| Course | DDBA 8307B Quantitative Business Data Analysis Using SPSS |
|---|---|
| Week | Week 11 |
| Paper type | Decision brief |
| Length | About 590 words, 4 pages |
| Format | Memo, APA 7 citations |
| School | Walden University |
| Program | Doctor of Business Administration (DBA) |
| Updated | October 2026 |
Free sample paper for DDBA 8307B Week 11
Memorandum
To: Plant Manager, Bluestem Dairy
From: Operations analyst
Date: October 13, 2026
Re: Which changeover procedure to standardize on the filling lines
Recommendation
Standardize on Procedure B for product changeovers on all three filling lines. In a 90-changeover trial over six weeks, Procedure B was the fastest on average, the most predictable from one changeover to the next and wasted the least product. It saves about six and a half minutes per changeover compared with the current Procedure A, which across roughly 1,400 changeovers a year adds up to about 150 hours of filling time.
What Was Compared
Bluestem Dairy, a composite cooperative-owned plant in Wisconsin, fills milk, cream and flavored milk into gallons, half gallons and pints on three lines. Each switch from one product to another requires a changeover: the line is stopped, flushed, sanitized where required and restarted. The plant has used Procedure A for years. Two alternatives were proposed: Procedure B, which prepares the next product's settings and flush water while the current run finishes, and Procedure C, which adds a longer flush to reduce the risk of carryover between products. Each procedure was used for 30 changeovers, assigned in rotation across lines and shifts so that no procedure got only the easy changeovers.
What the Trial Found
Procedures B and C were both clearly faster than A. B and C were close to each other on time; the trial cannot say which is faster with confidence. But B was more predictable, which matters for scheduling, and it flushed 13 fewer gallons per changeover than C, about 18,000 gallons a year. C's only advantage was a perfect sanitation record, compared with one failure for B; that difference is too small to rely on from 30 changeovers each.
Table 1
Changeover Results by Procedure
| Measure | Procedure A (current) | Procedure B | Procedure C | |
|---|---|---|---|
| Average minutes per changeover | 46.2 | 39.8 | 41.1 | |
| Typical spread (standard deviation, minutes) | 6.1 | 5.4 | 7.9 | |
| Average product flushed per changeover, gallons | 38 | 31 | 44 | |
| Changeovers failing first sanitation check | 2 of 30 | 1 of 30 | 0 of 30 | |
Trial of 90 changeovers, August 18 to September 26, 2026.
What This Does Not Show
The trial measured six weeks in late summer, when the product mix leans toward flavored milk. Changeovers in winter, with more cream runs, may behave differently. Crews also knew they were being timed. Shingo (1985), whose work on quick changeovers rested on separating setup work that can be done while a line runs from work that cannot, would predict B's advantage, which is reassuring, but the plant should keep timing changeovers for the first two months after standardizing to confirm the gain holds.
Next Steps
Train all three line crews on Procedure B over the next two weeks, update the standard work sheets, and review changeover times and sanitation results monthly through December.
Appendix: Statistics
A one-way analysis of variance found that changeover time differed by procedure, F(2, 87) = 8.00, p < .001, η² = .16. Tukey's post hoc comparisons showed A slower than B (difference 6.4 minutes, p < .001) and slower than C (5.1 minutes, p = .009); B and C did not differ clearly (1.3 minutes, p = .72). Levene's test did not indicate unequal variances. Field (2018) describes these procedures. The 95 percent confidence interval for the B minus A difference, about −9.8 to −3.0 minutes, is reported so the size of the saving can be judged and not just its significance, which is the practice Cumming (2014) recommends.
References
Cumming, G. (2014). The new statistics: Why and how. Psychological Science, 25(1), 7-29. https://doi.org/10.1177/0956797613504966
Field, A. (2018). Discovering statistics using IBM SPSS Statistics (5th ed.). SAGE Publications.
Shingo, S. (1985). A revolution in manufacturing: The SMED system. Productivity Press.
What the DDBA 8307B Week 11 instructions ask for
To close the course you write a short decision brief that carries one analysis to one decision maker. Put the recommendation in the first lines, with its practical benefit in the reader's units. Explain briefly what was compared and how the data were gathered, including any steps that made the comparison fair. Present the main findings in a plain table and a few sentences, without test statistics in the body. State what the analysis does not show and what the reader should watch after acting. Give next steps. Place the full statistical results in an appendix, including the test, post hoc comparisons and intervals. Cite sources where they support the method or the logic of the recommendation. Two pages plus an appendix is typical.
How this DDBA 8307B Week 11 example is built
The brief opens by recommending Procedure B and translating its 6.4-minute advantage into about 150 hours a year across roughly 1,400 changeovers. A section describes the dairy's three lines and three procedures, including B's preparation of settings and flush water during the run, and the rotation of 30 trials each across lines and shifts. A table compares average minutes, spread, gallons flushed and sanitation failures. Findings explain that B and C both beat A, that B and C could not be separated on time and that B's predictability and lower product loss decide it. Limits cite Shingo's work on preparing changeovers in advance and note summer mix and timed crews. The appendix reports the ANOVA, Tukey results and the interval for B minus A.
Reading the DDBA 8307B Week 11 rubric
The brief is graded on whether the decision maker can act from the first page. A recommendation buried after methods fails the format. Instructors check that findings are translated into the reader's units, such as hours and gallons, and that statistics are kept out of the body but complete in the appendix. Describing how the comparison was made fair, such as rotating procedures across lines and shifts, earns credit. Choosing between options that cannot be separated on the main measure by using secondary measures shows judgment. The limits section should be specific and paired with monitoring after the decision. Appendix statistics must be consistent with the body.
DDBA 8307B Week 11 help: mistakes that cost marks
Final briefs often read like shortened results chapters. Write for the person who will decide: start with what to do and what it saves. Keep test statistics out of the main text and put them in an appendix. Use a small table of the measures the reader cares about. If two options cannot be separated on your main measure, use other measures to choose and say so. Say what could make the result wrong and how to watch for it. End with concrete next steps. A tutor can help you move statistical detail into an appendix without losing accuracy.
Get a DDBA 8307B Week 11 example written to your instructions
Enclose the Week 11 guidelines and rubric, the analysis the brief reports, and who the decision-maker is. A decision brief with its technical appendix returns within 24-48h, and a first request is free. Placeholder figures stand in for results throughout, so your brief reports only what your analysis found.
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DDBA 8307B Week 11 questions, answered
Where can I find a free DDBA 8307B Week 11 sample paper?
The decision brief and its statistical appendix are on this page in full, free for any reader.
What decision does the DDBA 8307B Week 11 brief support?
Which of three changeover procedures a dairy plant should standardize on its filling lines.
Why is Procedure B recommended?
It was fastest on average, most predictable and flushed the least product, saving about 150 filling hours a year.
Could the trial separate Procedures B and C on time?
No; they differed by 1.3 minutes, which was not clear, so predictability and product loss decided the choice.
Where are the statistics reported?
In an appendix with the ANOVA, Tukey comparisons and the confidence interval for the time saving.