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Slide 1 Department of SCMS XXXXXXXXXXXiaowei XuRutgers 1 Project Guidelines...

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Slide 1
Department of SCMS XXXXXXXXXXXiaowei XuRutgers
1
Project Guidelines
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Department of SCMS XXXXXXXXXXXiaowei XuRutgers
2
What to do?
• Objective: Forecast ca
truck sales; balance sales with production and
inventory (S&OP) in the three NA countries; calculate days sales in
inventory
• Data Sources: Wards Auto
• Data Range: XXXXXXXXXXmonthly)
• Time Series Methods: MA(12) and exponential smoothing (Simple,
Holt’s and Winter’s)
• Make a presentation XXXXXXXXXXminutes, ~30 slides, Apr 19, 23, 26 or 30)
• Write a report (~ 20 pages) and follow the project format in Slides 5-
6.
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Department of SCMS XXXXXXXXXXXiaowei XuRutgers
3
The Basic S&OP Grid
History is included to
highlight past plan-to-
actual performance
Inventory Plan = Planned
Opening Inventory + Planned
Production - Planned Sales
Actual Inventory = Opening
Inventory + Actual Production -
Actual Sales
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Department of SCMS XXXXXXXXXXXiaowei XuRutgers
4
Inventory Turnove
Inventory turnover=
Cost of Goods Sold from Stock Sales during the Past 12 Months
Average Inventory Investment during the Past 12 Months
Days sales in inventory=365/Inventory turnove
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Department of SCMS XXXXXXXXXXXiaowei XuRutgers
5
Team Project – Report Format
• Your project must be word-processed using a standard font
(e.g., TimesNewRoman 12) and double-spaced.
• All charts, data sheets and tables (if any) should be done on
the computer. Graphs and charts should have a title and
properly and clearly labeled.
• All pages must be numbered.
• Order of pages:
– COVER SHEET—The first page of your project must be a cover sheet
that includes your name(s), date, the title of your project and the
percentage contribution of each team member’s effort .
– EXECUTIVE SUMMARY - Briefly describe the problem, your time
series models, results and recommendation to managers.
– TABLE OF CONTENTS
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Department of SCMS XXXXXXXXXXXiaowei XuRutgers
6
Team Project – Report Format
Order of pages:
• INTRODUCTION, PROBLEM, PURPOSE—This section should include the
statements of the project problem, goal and the data source.
• FINDINGS— Describe and visualize trends and seasonality. Calculate annual
sales growth and summarize the growth trend. Formulate quantitative models
and conduct quantitative analysis using Excel. Explain your findings and how
your findings could be helpful for managers.
• CONCLUSION—what can you conclude or not conclude from your research
and recommend the solution to production/sales managers.
• REFERENCE—citations and websites refe
ed if any.
• APPENDICES—attach anything technical or supplementary (e.g., spreadsheet
models and explanations).
Hand in a hard copy of your project and send me the electronic
version of your files, including excel spreadsheets (if any), the
project report and ppt presentation on May 3.
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Department of SCMS XXXXXXXXXXXiaowei XuRutgers
7
Ca
Truck Models
• Car (15): Charger, Focus, Fusion, Mustang, Camaro, Impala,
Malibu, Accord, Civic, Elantra, Sonata, Altima, Sentra, Camry,
Corolla/Matrix
• Light Truck (21): Grand Cherokee, Ram Pickup Light-Duty,
Edge, Escape, Explorer, F-Series Pickup Light-Duty, Equinox,
Silverado, Tahoe, Traverse, Acadia, Sie
a, CR-V, Pilot, Santa
Fe, Sorento, Outback, Highlander, RAV4, Tacoma, Tundra
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Department of SCMS XXXXXXXXXXXiaowei XuRutgers
8
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Department of SCMS XXXXXXXXXXXiaowei XuRutgers
9
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Department of SCMS XXXXXXXXXXXiaowei XuRutgers
10
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11
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Department of SCMS XXXXXXXXXXXiaowei XuRutgers
12
Durable Goods
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Department of SCMS XXXXXXXXXXXiaowei XuRutgers
13
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Department of SCMS XXXXXXXXXXXiaowei XuRutgers
14
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Answered Same Day Apr 14, 2021

Solution

Pooja answered on Apr 16 2021
158 Votes
United States
The dependent variable is sales. The independent variable is production and inventory. The regression output is given below.
    SUMMARY OUTPUT
    
    
    
    
    
    
    
    
    
    
    
    
    Regression Statistics
    
    
    
    
    
    Multiple R
    0.18585572
    
    
    
    
    
    R Square
    0.03454235
    
    
    
    
    
    Adjusted R Square
    0.01260013
    
    
    
    
    
    Standard E
o
    1512.2202
    
    
    
    
    
    Observations
    91
    
    
    
    
    
    
    
    
    
    
    
    
    ANOVA
    
    
    
    
    
    
    Â 
    df
    SS
    MS
    F
    Significance F
    
    Regression
    2
    7199981.26
    3599990.63
    1.57424129
    0.21294237
    
    Residual
    88
    201239274
    2286809.93
    
    
    
    Total
    90
    208439256
    Â 
    Â 
    Â 
    
    
    
    
    
    
    
    
    Â 
    Coefficients
    Standard E
o
    t Stat
    P-value
    Lower 95%
    Upper 95%
    Intercept
    8436.49961
    1036.89231
    8.13633153
    2.4402E-12
    6375.89403
    10497.1052
    Production
    0.11320547
    0.07059631
    1.60356087
    0.11239423
    -0.0270898
    0.2535008
    inventory
    -0.0174095
    0.03134992
    -0.5553292
    0.58007848
    -0.0797109
    0.04489185
The regression equation is given by: sales = 8436.4996 + 0.11320547*production -0.017409*inventory.
Null hypothesis, Ho; model is not significant. V/s H1: Model is significant. With (F=1.57, p<5%), I reject Ho and conclude that Model is significant.
The predicted values of sales is highlighted in the table below.
    Sorento
    Sales
    Production
    inventory
    Predicted sales
    Jun-10
    8,608
    12,172
    14,054
     $ 9,570
    Jul-10
    9,003
    9,682
    12,395
     $ 9,317
    Aug-10
    9,038
    11,767
    11,545
     $ 9,568
    Sep-10
    10,112
    12,528
    16,005
     $ 9,576
    Oct-10
    10,609
    9,835
    19,930
     $ 9,203
    Nov-10
    9,618
    9,049
    20,288
     $ 9,108
    Dec-10
    9,801
    8,348
    11,165
     $ 9,187
    Jan-11
    8,116
    11,562
    17,836
     $ 9,435
    Feb-11
    8,641
    11,642
    17,102
     $ 9,457
    Mar-11
    11,071
    13,207
    14,937
     $ 9,672...
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