1 How to Set Performance Targets in Inventory Control Dr. Everette S. Gardner, Jr.
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Transcript of 1 How to Set Performance Targets in Inventory Control Dr. Everette S. Gardner, Jr.
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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
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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
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Water Filtration Company: Status of 23,192 inventory items
4,202 with inadequate
demand to stock18%
2,928 substitute items13%
2,200 obsolete9%
7,526 with no hits in 12 months
33%
6,336 active items27%
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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
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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
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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
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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 moreconservative as the forecast horizon increases.
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The Damped Trend
1) Error = Actual demand – Forecast
2) Level= Forecast + Weight1(Error)
3) Trend = (Previous trend) + Weight2(Error)
4) Forecast for t+1= Level + Trend
5) Forecast for t+2 = Level + Trend + 2 Trend
.
.
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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
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30
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34
35
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Automatic Forecasting with the Damped TrendIn constant-level data, the forecasts emulate simple exponential smoothing:
12
20
25
30
35
40
45
50
55
60
In data with a consistent trend and little noise, the forecasts emulate Holt’s linear trend:
Automatic Forecasting with the Damped Trend
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Automatic Forecasting with the Damped Trend
When the trend is erratic, the forecasts are damped:
20
25
30
35
40
45
50 Saturation level
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Automatic Forecasting with the Damped TrendThe damping effect increases with the level of noise in the data:
20
25
30
35
40
45
50
Saturation level
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Damped-trend performance11-oz. Corn chips
$200,000
$250,000
$300,000
$350,000
$400,000
$450,000
$500,000
Actual
ForecastOutlier
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Investment analysis: 11-oz. Corn chipsForecast annual usage $4,138,770
Economic order quantity $318,367
Standard deviation of forecast errors $34,140
Nbr. shortages
per 1,000 Probability Safety Order Maximum
order cycles of shortage stock quantity investment
100.0000 0.1000 $43,758 $318,367 $362,12550.0000 0.0500 $56,167 $318,367 $374,5341.0000 0.0010 $105,510 $318,367 $423,8770.0100 0.0000 $145,601 $318,367 $463,9680.0001 0.0000 $177,496 $318,367 $495,863
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Safety stocks vs. shortages
$0
$20,000
$40,000
$60,000
$80,000
$100,000
$120,000
$140,000
$160,000
$180,000
$200,000
0 10 20 30 40 50 60 70 80 90 100
Shortages per 1,000 order cycles
Saf
ety
stoc
k
Target
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Safety stocks vs. forecast errors
($200,000)
($150,000)
($100,000)
($50,000)
$0
$50,000
$100,000
$150,000
$200,000Safety stock
Forecast errors
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11-Oz. Corn chipsTarget vs. actual packaging inventory
Actual Inventory from
subjective forecasts
Month
$0
$500,000
$1,000,000
$1,500,000
$2,000,000
$2,500,000
Target maximum inventory based on damped trend
Actual Inventory from
subjective forecasts
Monthly Usage
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How to forecast regional demand
Forecast total units with the damped trend
Forecast regional percentages with simple exponential smoothing
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Regional sales percentages: Corn chips
0%
10%
20%
30%
40%
50%
Mar Jun Sep Dec Mar Jun Sep Dec
South
West
North
East
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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
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Water Filtration Company:Inventory Classification
Active Items (some demand in past year)
Class Class LimitsTotal nbr. of items
Percent of items
Total sales forecast
Percent of forecast
A > $36,000 364 4% $11,743,610 60%
B $600 - $35,999 4,232 46% $7,316,999 38%
C < $600 4,668 50% $365,605 2%
Totals 9,264 100% $19,426,214 100%
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Water Filtration Company:
Inventory Classification
Class Definition
Number of items
Percent of items
Active Items A Active items: Sales > $36,000 364 1.51%
B Active items: Sales $600-$35,999 4,232 17.6%
C Active items: Sales < $600 4,668 19.42%
Slow Movers Z Zero forecast items: no hits in 6 mon. 1,548 6.44%
D Disposal items: no hits in 12 mon. 11,526 47.95%
Buys not based X One-time buys 146 0.61%
on demand N New items: established in last 12 mon. 968 4.03%
Miscellaneous F Free (no-cost) items 27 0.11%
P Problem items (missing data) 560 2.33%
Totals 24,039 100.0%
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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
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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
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Water Filtration Company:
Inventory Status as of July, 2009
Class DefinitionMinimum
hits to stockExcess
stock qty.Nbr items stocked
Nbr items not stocked Total
AActive items: Sales > $36,000
6 in 6 mon. > 6 mon. 290 74 364
BActive Items: Sales $600 - $35,999
3 in 6 mon. > 6 mon. 3,108 1,124 4,232
C Active items: Sales < $600 4 in 12 mon. > 12 mon. 2,938 1,730 4,668
ZZero forecast items: no hits in 6 mon.
- All - 1,548 1,548
DDisposal items: no hits in 12 mon.
- All - 11,526 11,526
X One-time buys - All - 146 146
NNew items: established in last 12 mon.
-Same as
ABC170 628 968
Totals 6,506 16,776 23,452
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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
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Stocking Warehouses
LA forecast FL forecast CA/OR forecast
1 LA + FL LA + CA/OR FL only 0
2 LA + CA/OR LA + FL 0 CA/OR only
3 FL + CA/OR 0 LA + FL CA/OR only
Who Supplies Whom?
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Effects of Consolidating Inventories: Manufacturer of Communication Systems
1.5
2.5
3.5
4.5
5.5
6.5
1 2 3 4
Number of Warehouses
Inve
stm
en
t (m
illio
ns
)
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Original Class Result of monthly review Action
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 year Change N to D (disposal)
A, B, or C
(active items)
No hits in last 6 months Set forecast = zero,
Change A, B, or C to Z (zero forecast)
Z (zero forecast) No hits in last 12 months Change Z to D (disposal)
1 or more hits Change Z to A, B, or C
D (disposal items) 1 or more hits Generate forecast,
Change D to A, B, or C
Monthly Item Migration Processing
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Control System
Inventory Class
Production Schedule
Lead-time Behavior
JIT A, B Level Certain
MRP A, B Variable Reliable
EOQ/Safety Stock
A, B Variable Variable
Annual buy C Any Any
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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
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Inventory tradeoffs for Class B items
Number of Class B active items 3,600
Sum of annual demand forecasts $14,337,666
Sum of monthly demand forecasts $1,194,806
Inventory carrying cost 20.00%
Order
Cost
Maximum Investment Number of annual buysEOQ in weeks of
stock
Total Avg. per item Total Avg. per item Min Max
$5 $1,428,356 $397 28,567 7.9 2.6 14.9
10 2,020,000 $561 20,200 5.6 3.6 21.0
15 2,473,985 $687 16,493 4.6 4.5 25.8
20 2,856,711 $794 14,282 4.0 5.2 29.8
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ClassControl System
Number of Items
Maximum Investment
Number of Annual Buys
A JIT 1,412 $4,945,000 16,944
B EOQ 3,999 $10,820,000 15,996
C Annual Buy 8,688 $2,004,000 8,688
Totals 14,099 $17,769,000 41,628
Communications Systems Manufacturer:Target inventory values for fiscal 2009
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Class Definition Nbr items On-hand Excess On-order
A,B,C Active items: On-hand ok 5,754 $3,884,064 $0 $1,958,932
A,B,C Active items: On-hand excessive 584 $887,048 $491,960 $23,220
A,B,C,ZNot enough hits to stock or zero forecast
3,878 $943,950 $902,774 $27,398
DDisposal items: no hits in 12 mon.
2,336 $458,968 $458,160 $121
X One-time buys 12 $5,128 $5,128 $0
NNew items: established in last 12 mon.
404 $127,124 $121,534 $93,362
Totals 12,968 $6,307,626 $1,979,556 $2,103,033
Water Filtration Company: Inventory Values
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Annual Purchasing Workload Estimates
New System:
Stock buys
Old System:
Stock buys
ClassNbr items
stocked
Annual reorders per item
Annual reorders per class Class
Nbr items stocked
Annual reorders per item
Annual reorders per
class
A (JIT) 290 12 3,480 A(JIT) 290 12 3,480
B(EOQ) 3,108 4 12,432 B(EOQ) 3,108 12 37,296
C(Ann.) 2,938 1 2,938 C(Ann.) 2,938 12 35,256
Total 18,850 Total 76,032
New system: Worst case estimate of number of drop-ship buys
Summary:
Workload comparisons
ClassNbr items
not stocked
Max# hits for no-
stock item
Number of drop-
ship buys
Old system New system
Stock buys 76,032 18,850
A (JIT) 74 11 814 Drop-ship buys ? 11,624
B(EOQ) 1124 5 5,620 New items, one time buys 600 600
C(Ann.) 1730 3 5,190 Redistribution actions ? 1,600
Total 11,624 Total 76,632 32,674
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Lead-times
Lead-time exceptions 4.5%
Average lead-time 3.20
Stock Levels
Target $19,900,878
Actual $23,422,012
Excess $3,521,134
Stock Status
Items in stock 92.20%
Items out of stock 7.80%
Items Out of Stock
With open order 82.2%
No open order 17.8%
Customer Orders
Percent shipped complete 94.3%
Warehouse Refusals
Percent occurrence 2.8%
Monthly Inventory Performance Report
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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
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Conclusions (cont.)
Performance measurement is essential to: Justify a new system Tailor the system to the inventory Track progress