SIMCHI CHAPTER 6 by YUSUF MAHOMED

Managing Uncertainty in the Supply Chain David Simchi-Levi Professor of Engineering Systems Massachusetts Institute of Technology Tel: 617-253-6160 E-mail: dslevi@mit.edu

Outline of the Presentation Introduction Push-Pull Systems Case Studies High Tech Automotive Electrical Components

Today’s Supply Chain Pitfalls • • • • •

Long Lead Times Uncertain Demand Complex Product Offering Component Availability System Variation Over Time

Order Size

The Dynamics of the Supply Chain

Customer Customer Demand Demand Distributor Distributor Orders Orders

Retailer RetailerOrders Orders

Production ProductionPlan Plan

Time Source: Tom Mc Guffry, Electronic Commerce and Value Chain Management, 1998

Order Size

The Dynamics of the Supply Chain

Customer Customer Demand Demand

Production ProductionPlan Plan

Time Source: Tom Mc Guffry, Electronic Commerce and Value Chain Management, 1998

What are the Causes…. • • • • • •

Example: Automotive Supply Chain • Custom order takes 60-70 days • Many different products – High level of demand uncertainty

• Dealers’ inventory does not capture demand accurately – GM estimates: “Research shows we lose 10% to 11% of sales because the car is not available”

Supply Chain Strategies • Achieving Global Optimization • Managing Uncertainty – Risk Pooling – Risk Sharing

From Sequential Optimization to Global Optimization Sequential Optimization Procurement Planning

Manufacturing Planning

Distribution Planning

Demand Planning

Global Optimization Supply Contracts/Collaboration/Integration/DSS

Procurement Planning

Source: Duncan McFarlane

Manufacturing Planning

Distribution Planning

Demand Planning

A new Supply Chain Paradigm • A shift from a Push System... – Production decisions are based on forecast

• …to a Push-Pull System

From Make-to-Stock Model…. Suppliers

Assembly

Configuration

Demand Forecast • The three principles of all forecasting techniques: – Forecasts are always wrong – The longer the forecast horizon the worst is the forecast – Aggregate forecasts are more accurate • Risk Pooling

A new Supply Chain Paradigm • A shift from a Push System... – Production decisions are based on forecast

• …to a Push-Pull System

Push-Pull Supply Chains The Supply Chain Time Line

Suppliers

PUSH STRATEGY Low Uncertainty

PULL STRATEGY High Uncertainty

Customers

A new Supply Chain Paradigm • A shift from a Push System... – Production decisions are based on forecast

….to Assemble-to-Order Model Suppliers

Assembly

Configuration

Outline of the Presentation Introduction Push-Pull Systems Case Studies High Tech Automotive Electrical Components

Shifting the Push-Pull Boundary: A Case Study • Manufacturer of circuit boards and other hightech products • Sells customized products with high value and short life cycles • Multi-stage BOM – e.g., copper & fiberglass ⇒ circuit board ⇒ enclosure ⇒ processor

How to Read the Diagrams A Gray Box is a processing stage

PART 2 DALLAS ($0.50)

Number on the lane is the transit time

0 PART 1 DALLAS ($260) 2

PART 3 88 MONTGOMERY ($220)

Number under the box is the processing time

Number in the white box is the commitment time to the next stage

Cost in the box is the value of the product

Bins indicate safety stock levels- more Red means more safety stock, empty means no safety stock

x2 PART 2 DALLAS ($0.50)

Safety Stock Cost = $74,100/yr

0 0

PART 4 MALAYSIA ($180)

PART 5 37 CHARLESTON ($12)

PART 1 DALLAS ($260) 28 3 3

PART 7 DENVER ($2.50)

PART 6 RALEIGH ($3)

PART 3 88 MONTGOMERY ($220)

8 x2

Safety Stock Cost = $45,400/yr (39% savings)

PART 2 DALLAS ($0.50)

PART 4 MALAYSIA ($180)

PART 5 37 CHARLESTON ($12)

PART 1 DALLAS ($260) 28 3 3

PART 7 DENVER ($2.50)

PART 6 RALEIGH ($3)

2 PART 3 13 MONTGOMERY ($220)

Safety Stock Cost = $53,700/yr (28% savings, 50% reduction in LT)

PART 2 DALLAS ($0.50)

PART 4 MALAYSIA ($180)

PART 5 37 CHARLESTON ($12)

PART 1 DALLAS ($260) 28 3 3

PART 7 DENVER ($2.50)

PART 6 RALEIGH ($3)

2 PART 3 50 MONTGOMERY ($220)

Comparison of Performance Measures

Scenario 1: Baseline 2: Optimization 3: Shorten Lead Time

Safety Stock Holding Cost ($/yr) $74,100 $45,400 $53,700

Lead Time to Customer (days) 30 30 15

Cycle Time (days) 105 105 105

Inventory Turns (turns/yr) 1.2 1.4 1.3

PART 31 40 SEA ($20)

PART 23 50 DAL ($30)

PART 18 51 DAL ($35)

4 PART 38 NJ ($8)

PART 32 10 NJ ($22)

PART 39 TAI ($15)

PART 35 NJ ($35)

2 3

3 PART 41 PHI ($32)

PART 36 20 NJ ($40) 13

PART 42 PHI ($2)

PART 37 10 DAL ($8) 4

50 PART 19 61 DAL ($210)

PART 12 62 DAL ($260)

PART 4 65 DAL ($285)

3 PART 5 DAL ($3)

PART 26 25 DAL ($80) 2

PART 34 49 WAS ($25) 2

PART 25 3 52 WAS ($75)

PART 33 42 WAS ($30)

PART 2 55 DAL ($55)

PART 3 50 DAL ($6)

9 35 PART 40 12 NZ ($22)

PART 24 16 NJ ($30)

PART 11 54 DAL ($40)

3 PART 27 NJ ($4)

PART 13 24 MEX ($11)

PART 6 46 DAL ($18) 14

1 PART 14 10 MEX ($4)

PART 28 17 DAL ($12)

PART 7 21 DAL ($9) 3

7 PART 20 18 WAS ($42)

PART 29 12 WAS ($40) 12

6 PART 21 35 41 NZ ($18)

Safety Stock Cost = $95,000/yr

PART 15 26 DAL ($60) 5 PART 16 81 DAL ($21) 5

PART 30 PHI ($6)

PART 22 23 DAL ($28) 16

PART 17 26 DAL ($30) 3

PART 8 56 DAL ($65) 30 PART 9 82 DAL ($30) 1 PART 10 38 DAL ($35) 12

PART 1 30 DAL ($535) 4

PART 31 40 SEA ($20)

PART 23 21 DAL ($30)

PART 18 22 DAL ($35)

4 PART 38 NJ ($8)

PART 32 NJ ($22)

8 PART 39 TAI ($15)

PART 35 NJ ($35)

2 3

PART 36 11 NJ ($40)

PART 37 DAL ($8) 4

PART 19 22 DAL ($210)

PART 4 26 DAL ($285)

PART 12 23 DAL ($260) 1

3 PART 5 DAL ($3)

PART 27 NJ ($4)

PART 13 24 MEX ($11)

PART 6 26 DAL ($18) 14

PART 14 10 MEX ($4)

PART 28 16 DAL ($12)

PART 7 21 DAL ($9) 3

PART 20 18 WAS ($42)

PART 29 12 WAS ($40) 12

Safety Stock Cost = $36,600/yr (62% savings) PART 30 PHI ($6)

13 PART 42 PHI ($2)

3 PART 41 PHI ($32)

PART 26 16 DAL ($80) 2

PART 34 10 WAS ($25) 2

PART 25 13 WAS ($75) 3

PART 33 10 WAS ($30)

PART 2 26 DAL ($55)

PART 3 26 DAL ($6)

9 35 PART 40 12 NZ ($22)

PART 24 14 NJ ($30)

PART 11 25 DAL ($40)

PART 21 35 41 NZ ($18)

PART 15 26 DAL ($60) 5 PART 16 25 DAL ($21) 5

PART 22 11 DAL ($28) 16

PART 17 14 DAL ($30) 3

PART 8 26 DAL ($65) 30 PART 9 26 DAL ($30) 1 PART 10 26 DAL ($35) 12

PART 1 30 DAL ($535) 4

Comparison of Performance Measures

Scenario 1: Baseline 2: Optimization

Safety Stock Holding Cost ($/yr) $95,000 $36,600

Lead Time to Customer (days) 30 30

Cycle Time (days) 86 86

Inventory Turns (turns/yr) 1.5 1.8

Safety Stock vs. Quoted Lead Time Safety Stock Cost vs. Quoted Lead Time $100,000

For a given lead-time, the optimized supply chain provides reduced costs

$90,000

Safety Stock Cost ($/year)

$80,000 $70,000

For a given cost, the optimized supply chain provides better lead-times

$60,000 $50,000

Baseline Cost Optimized Cost

$40,000 $30,000 $20,000 $10,000 $0 0

Lead Time Quoted to Customer (days)

100

Outline of the Presentation Introduction Push-Pull Systems Case Studies High Tech Automotive Electrical Components

Case Study: Spare Part Inventory Optimization •

INVENTORY STRATEGY – –

•

NETWORK DYNAMICS – – –

•

Optimal Safety Stock and Base Stock level at each location Optimal Committed Service Time

Understanding Inventory Drivers Sensitivity Analysis What-if analysis/Prioritizing Opportunities

SOURCING & PRICING – – –

Cost implications with different suppliers Supplier Contract Negotiations Differential Pricing

Spare Part Network with Plant & PDC CST = 0 D

D D

PDC 2

PDC 3

PDC 1

Supplier 1 Supplier 2 Supplier 3 Supplier 4/ Part 1 Supplier 4/ Part 2 Supplier 4/ Part 3

PDC 4

1.92

1.92 1.92

PDC 5

0.96

Water Pump Kit Plant

PDC 6

D PDC 7

0.96

PDC 8

0.96

D PDC 9

Committed Service Time (months)

PDC 10

D PDC 13

PDC 12

PDC 11

Raw Materials D

Water Pump Kit FG

Inventory Drivers Inventory by Location

Root Cause Analysis $2,500.00

$5,000.00 $4,000.00

$ 2,00 0.0 0

$3,000.00

$ 1,500 .00

$2,000.00

$1,0 00.00

Item

Holding Cost

Part 1

$1.37

Part 2

$0.02

Part 3

$0.09

Part 4

$0.47

Part 5

$0.02

P art 2 P art 1

W hs e

Intr ans it to W h s e

P art 4 P art 4 P art 3

Plant F G

P ar t 5

$ 0.00

Plant R M

P ar t 4

In trans it Stoc k

SS (Ups tream SF )

SS (N LT & Var)

Cy c le Stoc k

$0.00

$50 0.00

In tran s it to P la nts

P ar t 1 P ar t 2 P ar t 3

$1,000.00

IA – Impact of relaxing PDC CST T otal Holding Cost

10000 9000 8000 7000 6000

• CST from Plants is fixed

5000

T o t a l4000 H o ld in g C o s t 3000

• As the CST to dealers increases more inventory is held at the Plants and less at the RDCs

2000

P la nt T o W areho us e H o ld in g C o s t P la nt T o P la n t H oldin g C o s t W a reh o us e Ho ld in g C os t P la nt O utbo und Ho ld in g C o s t P la nt Inb ound Ho ld in g C os t

week s

Plant 0, PDC 4

Week s

Plant 0, PDC 2

Week

Plant 0, PD C 1

day s

Plant 0, PDC 3

day s

Plant 0, PDC 2

day

Plant 0, PDC 1

Plant 0, PDC 0

1000

IA â&#x20AC;&#x201C; Impact of changes in CST to Dealers Cost Vs CST $10,000

Cost/Month

$8,000 $6,000 $4,000 $2,000 $0 0

Com m itted Service Tim efrom PDC to Dealers Cost w ith CST changes at Plants and DCs

Cost w ith CST changes only at the DCs

IA â&#x20AC;&#x201C; Impact of Supplier CST Cost Vs Supplier CST for Oil Filter $12,000 $10,000

Cost

$8,000 $6,000 $4,000 $2,000 $0

Committed Service Time (days)

Prioritizing Savings Opportunities 14000

$26.5M

12000

$17.2M

$34.5M

$36.5M

$38.3M

Free Cash Flow

10000 8000

12000 10000

6000

13.9

18.4

16.2

20.2

20.7

21.2

8000

4000

6000

2000

4000

2000

Current 0

Baseline (Plant Only PDCs 0, PDC 0 CST) hold Inventory Baseline

Only PDCs hold Inventory

Reduced Supplier LT

Reduced Variability

Increased PDC CST

Reduced Supplier Reduced Variability LT

Increased Customer CST

Plant Inbound Holding Cost

Plant Outbound Holding Cost

Warehouse Holding Cost

Plant To Plant Holding Cost

Plant To Warehouse Holding Cost

Inventory Turns

Fewer Stock-outs & Improved Inventory Turns $35.17

$63.25

Safety Stock Savings: 33%

$35.01 CANADA $34.68

$90.45

MICHIGAN $66.89 BOSTON $48.62

Optimal Holding Cost

ILLINOIS $94.92

Current Holding Cost $118.57 $476.14

SUPPLIER

$530.09

$33.45

PLANT DENVER $30.76

$35.83

 Optimized Inventory Positioning leads to better Service Levels with lower Inventory Levels

NEVADA $43.87

$136.17

$43.31

W VIRGINA $159.04

$50.21

Raw Materials Finished Goods

MINNESOTA $53.19 LOS ANGELES $63.14

All numbers in ‘000,000s

IA – Supplier Choice •

Supplier 1: – 4 week CST – 95% Service Level – Lead Time to Proc. Plant: ½ Day

• Supplier 2: – 2.5 week CST – 98% Service Level – Lead Time to Proc. Plant: 1 week

Supplier Comparison

$14,000 $12,000

Plant To Warehouse Holding Cost

$10,000

Plant To Plant Holding Cost

$8,000

Warehouse Holding Cost

$6,000

Plant Outbound Holding Cost

$4,000

Plant Inbound Holding Cost

$2,000 $0 Supplier 1

Supplier 2

Outline of the Presentation Introduction Push-Pull Systems Case Studies High Tech Automotive Electrical Components

Supply Chain Structure ASIAN PLANTS

(35,4)

CA DC

CA PORT

(4,1)

EUROPEAN PLANTS

(15,3)

(4,1)

PHIL PORT

(4,1)

(3,1)

GA DC

(1,0)

LATIN AMERICAN PLANTS

(10,2) (4,1)

MIAMI PORT (2,0)

(3,1)

US PLANTS

(4,1)

IL DC

(4,1)

PA DC

(4,1) (4,1)

(3,1)

TX DC (3,1)

(4,1)

(Transit Time, Std Dev of Transit Time)

MFG #1

Inventory Allowed

Customers (4,1)

Inventory Not Allowed

(3,1)

CR MFG

Supply Chain Size • • • • • •

76 Plants 10 Warehouses 3105 Customers 8297 Products 8297 Plant – Warehouse Transit Lanes 20230 Warehouse – Warehouse Transit Lanes

• 64843 Warehouse – Customer Transit Lanes

Distribution of Inventory Across the Supply Chain

• Large part of the Inventory is In Transit

49.0% 50.0% 45.0% 40.0% 35.0% 30.0%

24.6%

25.0% 16.6%

20.0% 9.6%

15.0% 10.0% 0.3%

5.0% 0.0%

Warehouse

Customer

In Transit f rom Plant

In Transit betw een Warehouse

In Transit to Customer

– Plant to Warehouse – Warehouse to Customer – Warehouse to Warehouse

Across Warehouses RDC-IL

MFG #1 MFG #2 RDC-TX

RDC-GA RDC-CA

RDC-PA

• Most of the Inventory at the Warehouses is in RDC-PA

Safety Stock and Cycle Stock WAREHOUSES

• Top 20% of SKUs account for more than 97% of inventory

5000000 4500000 4000000 3500000 3000000 2500000 2000000 1500000 1000000 500000 0 Cycle Stock

Safety Stock

Top 20% SKUs

Bottom 80% SKUs

CUSTOMERS

12000 10000 8000 6000 4000 2000 0 Cycle Stock Top 20% SKUs

Safety Stock Bottom 80% SKUs

• More Inventory is held at Warehouses than at Customer Locations

Inventory Drivers Inventory by Location

Inventory by Reason

400 180

350

160

300

140

250

120

200

100

150

100

69-1200 39-2700-1 39-1701 Customer

Whse - Cust In Transit

Whse - Whse In Transit

Warehouse

Plant - Whse In Transit

40 69-1200

39-2700-1

0 In Trans it Inventory

39-1701 Cycle Stock

Safety Stock

Sensitivity Analysis

3,500,000

3,000,000

2,500,000

2,000,000

1,500,000

1,000,000 500,000 0 A

W arehous e To Cus tom er Holding Cos t W arehous e To W arehous e Holding Cos t P lant To W arehous e Holding Cos t Cus tom er Holding Cos t W arehous e Holding Cos t

A. B. C.

Customer Holding Cost is not significant (< 0.01%) With no Transit Time Variance from the Ports to PA RDC the Cost is reduced by 5% Reviewing Inventory Daily at warehouses can reduce Inventory Holding Cost by 14%

Inventory Savings Inventory (in $MM)

$120 $100

$100

$19 MM freed cash flow by globally optimizing inventory

$95 $81

$80

Could move from the lower quartile to the medium quartiles

$70

$60 $40

5.0

5.3

6.2

Current Inv

Proper Levels

Opt Positioning

7.1

$20 $0 Changing Policies

Lessons Learned • Globally optimizing inventory can have a dramatic impact – Take advantage of risk pooling and inventory positioning

• Identifying inventory drivers is not easy – Many policies and practices were causing poor inventory turnover ratio – Can be done with an inventory model – Highlights areas for improvement ©Copyright 2003 D. Simchi-Levi

Lessons Learned Manufacturing company inventory turns 8 7 6 5 4 3 2 1 0

Heuristics • Service Level not always met • Excess Inventory at some location

Calculation

Global Optimization

• Safety Stock at each node calculated independently • Few factors considered • Service Level not always met

• Safety Stock at each node depends on attributes of all nodes • Most complete model available • Positions safety stock across the network