1. Bill Hardgrave Auburn University Note: this document is copyrighted ( 2010) and confidential; do not distribute or cite without explicit permission.

2.  2003 – 2006: pallet -> case; Wal-Mart, Metro, DoD Issue: inventory management in the supply chain; unprecedented ‘affordable’ visibility Epiphany: most problems at the store Result: shift to store-level visibility and item-level  2006 – present: item-level apparel/footwear; American Apparel, Dillard’s, Bloomingdale’s, J.C. Penney, several in Europe Issue: inventory accuracy, loss prevention, etc. Epiphany: multi-use technology, start at the store and go up supply chain Result: more adopters, broader adoption

3. Playing Investigating Road mapping Phased deployment Full deployment

4.  Movement is being driven by RFID’s use case applications (solving problems) Inventory accuracy Out of stocks Locating product Loss prevention Dressing room management Price change management Etc.  Focus on inventory accuracy … The big four

5. Inventory Accuracy Sales

6. Inventory Accuracy Store execution Theft

7. Inaccuracy causes Results in overstated PI? Results in understated PI? Can RFID reduce the error? Incorrect manual adjustment Yes TheftYesNoYes Damaged/spoiledYesNoPartial Improper returnsYes Mis-shipment from DC Yes Cashier errorYes

8. So what can we do? More frequent cycle counts Eliminate / reduce source

9.  Cycle counting When to count? How often to count? What to count?  Currently, retailers have very little flexibility in answering these 3 questions

10. Barcode In 3 different settings, a 96% reduction in labor to cycle count (RFID handheld vs. barcode scanner) Barcode avg = 200 items per hour RFID avg = 5000 items per hour

11. Inventory Accuracy Store execution Theft

14.  Based on multiple studies … Before RFID:

15.  Based on multiple studies … After RFID:

16. Inventory Accuracy Store execution Theft OOS

17.  Recognizing out of stocks  Acting upon this information Awareness Prevention

18.  Worldwide average out of stock: ~8%  Potential sales loss to retailers: ~3.2%  Potential sales loss for suppliers: ~2.8%

22. Inventory Accuracy Store execution Theft OOS 2%, 3%, 10% reductions Supplier benefit

23. Inventory Accuracy Store execution Theft OOS Excess inventory 6%, 7%, 12% reductions 4.9 months supply to 2 months

24. Inventory Accuracy Customer satisfaction Store execution Theft OOS Excess inventory

25. Inventory Accuracy SalesCustomer satisfaction Store execution Theft OOS Excess inventory 2%, 3%, 14%, 15% Reduce markdowns / increase margins

26. Inventory Accuracy Forecasts SalesCustomer satisfaction Replenish- ment Store execution Theft OOS Excess inventory

27. Inventory Accuracy Forecasts SalesCustomer satisfaction Replenish- ment Store execution Theft OOS Dressing room Faster checkout Locating product Excess inventory

28.  Inventory accuracy  Out of stocks  Locating product  Loss prevention The big four

29.  How many people abandon a store because they cannot find the product they want? What do we have (inventory accuracy issue)? Where is it?

30. LocationEPCDate/timeReader DC 1230023800.241813.50000002410-04-09 23:15inbound DC 1230023800.241813.50000002510-04-09 23:22inbound DC 1230023800.241813.50000002410-08-09 7:15outbound DC 1230023800.241813.50000002510-09-09 8:23outbound ST 9870023800.241813.50000002410-08-09 20:31inbound ST 5670023800.241813.50000002510-09-09 19:10inbound ST 9870023800.241813.50000002410-09-09 20:54sales floor ST 5670023800.241813.50000002510-12-09 5:17sales floor If the product needed to be on the floor by 10/10/09 for the promotion, store 567 just missed an important window of opportunity – for themselves and for the supplier …

31. Backroom or sales floor?

32. On pallet rack in warehouse or sales floor (e.g., Sam’s)

33. With handheld or smart shelves

34. In 3-D space?

36. Insights / possibilities …  Complete visibility Product and process tracer Where is shrinkage occurring? Visibility where you don’t have it today  e.g., employee entrances; box crusher / trash

37. Test Store --Employee entrance Customer entrance 10 jeans carried in stack; walking100%93% 10 jeans carried in stack; running90%67% 2 jeans in bag; walking100% 5 jeans in bag; walking100% 1 jeans concealed under arm; walking100%0% 2 jeans concealed under arm; running50%67% *Real life theft: more than $3500 in merchandise left the store without being paid for …

38.  Technology Smaller, better, faster, cheaper Commodity pricing Variety of devices Variety of sensors Infrastructure considerations (fixed, mobile, shielding, etc.) It works, but must be deployed properly (data issue)

39.  Critical mass  Unrealistic expectations  Displacement of existing technology  Incremental vs. radical/disruptive: paving the cow paths  Massive investment / ROI / cost  People! (change management)  What to do with all this information …..

40. Bill Hardgrave hardgrave@auburn.edu For copies of white papers, visit http://itri.uark.edu/research Keyword: RFID