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A1: Shingle Sense (Updated
01/03/2012 02:51 PM
)
MGT 305
You are a supervisor of roof installation crews at a local
roofing operation (see for example Ray
St Clair Roofing). Your
boss, the director of operations, wants to measure the productivity of the work
crews. You’ve gathered the data
on square feet of roof installed below. Assume that each individual works a 40 hour week.
This year:
| Period |
Average Crew Size |
Square Feet Installed |
| Jan-Feb |
4 |
18050 |
| Mar-April |
3 |
14750 |
| May-June |
3 |
14600 |
| July-Aug |
2 |
12025 |
| Sept-Oct |
4 |
17500 |
| Nov-Dec |
2 |
11050 |
Last year:
| Period |
Average Crew Size |
Square Feet Installed |
| Jan-Feb |
3 |
14800 |
| Mar-April |
4 |
18750 |
| May-June |
2 |
11025 |
| July-Aug |
4 |
16700 |
| Sept-Oct |
3 |
14050 |
| Nov-Dec |
2 |
9800 |
Some issues to consider as you conduct your analysis and
report your findings:
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How is productivity officially defined and calculated?
(finding a textbook definition and citing it in
you memo would be a feather in your cap)
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In your memo, make sure you describe your analytical
method. This should include the data that you're using, where you got
it (cites), and how you plan to use it in your analysis.
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There are different types of productivity measures
(i.e., partial factor, multi factor, total factor).
Which one are we using here and why?
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What is this operations productivity?
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Does productivity depend on crew size? How does
sample size affect the confidence of your conclusions?
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How does productivity change from period to period?
(if you're baffled by how to calculate such a thing, click
here)
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How does this operations' productivity compare to national averages?
(the Bureau of Labor Statistics
is the best source for this type of data)
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What would an information systems that routinely
reports productivity for this organization look like? Is this something
that this should pursue?
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What might be a conservative next step (CNS) in improving
this operations'
productivity?
Report your findings to your boss in memo
format.
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