1. 2014 GSCMI Case Competition Team MECE Presentation Yejin Lee| Bumsun Ryu Saya Lee| Ryan Seongjin Shin

2. Agenda (Yejin) Problem Statement Recommendation Analysis Implementation / Risk Mitigation Evaluation of Alternatives Conclusion

3. Premium Freight Frequency Problem Statement (Yejin) Short-Term Inventory Level Build Supply Network Long-Term Problem Statement Recommendation Analysis Implementation & Risk Evaluation of Alternative Conclusion Unbalanced performance between the west and the east High premium freight frequency High overall inventory level Key Issues? Sustains the Growth

4. Recommendation (Yejin) Short-TermLong-Term Kanbanized Warehouse CMSC Problem Statement Recommendation Analysis Implementation & Risk Evaluation of Alternative Conclusion

5. 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

6. Analysis Continued (Saya) – Basic time (item to item) – Transportation time – Shipping rotation time – Consolidation wait time Problem Statement Recommendation Analysis Implementation & Risk Evaluation of Alternative Conclusion 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

7. Graphic Analysis (Bumsun) Before and After Dallasized 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 Implementation & Risk Evaluation of Alternative Conclusion Dallasized SF – SAT By matching COGS and order, it showed decreasing inventory and no premium shipment cost.

8. Analysis Continued (Bumsun) Dallasized to Kanbanized Project 12345678910111213 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 Implementation & Risk Evaluation of Alternative Conclusion

9. Implementation & Risk (Ryan) Problem Statement Recommendation Analysis Implementation & Risk Evaluation of Alternative Conclusion 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 RiskRisk LevelWhy?Solution SiteHighCost & Contract Issue Find potential sites and plan ahead Higher DemandLow Higher than the Facility Capacity Prioritize the location and build additional DBN Lower DemandMedium Lower than the Facility Capacity Little Effect Risk Risk Level Why?Solution SiteHigh High initial installation cost New Customers, Contract Lands Lower DemandMedium Outside import, competitors Target a new market, customized materials

10. Evaluation of Alternative (Ryan) Criteria Options CAPAMobility Cost (Initial, Long-term) New CMSC133 Warehouse212 New DBN321 Problem Statement Recommendation Analysis Implementation & Risk Evaluation of Alternative Conclusion

11. 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 necessary Strategic Approach Site of warehouse related issues Demand Uncertainty Competitors No experience with mass production Potential Risks Problem Statement Recommendation Analysis Implementation & Risk Evaluation of Alternative Conclusion

12. Fina nci al Res ult

13. Appendix

14. 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)

15. Location Optimization "Minisum" Straight Line Method San FransiscoLos AnglesPortlandSeattleTexasChicago Xi-122.166871-118.27425-122.740489-122.16687-96.2086-88.0715 Yi47.58508934.140765 45.395185 47.58508931.4243441.92453 Wi18.98%20.83%10.88%10.76%24.29%14.26% XiWi-23.19317751-24.6339286-13.35023538-13.1473382-23.36612-12.56062 YiWi9.0339500947.110771744.9375426965.1210058347.63200635.9792136 Optimal LocationX*-110.2514 Y*39.81449 PremiumShip Frequency (Month)PercentageTotal Order Amount ($)Percentage Weighted Percentage San Fransisco1222.018%1,208,25215.951%18.98% Los Angles1120.183% 1,626,431.9421.472%20.83% Portland916.514% 396,8985.240%10.88% Seattle916.514% 379,4745.010%10.76% Texas6.511.927%2,775,89036.647%24.29% Chicago712.844% 1,187,675.1515.680%14.26% Sum54.57,574,621100.00% Based on the Minisum Analysis, Results are 39°81‘44.9"N -110°25‘14“W