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This is my assignment for week 3 on my learning team. My part is to create a
with explanation. \
Analyze the data included in BIMS case study Part 1 by computing descriptive statistics in the form of
s, charts, measures of central tendency, and
.
Prepare a 1,050- to 1,750-word report of conclusions drawn from the data and make recommendations to the management.
Support recommendations by citing literature consistent with APA guidelines.
There are four areas which include computing descriptive statistics as well as intro/conclusion/compile:
- tablechart
- measure of central tendency
variability
This is in reference to the week two paper you completed for me.
Ballard Integrated Managed Services, Inc., Part 1
QNT/351 Version 3
2
University of Phoenix Material
Ballard Integrated Managed Services, Inc., Part 1
Barbara Tucker looked out her 6th floor office window to view the sprawling campus of the Douglas Medical Center (DMC). Her employer, Ballard Integrated Managed Services, Inc. (BIMS), provided food and hospitality services on a contractual basis for all patient and staff needs. As general manager of this site for BIMS, Barbara was concerned about her staff’s morale. She felt that it had been weakening over the past several months, but she could not figure out why. The turnover rate seemed somewhat higher than usual, but no new information was emerging from exit interviews. Her department heads and supervisors agreed that something was happening to morale, but they could not tell her why either.
Headquartered in New York City, BIMS is a support services company that specializes in providing housekeeping and foodservice to corporations and institutions. A nationwide company, BIMS contracts with large organizations that prefer to focus on their own core competencies and lease support functions to outside vendors. BIMS distinguishes itself in this highly competitive industry by combining several services: housekeeping, foodservice, general cleaning, and physical plant maintenance. The BIMS list of clientele includes 22 Fortune 100 businesses, over 100 midsized firms, 16 major universities, 14 medical centers, and 3 larger regional airports.
Located in a major metropolitan area, the contract for this 510-bed regional medical trauma center includes the full range of BIMS services. Four months ago, the two firms had completed negotiations to renew their contract, extending the initial 3-year, just-ended arrangement for 5 more years. The Douglas Medical Center had been very pleased with BIMS’s work to date and had been willing to renew under the same terms and conditions. The BIMS corporate headquarters had also been satisfied with Barbara Tucker’s management of this site and her successful efforts to renew the DMC contract.
As general manager, Barbara is responsible for three divisions at this site, each with its own management staff. The food service division, led by Flora Torres, is responsible for providing daily meals for the 5,300 staff members, nurses, and doctors as well as the general public in the six cafeterias. In addition, they prepare specialized meals for patient care. In this division there are 182 full-time equivalent positions; however, given the nature of the work, only 129 of those positions are actually full-time. An additional 106 part-time workers are currently scheduled to address the variable needs of this 24-hour operation. Twelve professional staff members help Flora manage this group of 235 craft workers.
The hospitality division, managed by Henry Dumas, is responsible for refreshing each hospital room, including changing the linens on empty beds, replacing towels, and sanitizing bathrooms, which includes maintaining the public areas: hallways, lobbies, elevators, and so on. The hospitality staff comprises 76 full-time workers, 28 part-time workers, and 10 supervisors who provide 18-hour service. In addition, a full-time skeleton crew of 10 workers and 1 supervisor handle any unplanned nighttime demands on all 7 nights of the week. Altogether, Henry manages this department of 114 craft workers and 11 supervisors.
The Physical Plant Maintenance division, led by Matt Lee, is responsible for all of the nonmedical equipment and physical aspects of the medical center. His full-time staff of 56 workers provides daily custodial services to areas not handled by hospitality, such as laboratories, offices, reception areas, clinics, and others. They clean, repair, or replace carpets, window blinds, wallboard, light fixtures; and service elevators and other nonmedical equipment such as beds, chairs, carts, stands, and tables. To provide off-hour service, four additional employees cover the evening shift and graveyard hours each week. Based on experience, this minimal coverage has proven adequate. Four supervisors help Matt manage this physical plant group. Altogether, BIMS employs 409 full- and part-time workers and 27 managers or supervisors in these three divisions, Along with Barbara, the three division managers form the top management team at this BIMS site. Including the 12-member office support staff—HRM, bookkeeping, and clerical support—the BIMS staff total is 452 workers.
Considering the low-skill nature of the majority of positions, BIMS typically experiences an annual turnover rate of 55 to 60% at this location. This rate is common for the industry in general and typical for BIMS in particular. However, during the past 4 months the rate has climbed to over 64%. Replacing the workers is not a particular challenge, as the area labor pool is sufficient; however, the increased cost of this activity is troublesome. Additionally, managers and supervisors do not understand why the rate has increased. Workers are providing the familiar response for leaving, not revealing any new information. The increase in the turnover rate remains a puzzle.
Whatever the cause of the higher turnover rate, a general malaise has settled over the staff. Use of sick time has increased. A large number of workers appear to waste time throughout the day. Their work has become poor, resulting in an increase in complaints from the hospital administration. After discussing the issue with the three division managers and HRM staff, Barbara has approved their suggestion of surveying the workers in an attempt to identify the root cause of their decrease in morale.
Debbie Horner, the HR manger at this site, originally made the survey suggestion to the senior management team. It has been about 2 years since she completed her MBA, and Debbie is excited about the opportunity to apply some of the research ideas she learned during her program. Debbie’s thesis concentrated on employee motivation, so she feels well prepared to tackle this current problem. Because of her background and education, Barbara has agreed to assign the leadership of this project to Debbie.
Drawing from her school experience, Debbie developed an employee survey instrument (see Exhibit A). She decided to administer the survey to all 449 employees; the top management team is excluded. Although responding will be voluntary and anonymous, the survey will be delivered with the biweekly payroll checks to ensure that each worker receives one.
The questions Debbie created asked workers to express their view about working conditions, shift hours, quality of training, level of compensation, fair treatment, internal company communications, and job security. A few demographics were also to be collected so that Debbie could separate responses by division. Her intent is to compute descriptive and frequency techniques, and then further study the data for possible correlations. The survey was initially sent out two pay periods ago, and a reminder message was provided with the last paycheck. A total of 78 responses have been received, which is about a 17.3% response rate. Debbie was somewhat disappointed at this rate but recalled from her studies that this lower percentage was common for a survey. She decided that additional efforts to encourage participating would be unlikely to generate many more useable responses.
The raw data has been coded and entered into a spreadsheet titled Survey A Data Set by Debbie’s office support staff (see Exhibit B). Your Learning Team acts as a consulting group to the top management team. General manager Barbara Tucker has asked your team to analyze the data—including making sure it is useful, valid data—interpret it, and then prepare a 5- to 7-slide Microsoft® PowerPoint® slideshow to present the results (see Exhibit B for the data set details). She has also requested a 1,050- to 1,750-word written report to accompany the slideshow that details the team’s findings.
Exhibit A
BIMS Employee Survey
Using the scale provided, record your answer by circling the number that is closest to your view where 5 is a very positive response and 1 is a very negative choice.
Very Negative Very Positive
|
1. How well do you enjoy working for BIMS? 2. You enjoy your assigned shift. 3. Your request for your desired shift was fulfilled. 4. How many times have you called in sick in the last month? 5. You are well trained for your work. 6. You are paid fairly for the work you do. 7. Your supervisor treats you fairly. 8. Your supervisor’s boss treats your division fairly. 9. The company is good at communicating. 10. You do not fear that you will lose your job. A. In which division do you work? B. How long have you worked for BIMS? C. What is your gender? D. Are you a manager or supervisor? |
1 2 3 4 5 1 2 3 4 5 Food: _ Housekeeping: _ Maintenance: _ Years: _____ Months: _____ Female: _____ Male: _____ Yes: _____ No: _____ |
Exhibit B
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
6
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
6
3
2
2
1
2
3
1
5
2
2
68
2
4
2
2
2
1
3
6
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
6
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
6
3
47
1
2
77
2
1
1
2
5
4
2
1
1
2
1
63
1
2
78
1
2
3
6
2
1
1
2
1
4
2
10
2
2
Sally, the office support staff member in charge of data entry, made a decision when she was entering the data: For any missing data, she would enter a 0. She felt that would best represent any questions that people failed to answer. She also has a bad habit of typing 6 when she means 5. However, she was very careful when entering an employee’s length of service. She did not make any errors in that column when she converted the years and months into just total months.
BIMS Data Collection
QNT/351
October 27, 2013
Running head: BIMS DATA COLLECTION
1
BIMS DATA COLLECTION
9
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
