2014 GSCMI Case Competition
Team MECE Presentation
Yejin Lee| Bumsun Ryu
Saya Lee| Ryan Seongjin Shin
Agenda (Yejin)
•
•
•
•
•
•
Problem Statement
Recommendation
Analysis
Implementation / Risk Mitigation
Evaluation of Alternatives
Conclusion
Problem Statement (Yejin)
Key Issues?
•
•
•
Unbalanced performance between the west and the east
High premium freight frequency
High overall inventory level
Short-Term
Problem
Statement
Long-Term
Premium Freight
Frequency
Build Supply Network
Inventory Level
Sustains the Growth
Recommendation
Analysis
Implementation
& Risk
Evaluation of
Alternative
Conclusion
Recommendation (Yejin)
Short-Term
Long-Term
Kanbanized Warehouse
Problem
Statement
Recommendation
Analysis
CMSC
Implementation
& Risk
Evaluation of
Alternative
Conclusion
Multiples Analysis (Saya)
• How to reduce inventory level?
• Lean manufacturing – Dallas
– Balanced lead-time
• Barely use of plants and CDCs
– Lead-time vs. Inventory level
• Balanced lead-time  Less WIP 
low Inventory
No bottleneck
• Bottleneck in Supply Chain
Problem
Statement
Recommendation
Analysis
Implementation
& Risk
Evaluation of
Alternative
Conclusion
Analysis Continued (Saya)
What causes bottleneck?
–
–
–
–
Basic time (item to item)
Transportation time
Shipping rotation time
Consolidation wait time
Problem
Statement
Recommendation
Analysis
Lean Manufacturing – Dallas
– Overcome Basic time by
maximizing warehouse uses
– Overcome Transportation
time by Premium Freight
– Overcome Shipping rotation
time, Consolidation wait time
by barely use of plants or
CDCs
Implementation
& Risk
Evaluation of
Alternative
Conclusion
Graphic Analysis (Bumsun)
Before and After Dallasized
1,200,000
San Francisco – SAT
It shows high freight
cost, inventory, and
difference between
COGS and order. The
average turn over
ratio is 50%.
1,000,000
800,000
COGS
600,000
Inventory
400,000
ORDER
200,000
1
2
3
4
5
700,000
600,000
500,000
COGS
Inventory
400,000
ORDER
300,000
200,000
1
2
Problem
Statement
3
4
5
6
7
Recommendation
8
9
10
11
6
7
8
9
10
11
12
Dallasized SF – SAT
By matching COGS
and order, it showed
decreasing
inventory and no
premium shipment
cost.
12
Analysis
Implementation
& Risk
Evaluation of
Alternative
Conclusion
Analysis Continued (Bumsun)
Dallasized and Kanbanized
Dallasized to Kanbanized Project
1
2
3
4
5
6
7
8
9
10
11
12
13
SF-SAT (Max)
SF-SAT (Min/Premium)
SF-SAT (Ave)
Dallas-SVC(Max)
Dallas-SVC(Min/Premium)
Dallas-SVC(Ave)
Manufacturing
CDC or Rotation
Warehouse(Dallasized)
Transportation
Warehouse(Kanbanized)
Problem
Statement
Recommendation
Analysis
Implementation
& Risk
Evaluation of
Alternative
Conclusion
Implementation & Risk (Ryan)
Short-Term
Action Plan
• Contract with warehouse in
West based on an optimized
location
• Change Shipping Structure
• Hire Supply Network Director
in West
• Store longer lead-time
needed materials
Risk
Risk Level
Why?
Solution
Site
High
Cost & Contract Issue
Find potential sites
and plan ahead
Higher Demand
Low
Higher than the
Facility Capacity
Prioritize the
location and build
additional DBN
Lower Demand
Medium
Lower than the
Facility Capacity
Little Effect
Risk
Risk
Level
Site
High
Lower Demand
Medium
Long-Term
Action Plan
•
•
•
Purchase new warehouse
location and customize
based on the efficiency of
the center
Build CMSC in West based
on the data collected
Global Market
Problem
Statement
Recommendation
Analysis
Why?
Solution
High initial
installation cost
Outside import,
competitors
Implementation
& Risk
New Customers,
Contract Lands
Target a new market,
customized materials
Evaluation of
Alternative
Conclusion
Evaluation of Alternative
(Ryan)
Criteria
CAPA
Mobility
Cost (Initial, Long-term)
New CMSC
1
3
3
Warehouse
2
1
2
New DBN
3
2
1
Options
Problem
Statement
Recommendation
Analysis
Implementation
& Risk
Evaluation of
Alternative
Conclusion
Conclusion (Ryan)
Recommendation
Implementation
• Build a warehouse
• Dallasization & Kabanization
with DOE terms necessary
Strategic• Compliance
Approach
• Collect more data to build or
buy any additional needed
• Build an optimized location for
the warehouse
• Purchase new warehouse on the
efficiency of the center
• Build CMSC in West based on the
data collected
• Build CMSC for further market
No experience with mass production
Potential •Risks
• Site of warehouse related issues
• Demand Uncertainty
• Target Global market
Problem
Statement
Recommendation
• Competitors
Analysis
Implementation
& Risk
Evaluation of
Alternative
Conclusion
Fina
nci
al
Res
ult
Appendix
Key Assumption
• Manufacturing process and ability are similar across
all CMSC.
• CMSC is focused on customization orders that leads
Advanced Purchase items.
• The amount of order in dollar matches the COGS
within 10% distribution due to Dallasizing (Slide 7).
• Manufacturing process takes 5 days and same for all
parts (Slide 8).
• *Premium Shipment Frequency & Total Order Amount
is Equally Weighted (Appendix)
• *Premium Order / Total Order = Average Above 7.5%
Considered (Appendix)
Location Optimization
Based on the Minisum Analysis, Results are 39°81‘44.9"N -110°25‘14“W
PremiumShip Frequency (Month)
Percentage
San Fransisco
12
22.018%
Los Angles
11
20.183%
Portland
9
16.514%
Seattle
9
16.514%
Texas
6.5
11.927%
Chicago
7
12.844%
Sum
54.5
Percentage
Weighted
Percentage
15.951%
18.98%
1,626,431.94
21.472%
20.83%
396,898
5.240%
10.88%
379,474
5.010%
10.76%
36.647%
24.29%
15.680%
14.26%
Total Order Amount ($)
1,208,252
2,775,890
1,187,675.15
7,574,621
100.00%
"Minisum" Straight Line Method
San Fransisco
Los Angles
Portland
Seattle
Texas
Chicago
Xi
-122.166871
-118.27425
-122.740489
-122.16687
-96.2086
-88.0715
Yi
47.585089
34.140765
45.395185
47.585089
31.42434
41.92453
Wi
18.98%
20.83%
10.88%
10.76%
24.29%
14.26%
XiWi
-23.19317751
-24.6339286
-13.35023538
-13.1473382
-23.36612
-12.56062
YiWi
9.033950094
7.11077174
4.937542696
5.121005834
7.6320063
5.9792136
X*
-110.2514
Y*
39.81449
Optimal Location