| Course | MAN-6300 Management Capstone |
|---|---|
| Module | Module 3 |
| Paper type | Written assignment 3: data analysis and evidence-based findings |
| Length | About 1,016 words, 6 pages |
| Format | APA 7 student paper |
| School | Thomas Edison State University |
| Program | Master of Science in Management |
| Updated | October 2026 |
Free sample paper for MAN 6300 Module 3
Where the Silence Sits: Survey, Turnover, Deviation and Interview Data From a Contract Drug Manufacturer, Coded and Counted
Student Name
Master of Science in Management, Thomas Edison State University
MAN-6300: Management Capstone
Mentor Name
Month Day, Year
Where the Silence Sits: Survey, Turnover, Deviation and Interview Data From a Contract Drug Manufacturer, Coded and Counted
Module 1 defined the problem at the composite Somerset County drug manufacturer Millstone Pharma Services as a post-acquisition decline in employees' willingness to raise quality concerns promptly, and Module 2 confirmed from the research that such a decline is a recognized and costly pattern. This assignment analyzes the site's own data to establish where the problem is concentrated, what is associated with it, what it costs and what the acquisition has improved. Four sources were used: the 2026 employee survey, human resources turnover records, the quality system's deviation log for January to August 2026, and eighteen confidential interviews.
Methods
The survey was completed by 312 of 480 employees, a 65 percent response rate. I analyzed the item on raising quality concerns without fear as the main outcome, reporting the percentage who agreed or strongly agreed, and computed correlations between it and three other measures: a three-item index of supervisor openness, perceived workload and length of service. Turnover and deviation figures came from system reports, with costs estimated from finance and HR records.
For the qualitative strand, I conducted eighteen semi-structured interviews of thirty to forty-five minutes with operators, quality staff, supervisors and engineers from all three shifts. Participants gave consent, names were removed, and recordings were deleted after transcription. I coded transcripts in two cycles, first openly and then into a codebook of eight codes grouped into themes, following established guidance on thematic analysis and coding cycles (Braun & Clarke, 2006; Saldaña, 2021). An HR business partner independently coded six transcripts with the same codebook, and we agreed on 84 percent of code assignments before discussing the differences.
Quantitative Findings
Agreement with the speaking-up item was 41 percent overall, but it varied sharply. By department, it was lowest in quality assurance and quality control, at 29 percent, compared with 46 percent in production, 44 percent in the warehouse and 52 percent in maintenance and engineering. By shift it fell from 49 percent on days to 38 percent on evenings and 31 percent on nights.
| Group | Agree they can raise concerns | Voluntary turnover (12 months) | Share of late-reported deviations |
|---|---|---|---|
| Quality assurance and control | 29% | 31% | n/a (they receive reports) |
| Production | 46% | 22% | 71% of late reports |
| Maintenance and engineering | 52% | 14% | 18% of late reports |
| Warehouse | 44% | 19% | 11% of late reports |
| Night shift (all departments) | 31% | 27% | 45% of late reports |
Among the correlations, supervisor openness was most closely associated with the outcome (r = 0.58), well ahead of workload (r = 0.31). Length of service had a small negative association (r = -0.12), meaning long-serving staff, who remember the old culture, were slightly less likely to feel safe. These are associations in a single survey and do not prove causation, but they match the research on leader openness reviewed in Module 2 (Detert & Burris, 2007).
Deviations rose from about 103 in 2023, when the site produced some 2,700 batches, to an annualized 176 on about 2,880 batches in 2026. Each investigation takes an average of twenty-two hours of quality staff time at a loaded cost of $68 an hour, so investigation labor alone grew from about $154,000 to $263,000 a year, before counting rework or rejected batches. Twenty-three of the seventy-four quality staff left in the past twelve months; at an estimated replacement cost of $38,000 each for recruiting and six months of training, that turnover cost about $874,000.
The acquisition's gains are also real. Overall equipment effectiveness rose from 58 to 66 percent, and output per labor hour increased 9 percent, largely because of the new compression suites and better maintenance planning. Any recommendation should protect these gains.
Qualitative Findings
Six themes emerged from the interviews. The most frequent was numbers over quality, raised in fourteen of eighteen interviews: participants described the morning meeting, the color-coded boards and the supervisors' output bonus as signals that output mattered most. Fear of blame for stopping the line appeared in twelve interviews, often with examples of supervisors asking "Can this wait until tomorrow?" Eleven participants said that a supervisor's reaction depended on how the day's numbers looked, which made speaking up feel like a gamble. Nine described the loss of familiar colleagues and the relationships that once made it easy to ask for help. Eight said that the parent company's stated values seemed sincere but were not lived on the floor.
The sixth theme was positive and appeared in ten interviews: appreciation for new equipment, training and clearer procedures. Several participants said they did not want the old, slower Millstone back; they wanted the new one to listen.
Evidence-Based Findings
Integrating both strands produces four findings. First, the problem is concentrated: it is most severe in quality functions and on the night shift, where speaking-up scores are lowest, turnover is highest and nearly half of late reports originate. Second, supervisor behavior is the strongest identifiable factor, both in the survey correlation and in the interview theme of reactions that vary with the day's numbers. Third, the incentive and measurement system sends a message that contradicts the espoused value of quality first; employees read the output bonus and the color-coded boards as the real priorities. Fourth, the problem has a measurable cost, about $1.1 million a year in investigation labor growth and quality-staff turnover, plus regulatory and client risk that is harder to price, while the productivity gains of the acquisition are worth preserving.
These findings answer the second research question from Module 1 and set up the third: the recommendations in Module 4 must change supervisor behavior and the reward system, focus first on quality functions and the night shift, and keep the productivity improvements.
Limitations
The survey is cross-sectional, and the 2023 comparison came from a different instrument used by the former owner. The interview sample is small and was chosen to cover departments and shifts rather than at random. The cost estimates rely on averages. These limits argue for treating the findings as strong indications to be monitored as changes are made, not as final proof.
References
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77-101. https://doi.org/10.1191/1478088706qp063oa
Detert, J. R., & Burris, E. R. (2007). Leadership behavior and employee voice: Is the door really open? Academy of Management Journal, 50(4), 869-884. https://doi.org/10.5465/amj.2007.26279183
Saldaña, J. (2021). The coding manual for qualitative researchers (4th ed.). SAGE.
What the MAN 6300 Module 3 instructions ask for
In MAN-6300, Module 3 is devoted to data analysis and evidence-based findings, linked to the objectives on evaluating human capital productivity and organizational performance through quantitative analysis and qualitative coding, and on preparing recommendations that weigh legal, money and people consequences. The written assignment asks you to analyze data from your organization, so plan collection early and get permission for surveys or interviews. Report your methods in enough detail for a reader to judge them, and present findings that answer the research questions you set in Module 1. Plan to present at least one table, since numbers grouped by department or shift reveal patterns that totals hide. Protect participants' privacy in everything you report.
How this MAN 6300 Module 3 example is built
The paper restates the problem and research, then explains four data sources and the methods for each, including response rate, outcome measure, correlations, interview procedure, coding cycles and a second-coder check. Quantitative results are shown by department and shift in one table and interpreted with appropriate caution about correlation. Costs are calculated from stated assumptions, and productivity gains are reported honestly. Interview themes are counted and illustrated, and the integration produces four numbered findings that point directly to the recommendations. Limitations are stated plainly at the end, so the findings claim no more than the data can support. Quotations are short and chosen to illustrate a theme, not to stand in for analysis.
Where the marks sit in the MAN 6300 Module 3 rubric
Each MAN-6300 written assignment earns a grade between 0 and 100. In this module mentors look for sound use of both quantitative and qualitative methods, findings that follow from the data rather than from assumptions, and clear links to the problem statement and literature. Transparency about methods, sample, ethics and limitations is expected at the graduate level. Tables, cost estimates with stated assumptions, and themes supported by counts and quotations strengthen the paper, along with professional writing and APA style. A short limitations section, written honestly, is a mark of graduate-level analysis rather than a weakness. Linking each finding back to a research question shows the mentor that the capstone is building as planned.
MAN 6300 Module 3 help: mistakes that cost marks
Students often present data without saying how it was collected, or report correlations as if they proved causes. Qualitative sections commonly list quotations without a codebook or any check on the coding. Another frequent problem is reporting only data that supports the expected conclusion; including improvements or contrary evidence makes the findings more persuasive. Get consent and protect confidentiality in interviews. Our writers can prepare a MAN 6300 data analysis assignment using the data you have gathered at your organization. Break results down by group; the most useful findings usually appear there. Report the counts behind each theme so readers can judge how common it is.
Write yours, or have the desk draft it
This paper is an original model document written by our desk, not a submitted student paper and not an official Thomas Edison State University document. Read it for the moves, then write your own to the instructions in your classroom. If you want one built to your exact prompt and rubric, the first custom sample is free and arrives in 24 to 48 hours.
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MAN 6300 Module 3 questions, answered
Where can I find a free MAN 6300 Module 3 sample paper?
The third Management Capstone written assignment is reproduced above: survey, turnover, deviation and cost data analyzed alongside eighteen coded interviews, producing four evidence-based findings for a manufacturer.
Does the MAN-6300 capstone require qualitative coding?
Yes; the course objectives include evaluating performance with quantitative data analysis and qualitative coding techniques to identify patterns and draw evidence-based conclusions.
How can coding reliability be checked in a small project?
Have a second person code part of the transcripts with the same codebook, report the agreement rate and resolve differences by discussion.
Why report what an organization is doing well in a problem analysis?
Balanced findings are more credible to decision makers and show which gains the recommendations must protect.
What are the main limitations of workplace survey data?
Cross-sectional surveys show associations, not causes, and comparisons across different instruments or years need caution.