2 5 1 4 2 1 8 2 1

45 1 0 2 3 5 1 4 4 2 5 2 57 2 2

46 1 3 1 2 4 1 2 3 2 4 2 277 1 2

47 2 2 5 5 2 3 1 2 2 2 1 328 2 2

48 5 1 3 3 1 2 5 5 3 1 2 57 2 2

49 4 4 2 2 5 2 3 3 1 0 1 97 1 2

50 2 3 1 1 3 3 2 2 1 3 2 54 2 2

51 1 2 4 4 2 2 1 1 2 2 3 17 2 2

52 5 5 3 4 1 1 4 4 3 1 1 6 2 2

53 3 3 2 1 4 2 3 4 2 4 2 209 1 2

54 2 2 5 2 3 4 2 1 2 3 1 96 2 2

55 1 1 3 5 2 1 5 2 1 2 1 5 2 1

56 4 4 2 2 5 2 3 5 3 5 2 6 2 2

57 3 4 1 3 3 2 2 2 3 3 2 12 2 2

58 2 1 4 3 2 2 1 3 2 2 1 4 2 2

59 5 2 4 2 1 3 4 3 1 1 2 7 2 2

60 3 5 1 3 0 3 4 2 1 4 3 19 1 2

61 2 2 2 2 4 2 1 3 3 4 2 119 2 2

62 1 3 5 1 1 3 2 2 2 1 1 53 2 2

63 4 3 2 4 2 2 5 1 2 2 2 22 2 1

64 4 2 3 5 5 1 2 4 3 5 1 14 2 2

65 1 3 3 2 2 4 3 5 2 2 2 23 1 2

66 2 2 2 1 3 1 3 2 1 3 1 7 2 2

67 5 1 3 5 3 2 2 1 2 3 1 5 2 2

68 2 4 2 2 2 1 3 5 4 2 2 9 1 2

69 3 5 1 0 3 3 2 2 1 3 2 19 2 2

70 3 2 4 4 2 2 1 0 2 2 3 18 1 2

71 2 1 5 5 1 0 4 4 2 1 2 57 1 2

72 3 5 2 1 4 3 5 5 2 4 2 49 2 2

73 2 2 1 2 5 2 2 1 3 5 1 61 1 2

74 1 0 4 4 2 1 1 2 3 2 1 11 2 2

75 4 4 5 5 1 2 4 4 2 1 2 90 2 1

76 5 5 2 1 4 2 5 5 3 5 3 47 1 2

77 2 1 1 2 5 4 2 1 1 2 1 63 1 2

78 1 2 3 5 2 1 1 2 1 4 2 10 2 2