Discussion 2

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chopra_scm5_ch12.pptx

12

Managing Uncertainty in a Supply Chain: Safety Inventory

PowerPoint presentation to accompany

Chopra and Meindl Supply Chain Management, 5e

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Learning Objectives

Understand the role of safety inventory in a supply chain

Identify factors that influence the required level of safety inventory

Describe different measures of product availability

Utilize managerial levers available to lower safety inventory and improve product availability

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The Role of Safety Inventory

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

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 improve product availability while reducing safety inventory?

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The Role of Safety Inventory

Figure 12-1

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Determining the Appropriate Level

Determined by two factors

The uncertainty of both demand and supply

The desired level of product availability

Measuring Demand Uncertainty

D = Average demand per period

sD = 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 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 (CSL)

Fraction of replenishment cycles that end with all customer demand being met

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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 (ROP)

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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Evaluating Cycle Service Level and Fill Rate

Evaluating Safety Inventory Given a Replenishment Policy

Expected demand during lead time = DL

Safety inventory, ss = ROP – DL

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Evaluating Cycle Service Level and Fill Rate

Average demand per week, D = 2,500

Standard deviation of weekly demand, sD = 500

Average lead time for replenishment, L = 2 weeks

Reorder point, ROP = 6,000

Average lot size, Q = 10,000

Safety inventory, ss = ROP – DL = 6,000 – 5,000 = 1,000

Cycle inventory = Q/2 = 10,0002 = 5,000

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Evaluating Cycle Service Level and Fill Rate

Average inventory = cycle inventory + safety inventory

= 5,000 + 1,000 = 6,000

Average flow time = average inventory/throughput

= 6,000/2,500 = 2.4 weeks

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Evaluating Cycle Service Level and Fill Rate

Evaluating Cycle Service Level Given a Replenishment Policy

CSL = Prob(ddlt of L weeks ≤ ROP)

CSL = F(ROP, DL, sL) = NORMDIST(ROP, DL, sL, 1)

(ddlt = demand during lead time)

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Evaluating Cycle Service Level and Fill Rate

Q = 10,000, ROP = 6,000, L = 2 weeks

D = 2,500/week, sD = 500

CSL = F(ROP,DL,sL) = NORMDIST(ROP,DL,sL,1)

= NORMDIST(6,000,5,000,707,1) = 0.92

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Evaluating Fill Rate Given a Replenishment Policy

Expected shortage per replenishment cycle (ESC) is the average units of demand that are not satisfied from inventory in stock per replenishment cycle

Product fill rate

fr = 1 – ESC/Q = (Q – ESC)/Q

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Evaluating Fill Rate Given a Replenishment Policy

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Evaluating Fill Rate Given a Replenishment Policy

Lot size, Q = 10,000

Average demand during lead time, DL = 5,000

Standard deviation of demand during lead time, sL = 707

Safety inventory, ss = ROP – DL = 6,000 – 5,000 = 1,000

fr = (Q – ESC)/Q = 110,000 – 252/10,000 = 0.9975

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Evaluating Fill Rate Given a Replenishment Policy

Figure 12-2

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Evaluating Safety Inventory Given Desired Cycle Service Level

Desired cycle service level = CSL

Mean demand during lead time = DL

Standard deviation of demand during lead time = σL

Probability(demand during lead time ≤ DL + ss) = CSL

Identify safety inventory so that

F(DL + ss, DL, sL) = CSL

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Evaluating Safety Inventory Given Desired Cycle Service Level

or

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Evaluating Safety Inventory Given Desired Cycle Service Level

Q = 10,000, CSL = 0.9, L = 2 weeks

D = 2,500/week, sD = 500

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Evaluating Safety Inventory Given Desired Fill Rate

Expected shortage per replenishment cycle is

ESC = (1 – fr)Q

No equation for ss

Try values or use GOALSEEK in Excel

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Evaluating Safety Inventory Given Desired Fill Rate

Desired fill rate, fr = 0.975

Lot size, Q = 10,000 boxes

Standard deviation of ddlt, sL = 707

ESC = (1 – fr)Q = (1 – 0.975)10,000 = 250

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Evaluating Safety Inventory Given Desired Fill Rate

Use GOALSEEK to find safety inventory ss = 67 boxes

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Evaluating Safety Inventory Given Desired Fill Rate

Figure 12-3

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Impact of Desired Product Availability and Uncertainty

As desired product availability goes up the required safety inventory increases

Fill Rate Safety Inventory
97.5% 67
98.0% 183
98.5% 321
99.0% 499
99.5% 767

Table 12-1

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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 sD)

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Benefits of Reducing Lead Time

D = 2,500/week, sD = 800, CSL = 0.95

If lead time is reduced to one week

If standard deviation is reduced to 400

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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

sD: 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

Average demand per period, D = 2,500

Standard deviation of demand per period, sD = 500

Average lead time for replenishment, L = 7 days

Standard deviation of lead time, sL = 7 days

Mean ddlt, DL = DL = 2,500 x 7 = 17,500

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Impact of Lead Time Uncertainty on Safety Inventory

Required safety inventory

sL sL 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

Table 12-2

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Impact of Aggregation on Safety Inventory

How does aggregation affect forecast accuracy and safety inventories

Di: Mean weekly demand in region i, i = 1,…, k

si: Standard deviation of weekly demand in region i, i = 1,…, k

rij: Correlation of weekly demand for regions i, j, 1 ≤ i ≠ j ≤ k

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Impact of Aggregation on Safety Inventory

Total safety inventory

in decentralized option

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Impact of Aggregation on Safety Inventory

Require safety inventory on aggregation

Holding-cost savings on aggregation per unit sold

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Impact of Aggregation on Safety Inventory

The safety inventory savings on aggregation increase with the desired cycle service level CSL

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 Aggregation on Safety Inventory

The Square-Root Law

Figure 12-4

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Impact of Correlation on Value of Aggregation

Standard deviation of weekly demand, sD = 5;

Replenishment, L = 2 weeks; Decentralized CSL = 0.9

Total required safety inventory,

Aggregate r = 0

Standard deviation of weekly demand at central outlet,

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Impact of Correlation on Value of Aggregation

r Disaggregate Safety Inventory Aggregate Safety Inventory
0 36.24 18.12
0.2 36.24 22.92
0.4 36.24 26.88
0.6 36.24 30.32
0.8 36.24 33.41
1.0 36.24 36.24

Table 12-3

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Impact of Correlation on Value of Aggregation

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

Use four regional or one national distribution center

D = 1,000/week, sD = 300, L = 4 weeks, CSL = 0.95

Total required safety inventory,

Four regional centers

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Trade-offs of Physical Centralization

One national distribution center, r = 0

Standard deviation of weekly demand,

Decrease in holding costs = (3,948 – 1,974) $1,000 x 0.2

= $394,765

Decrease in facility costs = $150,000

Increase in transportation = 52 x 1,000 x (13 – 10)

= $624,000

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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

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

Motors Cleaner
Inventory is stocked in each store
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
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
Savings
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%

Table 12-4

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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 inventor

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

27 PCs, 3 components, 3 x 27 = 81 distinct components

Monthly demand = 5,000

Standard deviation = 3,000

Replenishment lead time = 1 month

CSL = 0.95

Total safety inventory required

Safety inventory per common component

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Value of Component Commonality

With component commonality

Nine distinct components

Total safety inventory required

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Value of Component Commonality

Number of Finished Products per Component Safety Inventory Marginal Reduction in Safety Inventory Total Reduction in Safety Inventory
1 399,699
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

Table 12-5

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Postponement

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

Figure 12-5

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Value of Postponement

100 different paint colors, D = 30/week, sD = 10,

L = 2 weeks, CSL = 0.95

Total required safety inventory,

Standard deviation of

base paint weekly demand,

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Impact of Replenishment Policies on Safety Inventory

Continuous Review Policies

D: Average demand per period

sD: Standard deviation of demand per period

L: Average lead time for replenishment

Mean demand during lead time,

Standard deviation of demand during lead time,

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Impact of Replenishment Policies on Safety Inventory

Periodic Review Policies

Lot size determined by prespecified order-up-to level (OUL)

D: Average demand per period

sD: Standard deviation of demand per period

L: Average lead time for replenishment

T: Review interval

CSL: Desired cycle service level

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Impact of Replenishment Policies on Safety Inventory

Probability(demand during L + T ≤ OUL) = CSL

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Impact of Replenishment Policies on Safety Inventory

Figure 12-6

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Evaluation Safety Inventory for a Periodic Review Policy

D = 2,500, sD = 500, L = 2 weeks, T = 4 weeks

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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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The Role of IT in Inventory Management

IT systems can help

Improve inventory visibility

Coordination in the supply chain

Track inventory (RFID)

Value tightly linked to the accuracy of the inventory information

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Estimating and Managing Safety Inventory in Practice

Account for the fact that supply chain demand is lumpy

Adjust inventory policies if demand is seasonal

Use simulation to test inventory policies

Start with a pilot

Monitor service levels

Focus on reducing safety inventories

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Summary of Learning Objectives

Understand the role of safety inventory in a supply chain

Identify factors that influence the required level of safety inventory

Describe different measures of product availability

Utilize managerial levers available to lower safety inventory and improve product availability

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DL = Di σL = σ i 2 + 2 ρijσ iσ j

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)–D

L

ss = FS –1(CSL)×σL = FS

–1(CSL)× LσD

ss=F

S

–1

(CSL)´s

L

=F

S

–1

(CSL)´Ls

D

= NORMSINV(CSL)× LσD

=NORMSINV(CSL)´Ls

D

DL = DL = 2×2,500 = 5,000

σL = LσD = 2 ×500 = 707

D

L

=DL=2´2,500=5,000

s

L

=Ls

D

=2´500=707

ss = Fs –1(CSL)×σL = NORMSINV(CSL)×σL

ss=F

s

–1

(CSL)´s

L

=NORMSINV(CSL)´s

L

= NORMSINV(0.90)×707 = 906

=NORMSINV(0.90)´707=906

ESC = 250 = –ss 1– Fs ss σL

⎛

⎝ ⎜

⎞

⎠ ⎟

⎡

⎣ ⎢ ⎢

⎤

⎦ ⎥ ⎥ +σL fs

ss σL

⎛

⎝ ⎜

⎞

⎠ ⎟

ESC=250=–ss1–F

s

ss

s

L

æ

è

ç

ö

ø

÷

é

ë

ê

ê

ù

û

ú

ú

+s

L

f

s

ss

s

L

æ

è

ç

ö

ø

÷

= –ss 1– Fs ss 707 ⎛

⎝ ⎜

⎞

⎠ ⎟

⎡

⎣ ⎢

⎤

⎦ ⎥+707 fs

ss 707 ⎛

⎝ ⎜

⎞

⎠ ⎟

=–ss1–F

s

ss

707

æ

è

ç

ö

ø

÷

é

ë

ê

ù

û

ú

+707f

s

ss

707

æ

è

ç

ö

ø

÷

250 = –ss[1– NORMDIST(ss /707,0,1,1)]

250=–ss[1–NORMDIST(ss/707,0,1,1)]

+707NORMDIST(ss /707,0,1,0)

+707NORMDIST(ss/707,0,1,0)

ss = NORMSINV(CSL)× LσD

ss=NORMSINV(CSL)´Ls

D

= NORMSINV(.95)× 9 ×800 = 3,948

=NORMSINV(.95)´9´800=3,948

ss = NORMSINV(.95)× 1×800 =1,316

ss=NORMSINV(.95)´1´800=1,316

ss = NORMSINV(.95)× 9 ×400 =1,974

ss=NORMSINV(.95)´9´400=1,974

DL = DL σL = LσD 2 + D2sL

2

D

L

=DL s

L

=Ls

D

2

+D

2

s

L

2

Standard deviation of ddlt σL = LσD 2 + D2sL

2

Standard deviation of ddlt s

L

=Ls

D

2

+D

2

s

L

2

= 7×5002 +2,5002 ×72

=17,500

=7´500

2

+2,500

2

´7

2

=17,500

ss = FS –1(CSL)×σL = NORMSINV(CSL)×σL

ss=F

S

–1

(CSL)´s

L

=NORMSINV(CSL)´s

L

= NORMSINV(0.90) ×17,500 = 22,491 hard drives

=NORMSINV(0.90)´17,500

=22,491 hard drives

= FS –1(CSL)× L ×σ i

i=1

k

=F

S

–1

(CSL)´L´s

i

i=1

k

å

DC = Dii=1 k

∑ ; var DC( ) = σ i2 + 2 ρijσ iσ j i> j ∑

i=1

k

∑ ;

D

C

=D

i

i=1

k

å

; varD

C

(

)

=s

i

2

+2r

ij

s

i

s

j

i>j

å

i=1

k

å

;

σD C = var DC( )

s

D

C

=varD

C

(

)

DC = kD σD C = kσD

D

C

=kD s

D

C

=ks

D

= FS –1(CSL)× L ×σD

C

i=1

k

=F

S

–1

(CSL)´L´s

D

C

i=1

k

å

= FS –1(CSL)× L × H

DC × σ i –σD

C

i=1

k

∑ ⎛

⎝ ⎜⎜

⎞

⎠ ⎟⎟

=

F

S

–1

(CSL)´L´H

D

C

´s

i

–s

D

C

i=1

k

å

æ

è

ç

ç

ö

ø

÷

÷

ss = k × Fs –1(CSL)× L ×σD

ss=k´F

s

–1

(CSL)´L´s

D

= 4 × Fs –1(0.9) × 2 × 5

= 4 × NORMSINV(0.9) × 2 × 5 = 36.24 cars

=4´F

s

–1

(0.9)´2´5

=4´NORMSINV(0.9)´2´5=36.24 cars

σD C = 4 ×5 =10

s

D

C

=4´5=10

ss = Fs –1(0.9)× L ×σD

C = NORMSINV(0.9)× 2 ×10 =18.12

ss=F

s

–1

(0.9)´L´s

D

C

=NORMSINV(0.9)´2´10=18.12

ss = 4× Fs –1(CSL)× L ×σD

ss=4´F

s

–1

(CSL)´L´s

D

= 4× NORMSINV(0.95)× 4 ×300 = 3,948

=4´NORMSINV(0.95)´4´300=3,948

σD C = 4 ×300 = 600

s

D

C

=4´300=600

ss = Fs –1(0.95)× L ×σD

C

ss=F

s

–1

(0.95)´L´s

D

C

= NORMSINV(0.95)× 4 ×600 =1,974

=NORMSINV(0.95)´4´600=1,974

= 81× NORMSINV(0.95)× 1×3,000

=81´NORMSINV(0.95)´1´3,000

= 399,699 units

=399,699 units

= NORMSINV(0.95)× 1× 9 ×3,000

=NORMSINV(0.95)´1´9´3,000

= 14,804 units

=14,804 units

= 9×14,804 =133,236

=9´14,804=133,236

ss =100× Fs –1(CSL)× L ×σD

ss=100´F

s

–1

(CSL)´L´s

D

=100× NORMSINV(0.95)× 2 ×10 = 2,326

=100´NORMSINV(0.95)´2´10=2,326

σD C = 100 ×10 =100

s

D

C

=100´10=100

ss = Fs –1(CSL)× L ×σD

C = NORMSINV(0.95)× 2 ×100 = 233

ss=F

s

–1

(CSL)´L´s

D

C

=NORMSINV(0.95)´2´100=233

DL = DL

σL = LσD

D

L

=DL

s

L

=Ls

D

ss = FS –1(CSL)×σL = NORMSINV(CSL)× LσD,ROP = DL + ss

ss=F

S

–1

(CSL)´s

L

=NORMSINV(CSL)´Ls

D

,ROP=D

L

+ss

Mean demand during T + L periods, DT+L = (T + L)D

Mean demand during T+L periods, D

T+L

=(T+L)D

Std dev demand during T + L periods, σT+L = T + LσD

Std dev demand during T+L periods, s

T+L

=T+Ls

D

OUL = DT+L + ss

ss = FS –1(CSL) ×σD+L = NORMSINV(CSL) ×σT+L

Average lot size, Q = DT = DT

OUL=D

T+L

+ss

ss=F

S

–1

(CSL)´s

D+L

=NORMSINV(CSL)´s

T+L

Average lot size, Q=D

T

=DT

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

5

OUL

DT

DL Safety Inventory

T = 7

L = 4 W

ar eh

ou se

In ve

nt or

y

10

L

T L

SS 0

Review Point 0

Review Point 1

Review Point 2

Review Point 3

15 Days

20 25

2

1

FIGURE 12-6 Inventory Profile for Periodic Review Policy with L " 4, T " 7

M12_CHOP3952_05_SE_C12.QXD 11/15/11 6:52 PM Page 343

schopra
insert some space between the square root and sigma

Mean demand during T + L periods, DT+L = (T + L)D = (2 + 4)2,500 = 15,000

Mean demand during T+L periods, D

T+L

=(T+L)D

=(2+4)2,500=15,000

Std dev demand during T + L periods, σT+L = T + LσD = 4 + 2( )500 = 1,225

Std dev demand during T+L periods, s

T+L

=T+Ls

D

=4+2

()

500=1,225

ss = FS –1(CSL) ×σD+L = NORMSINV(CSL) ×σT+L

= NORMSINV(0.90) ×1,225 = 1,570 boxes

ss=F

S

–1

(CSL)´s

D+L

=NORMSINV(CSL)´s

T+L

=NORMSINV(0.90)´1,225=1,570 boxes

OUL = DT+L + ss =15,000+1,570 =16,570

OUL=D

T+L

+ss=15,000+1,570=16,570