QNT 351 BIMS Research Study

Name: QNT 351 BIMS Research Study
Brand: University of Phoenix
Price: 2 USD
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Author: William Chen

This assignment presents a statistical evaluation of the BIMS research study, focusing on data-driven decision-making.

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Running head: BIMS RESEARCH STUDY 1
BIMS Research Study
Name
QNT 351
date
Instructor
Analyze the BIMS Research Study report, focusing on the research methodology, data analysis,
and hypothesis testing used to investigate employee turnover and morale issues at the Douglas
Medical Center site. In your analysis, evaluate the effectiveness of the survey design, the validity
of the conclusions drawn, and provide recommendations for improving employee retention. Your
response should be between 1,500 to 2,000 words, supported by relevant statistical concepts and
references.

BIMS RESEARCH STUDY 2
BIMS Research Study
Background and Purpose
Headquartered in New York City, The Ballard Integrated Managed Services (BIMS) is a
support service company that specializes in providing housekeeping and food services to many
corporations and institutions to include 22 Fortune-100 businesses. The focus of the research is
the BIMS site at Douglas Medical Center (BIMS-DMC). The problem BIMS is facing is to
determine the cause for the decrease in worker productivity and morale, which resulted in an
increase in complaints from the hospital staff and administration (University of Phoenix, 2012
part 1).
The purpose of the survey is for BIMS-DMC (hereafter called BIMS) employees to
express their view about their job and to compute descriptive and frequency techniques and
further study data for possible correlations. The research questions ask if respondents enjoy
working for BIMS, how many times they called in sick, if they are well trained, if they are paid
fairly, and if they like their supervisor. This (survey 2) was the second attempt to complete a
survey to satisfy research efforts. The initial survey by BIMS HR personnel did not produce
useful findings. The initial sample instrument (survey) had several flaws that made the majority
of the results questionable. The initial survey contained biased items and awkwardly worded
questions, was missing critical questions, was plagued by data entry errors and was never
validated by pretest. Further, to improve the dismal 17.3% response rate of survey 1, HR
personnel gave advance information about the purpose and sponsor of the survey, need for
gathering employee views, reassurances about confidentiality and anonymity, plus descriptions
of how the information would be used (University of Phoenix, 2012 part 2). After pretesting (on

BIMS RESEARCH STUDY 3
management and a small worker control group), refinement, and finalization, survey 2 was
issued to BIMS employees.
The survey goal was to reduce employee turnover and improve morale, so BIMS’ HR
manager decided to issue Survey 2 to former employees during exit interviews. This would
allow HR interviewers to use both descriptive statistics and frequencies by using the data to
predict future resignations and to identify areas of greatest concern to the resigning employees.
Both quantitative data and qualitative data are collected in the BIMS survey, although most data
is qualitative because of the nature of the company’s main concerns. BIMS then scaled the
survey data so managers could troubleshoot the morale and productivity issues. Again, only 78
respondents comprise the sample that represents the 449 employees (minus management staff) of
BIMS-DMC, although they represented the exiting population instead of current employees.
Survey 2 Construct
The survey contained 10 statements (S1-S10) to gauge perception and job satisfaction,
one question (Q11) to determine the respondent’s reason for quitting the job, and three questions
(QA-QC) to gather demographic information (University of Phoenix, 2012 part 2). The
responses for questions 1-10 are ordinal-level data. The respondents provide an answer on a
scale of 1–5. A response of 1 represents “Do Not Agree,” 3 indicates a neutral response, and 5
represents “Strongly Agree.” The data is considered ordinal-level data because a rating of 5 does
not indicate the respondent agrees 5 times more strongly than a rating of 1. Question 11 is
answered at the nominal level because the ratings of A, B, C, D, and E represent a written
description of why the respondent left the company. Responses to demographic question A are
at the nominal level because the respondent indicates which of three divisions for the respondent

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University of Phoenix

Subject

Statistics

QNT 351 BIMS Research Study

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