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 ...
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BIMS Data CollectionQNT351October 27, 2013Running.docx
1. 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
2. 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.
3. 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
4. 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_3
51/20120110
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
9. 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
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
10. 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
11. 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.
12. 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
13. 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.
14. 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
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
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
49. 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 verycareful 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.