2014 GSCMI Case CompetitionTeam MECE Presentation

Yejin Lee| Bumsun RyuSaya Lee| Ryan Seongjin Shin

Agenda (Yejin)

• Problem Statement• Recommendation• Analysis• Implementation / Risk Mitigation• Evaluation of Alternatives• Conclusion

Premium Freight Frequency

Problem Statement (Yejin)

Short-Term

Inventory Level

Build Supply Network

Long-Term

Problem Statement

Recommendation Analysis Implementatio

n & Risk

Evaluation of

AlternativeConclusion

• Unbalanced performance between the west and the east• High premium freight frequency• High overall inventory level

Key Issues?

Sustains the Growth

Recommendation (Yejin)

Short-Term Long-Term

Kanbanized Warehouse CMSC

Problem Statement

Recommendation Analysis Implementatio

n & Risk

Evaluation of

AlternativeConclusion

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 Implementatio

n & Risk

Evaluation of

AlternativeConclusion

Analysis Continued (Saya)

– Basic time (item to item)

– Transportation time– Shipping rotation time– Consolidation wait time

Problem Statement

Recommendation Analysis Implementatio

n & Risk

Evaluation of

AlternativeConclusion

What causes bottleneck?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

Graphic Analysis (Bumsun)Before and After Dallasized

1 2 3 4 5 6 7 8 9 10 11 12 -

200,000

400,000

600,000

800,000

1,000,000

1,200,000

COGSInventoryORDER

San Francisco – SAT

It shows high freight cost, inventory, and difference between

COGS and order. The average turn over

ratio is 50%.

Problem Statement

Recommendation Analysis Implementatio

n & Risk

Evaluation of

AlternativeConclusion

1 2 3 4 5 6 7 8 9 10 11 12 200,000

300,000

400,000

500,000

600,000

700,000

COGSInventoryORDER

Dallasized SF – SAT

By matching COGS and order, it

showed decreasing inventory and no

premium shipment cost.

Analysis Continued (Bumsun)

Dallasized to Kanbanized Project1 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)

Dallasized and Kanbanized

Problem Statement

Recommendation Analysis Implementatio

n & Risk

Evaluation of

AlternativeConclusion

Implementation & Risk (Ryan)

Problem Statement

Recommendation Analysis Implementatio

n & Risk

Evaluation of

AlternativeConclusion

Short-Term

Long-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

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

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 Why? Solution

Site High High initial installation cost

New Customers, Contract Lands

Lower Demand Medium Outside import, competitors

Target a new market, customized materials

Evaluation of Alternative(Ryan)

Criteria

Options

CAPA Mobility Cost (Initial, Long-term)

New CMSC 1 3 3

Warehouse 2 1 2

New DBN 3 2 1

Problem Statement

Recommendation Analysis Implementatio

n & Risk

Evaluation of

AlternativeConclusion

Conclusion (Ryan)

• Build a warehouse

•Dallasization & Kabanization

Recommendation

• 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

Implementation

• Collect more data to build or buy any additional needed

• Target Global market

• Compliance with DOE terms necessaryStrategic Approach

• Site of warehouse related issues

•Demand Uncertainty

• Competitors

• No experience with mass productionPotential Risks

Problem Statement

Recommendation Analysis Implementatio

n & Risk

Evaluation of

AlternativeConclusion

Financial ResultQ

&A

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

"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

Optimal Location X* -110.2514

Y* 39.81449

PremiumShip Frequency (Month) Percentage Total Order Amount ($) Percentage Weighted Percentage

San Fransisco 12 22.018% 1,208,252 15.951% 18.98%

Los Angles 11 20.183% 1,626,431.94 21.472% 20.83%

Portland 9 16.514% 396,898 5.240% 10.88%

Seattle 9 16.514% 379,474 5.010% 10.76%

Texas 6.5 11.927% 2,775,890 36.647% 24.29%

Chicago 7 12.844% 1,187,675.15 15.680% 14.26%

Sum 54.5 7,574,621 100.00%

Based on the Minisum Analysis, Results are 39°81‘44.9"N -110°25‘14“W