Homework 12
Supply Chain Management: Strategy, Planning, and Operation
Seventh Edition
Chapter 12
Managing Uncertainty in a Supply Chain Safety Inventory
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Learning Objectives (1 of 2)
12.1 Understand the role of safety inventory in a supply chain.
12.2 Identify factors that influence the required level of safety inventory.
12.3 Evaluate the appropriate level of safety inventory for a supply chain.
12.4 Discuss the impact of supply uncertainty on safety inventory.
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Learning Objectives (2 of 2)
12.5 Understand how aggregation helps reduce the required safety inventory in a supply chain.
12.6 Determine the impact of replenishment policies on safety inventory.
12.7 Improve the management of safety inventory in a multiechelon supply chain.
12.8 Identify managerial levers that lower safety inventory without hurting product availability.
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The Role of Safety Inventory (1 of 3)
Safety inventory is carried to satisfy demand that exceeds the amount forecasted
Raising the level of safety inventory increases product availability and thus the margin captured from customer purchases
Raising the level of safety inventory increases inventory holding costs
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The Role of Safety Inventory (2 of 3)
Figure 12-1 Inventory Profile with Safety Inventory
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The Role of Safety Inventory (3 of 3)
Three key questions
What is the appropriate level of product availability?
How much safety inventory is needed for the desired level of product availability?
What actions can be taken to reduce safety inventory without hurting product availability?
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Summary of Learning Objective 1
Safety inventory helps a supply chain provide customers with a high level of product availability in spite of supply and demand uncertainty. It is carried just in case demand exceeds the amount forecasted or supply arrives later than expected.
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Factors Affecting the Level of Safety Inventory
The desired level of product availability
The uncertainty of demand
The uncertainty of supply
Inventory replenishment policies
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Measuring Product Availability
Product fill rate (fr)
Fraction of product demand satisfied from product in inventory
Order fill rate
Fraction of orders filled from available inventory
Cycle service level (C S L)
Fraction of replenishment cycles that end with all customer demand being met
Replenishment cycle – the interval between two successive replenishment deliveries
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Measuring Demand Uncertainty
D = Average demand per period
σD = Standard deviation of demand (forecast error) per period
Lead time (L) is the gap between when an order is placed and when it is received
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Evaluating Demand Distribution over L Periods
The coefficient of variation
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Measuring Supply Uncertainty
Lead time (L) is normally distributed with
L = Average lead time
σL = Standard deviation of lead time
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Replenishment Policies
Continuous review
Inventory is continuously tracked
Order for a lot size Q is placed when the inventory declines to the reorder point (R O P)
Periodic review
Inventory status is checked at regular periodic intervals
Order is placed to raise the inventory level to a specified threshold
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Summary of Learning Objective 2
Safety inventory is influenced by the desired product availability, demand uncertainty, replenishment lead times, and lead time variability. Product availability is measured using the fill rate or cycle service level. Demand uncertainty is measured by the forecast error. For lead time one measures both the mean and the standard deviation. The required safety inventory is also influenced by the inventory policy implemented. Continuous review policies order a fixed quantity after variable replenishment intervals. Periodic review policies order variable quantities after fixed replenishment intervals.
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Determining the Appropriate Level of Safety Inventory (1 of 8)
Evaluating Safety Inventory Given a Reorder Point
Expected demand during lead time = D × L
Safety inventory, ss = R O P − D × L
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Determining the Appropriate Level of Safety Inventory (2 of 8)
Average demand per week, D = 2,500
Standard deviation of weekly demand, sD = 500
Average lead time for replenishment, L = 2 weeks
Reorder point, R O P = 6,000
Average lot size, Q = 10,000
Safety inventory, ss = R O P −D L = 6,000 −5,000 = 1,000
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Determining the Appropriate Level of Safety Inventory (3 of 8)
Average inventory = cycle inventory + safety inventory
= 5,000 + 1,000 = 6,000
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Determining the Appropriate Level of Safety Inventory (4 of 8)
Evaluating Cycle Service Level Given a Reorder Point
(ddlt = demand during lead time)
C S L = F(R O P, DL, σL) = NORMDIST(R O P, DL, σL, 1)
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Determining the Appropriate Level of Safety Inventory (5 of 8)
Q = 10,000, R O P = 6,000, L = 2 weeks
D = 2,500/week, σD = 500
C S L = F(R O P, DL, σL) = NORMDIST(ROP, DL, σL, 1)
= NORMDIST(6,000, 5,000, 707, 1) = 0.92
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Determining the Appropriate Level of Safety Inventory (6 of 8)
Evaluating Required Safety Inventory Given a Desired Cycle Service Level
Desired cycle service level = C S L
Mean demand during lead time = DL
Standard deviation of demand during lead time = σL
Probability(demand during lead time
Identify safety inventory ss so that
F(DL + ss, DL, sL) = CSL
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Determining the Appropriate Level of Safety Inventory (7 of 8)
or
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Determining the Appropriate Level of Safety Inventory (8 of 8)
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Evaluating Fill Rate Given a Reorder Point (1 of 4)
Expected shortage per replenishment cycle (E S C) is the average units of demand that are not satisfied from inventory in stock per replenishment cycle
Product fill rate
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Evaluating Fill Rate Given a Reorder Point (2 of 4)
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Evaluating Fill Rate Given a Reorder Point (3 of 4)
Lot size, Q = 10,000
Average demand during lead time, DL =5,000
Standard deviation of demand during lead time,
Safety inventory, ss = R O P − DL = 6,000−5,000 = 1,000
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Evaluating Fill Rate Given a Reorder Point (4 of 4)
Figure 12-2 Excel Solution of Example 12-4
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Evaluating Safety Inventory Given Desired Fill Rate (1 of 4)
Expected shortage per replenishment cycle is
E S C = (1 − fr)Q
No equation for ss
Try values or use G O A L S E E K in Excel
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Evaluating Safety Inventory Given Desired Fill Rate (2 of 4)
Desired fill rate, fr = 0.975
Lot size, Q = 10,000 boxes
Standard deviation of ddlt,
ESC = (1−fr)Q = (1 − 0.975)10,000 = 250
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Evaluating Safety Inventory Given Desired Fill Rate (3 of 4)
Use G O A L S E E K to find safety inventory ss = 67 boxes
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Evaluating Safety Inventory Given Desired Fill Rate (4 of 4)
Figure 12-3 Spreadsheet to Solve for ss Using GOALSEEK
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Impact of Desired Product Availability, Lead Time, and Demand Uncertainty
As desired product availability goes up the required safety inventory increases
Table 12- Required Safety Inventory for Different Values of Fill Rate
| Fill Rate | Safety Inventory |
| 97.5% | 67 |
| 98.0% | 183 |
| 98.5% | 321 |
| 99.0% | 499 |
| 99.5% | 767 |
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Impact of Desired Product Availability and Uncertainty
Goal is to reduce the level of safety inventory required in a way that does not adversely affect product availability
Reduce the supplier lead time L
Reduce the underlying uncertainty of demand (represented by σD )
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Benefits of Reducing Lead Time and Demand Uncertainty
D = 2,500/week σD, CSL = 0.95
If lead time is reduced to one week
If standard deviation is reduced to 400
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Adjusting Safety Inventory for Demand Lumpiness and Seasonality
Orders typically in large lots
Demand at various stages in the supply chain tends to be lumpy
Raise safety inventory by half the average size of a customer order
Demand is often seasonal
Fixing a R O P may lead to stockouts
Keep R O P constant in terms of days of demand
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Summary of Learning Objective 3 (1 of 2)
Given a desired cycle service level C S L, a lead time L, and a standard deviation of periodic demand σD , the required safety inventory ss for a continuous review policy is given
by
Given a reorder point
R O P, a lead time L, a standard deviation of periodic demand σD, and periodic demand D, the resulting cycle service level is given by
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Summary of Learning Objective 3 (2 of 2)
Given a level of safety inventory, one can evaluate the resulting fill rate. Given a desired fill rate, one can evaluate the required safety inventory. The required safety inventory increases with an increase in desired product availability, lead time, and uncertainty of periodic demand. In practice, it is best to evaluate safety inventory in terms of days of demand to account for seasonality of demand.
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Impact of Supply Uncertainty on Safety Inventory
We incorporate supply uncertainty by assuming that lead time is uncertain
D : Average demand per period
σL : Standard deviation of demand per period
L : Average lead time for replenishment
sL : Standard deviation of lead time
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Impact of Lead Time Uncertainty on Safety Inventory (1 of 3)
Average demand per period, D = 2,500
Standard deviation of demand per period, σD = 500
Average lead time for replenishment, L = 7 days
Standard deviation of lead time, sL = 7 days
Mean ddlt, DL = DL = 2,500 × 7 = 17,500
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Impact of Lead Time Uncertainty on Safety Inventory (2 of 3)
Required safety inventory
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Impact of Lead Time Uncertainty on Safety Inventory (3 of 3)
Table 12-2 Required Safety Inventory as a Function of Lead Time Uncertainty
| sL | σL | ss (units) | ss (days) |
| 6 | 15,058 | 19,298 | 7.72 |
| 5 | 12,570 | 16,109 | 6.44 |
| 4 | 10,087 | 12,927 | 5.17 |
| 3 | 7,616 | 9,760 | 3.90 |
| 2 | 5,172 | 6,628 | 2.65 |
| 1 | 2,828 | 3,625 | 1.45 |
| 0 | 1,323 | 1,695 | 0.68 |
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Summary of Learning Objective 4
An increase in supply uncertainty significantly increases the amount of safety inventory required for a given level of product availability. Lead time uncertainty has a more significant impact on the required safety inventory than lead time itself. A reduction in supply uncertainty can help to dramatically reduce the required safety inventory without hurting product availability.
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Impact of Aggregation on Safety Inventory (1 of 5)
How does aggregation affect forecast accuracy and safety inventories
Di: Mean periodic demand in region i, i = 1, …, k
σi : Standard deviation of periodic demand in region i, i =, …, k
ρij: Correlation of periodic demand for regions i, j,
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Impact of Aggregation on Safety Inventory (2 of 5)
Total safety inventory in decentralized option
Simplified to
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Impact of Aggregation on Safety Inventory (3 of 5)
Require safety inventory on aggregation
Holding – cost savings on aggregation per unit sold
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Impact of Aggregation on Safety Inventory (4 of 5)
The safety inventory savings on aggregation increase with the desired cycle service level C S L
The safety inventory savings on aggregation increase with the replenishment lead time L
The safety inventory savings on aggregation increase with the holding cost H
The safety inventory savings on aggregation increase with the coefficient of variation of demand
The safety inventory savings on aggregation decrease as the correlation coefficients increase
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Impact of Correlation on Value of Aggregation (1 of 3)
Standard deviation of weekly demand, σD =5
Replenishment, L = 2 weeks; Decentralized C S L = 0.9
Total required safety inventory,
Aggregate ρ = 0
Standard deviation of weekly demand at central outlet,
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Impact of Correlation on Value of Aggregation (2 of 3)
Table 12-3 Safety Inventory in the Disaggregate and Aggregate Options
| Rho | Disaggregate Safety Inventory | Aggregate Safety Inventory |
| 0 | 36.25 | 18.12 |
| 0.2 | 36.25 | 22.93 |
| 0.4 | 36.25 | 26.88 |
| 0.6 | 36.25 | 30.33 |
| 0.8 | 36.25 | 33.42 |
| 1.0 | 36.25 | 36.25 |
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Impact of Aggregation on Safety Inventory (5 of 5)
Figure 12-4 Square-Root Law
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Impact of Correlation on Value of Aggregation (3 of 3)
Two possible disadvantages to aggregation
Increase in response time to customer order
Increase in transportation cost to customer
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Trade-Offs of Physical Centralization (1 of 2)
Use four regional or one national distribution center
Four regional centers
Total required safety inventory,
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Trade-Offs of Physical Centralization (2 of 2)
One national distribution center, = 0
Standard deviation of weekly demand,
Decrease in holding costs
Decrease in facility costs
Increase in transportation
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Information Centralization
Online systems that allow customers or stores to locate stock
Improves product availability without adding to inventories
Reduces the amount of safety inventory
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Specialization (1 of 2)
Inventory is carried at multiple locations
Should all products should be stocked at every location?
Required level of safety inventory
Affected by coefficient of variation of demand
Low demand, slow-moving items, typically have a high coefficient of variation
High demand, fast-moving items, typically have a low coefficient of variation
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Impact of Coefficient of Variation on Value of Aggregation (1 of 2)
Table 12-4 Value of Aggregation at W.W. Grainger
| Blank | Motors | Cleaner |
| Inventory is stocked in each store | Blank | Blank |
| Mean weekly demand per store | 20 | 1,000 |
| Standard deviation | 40 | 100 |
| Coefficient of variation | 2.0 | 0.1 |
| Safety inventory per store | 132 | 329 |
| Total safety inventory | 211,200 | 526,400 |
| Value of safety inventory | $105,600,000 | $15,792,000 |
| Inventory is aggregated at the DC | Blank | Blank |
| Mean weekly aggregate demand | 32,000 | 1,600,000 |
| Standard deviation of aggregate demand | 1,600 | 4,000 |
| Coefficient of variation | 0.05 | 0.0025 |
| Aggregate safety inventory | 5,264 | 13,159 |
| Value of safety inventory | $2,632,000 | $394,770 |
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Impact of Coefficient of Variation on Value of Aggregation (2 of 2)
Table 12-4 [Continued]
| Blank | Motors | Cleaner |
| Savings | Blank | Blank |
| Total inventory saving on aggregation | $102,968,000 | $15,397,230 |
| Total holding cost saving on aggregation | $25,742,000 | $3,849,308 |
| Holding cost saving per unit sold | $15.47 | $0.046 |
| Savings as a percentage of product cost | 3.09% | 0.15% |
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Specialization (2 of 2)
| Item Type | Centralized Inventories | Decentralized Inventories |
| Fast Moving Predictable {Low Value} | Customer willing to pay premium? | Low cost |
| Slow Moving Unpredictable {High Value} | Low cost | Customer willing to pay premium? |
Figure 12-5 Specialization of Inventory Based on Product Type
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Product Substitution
The use of one product to satisfy demand for a different product
Manufacturer-driven substitution
Allows aggregation of demand
Reduce safety inventories
Influenced by the cost differential, correlation of demand
Customer-driven substitution
Allows aggregation of safety inventory
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Component Commonality
Without common components
Uncertainty of demand for a component is the same as for the finished product
Results in high levels of safety inventory
With common components
Demand for a component is an aggregation of the demand for the finished products
Component demand is more predictable
Component inventories are reduced
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Value of Component Commonality (1 of 3)
27 servers, 3 components, 3 × 27 = 81 distinct components
Monthly demand = 5,000
Standard deviation = 3,000
Replenishment lead time = 1 month
C S L = 0.95
Total safety inventory required
Safety inventory per common component
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Value of Component Commonality (2 of 3)
With component commonality
Nine distinct components
Total safety inventory required
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Value of Component Commonality (3 of 3)
Table 12-5 Marginal Benefit of Component Commonality
| Number of Finished Products per Component | Safety Inventory | Marginal Reduction in Safety Inventory | Total Reduction in Safety Inventory |
| 1 | 399,699 | Blank | Blank |
| 2 | 282,630 | 117,069 | 117,069 |
| 3 | 230,766 | 51,864 | 168,933 |
| 4 | 199,849 | 30,917 | 199,850 |
| 5 | 178,751 | 21,098 | 220,948 |
| 6 | 163,176 | 15,575 | 236,523 |
| 7 | 151,072 | 12,104 | 248,627 |
| 8 | 141,315 | 9,757 | 258,384 |
| 9 | 133,233 | 8,082 | 266,466 |
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Postponement (1 of 2)
Delay product differentiation or customization until closer to the time the product is sold
Have common components in the supply chain for most of the push phase
Move product differentiation as close to the pull phase of the supply chain as possible
Inventories in the supply chain are mostly aggregate
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Postponement (2 of 2)
Figure 12-6 Supply Chain Flows without and with Postponement
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Value of Postponement
100 different paint colors, D = 30/week, D = 10, L = 2 weeks, CSL = 0.95
Total required safety inventory,
Standard deviation of base paint weekly demand,
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Summary of Learning Objective 5
Aggregation reduces the required safety inventory as long as the demand across the aggregated regions is not perfectly, positively correlated. The safety inventory savings on aggregation increase with the desired C S L, the replenishment lead time, the product holding cost, and the coefficient of variation of demand. The safety inventory savings on aggregation decrease as the correlation of demand across regions increases. Firms can aggregate inventories through physical aggregation, information centralization, product substitution, component commonality, and postponement.
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Impact of Replenishment Policies on Safety Inventory (1 of 4)
Continuous Review Policies
D : Average demand per period
σD : Standard deviation of demand per period
L : Average lead time for replenishment
Mean demand during lead time, DL = D×L
Standard deviation of demand during lead time,
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Impact of Replenishment Policies on Safety Inventory (2 of 4)
Periodic Review Policies
Lot size determined by prespecified order-up-to level (O U L)
D : Average demand per period
σD : Standard deviation of demand per period
L : Average lead time for replenishment
T : Review interval
C S L : Desired cycle service level
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Impact of Replenishment Policies on Safety Inventory (3 of 4)
Probability
Mean demand during T+L periods,
Std dev demand during T+L periods,
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Impact of Replenishment Policies on Safety Inventory (4 of 4)
Figure 12-7 Inventory Profile for Periodic Review Policy with L = 4, T = 7
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Evaluation Safety Inventory for a Periodic Review Policy
D = 2,500, σD= 500, L = 2 weeks, T = 4 weeks
Mean demand during T + L periods,
Std dev demand during T + L periods,
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Summary of Learning Objective 6
Whereas the required safety inventory is proportional to for a continuous review policy, the required safety inventory for a periodic review replenishment policy is proportional to
where T is the reorder interval. As a result, periodic
review replenishment policies require more safety inventory than continuous review policies for the same lead time and level of product availability.
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Managing Safety Inventory in a Multiechelon Supply Chain
In multiechelon supply chains, stages often do not know demand and supply distributions
Inventory between a stage and the final customer is called the echelon inventory
Reorder points and order-up-to levels at any stage should be based on echelon inventory
Decisions must be made about the level of safety inventory carried at different stages
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Summary of Learning Objective 7
In a multiechelon supply chain, it is important to manage safety inventory across stages in a coordinated manner. Increasing safety inventory at upstream stages allows downstream stages to decrease the amount of safety inventory they carry.
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Managerial Levers to Reduce Safety Inventory
Reduction of supply uncertainty
Sharing information
Coordinated demand
Reduction of lead times
Delays contribute more to lead time than production and transportation time
Reduction of demand uncertainty
Reduce information distortion through sharing
Aggregate demand
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Summary of Learning Objective 8
The required level of safety inventory may be reduced and product availability may be improved if a supply chain can reduce demand uncertainty, replenishment lead times, and the variability of lead times. A switch from periodic monitoring to continuous monitoring can also help reduce inventories. Another key managerial lever to reduce the required safety inventories is to exploit aggregation. This may be achieved by physically aggregating inventories, virtually aggregating inventories using information centralization, specializing inventories based on demand volume, exploiting substitution, using component commonality, and postponing product differentiation.
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Copyright
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315
However, given demand fluctuations and forecast errors, actual demand over the three weeks may be higher or lower than the 300 purses that were forecast. If the actual demand at Bloomingdale’s is higher than 300, some customers will be unable to purchase purses, resulting in a potential loss of margin for Bloomingdale’s. The store manager thus decides to place an order with Gucci when the store still has 400 purses. This policy improves product availability for the customer because the store now runs out of purses only if the demand over the three weeks exceeds 400. Given an average weekly demand of 100 purses, the store will have an aver- age of 100 purses remaining when the replenishment lot arrives. Safety inventory is the average inventory remaining when the replenishment lot arrives. Thus, Bloomingdale’s carries a safety inventory of 100 purses.
Given a lot size of Q = 600 purses, the cycle inventory, the focus of the previous chapter, is Q>2 = 300 purses. The inventory profile at Bloomingdale’s in the presence of safety inven- tory is shown in Figure 12-1, which illustrates that the average inventory at Bloomingdale’s is the sum of the cycle and safety inventories.
This example illustrates a trade-off that a supply chain manager must consider when plan- ning safety inventory. On one hand, raising the level of safety inventory increases product avail- ability, and thus the margin captured from customer purchases. On the other hand, raising the level of safety inventory increases inventory holding costs. This issue is particularly significant in industries in which product life cycles are short and demand is volatile. Carrying excessive inven- tory can help counter demand volatility but can really hurt if new products come onto the market and demand for the product in inventory dries up. The inventory on hand then becomes worthless.
In today’s business environment, it has become easier for customers to search across stores for product availability. If Amazon is out of a book, for example, a customer can easily check to see whether barnesandnoble.com has the title available. The increased ease of searching puts pressure on firms to improve product availability. Simultaneously, product variety has grown with increased customization. As a result, markets have become increasingly heterogeneous and demand for individual products is unstable and difficult to forecast. Both the increased variety and the greater pressure for availability push firms to raise the level of safety inventory they hold. Given the product variety and high demand uncertainty in most high-tech supply chains, a sig- nificant fraction of the inventory carried is safety inventory.
As product variety has grown, however, product life cycles have shrunk. Thus, it is more likely that a product that is “hot” today will be obsolete tomorrow, which increases the cost to firms of carrying too much inventory. Thus, a key to the success of any supply chain is to figure out ways to decrease the level of safety inventory carried without hurting the level of product availability.
The importance of reduced safety inventories is emphasized by the experience of Nord-
Average Inventory
Cycle Inventory
Safety Inventory
Inventory
Time
Q
FIGURE 12-1 Inventory Profile with Safety Inventory
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332 Chapter 12 • Managing Uncertainty in a Supply Chain: Safety Inventory
Most online retailers exploit the benefits of aggregation in terms of reduced inventories. For example, Blue Nile sells diamonds online and serves the entire United States out of one warehouse. As a result, it has lower levels of diamond inventories than jewelry chains such as Tiffany and Zales, which must keep inventory in every retail store.
There are, however, situations where physical aggregation of inventories in one location may not be optimal. There are two major disadvantages of aggregating all inventories in one location:
1. Increase in response time to customer order 2. Increase in transportation cost to customer
Both disadvantages result because the average distance between the inventory and the customer increases with aggregation. Either the customer has to travel farther to reach the product or the product has to be shipped over longer distances to reach the customer. A retail chain such as Gap has the option of building many small retail outlets or a few large ones. Gap tends to have many smaller outlets distributed evenly in a region because this strategy reduces the distance that customers travel to reach a store. If Gap had one large centralized outlet, the average distance that customers need to travel would increase and thus the response time would increase. A desire to decrease customer response time is thus the impetus for the firm to have multiple outlets. Another example is McMaster-Carr, a distributor of MRO supplies. McMaster-Carr uses UPS for shipping product to customers. Because shipping charges are based on distance, having one centralized warehouse increases the average shipping cost as well as the response time to the customer. Thus, McMaster-Carr has five warehouses that allow it to provide next-day delivery to a large fraction of the United States. Next-day delivery by UPS would not be feasible at a reasonable cost if McMaster-Carr had only one warehouse. Even Amazon.com, which started with one warehouse in Seattle, has added more warehouses in other parts of the United States in an effort to improve response time and reduce transportation cost to the customer. We illustrate the trade-offs of centralization in Example 12-9.
Trade-offs of Physical Centralization
An online retailer is debating whether to serve the United States through four regional distribu- tion centers or one national distribution center. Weekly demand in each region is normally distributed, with a mean of 1,000 and a standard deviation of 300. Demand experienced in each region is independent, and supply lead time is four weeks. The online retailer has a holding cost of 20 percent and the cost of each product is $1,000. The retailer promises its customers next-day delivery. With four regional distribution centers, the retailer can provide next-day delivery using ground transportation at a cost of $10/unit. With a single national distribution center, the retailer
EXAMPLE 12-9
Number of Independent Stocking Locations
Total Safety Inventory
FIGURE 12-4 Square-Root Law
M12_CHOP3952_05_SE_C12.QXD 11/15/11 6:52 PM Page 332
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340 Chapter 12 • Managing Uncertainty in a Supply Chain: Safety Inventory
when planning production. Today, a factory manager needs to forecast only aggregate paint demand because mixing has been postponed until after customer demand is known. As a result, each retail store primarily carries aggregate inventory in the form of base paint that is configured to the appropriate color based on customer demand.
Another classic example of postponement is the production process at Benetton to make colored knit garments. The original process called for the thread to be dyed and then knitted and assembled into garments. The entire process required up to six months. Because the color of the final garment was fixed the moment the thread was dyed, demand for individual colors had to be forecast far in advance (up to six months). Benetton developed a manufacturing technology that allowed it to dye knitted garments to the appropriate color. Now greige thread (the term used for thread that has not yet been dyed) can be purchased, knitted, and assembled into garments before dyeing. The dyeing of the garments is done much closer to the selling season. In fact, part of the dyeing is done after the start of the selling season, when demand is known with great accuracy. In this case, Benetton has postponed the color customization of the knit garments. When thread is purchased, only the aggregate demand across all colors needs to be forecast. Given that this decision is made far in advance, when forecasts are least likely to be accurate, there is great advantage to this aggregation. As Benetton moves closer to the selling season, the forecast uncertainty reduces. At the time Benetton dyes the knit garments, demand is known with a high degree of accuracy. Thus, postponement allows Benetton to exploit aggregation and significantly reduce the level of safety inventory carried. Supply chain flows with and without postponement are illustrated in Figure 12-5.
Without component commonality and postponement, product differentiation occurs early on in the supply chain, and most of the supply chain inventories are disaggregate. Postponement allows the supply chain to delay product differentiation. As a result, most of the inventories in the supply chain are aggregate. Postponement thus allows a supply chain to exploit aggregation to reduce safety inventories without hurting product availability. We illustrate the benefits of postponement in Example 12-12. A more nuanced discussion of the value of postponement is given in Chapter 13.
Value of Postponement
Consider a paint retailer who sells 100 different colors of paint. Assume that weekly demand for each color is independent and is normally distributed with a mean of 30 and a standard deviation of 10. The replenishment lead time from the paint factory is two weeks and the retailer aims for a CSL ! 0.95. How much safety stock will the retailer have to hold if paint is mixed at the factory and held in inventory at the retailer as individual colors? How does the safety stock requirement change if the retailer holds base paint (supplied by the paint factory) and mixes colors on demand?
EXAMPLE 12-12
Supply Chain Flows Without Postponement
Supply Chain Flows with Component Commonality and Postponement
FIGURE 12-5 Supply Chain Flows with Postponement
M12_CHOP3952_05_SE_C12.QXD 11/15/11 6:52 PM Page 340
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Chapter 12 • Managing Uncertainty in a Supply Chain: Safety Inventory 343
The next step is to evaluate the distribution of demand during the time interval T ! L. Using Equation 12.2, demand during the time interval T ! L is normally distributed, with
The safety inventory in this case is the quantity in excess of DT+L carried by Wal-Mart over the time interval T ! L. The OUL and the safety inventory ss are related as follows:
(12.17)
Given the desired CSL, the safety inventory (ss) required is given by
(12.18)
The average lot size equals the average demand during the review period T and is given as
(12.19)
In Figure 12-6, we show the inventory profile for a periodic review policy with lead time L " 4 and reorder interval T " 7. Observe that on day 7, the company places an order that determines available inventory until day 18 (as illustrated in the line from point 1 and point 2). As a result, the safety inventory must be sufficient to buffer demand variability over T ! L " 7 ! 4 " 11 days.
We illustrate the periodic review policy for Wal-Mart in Example 12-13.
Evaluation Safety Inventory for a Periodic Review Policy
Weekly demand for Legos at a Wal-Mart store is normally distributed, with a mean of 2,500 boxes and a standard deviation of 500. The replenishment lead time is two weeks, and the store manager has decided to review inventory every four weeks. Assuming a periodic-review replenishment policy, evaluate the safety inventory that the store should carry to provide a CSL of 90 percent. Evaluate the OUL for such a policy.
Analysis: In this case, we have
Average demand per period, D " 2,500
Standard deviation of demand per period, sD = 500
EXAMPLE 12-13
Average lot size, Q = DT = DT
ss = FS-11CSL2 * sT+L = NORMSINV1CSL2 * sT+L OUL = DT+L + ss
Standard deviation of demand during T + L periods, sT+L = 1T + LsD Mean demand during T + L periods, DT+L = 1T + L2D
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M12_CHOP3952_05_SE_C12.QXD 11/15/11 6:52 PM Page 343
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