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INFO564: Supply Chain and Operations Management
Midterm Exam
1.Case: NY City launched a bicycle program called Citi Bike that has been quite successful. Here is
some more information about this program: (15 Points)
About Citi Bike
Citi Bike is New York City’s bike share system, and the largest in the nation. Citi Bike
launched in May 2013 and has become an essential part of our transportation network. It’s fun,
efficient and affordable – not to mention healthy and good for the environment.
Citi Bike, like other bike share systems, consists of a fleet of specially designed, sturdy and
durable bikes that are locked into a network of docking stations throughout the city. The bikes
can be unlocked from one station and returned to any other station in the system, making them
ideal for one-way trips. People use bike share to commute to work or school, run errands, get
to appointments or social engagements, and more.
Citi Bike is available for use 24 hours/day, 7 days/week, 365 days/year, and riders have access
to thousands of bikes at hundreds of stations across Manhattan, Brooklyn, Queens and Jersey
City,
Join
Become an Annual Member or buy a short-term pass through the Citi Bike app.
See pricing
Unlock
Find an available bike nearby and get a ride code or use your member key to
unlock it.
Find a bike
Ride
Take as many short rides as you want while your pass or membership is active.
See popular rides
Return
Return your bike to any station and wait for the green light on the dock to
make sure it’s locked.
Get started
a.
If you were to start this program, what business strategy would you use and why?
If I were to start this program I would try to use a marketing strategy because Citi is involved
in the banking industry but they are coming up with innovative ways to market their brand
recognition through Citi Bike. Citi Bike allows people to share a common denominator
regarding traveling in the city. The name “CITIBIKE” would be used as a slogan for bringing
about the topic of Citi. Essentially what this does is spread Citi banking’s marketing across
New York’s cities.
b.
If you were the operations manager for this program, what would you do? (How would you
go about launching this program and handle day to day operations?)
If I were the operations manager of this program I would target specific locations where we
can manage the use of one bike taken and returned in a convenient location. The goal here is
not to spend a lot of money really but mainly to use this location to maximize our marketing
budgets effectively. Having our name on the bikes creates a dynamic marketing structure that
is not only the topic of discussion on busy avenues in NY but also it is a very effective way to
market your product while providing a ecofriendly environment.
2. The Abco Company manufactures electrical assemblies. The current process uses 10 workers and
produces 200 units per hour. You are considering changing the process with new assembly methods
that increase output to 300 units per hour but will require 14 workers. Particulars are as follows:
OUTPUT (UNITS / HOUR)
NUMBER OF WORKERS
MATERIAL COST / HOUR
CURRENT PROCESS
200
10
$120
NEW PROCESS
300
14
$150
Workers are paid at a rate of $10 per hour, and overhead is charged at 140% (or 1.4 times) labor costs.
Finished switches sell for $20/unit. (15 Points)
a. Calculate the percentage change in labor productivity.
b. Calculate the percentage change in the multifactor productivity
d. Determine if the new process should be implemented.
SEE ATTACHMENT
3.The textbook discusses seven mistakes when managing processes, arguing that failure to manage
processes is ultimately a failure to manage the business. Discuss any four of those mistakes. (15 Points)
o Not connecting with Strategic Issues. The core processes are not working for the
common goal.
o Not Involving the Right People in the Right Way. Not putting the right staff in the
right unit in which they can help.
o Not Giving the Design Teams and Process Analysts a Clear Charter, and Then
Holding Them Accountable. Failing to explain what is needed to the process team and
blaming them for mistakes. No communication between teams that later on fall on one
particular team.
o Not Considering the Impact on People. The communication with those who develop
new designs are not being considered the impact that it will have on them.
4. Suppose you have owned and operated your own package delivery business for a year. You would
like to engage in competitive benchmarking to make sure your business is run as smoothly as possible.
What kinds of firms and processes would you consider for benchmarking? Defend your choices of
these firms and processes. What specific metrics would you focus on and why? How could the data be
reliably collected at your own business? (15 Points)
UPS would be a good example of a company to benchmark against. Here are some typical processes:


Using logistics to streamline shipping orders effectively so that the delivery of the product is
on time.
o Selecting drivers strategically to operate in the various delivery zones
o Using technology to maximize delivery routes
Handling damaged package claims in an effective and timely manner
Reporting up-to-the-minute tracking detail using barcode scanning
Here are some of the key metrics that are measured for package delivery companies:
– Traffic volume: measuring quantity of items being shipped and received; this is important
because traffic will vary depending on the season
– Route times: how fast and how efficient the driver can deliver in his/her route; this will

maximize the driver’s route and ability to avoid wasted resources
Service levels: different shipment options depending overnight, two-day, ground, and
standard delivery; this gives the customer more options as well increased profitability for the
company
5. Calculate three forecasts using the following data. First, for periods 4 through 10, develop the
exponentially smoothed forecasts using a forecast for period 3 (F3) of 45.0 and an alpha of 0.4. Second,
calculate the three-period moving-average forecast for periods 4 through 10. Third, calculate the
weighted moving average for periods 4 through 10, using weights of .70, .20, and .10, with 0.70
applied to the most recent data. Calculate the mean absolute deviation (MAD) for each forecasting
procedure. Which forecasting procedure would you select? Why? (20 Points)
Month
1
2
3
4
5
6
7
8
9
10
Demand
45
48
43
48
49
54
47
50
46
47
SEE ATTACHMENT
6. A local moving company has collected data on the number of moves they have been asked to
perform over the past three years. (20 Points)
a.
b.
c.
Plot the data to see if there are seasonal effects along with a trend present in the data.
Calculate the seasonal indexes for each quarter.
A regression analysis was done for the three years of data and the regression equation for total
annual demand was found to be: y = 120.33 + 19*year. Using this equation, calculate the forecast
for year 4.
d. Using the number obtained in part c, calculate the forecast for each quarter of year 4.
SEE EXCEL SHEET
1.Case: NY City launched a bicycle program called Citi Bike that has been quite successful. Here is
some more information about this program: (15 Points)
About Citi Bike
Citi Bike is New York City’s bike share system, and the largest in the nation. Citi Bike
launched in May 2013 and has become an essential part of our transportation network. It’s fun,
efficient and affordable – not to mention healthy and good for the environment.
Citi Bike, like other bike share systems, consists of a fleet of specially designed, sturdy and
durable bikes that are locked into a network of docking stations throughout the city. The bikes
can be unlocked from one station and returned to any other station in the system, making them
ideal for one-way trips. People use bike share to commute to work or school, run errands, get
to appointments or social engagements, and more.
Citi Bike is available for use 24 hours/day, 7 days/week, 365 days/year, and riders have access
to thousands of bikes at hundreds of stations across Manhattan, Brooklyn, Queens and Jersey
City,
Join
Become an Annual Member or buy a short-term pass through the Citi Bike app.
See pricing
Unlock
Find an available bike nearby and get a ride code or use your member key to
unlock it.
Find a bike
Ride
Take as many short rides as you want while your pass or membership is active.
See popular rides
Return
Return your bike to any station and wait for the green light on the dock to
make sure it’s locked.
Get started
a.
b.
If you were to start this program, what business strategy would you use and why?
If you were the operations manager for this program, what would you do? (How would you
go about launching this program and handle day to day operations?)
2.The Abco Company manufactures electrical assemblies. The current process uses 10 workers and
produces 200 units per hour. You are considering changing the process with new assembly methods
that increase output to 300 units per hour but will require 14 workers. Particulars are as follows:
OUTPUT (UNITS / HOUR)
CURRENT PROCESS
200
NEW PROCESS
300
NUMBER OF WORKERS
MATERIAL COST / HOUR
10
$120
14
$150
Workers are paid at a rate of $10 per hour, and overhead is charged at 140% (or 1.4 times) labor costs.
Finished switches sell for $20/unit. (15 Points)
a. Calculate the percentage change in labor productivity.
b. Calculate the percentage change in the multifactor productivity
d. Determine if the new process should be implemented.
3.The textbook discusses seven mistakes when managing processes, arguing that failure to manage
processes is ultimately a failure to manage the business. Discuss any four of those mistakes. (15 Points)
4. Suppose you have owned and operated your own package delivery business for a year. You would
like to engage in competitive benchmarking to make sure your business is run as smoothly as possible.
What kinds of firms and processes would you consider for benchmarking? Defend your choices of
these firms and processes. What specific metrics would you focus on and why? How could the data be
reliably collected at your own business? (15 Points)
5. Calculate three forecasts using the following data. First, for periods 4 through 10, develop the
exponentially smoothed forecasts using a forecast for period 3 (F3) of 45.0 and an alpha of 0.4. Second,
calculate the three-period moving-average forecast for periods 4 through 10. Third, calculate the
weighted moving average for periods 4 through 10, using weights of .70, .20, and .10, with 0.70
applied to the most recent data. Calculate the mean absolute deviation (MAD)for each forecasting
procedure. Which forecasting procedure would you select? Why? (20 Points)
Month
1
2
3
4
5
6
7
8
9
10
Demand
45
48
43
48
49
54
47
50
46
47
6. A local moving company has collected data on the number of moves they have been asked to
perform over the past three years. (20 Points)
a.
b.
c.
Plot the data to see if there are seasonal effects along with a trend present in the data.
Calculate the seasonal indexes for each quarter.
A regression analysis was done for the three years of data and the regression equation for total
annual demand was found to be: y = 120.33 + 19*year. Using this equation, calculate the forecast
for year 4.
d. Using the number obtained in part c, calculate the forecast for each quarter of year 4.
output
number of workers
material cost
current process new process
200
300
10
14
120
150
workers – pay
overhead
switches sell
a) calculate
percentage change
in productivity
step 1)
step 2)
b) calculate the %
change in the
multifactor
productivity
step 1) – multifactor
productivity for current
process
step 2) – multifactor
productivity for new
process
Step 3) multifactor
productivity change
Step 4) percentage
change
Yes, the new processes
should be implemented
c) Determine if the due to the fact the
new process should multifactor productivity
be implemented
increases.
10
1.4
20
300-200=100
100/200=.5
(200*20)/((10*10
)+(120)+(1.4*10)*
(10))=4000/360
(300*20)/((14*10
)+(150)+(1.4*14)*
(10))
12.34-11.1
19.7/11.1
200 change
50% percentage change in multifactor
11.1111111
12.345679
1.2345679
11%
centage change in multifactor productivity
alpha
Exponential Smoothed Forecast
Month
Demand
Exponential Smoothing
1
45
2
48
3
43
4
48
5
49
6
54
7
47
8
50
9
46
10
47
0.4
Exponential Smoothing Answer
45
46.20
47.32
49.99
48.80
49.28
47.97
47.58
Totals
Average
three-period moving average forecast
Three Month Simple Moving
Month
Demand
Average
1
45
2
48
3
43
4
48
5
49
6
54
7
47
8
50
9
46
10
47
Blank
45
45.33
46.33
46.67
50.33
50.00
50.33
47.67
Totals
Average
weighted moving average
Month
Demand
1
45
2
48
3
43
4
48
5
49
6
54
7
47
8
50
41.20
43.80
45.33
49.20
45.33
9
46
10
47
46.20
43.77
Totals
Average
Absolute Deviation – MAD
1.80
1.68
4.01
1.80
0.72
1.97
0.58
12.55
1.793
Absolute Deviation – MAD
2
2.67
2.67
7.33
3.33
0.00
4.33
0.67
21.00
3.00
Absolute Deviation – MAD
6.80
5.20
8.67
2.20
4.67
0.20
3.23
30.97
4.42
YEAR 1
YEAR 2
Quarter
1
2
3
4
Average
YEAR 3
Seasonal
Forecast
Demand Year 1
Quarter Demand Year 2
20 0.5925926
1
27
40 1.1851852
2
45
45 1.3333333
3
55
30 0.8888889
4
40
33.75
C. y=120.33+19*(x)
y= 120.33+19 (4)
y= 120.33+76
y= 196.33 forecast for year 4
Average
Seasonal
Forecast Quarter
0.646707
1
1.077844
2
1.317365
3
0.958084
4
41.75
Average
Chart Title
60
50
40
40
30
20
20
10
0
1
2
Demand Year 1
Demand Year 2
Demand Year 2
d)
Seasonal
Forecast
Demand Year
3
33 0.763006
45 1.040462
55 1.271676
40 0.924855
Average
Seasonal
Factor
0.667435
1.101164
1.307458
0.923943
43.25
45
30
3
4
Demand Year 3
Year 5
32.75437
54.03962
64.16352
45.34249
•:>~
.Q• per ,at ions Mana ,gement
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l211JmDl”I

4a
O tO
TENTH EDITION
Operations
Management
PROCESSES AND SUPPLY CHAINS
LEE J. KRAJEWSKI
Professor Emeritus at
The Ohio State University
and the University of Notre Dame
LARRY P. RITZMAN
Professor Emeritus at
The Ohio State University
and Boston College
MANOJ K. MALHOTRA
University of South Carolina
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appropriate page within text.
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Screen shots and icons reprinted with permission from the Microsoft Corporation. This book is not sponsored or
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Copyright © 2013, 2010, 2007, 2005, 2002 Pearson Education, Inc., publishing as Prentice Hall, One Lake Street, Upper
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Library of Congress Cataloging-in-Publication Data
Krajewski, Lee J.
Operations management : processes and supply chains / Lee J. Krajewski,
Larry P. Ritzman, Manoj K. Malhotra. — 10th ed.
p. cm.
Includes index.
ISBN 978-0-13-280739-5 (alk. paper)
1. Production management. I. Ritzman, Larry P. II. Malhotra, Manoj K. (Manoj Kumar), 1960- III. Title.
TS155.K785 2013
658.5—dc23
2011043411
10 9 8 7 6 5 4 3 2 1
www.pearsonhighered.com
PEARSON
ISBN 10:
0-13-280739-4
ISBN 13: 978-0-13-280739-5
Dedicated with love to our families.

Judie Krajewski
Gary and Christine; Gabrielle
Lori and Dan; Aubrey, Madeline, Amelia, and Marianna
Carrie and Jon; Jordanne, Alaina, and Bradley
Selena and Jeff; Alex
Virginia and Jerry
Virginia and Larry

Barbara Ritzman
Karen and Matt; Kristin and Alayna
Todd; Cody, Cole, Taylor, and Clayton
Kathryn and Paul
Mildred and Ray

Maya Malhotra
Vivek, Pooja, and Neha
Santosh and Ramesh Malhotra
Indra and Prem Malhotra; Neeti and Neil Ardeshna, and Deeksha
Sadhana Malhotra
Leela and Mukund Dabholkar
Aruna and Harsha Dabholkar; Aditee
Mangala and Pradeep Gandhi; Priya and Medha
About the Authors
Lee J. Krajewski
is Professor Emeritus at The Ohio State
University and Professor Emeritus at the University of Notre Dame.
While at The Ohio State University, he received the University Alumni
Distinguished Teaching Award and the College of Business Outstanding
Faculty Research Award. He initiated the Center for Excellence in Manufacturing Management and served as its director for 4 years. In addition, he received the National President’s Award and the National
Award of Merit of the American Production and Inventory Control Society. He served as president of the Decision Sciences Institute and was
elected a fellow of the institute in 1988. He received the Distinguished
Service Award in 2003.
Lee received his PhD from the University of Wisconsin. Over the
years, he has designed and taught courses at both graduate and undergraduate levels on topics such as operations strategy, introduction to operations management,
operations design, project management, and manufacturing planning and control systems.
Lee served as the editor of Decision Sciences, was the founding editor of the Journal of Operations
Management, and has served on several editorial boards. Widely published himself, Lee has contributed numerous articles to such journals as Decision Sciences, Journal of Operations Management,
Management Science, Production and Operations Management, International Journal of Production
Research, Harvard Business Review, and Interfaces, to name just a few. He has received five bestpaper awards. Lee’s areas of specialization include operations strategy, manufacturing planning
and control systems, supply chain management, and master production scheduling.
Larry P. Ritzman
is Professor Emeritus at The Ohio State University
and Professor Emeritus at Boston College. While at The Ohio State
University, he served as department chairman and received several
awards for both teaching and research, including the Pace Setters …
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