Price Support (Vendor Rebates) Outside Vendor Window Black Belt: Debbi Youmans-McCreary Division: INA - eIKON BU – Ops/Vendor Credits/Southeast

2 Agenda: DMAIC Process n D efine – Project Definition, Defect, Scope and DPMO n M easure – Data Collection n A nalyze – FMEA and Hypothesis Testing n I mprove – Pilot and Benefits n C ontrol – Control Charts and Process Ownership n Question and Answer n Appendix

3 Define: Problem Statement and Defect Definition n Problem: IKON does not currently take advantage of all price support (vendor rebates) available on registered customers. Orders that are not identified as price supported at the time of booking are not routed to the VCTS system and are potentially lost rebates. n Defect: Orders for customers registered with Canon for which IKON does not claim price support. n Goal: Improve visibility and accuracy of input data to ensure all price support credits are taken. n Scope: Canon Price Supports in the Southeast and Central Regions (Oracle 11.I) with leveragability to all future Oracle 11.I. Regions

4 Team Members n Project Champions – Linda Frisinger, Ops and Bruce Fiscus, Sales n Core Team – n Ben Rotz, eIKON Sales n Trish Daly, Financial Analyst n Mark Armstrong, Sales n JoAnn Walton and Kris Schneider, Vendor Credit Specialists n Becky Finger, Cindy Bourgeois and Bonnie Gilbert, Order Management n Martha Brennaman, MSSC A/P n Trish Daly, FA n Linda Hampel, IT n Master Black Belt – Bob Conrad

5 Measure: DPMO and Sigma Level n DPMO (Total number of registrations including not entered): n 116,000 based on Canon’s registration file compared to IKON’s Oracle Sales On-Line registration file. n Sigma Level – 1.2 long term

6 Measure: Where is the data? Claims to Credits data for through Reconcile Canon to IKON’s OSO OSO Registrations eIKON equipment orders From 7/31/02-7/31/03 Match to registrations to ID $$

7 Analyze: FMEA Sales Entry Errors Score FMEA Risk Scores Data Sample (based on 11,000 of the 21,000 registered parties) # of Errors

8 Analyze: Hypothesis – Make registrations visible for VCS to file for credits! SALES: Registration VCS: Claims to Credits 10% Loss Rate Loss Rate: 16% Late 4% Other Theory: Get visibility from registration (anticipation) to reduce loss rates.

9 Analyze: Regression - SED Anticipated vs. Actual Credits Explains 81% of variation between anticipated and actual If registrations cannot be anticipated through VCTS, then IKON will not be able to file credits.

10 Analyze: Regression - CER Anticipated vs. Actual Credits Explains 77% of variation between anticipated and actual If registrations cannot be anticipated through VCTS, then IKON will not be able to file credits.

11 Improve: Pilot Process n Reconcile Canon’s system to IKON’s system then use exception reports to match to invoices that are not coded as price supported to file with Canon (automated process) n Pull registration and invoice reports (run via script each week) n Identify and correct unmatched registrations n Compare unmatched registrations to equipment invoices for the week n File claims with Canon

12 Improve: DPMO Decrease from 110,000 to ZERO IKON can reconcile 100% of Canon Registrations for Oracle 11.I.!

13 Improve: Benefits

14 Control: Who, What, When, How? n MSSC, Manager Vendor Marketing, Charles Adams, is the process owner. VCS personnel, Kris Schneider, works CER and JoAnn Walton, works SED corrections. n Charles updates three charts weekly and validates the process is in Control. If not, he follows up with the Vendor Credit Specialists or IT. n Registrations – LCL cannot fall below 78% n Claims – Aging cannot exceed 60 days n Customer Database n References for corrective actions - BP_OP_01_ and BP_CP_01_50-400

15 Project Summary n Visibility to all Canon registrations (COGS) n Reduction of manual research (Production) n Benefits of $876,942 (Reduction to COGS) n Chartered for SED, but expanded to include CER (COGS and Production) n Leveragability to Oracle 11.I. Regions (COGS and Production) n Identification of three new project charters (COGS and Production)

16 Conclusion Questions and Discussion

17 Appendix n Registrations – Perfect Match, Correction Needed, Unmatched n Project Charters (and potentials) Identified n OMD Reporting – Project No n Ricoh Registrations – Project No n New Charters proposed n Claims Not Received (data attached) n Reasons for Claims Not Received (data attached) n Registrations across District/Region paths to raise credit levels

18 Control: Registrations Below 77% is unsustainable due to manual re-work. Process must not fall below this line. Process will increase to above 80%.

19 Potential Claims Project n DPMO (Claims to credits): n 200,000 based on total claims per VCTS to total credits received per VCTS (7/31/02-7/31/03). For SED, in 2003, this loss totaled $550k. n Sigma Level –.8 long term

20 Measure: FMEA Invoice and Serial Number Errors Score # of Samples Data Sample FMEA Scores