A case study on how to implement a world class forecasting process to achieve world class forecast accuracy performance

1. Stephen P. Crane, CSCP, Director Strategic Supply Chain Management Institute of Business Forecasting & Planning Conference Phoenix, AZ February 22-24, 2009 A ROADMAP TO WORLD CLASS FORECASTING ACCURACY Six Keys to Improving Forecast Accuracy

9. INVENTORY LEVEL VS. FORECAST ACCURACY Source: Aberdeen Group 2008

16. WORLD CLASS FORECASTING ACCURACY REQUIRES MAKING THE RIGHT DECISIONS

19. SALES & OPERATIONS PLANNING PROCESS Supply Networking Planning WD 1- 6 Submit Supply Plan with Documented Options Approve Supply Plan Sequential Business Unit Planning [WD 1-5] Finalize & Approve Supply Plan [WD 6] Upload WD 1 Inventory Develop Updated Supply Plan Proposal Review Supply Shortage & Capacity Overload Alerts Resolve Supply Alerts Adjust Target Stock Levels Fix SNP Planned orders Enter Adjusted Demand Supply Planning WD 13 -End Adjust Supply Planning Constraints Supply Network Planning Preparation Phase Analyze Draft Supply / Capacity Plan Update Supply Change Summary Submit Off System Demand Figures Update Loc Shift Table For Future Source Changes Release FC to R3 For MRP Update Master Data & Upload Inventory Refresh Inactive Version / Release DP to SNP Review Supply Planning Metrics Preferred Sources Assigned to Demand Forecasting & Demand Planning WD 0 -16 Add New Business Entries in R3 Upload New Sales History & Business Combos Apply Future Demand Changes Create Statistical Forecast DP Passed to CO for Financial Forecast Demand Planning Data Preparation Phase [WD 0-7] Review Historical Sales Data Create Unconstrained Demand Plan [WD 8-16] Review Final Sales Manager Figures Review Demand Metrics Review FC Adjustments with Sales Managers BT/BU Review & Approve Unconstrained Demand Plan Update Demand Change Summary Apply Planning Type Assignments Apply Historical Sales Data Adjustments APO Data Passed to BW Publish Unconstrained Demand Plan Approve Supply Chain Plans WD 7-8 Agree & Communicate Approved Plans Communicate Implications to Financial & Sales Plans Partnership Meeting [WD 7] Executive S&OP [WD 8] Review Action Items from Last Month Review Revenue Projections Review Unconstrained Demand Plan Exceptions Review Supply Options & Cost Projections Review Performance Metrics Summarize Supply Chain Plans Review Financial Plan Key Business Issues & Resolution Review Supply Chain Plans Review Performance Metrics Review Action Items from Last Month Automated Jobs

28. STEP 3: FORECASTING SEGMENTATION - 80/20 ANALYSIS It is crucial to distinguish the “high-value” items for special attention while automating the “not-as-valuable” items High Low Statistical Forecastability (measured by 1/COV) High Sales Volume/Impact Low Manage by Exception using Exception Reports Collaborate with Customer (if possible) High Impact Items Non-High Impact Items Use Data Aggregation in Statistical Model for all Non-HI Items Gather Business Intelligence for all HI items ~ 80% Total Volume COV (Coefficient of Variation) = STD Deviation/Ave. Demand Notes

29. STEP 3: FORECASTING SEGMENTATION EXAMPLE

34. STEP 5: SALES ADJUSTMENTS TO STATISTICAL FORECAST Accurate forecasting is not just getting a forecast from the customer. The customer isn’t always right!

41. ACCURACY OF FORECAST ADJUSTMENTS (Units in KGS) Statistical Forecast Final S&OP Forecast (Includes Forecast Adjustments) Impact +/- Ship-to Customer Jun06 Stat Fcst Stat Fcst Abs Error Jun06 S&OP Final S&OP Abs Error Impact +/- Customer A 2,167,904 1,465,968 701,936 1,691,155 476,749 225,187 Customer B 286,650 494,531 207,881 281,859 4,791 203,090 Customer C 316,315 454,387 138,072 313,809 2,506 135,566 Customer D 743,619 906,002 162,383 680,000 63,619 98,764 Customer E 20,266 0 20,266 50,000 29,734 (9,467) Customer F 244,023 370,466 126,443 205,698 38,325 88,117 Customer G 332,211 252,729 79,482 330,000 2,211 77,271 Customer H 20,312 40,547 20,236 113,400 93,088 (72,853) Customer I 50,000 130,416 80,416 80,000 30,000 50,416 Customer J 301,221 111,502 189,719 159,757 141,464 48,255 Customer K 40,479 56,471 15,992 102,000 61,521 (45,529) Customer L 142,709 84,879 57,830 155,800 13,091 44,739 Customer M 163,592 237,196 73,604 193,000 29,408 44,196 Customer N 0 1,603 1,603 40,000 40,000 (38,397) Customer O 40,615 0 40,615 37,800 2,815 37,800 Customer P 0 52,893 52,893 16,000 16,000 36,893 Customer Q 152,434 194,153 41,719 140,000 12,434 29,285 Jun06 Act

42. ACCURACY OF FORECAST ADJUSTMENTS Accurate customer intelligence provided by Sales can significantly improve forecast accuracy (Units in KGS) If adjustments to the statistical forecast do not improve forecast accuracy, why make them Month Actual Demand Stat Forecast Stat Forecast Error S&OP Forecast S&OP Forecast Error Impact Jan06 6,091,955 7,593,962 5,196,370 5,918,751 1,886,262 54.3% Feb06 9,147,987 8,661,173 4,497,213 9,061,139 3,013,993 16.2% Mar06 11,570,962 11,932,441 3,992,114 12,448,817 2,885,691 9.6% Apr06 10,625,650 12,512,901 5,348,524 13,477,086 4,550,418 7.5% May06 10,815,034 9,840,902 3,791,501 11,297,905 3,059,782 6.8% Jun06 8,817,693 9,041,067 3,697,356 9,311,634 2,569,887 12.8% Last 6 Month Ave. 57,069,281 59,582,446 26,523,078 61,515,332 17,966,033 15.0%

47. FORECAST ACCURACY IMPROVEMENT (Product Mix Level) Process, People, Statistical Forecasting Exception Analysis Forecast Adjustments Forecast Segmentation Data Aggregation World Class + 6% + 15% + 7%

48. 38% Improvement 2004 2007 PRODUCTION PLAN ADHERENCE SUPPLY PLANNING ACCURACY

49. 21% Improvement 2004 2007 FINANCIAL FORECAST ACCURACY

50. ACTUAL FORECAST DEVIATION TREND Forecast deviation at product level APO Go-Live Target .0 .1 .2 .3 .4 .5 Jul-07 Aug-07 Sep-07 Oct-07 Nov-07 Dec-07 Jan-08 Feb-08 Mar-08 Apr-08 May-08 Jun-08 Jul-08 Aug-08 Sep-08 Oct-08 Nov-08 Dec-08 Jan-09 Forecast Deviation AP WACKER

52. CONCLUSIONS If you follow the Roadmap to improve your companies sales forecasting practices, you will experience reductions in costs and increases in customer and employee satisfaction. Costs will decline in inventory levels, raw materials, production, and logistics. But the first step a company must take before realizing these kind of benefits, is to recognize the importance of sales forecasting as a management function, and be willing to commit the necessary resources to becoming world class.

53. The Wacker Group THANK YOU FOR YOUR ATTENTION Stephen P. Crane Director Strategic Supply Chain Management [email_address] CREATING TOMORROW'S SOLUTIONS