Supply Chain analysis at Purdue University Team Name

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

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

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 GSCMI 2013 Case Competition 3

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 W 87 & DBN GSCMI 2013 Case Competition 4

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

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

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 GSCMI 2013 Case Competition 7

Data Analysis (Junming Liu) § Days of Inventory Outstanding Mean 49. 11 days SD = 7. 65 days GSCMI 2013 Case Competition 8

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

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

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

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

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

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

Data Analysis (Junming Liu) § Los Angeles (Best Case) 1 2 3 1. 2. 3. 4. 5. 6. Order from Closer Sources Average Premium Shipping Percentage Balanced Order Sources Highly Utilization of W 87 Highest Purchases High COGS (Demand) 4 GSCMI 2013 Case Competition 15

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

Proposals (Yu He) We suggest to build a major warehouse to enhance the whole supply chain system. Our Reasons: 1. W 87 is relatively useless to Electrical Sector. Fayetteville, NC TOTAL 22. 15% Sumter, SC W 34 W 87 DBN CDC 13. 57% 21. 95% 3. 92% 2. 07% 4. 15% 2. Electrical Sector has no priority. 3. Relieve W 34 and W 87’s pressure. 4. Shorten distance of supply to some CMSC sites. 5. Increasing trend of demand in the future. GSCMI 2013 Case Competition 17

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

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 GSCMI 2013 Case Competition 19

Summary Problem (Yanjun Chen) Analysis GSCMI 2013 Case Competition Solution 20

Thank you! GSCMI 2013 Case Competition 21