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Resource: University of Phoenix Material: Ballard Integrated Managed Services, Inc., Part 2. (Down here)
Read the University of Phoenix Material: Ballard Integrated Managed Services, Inc., Part 2. Your team acts as a consultant group that analyzes and interprets this second set of data. The intent is to increase senior management’s understanding of the sources of employee dissatisfaction and to create a model that predicts employee resignation. Write 300-350 words On how you will increase senior management’s understanding of the sources of employee dissatisfaction .
Ballard Integrated Managed Services, Inc., Part 2 QNT/351 Version 4 |
University of Phoenix Material
Ballard Integrated Managed Services, Inc., Part 2
The initial survey effort led by Debbie Horner, HR manager of Ballard Integrated Managed Services, Inc. (BIMS), did not produce useful findings. The survey had several flaws that made the majority of the results questionable. Some items were biased. A few questions were worded awkwardly, likely affecting the response. Some of the information needed was not asked, further reducing the value of the effort. Additionally, the data entry typist and general office support person made a number of errors when keying the data into the spreadsheet, compounding the poor results.
In hindsight, Debbie suggested that she should have pretested the sample instrument before issuing it to the workforce. Such a step would have likely revealed many of these problems. Further, to improve the 17.3% response rate, she should have taken different steps to encourage employee participation. Just inserting it into the payroll process did not inform employees sufficiently about the purpose and sponsor of the survey. Advance information to explain the need for gathering their views, as well as reassurances about confidentiality and anonymity,plus descriptions of how the information would be used are among the many steps that Debbie might have taken to increase the response rate.
Knowing that Barbara Tucker, general manager of the BIMS operation at the Douglas Medical Center, and the rest of the top management team were disappointed in the findings, Debbie proposed that she create a second, improved survey effort that was better planned and marketed. Although somewhat reluctant to authorize the effort for fear of creating more damage, Barbara approved the request. She felt the need to understand the current employee dissatisfaction and increased turnover rate was urgent and thus merited the continued effort.
Learning from the initial effort, Debbie designedanother survey instrument. This time she circulated it among the senior management team, inviting each person to complete the survey, reading for comprehension and flow of the actual wording, as well as for completeness. A number of suggestions were made in terms of question phrasing as well as about adding new items. These ideas were incorporated into the survey design. The revised instrument was again circulated among the same group of senior managers. The group’s consensus was that the revised instrument was complete and ready to administer.
To ensure the instrument was easily understood from the employee perspective, Debbie solicited five craft workers to voluntarily pretest it as well. These five were all on noncritical medical leave, so they were able to comfortably conduct the review. Additionally, as they were currently on leave, none would be in the actual surveyed population when the study instrument was issued later that month. Each of the five had minor phrasing suggestions that Debbie incorporated. Finally, Debbie sent this last version to the senior management team for final review. It was approved unanimously (see Exhibit C for this second data collection instrument).
Then, Debbie had a sudden thought. Why interview current employees about why they might quit and about their level of satisfaction? Perhaps she should be surveying those that had already left the organization. By asking them, “Why?” she might learn more about who would quit in the future. She might be able to develop a model for predicting voluntary terminations. This indeed would be an important contribution to the company.
With this in mind, Debbie decided that her next study population would be those who voluntarily left their employment with BIMS. Given the higher than normal,and unfortunate, turnover rate, Debbie was certain that she would be able to collect the data over the next 2 to 3 months. She would ask those departing to complete the survey during their exit interview with her office. Usually the exit interview was conducted by the immediate supervisor, but given the nature of this effort, Debbie felt that her staff should assume that responsibility on a temporary basis—just for the few months that were required to accumulate 75 to 80 completed surveys. After that time, the task of conducting the exit interview would revert to the immediate supervisor.
Debbie’s goal was to use the data to create a regression statement that could be used to predict future resignations. She also intended to use the information to identify the areas of greatest concern to the resigning employees; therefore, both descriptive statistics and frequencies were to be calculated. As the goal was to reduce employee turnover and improve morale, these key areas would become the center of attention for future internal HR development programs.
Once again, Barbara Tucker has asked your Learning Team to act as consultants who analyze and interpret this second set of data. As described by Debbie, the intent is to increase senior management’s understanding of the sources of employee dissatisfaction and to possibly create a model that predicts employee resignation. As before, Barbara asks that your team prepare a 1,050- to 1,750-word written report along with a 7– to 9-slide Microsoft®PowerPoint® presentation for the senior management team that presents your findings (see Exhibit D for the data set of this second survey).
Exhibit C
BIMS Exit Interview 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 (you strongly agree with the statement) and 1 is a very negative choice (you do not agree at all with the statement).
Do Not Agree Neutral Strongly Agree
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1. You are well trained for your work.
2. The company provided the needed training.
3. You were fairly paid for the work you did.
4. You were given as many hours that you desired.
5. Your supervisor treated you fairly.
6. Your manager treated your division fairly.
7. The company is good at communicating.
8. Your job was secure.
9. You liked working at this location.
10. Getting to and from work was easy.
11. What was the PRIMARY reason that led you to decide to quit? (Select only one.)
A. In which division didyou work?
B. How long have you worked for BIMS?
C. What is your gender?
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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
A. I do not like the work. B. I do not like my supervisor. C. I am not satisfied with the pay. D. I am not satisfied with my shift. E. Other: ____________________
Food: _ Housekeeping: _ Maintenance: _
Years: _____ Months: _____
Female: _____ Male: _____ |
Exhibit D
Survey B Data Set
No.Q1Q2Q3Q4Q5Q6Q7Q8Q9Q10Q11ABC
1335513432223142
223435244251161
3222213111122222
4421335513432182
533323435244232
632331241213151
753134521422172
843435412251232
923522235345312
1012234345514151
1133412234352262
1231213534342122
13113232123311141
144233544123321011
15535155533523152
16215445234412452
1743352412122141
1822345214223282
1933124122532112
2042252353432222
2125533455111142
2224122343541341
2352142445252262
24412252122212252
2523534314441381
2634551223222161
2723435553333272
2813445515343292
294224124422211871
30223244221521112
3133222331443252
3233551343212192
3323435244212371
3425512431222282
35354532543511102
36224551451131131
3724224342342252
3833244324221121
39533321223322152
4045132433223152
41441535142332132
4222241212312281
43215214252111612
4433412254422182
45132353412532122
461134551343222711
47242343524421132
48553453553122122
49422534311311162
5024121344133291
5112135242222381
5253525533315162
53345531142422112
54223124112331511
5515241222121152
5644124335351262
5731433422332232
5822412131223142
5955214214112272
60341225151433101
61323534212422112
6223455132222182
6342343521533242
6443321333341152
6513334422222251
6622215513153172
6751352143442152
6824222135311291
69351333222122101
70324241215233182
71215521423542122
72352412252132132
7322123534142172
7413434551421122
7544523435435291
76552142551323112
7721125421221192
78123521125122102
