1. Supply Chain analysis at Purdue University Team Name: Panda Elites Xian Zhu Junming Liu Yu He Yangon Chen

2. GSCMI 2013 Case Competition 2 Agenda (Xian Zhu) Recommendations Proposals Data Analysis Concerns Objectives

3. GSCMI 2013 Case Competition 3 Objectives (Xian Zhu)  Short-term  To balance the performance between the west & east coasts  Lower the Transportation Cost in the western sites;  Lower the Inventory Cost in the western sites  Long-term  Support the growth of the whole Eaton Power Distribution Systems  Lean operation

4. GSCMI 2013 Case Competition 4 Concerns (Xian Zhu)  From the Data  High Turnover rate of Dallas SVC  The huge monthly variation of demand  The frequent usage of premium freight  The limited capacity of W87 & DBN

5. GSCMI 2013 Case Competition 5 Data Analysis (Junming Liu)  Cost of Good Sold

6. GSCMI 2013 Case Competition 6 Data Analysis (Junming Liu)  Turnover  Annualize COGS Extreme case of Dallas-SVT

7. GSCMI 2013 Case Competition 7 Data Analysis (Junming Liu)  Highlight on DIO  Atlanta-SAT April DIO = 1537 days  Chicago-SVT May DIO = 3862 days  Houston-SVC Feb. DIO = 1052 days

8. GSCMI 2013 Case Competition 8 Data Analysis (Junming Liu)  Days of Inventory Outstanding Mean 49.11 days SD = 7.65 days

9. GSCMI 2013 Case Competition 9 Data Analysis (Junming Liu)  Trend on COGS (Sales)

10. GSCMI 2013 Case Competition 10 Data Analysis (Junming Liu)  High COGS Fluctuation  No Pattern on Demand  Low Responsiveness to the Change of Demand

11. GSCMI 2013 Case Competition 11 Data Analysis (Junming Liu)  Overall Trend

12. GSCMI 2013 Case Competition 12 Data Analysis (Junming Liu)  Premium Ship Percentage  Chicago, Dallas, San Francisco: High Percentage

13. GSCMI 2013 Case Competition 13 Data Analysis (Junming Liu)  Reasons  Distance with Suppliers  Demand Varies  Local Economy  Unemployment  New Construction Extreme Case for Dallas-SVC

14. GSCMI 2013 Case Competition 14 Data Analysis (Junming Liu)  Percentage of Order by Source

15. GSCMI 2013 Case Competition 15 Data Analysis (Junming Liu)  Los Angeles (Best Case) 1 2 3 4 1.Order from Closer Sources 2.Average Premium Shipping Percentage 3.Balanced Order Sources 4.Highly Utilization of W87 5.Highest Purchases 6.High COGS (Demand)

16. GSCMI 2013 Case Competition 16 Data Analysis (Junming Liu)  In Addition, Low Capacity of Warehouse

17. GSCMI 2013 Case Competition 17 Proposals (Yu He) We suggest to build a major warehouse to enhance the whole supply chain system. Our Reasons: 1. W87 is relatively useless to Electrical Sector. 2. Electrical Sector has no priority. 3. Relieve W34 and W87’s pressure. 4. Shorten distance of supply to some CMSC sites. 5. Increasing trend of demand in the future. Fayetteville, NCSumter, SCW34W87DBNCDC TOTAL22.15%13.57%21.95%3.92%2.07%4.15%

18. GSCMI 2013 Case Competition 18 Proposals (Yu He)  Adjust three-day rotation ABC Classifications

19. GSCMI 2013 Case Competition 19 Recommendations (Yanjun Chen)  Kanban card- It’s time to change!  LTL Problem  Demand Forecasting  Aggregate Planning -- Level strategy  Looking for more external suppliers in West Coast

20. GSCMI 2013 Case Competition 20 Summary (Yanjun Chen) ProblemAnalysisSolution

21. GSCMI 2013 Case Competition 21 Thank you!