1. 1 How to Set Performance Targets in Inventory Control Dr. Everette S. Gardner, Jr.

2. 2 How to Set Performance Targets in Inventory Control  Clean up the parts list  Develop a basic forecasting system  Use the forecasts to classify parts (ABC+)  Decide what to stock  Decide where to stock it  Divide the inventory into control groups:  JIT, MRP, EOQ, Annual buy  Develop benchmark performance measures

3. 3 Clean Up the Parts List  Code substitute items  Ensure historical demand recorded against primary items  Delete obsolete items (no longer used in current product line)  Do the part numbers apply to other customers or products?  Review items with no recent demand  Stocking rules usually depend on demand in the last 6 months or the last year  Negotiate with vendors to return parts for credit

4. 4 Water Filtration Company: Status of 23,192 inventory items

5. 5 The Importance of Forecasting  Forecasts determine production and inventory quantities  MRP: Master schedule  EOQ: Order quantity, leadtime demand, safety stock  JIT: Requirements to internal and external suppliers

6. 6 The Importance of Forecasting (cont.)  Better forecast accuracy cuts inventory investment. Example:  Forecast accuracy is measured by the standard deviation of the forecast error.  Safety stocks are usually set at 3 times the standard deviation  If the standard deviation is cut by $1, safety stocks are cut by $3

7. 7 Forecasting Tools for Inventory Control  Simple exponential smoothing  Weighted-moving-average technique for stable items  Highly recommended for repair parts demand  Trend-adjusted exponential smoothing  Estimates and projects growth (or decline) in demand  Types of growth  Exponential  Linear  Damped  Both models are easily modified to handle seasonal demands

8. 8 Origins of the Damped Trend  Reference  Gardner & McKenzie, Management Science, 1985  Operational requirement  Automatic forecasting system for military repair and maintenance parts  Theory  Lewandowski, IJF, 1982 (M1-Competition) Trend extrapolation should become more conservative as the forecast horizon increases.

9. 9 The Damped Trend 1)Error = Actual demand – Forecast 2)Level= Forecast + Weight 1 (Error) 3)Trend =  (Previous trend) + Weight 2 (Error) 4)Forecast for t+1= Level +  Trend 5)Forecast for t+2 = Level +  Trend +  2 Trend.

10. 10 Automatic Forecasting with the Damped Trend  Constant-level data  Forecasts emulate simple smoothing  Consistent trend  Forecasts emulate Holt’s linear trend  Erratic trend  Forecasts are damped

11. 11 Automatic Forecasting with the Damped Trend In constant-level data, the forecasts emulate simple exponential smoothing:

12. 12 In data with a consistent trend and little noise, the forecasts emulate Holt’s linear trend: Automatic Forecasting with the Damped Trend

13. 13 Automatic Forecasting with the Damped Trend When the trend is erratic, the forecasts are damped:

14. 14 Automatic Forecasting with the Damped Trend The damping effect increases with the level of noise in the data:

15. 15 11-Oz. Corn chips Monthly Inventory and Sales Actual Inventory Sales

16. 16 Damped-trend performance 11-oz. Corn chips Outlier

17. 17 Investment analysis: 11-oz. Corn chips

18. 18 Safety stocks vs. shortages

19. 19 Safety stocks vs. forecast errors Safety stock Forecast errors

20. 20 11-Oz. Corn chips Target vs. actual packaging inventory Actual Inventory from subjective forecasts Month Target maximum inventory based on damped trend Actual Inventory from subjective forecasts Monthly Usage

21. 21 How to forecast regional demand Forecast total units with the damped trend Forecast regional percentages with simple exponential smoothing

22. 22 Regional sales percentages: Corn chips

23. 23 Target Inventory Analysis  Actual inventory based on subjective decisions: $182.6 million  Target inventory based on the damped trend and EOQ/Safety stocks: $135.0 million  Projected savings: $47.6 million

24. 24 Water Filtration Company: Inventory Classification Active Items (some demand in past year) ClassClass Limits Total nbr. of items Percent of items Total sales forecast Percent of forecast A> $36,0003644%$11,743,61060% B$600 - $35,9994,23246%$7,316,99938% C< $6004,66850%$365,6052% Totals9,264100%$19,426,214100%

25. 25 Water Filtration Company: Inventory Classification ClassDefinition Number of items Percent of items Active ItemsAActive items: Sales > $36,0003641.51% BActive items: Sales $600-$35,9994,23217.6% CActive items: Sales < $6004,66819.42% Slow MoversZZero forecast items: no hits in 6 mon.1,5486.44% DDisposal items: no hits in 12 mon.11,52647.95% Buys not basedXOne-time buys1460.61% on demandNNew items: established in last 12 mon.9684.03% MiscellaneousFFree (no-cost) items270.11% PProblem items (missing data)5602.33% Totals24,039100.0%

26. 26 What to Stock?  Compare costs  Cost to stock = (Avg inventory balance x holding rate) + (number of stock orders x transportation cost)  Cost to not stock = Number of customer orders x transportation cost  Transportation costs for not stocking may be both in- and out bound, depending on whether we choose to drop-ship from the vendor

27. 27 What to Stock? (cont.)  Simplify decisions using “hit” rules  A “hit” is one customer order for any number of units. Cost comparisons usually result in minimum number of hits that must occur before it is economical to stock.  Example:  Class A 6 hits in 6 months  Class B 4 hits in 6 months  Class C 3 hits in 12 months

28. 28 Water Filtration Company: Inventory Status as of July, 2009 ClassDefinition Minimum hits to stock Excess stock qty. Nbr items stocked Nbr items not stockedTotal A Active items: Sales > $36,000 6 in 6 mon.> 6 mon.29074364 B Active Items: Sales $600 - $35,999 3 in 6 mon.> 6 mon.3,1081,1244,232 CActive items: Sales < $6004 in 12 mon.> 12 mon.2,9381,7304,668 Z Zero forecast items: no hits in 6 mon. -All-1,548 D Disposal items: no hits in 12 mon. -All-11,526 XOne-time buys-All-146 N New items: established in last 12 mon. - Same as ABC 170628968 Totals6,50616,77623,452

29. 29 Where to Stock?  Centralized order entry is mandatory  Apply the hit rules by location  This automatically tailors the range of stock to the customer base at each location  Must designate who suppliers whom when a hit occurs at a non-stocking location  Recognize that consolidating stocks makes dramatic reductions in total inventory investment

30. 30 Stocking Warehouses LA forecastFL forecastCA/OR forecast 1 LA + FLLA + CA/ORFL only0 2 LA + CA/ORLA + FL0CA/OR only 3 FL + CA/OR0LA + FLCA/OR only Who Supplies Whom?

31. 31 Effects of Consolidating Inventories: Manufacturer of Communication Systems Number of Warehouses Investment (millions)

32. 32 Original ClassResult of monthly reviewAction N (new items)Enough hits in last 6 months to stock. Generate forecast, change N to A,B, or C At least 1 hit in last 6 months, but not enough to stock Generate forecast, change N to A, B, or C No hits in last 6 months, but hits occurred 7-12 months ago Set forecast = zero, change N to Z (zero forecast) No hits in last yearChange N to D (disposal) A, B, or C (active items) No hits in last 6 monthsSet forecast = zero, Change A, B, or C to Z (zero forecast) Z (zero forecast)No hits in last 12 monthsChange Z to D (disposal) 1 or more hitsChange Z to A, B, or C D (disposal items)1 or more hitsGenerate forecast, Change D to A, B, or C Monthly Item Migration Processing

33. 33 Control System Inventory Class Production Schedule Lead-time Behavior JITA, BLevelCertain MRPA, BVariableReliable EOQ/Safety Stock A, BVariable Annual buyCAny

34. 34 The Economic Order Quantity (EOQ)  Controls  Cost per order  Holding rate (% of inventory value)  The EOQ  Increases with the order cost  Decreases with the holding rate  Do not treat order cost and holding rate as fixed values. Instead, do what-if analysis to hit target values for  Inventory investment on the balance sheet  Stock replenishment workload

35. 35 Inventory tradeoffs for Class B items Number of Class B active items3,600 Sum of annual demand forecasts$14,337,666 Sum of monthly demand forecasts$1,194,806 Inventory carrying cost20.00% Order Cost Maximum InvestmentNumber of annual buys EOQ in weeks of stock TotalAvg. per itemTotalAvg. per itemMinMax $5 $1,428,356$39728,5677.92.614.9 102,020,000$56120,2005.63.621.0 152,473,985$68716,4934.64.525.8 202,856,711$79414,2824.05.229.8

36. 36 Class Control System Number of Items Maximum Investment Number of Annual Buys AJIT1,412$4,945,00016,944 BEOQ3,999$10,820,00015,996 CAnnual Buy8,688$2,004,0008,688 Totals14,099$17,769,00041,628 Communications Systems Manufacturer: Target inventory values for fiscal 2009

37. 37 ClassDefinitionNbr itemsOn-handExcessOn-order A,B,CActive items: On-hand ok5,754$3,884,064$0$1,958,932 A,B,CActive items: On-hand excessive584$887,048$491,960$23,220 A,B,C,Z Not enough hits to stock or zero forecast 3,878$943,950$902,774$27,398 D Disposal items: no hits in 12 mon. 2,336$458,968$458,160$121 XOne-time buys12$5,128 $0 N New items: established in last 12 mon. 404$127,124$121,534$93,362 Totals12,968$6,307,626$1,979,556$2,103,033 Water Filtration Company: Inventory Values

38. 38 Annual Purchasing Workload Estimates New System: Stock buys Old System: Stock buys Class Nbr items stocked Annual reorders per item Annual reorders per classClass Nbr items stocked Annual reorders per item Annual reorders per class A (JIT)290123,480A(JIT)290123,480 B(EOQ)3,108412,432B(EOQ)3,1081237,296 C(Ann.)2,9381 C(Ann.)2,9381235,256 Total18,850Total76,032 New system: Worst case estimate of number of drop-ship buys Summary: Workload comparisons Class Nbr items not stocked Max# hits for no- stock item Number of drop- ship buys Old systemNew system Stock buys 76,03218,850 A (JIT)7411814Drop-ship buys ?11,624 B(EOQ)112455,620New items, one time buys 600 C(Ann.)173035,190Redistribution actions ?1,600 Total11,624Total 76,63232,674

39. 39 Lead-times Lead-time exceptions4.5% Average lead-time3.20 Stock Levels Target$19,900,878 Actual$23,422,012 Excess$3,521,134 Stock Status Items in stock92.20% Items out of stock7.80% Items Out of Stock With open order82.2% No open order17.8% Customer Orders Percent shipped complete94.3% Warehouse Refusals Percent occurrence2.8% Monthly Inventory Performance Report

40. 40 Conclusions  Forecasting drives any inventory control system  Standard ABC classification doesn’t go far enough  Decision rules for what/where to stock must be established early

41. 41 Conclusions (cont.)  Performance measurement is essential to:  Justify a new system  Tailor the system to the inventory  Track progress

42. 42 Conclusions (cont.)  The best inventory system is likely to be a hybrid of:  JIT  MRP  EOQ  Annual buy