Transcript Simchi-Levi_ISEP_04

Innovation and Strategies in
Supply Chain Management
David Simchi-Levi
Professor of Engineering Systems
Massachusetts Institute of Technology
Tel: 617-253-6160
E-mail: [email protected]
Outline of the Presentation
 Introduction
 Push-Pull Systems
 Supply Contracts
©Copyright 2004 D. Simchi-Levi
Today’s Supply Chain Pitfalls
•
•
•
•
•
Long Lead Times
Uncertain Demand
Complex Product Offering
Component Availability
System Variation Over Time
©Copyright 2004 D. Simchi-Levi
The Bullwhip Effect
and its Impact on the Supply Chain
• Consider the order pattern of a single color
television model sold by a large electronics
manufacturer to one of its accounts, a
national retailer.
Figure 1. Order
Stream
Huang at el. (1996), Working paper, Philips Lab
©Copyright 2004 D. Simchi-Levi
The Bullwhip Effect
and its Impact on the Supply Chain
Figure 2. Point-of-sales
Data-Original
Figure 3. POS Data After
Removing Promotions
©Copyright 2004 D. Simchi-Levi
The Bullwhip Effect
and its Impact on the Supply Chain
Figure 4. POS Data After Removing Promotion & Trend
©Copyright 2004 D. Simchi-Levi
Higher Variability in Orders Placed by Computer
Retailer to Manufacturer Than Actual Sales
Lee, H, P. Padmanabhan and S. Wang (1997), Sloan Management Review
©Copyright 2004 D. Simchi-Levi
Increasing Variability of Orders
Up the Supply Chain
Lee, H, P. Padmanabhan and S. Wang (1997), Sloan Management Review
©Copyright 2004 D. Simchi-Levi
We Conclude ….
• Order Variability is amplified up the
supply chain; upstream echelons face
higher variability.
• What you see is not what they face.
©Copyright 2004 D. Simchi-Levi
The Bullwhip Effect
P&G
Retailers
Customers
©Copyright 2004 D. Simchi-Levi
What are the Causes….
• Promotional sales
• Volume and Transportation Discounts
• Inflated orders
- IBM Aptiva orders increased by 2-3
times when retailers thought that IBM
would be out of stock over Christmas
- Same with Motorola’s Cellular phones
©Copyright 2004 D. Simchi-Levi
What are the Causes….
• Single retailer, single manufacturer.
– Retailer observes customer demand,
Dt.
– Retailer orders qt from manufacturer.
Dt
Retailer
qt
L
Manufacturer
©Copyright 2004 D. Simchi-Levi
What are the Causes….
•
•
•
•
•
Promotional sales
Volume and Transportation Discounts
Inflated orders
Demand Forecast
Long cycle times
©Copyright 2004 D. Simchi-Levi
Consequences….
• Increased safety stock
• Reduced service level
©Copyright 2004 D. Simchi-Levi
Consequences….
• Single retailer, single manufacturer.
– Retailer observes customer demand,
Dt.
– Retailer orders qt from manufacturer.
Dt
Retailer
qt
L
Manufacturer
©Copyright 2004 D. Simchi-Levi
Consequences….
• Increased safety stock
• Reduced service level
• Inefficient allocation of resources
• Increased transportation costs
©Copyright 2004 D. Simchi-Levi
Multi-Stage Supply Chains
Consider a multi-stage supply chain:
– Stage i places order qi to stage i+1.
– Li is lead time between stage i and
i+1.
qo=D
Retailer
Stage 1
q1
L1
Manufacturer
Stage 2
q2
L2
Supplier
Stage 3
©Copyright 2004 D. Simchi-Levi
What are the Causes….
•
•
•
•
•
•
Promotional sales
Volume and Transportation Discounts
Inflated orders
Demand Forecast
Long cycle times
Luck of centralized demand
information
©Copyright 2004 D. Simchi-Levi
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”
©Copyright 2004 D. Simchi-Levi
Supply Chain Strategies
• Achieving Global Optimization
• Managing Uncertainty
– Risk Pooling
– Risk Sharing
©Copyright 2004 D. Simchi-Levi
Sequential Optimization vs.
Global Optimization
Sequential Optimization
Procurement
Planning
Manufacturing
Planning
Distribution
Planning
Demand
Planning
Global Optimization
Supply Contracts/Collaboration/Integration/DSS
Procurement
Planning
Manufacturing
Planning
Distribution
Planning
Demand
Planning
Source: Duncan McFarlane
©Copyright 2004 D. Simchi-Levi
A new Supply Chain Paradigm
• A shift from a Push System...
– Production decisions are based on forecast
• …to a Push-Pull System
©Copyright 2004 D. Simchi-Levi
From Make-to-Stock Model….
Suppliers
Assembly
Configuration
©Copyright 2004 D. Simchi-Levi
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
©Copyright 2004 D. Simchi-Levi
A new Supply Chain Paradigm
• A shift from a Push System...
– Production decisions are based on forecast
• …to a Push-Pull System
©Copyright 2004 D. Simchi-Levi
Push-Pull Supply Chains
The Supply Chain Time Line
Customers
Suppliers
PUSH STRATEGY
Low Uncertainty
PULL STRATEGY
High Uncertainty
Push-Pull Boundary
©Copyright 2004 D. Simchi-Levi
A new Supply Chain Paradigm
• A shift from a Push System...
– Production decisions are based on forecast
• …to a Push-Pull System
– Parts inventory is replenished based on
forecasts
– Assembly is based on accurate customer
demand
©Copyright 2004 D. Simchi-Levi
….to Assemble-to-Order Model
Suppliers
Assembly
Configuration
©Copyright 2004 D. Simchi-Levi
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
©Copyright 2004 D. Simchi-Levi
Business models in the Book
Industry
• From Push Systems...
– Barnes and Noble
• ...To Pull Systems
– Amazon.com, 1996-1999
• And, finally to Push-Pull Systems
– Amazon.com, 1999-present
• 7 warehouses, 3M sq. ft.,
©Copyright 2004 D. Simchi-Levi
Direct-to-Consumer:Cost Trade-Off
Cost ($ million)
Cost Trade-Off for BuyPC.com
$20
$18
$16
$14
$12
$10
$8
$6
$4
$2
$0
Total Cost
Inventory
Transportation
Fixed Cost
0
5
10
Number of DC's
15
Business models in the Grocery
Industry
• From Push Systems...
– Supermarket supply chain
• ...To Pull Systems
– Peapod, 1989-1999
• Stock outs 8% to 10%
• And, finally to Push-Pull Systems
– Peapod, 1999-present
• Dedicated warehouses
• Stock outs less than 2%
©Copyright 2004 D. Simchi-Levi
Business models in the Grocery
Industry
• Key Challenges for e-grocer:
– Transportation cost
• Density of customers
– Very short order cycle times
• Less than 12 hours
©Copyright 2004 D. Simchi-Levi
e-Business in the Retail Industry
• Brick-&-Mortar companies establish Virtual
retail stores
– Wal-Mart, K-Mart, Barnes and Noble
• Use a hybrid approach in stocking
– Fast moving/High volume products for local
storage
– Slow moving/Low volume products for on-line
purchase
• Channel Conflict Issues
©Copyright 2004 D. Simchi-Levi
Matching Supply Chain Strategies
with Products
Demand
uncertainty
(C.V.)
Pull
H
I
II
Computer
IV
Push
III
Delivery cost
Unit price
L
L
Pull
H
Economies of
Scale
Push
©Copyright 2004 D. Simchi-Levi
Shifting the Push-Pull Boundary:
A Case Study
• Manufacturer of circuit boards and other
high-tech products
• Sells customized products with high value and
short life cycles
• Multi-stage BOM
– e.g., copper & fiberglass  circuit board 
enclosure  processor
• Case study concerns one of 27,000 SKUs
©Copyright 2004 D. Simchi-Levi
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
5
Number in the white
box is the commitment
time to the next stage
0
PART 1
DALLAS ($260)
2
30
15
PART 3
88
MONTGOMERY ($220)
15
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
Number under the box
is the processing time
©Copyright 2004 D. Simchi-Levi
x2
PART 2
DALLAS ($0.50)
Safety Stock Cost = $74,100/yr
0
0
5
PART 4
MALAYSIA ($180)
7
PART 5
37
CHARLESTON ($12)
PART 1
DALLAS ($260)
28
3
3
PART 7
DENVER ($2.50)
58
4
PART 6
RALEIGH ($3)
2
30
15
PART 3
88
MONTGOMERY ($220)
15
70
8
x2
Safety Stock Cost = $45,400/yr
(39% savings)
PART 2
DALLAS ($0.50)
5
5
PART 4
MALAYSIA ($180)
7
PART 5
37
CHARLESTON ($12)
PART 1
DALLAS ($260)
28
3
3
PART 7
DENVER ($2.50)
58
4
PART 6
RALEIGH ($3)
8
0
2
PART 3
13
MONTGOMERY ($220)
15
32
©Copyright 2004 D. Simchi-Levi
15
30
Safety Stock Cost = $53,700/yr
(28% savings, 50% reduction in LT)
PART 2
DALLAS ($0.50)
0
5
PART 4
MALAYSIA ($180)
7
PART 5
37
CHARLESTON ($12)
PART 1
DALLAS ($260)
28
3
3
PART 7
DENVER ($2.50)
58
4
PART 6
RALEIGH ($3)
0
2
PART 3
50
MONTGOMERY ($220)
15
32
8
©Copyright 2004 D. Simchi-Levi
15
15
Comparison of Performance Measures
Scenario
1: Baseline
2: Optimization
3: Shorten Lead Time
Safety Stock
Holding Cost
($/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
©Copyright 2004 D. Simchi-Levi
PART 31
40
SEA ($20)
6
PART 23
50
DAL ($30)
PART 18
51
DAL ($35)
4
PART 38
NJ ($8)
PART 32
10
NJ ($22)
8
PART 39
TAI ($15)
5
28
3
2
3
3
PART 41
PHI ($32)
6
1
PART 36
20
NJ ($40)
13
PART 42
PHI ($2)
3
3
PART 37
10
DAL ($8)
4
50
PART 19
61
DAL ($210)
PART 12
62
DAL ($260)
PART 4
65
DAL ($285)
1
6
3
PART 5
DAL ($3)
PART 26
25
DAL ($80)
2
PART 34
49
WAS ($25)
PART 35
NJ ($35)
1
2
PART 25
3
52
WAS ($75)
PART 33
42
WAS ($30)
2
3
PART 3
50
DAL ($6)
6
9
35
PART 40
12
NZ ($22)
1
PART 2
55
DAL ($55)
PART 24
16
NJ ($30)
2
8
PART 11
54
DAL ($40)
2
4
3
PART 27
NJ ($4)
PART 13
24
MEX ($11)
1
8
PART 6
46
DAL ($18)
14
1
PART 1
30
DAL ($535)
4
PART 14
10
MEX ($4)
PART 28
17
DAL ($12)
8
PART 7
21
DAL ($9)
3
7
PART 20
18
WAS ($42)
PART 29
12
WAS ($40)
12
3
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)
4
4
3
PART 22
23
DAL ($28)
16
PART 17
26
DAL ($30)
PART 8
56
DAL ($65)
30
PART 9
82
DAL ($30)
1
PART 10
38
DAL ($35)
3
12
©Copyright
2004 D. Simchi-Levi
PART 31
40
SEA ($20)
6
PART 23
21
DAL ($30)
PART 18
22
DAL ($35)
4
PART 38
NJ ($8)
PART 32
NJ ($22)
6
PART 39
TAI ($15)
5
28
3
2
3
6
1
PART 36
11
NJ ($40)
3
3
PART 37
DAL ($8)
4
PART 4
26
DAL ($285)
PART 12
23
DAL ($260)
1
6
3
PART 5
DAL ($3)
2
PART 27
NJ ($4)
9
PART 13
24
MEX ($11)
1
8
PART 6
26
DAL ($18)
14
PART 1
30
DAL ($535)
4
PART 14
10
MEX ($4)
PART 28
16
DAL ($12)
8
PART 7
21
DAL ($9)
3
PART 20
18
WAS ($42)
PART 29
12
WAS ($40)
12
3
6
PART 21
35
41
NZ ($18)
Safety Stock Cost = $36,600/yr
(62% savings)
PART 30
PHI ($6)
4
4
3
7
13
PART 42
PHI ($2)
PART 19
22
DAL ($210)
1
3
PART 41
PHI ($32)
50
PART 26
16
DAL ($80)
2
PART 34
10
WAS ($25)
PART 35
NJ ($35)
1
2
PART 25
13
WAS ($75)
3
PART 33
10
WAS ($30)
2
3
PART 3
26
DAL ($6)
6
9
35
PART 40
12
NZ ($22)
1
PART 2
26
DAL ($55)
PART 24
14
NJ ($30)
8
2
8
PART 11
25
DAL ($40)
PART 15
26
DAL ($60)
5
PART 16
25
DAL ($21)
5
4
3
PART 22
11
DAL ($28)
16
PART 17
14
DAL ($30)
PART 8
26
DAL ($65)
30
PART 9
26
DAL ($30)
1
PART 10
26
DAL ($35)
3
12
©Copyright
2004 D. Simchi-Levi
Comparison of Performance Measures
Scenario
1: Baseline
2: Optimization
Safety Stock
Holding Cost
($/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
©Copyright 2004 D. Simchi-Levi
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
20
40
60
80
100
©Copyright 2004 D. Simchi-Levi
Lead Time Quoted to Customer (days)
Outline of the Presentation
 Introduction
 Push-Pull Systems
 Supply Contracts
©Copyright 2004 D. Simchi-Levi
Supply Contracts
• Fashion items
– short life cycles
– High product variety
– One production opportunity
– Simple supply chain structure
– High demand uncertainty
©Copyright 2004 D. Simchi-Levi
Supply Contracts
Fixed Production Cost =$100,000
Variable Production Cost=$35
Wholesale Price =$80
Selling Price=$125
Salvage Value=$20
Manufacturer
Manufacturer DC
Retail DC
Stores
©Copyright 2004 D. Simchi-Levi
Demand Scenarios
18
00
0
16
00
0
14
00
0
12
00
0
10
00
0
30%
25%
20%
15%
10%
5%
0%
80
00
Probability
Demand Scenarios
Sales
©Copyright 2004 D. Simchi-Levi
Summary of Retailer Information
•
•
•
•
Wholesale cost per unit (C): $80
Selling price per unit (S): $125
Salvage value per unit (V): $20
Average demand = 13,000 units
• Should the retailer order more than
average demand, less than average
demand or exactly average
demand?
©Copyright 2004 D. Simchi-Levi
Scenario Analysis
• Scenario One:
– Suppose you make 12,000 jackets and
demand ends up being 13,000 jackets.
– Profit = 125(12,000) - 80(12,000) = $540,000
• Scenario Two:
– Suppose you make 12,000 jackets and
demand ends up being 11,000 jackets.
– Profit = 125(11,000) - 80(12,000) + 20(1000) =
$435,000
©Copyright 2004 D. Simchi-Levi
Distributor Expected Profit
Expected Profit
500000
400000
300000
200000
100000
0
6000
8000
10000
12000
14000
16000
18000
20000
Order Quantity
©Copyright 2004 D. Simchi-Levi
Distributor Expected Profit
Expected Profit
500000
400000
300000
200000
100000
0
6000
8000
10000
12000
14000
16000
18000
20000
Order Quantity
©Copyright 2004 D. Simchi-Levi
Supply Contracts (cont.)
• Distributor optimal order quantity is
12,000 units
• Distributor expected profit is $470,000
• Manufacturer profit is $440,000
• Supply Chain Profit is $910,000
–IS there anything that the distributor and
manufacturer can do to increase the profit
of both?
©Copyright 2004 D. Simchi-Levi
Supply Contracts
Fixed Production Cost =$100,000
Variable Production Cost=$35
Wholesale Price =$80
Selling Price=$125
Salvage Value=$20
Manufacturer
Manufacturer DC
Retail DC
Stores
©Copyright 2004 D. Simchi-Levi
Retailer Profit
(Buy Back=$55)
Retailer Profit
600,000
500,000
400,000
300,000
200,000
100,000
0
00 00 00 00
00 00 00 00 00
00 00 00 00
60 70 80 90 100 110 120 130 140 150 160 170 180
Order Quantity
©Copyright 2004 D. Simchi-Levi
Retailer Profit
(Buy Back=$55)
Retailer Profit
600,000
$513,800
500,000
400,000
300,000
200,000
100,000
0
00 00 00 00
00 00 00 00 00
00 00 00 00
60 70 80 90 100 110 120 130 140 150 160 170 180
Order Quantity
©Copyright 2004 D. Simchi-Levi
Manufacturer Profit
(Buy Back=$55)
500,000
400,000
300,000
200,000
100,000
0
60
00
70
00
80
00
90
00
10
00
0
11
00
0
12
00
0
13
00
0
14
00
0
15
00
0
16
00
0
17
00
0
18
00
0
Manufacturer Profit
600,000
Production Quantity
©Copyright 2004 D. Simchi-Levi
Manufacturer Profit
(Buy Back=$55)
500,000
$471,900
400,000
300,000
200,000
100,000
0
60
00
70
00
80
00
90
00
10
00
0
11
00
0
12
00
0
13
00
0
14
00
0
15
00
0
16
00
0
17
00
0
18
00
0
Manufacturer Profit
600,000
Production Quantity
©Copyright 2004 D. Simchi-Levi
Supply Contracts
Fixed Production Cost =$100,000
Variable Production Cost=$35
Wholesale Price =$80
Selling Price=$125
Salvage Value=$20
Manufacturer
Manufacturer DC
Retail DC
Stores
©Copyright 2004 D. Simchi-Levi
Retailer Profit
(Wholesale Price $70, RS 15%)
500,000
400,000
300,000
200,000
100,000
0
60
00
70
00
80
00
90
00
10
00
0
11
00
0
12
00
0
13
00
0
14
00
0
15
00
0
16
00
0
17
00
0
18
00
0
Retailer Profit
600,000
Order Quantity
©Copyright 2004 D. Simchi-Levi
Retailer Profit
(Wholesale Price $70, RS 15%)
$504,325
500,000
400,000
300,000
200,000
100,000
0
60
00
70
00
80
00
90
00
10
00
0
11
00
0
12
00
0
13
00
0
14
00
0
15
00
0
16
00
0
17
00
0
18
00
0
Retailer Profit
600,000
Order Quantity
©Copyright 2004 D. Simchi-Levi
Manufacturer Profit
(Wholesale Price $70, RS 15%)
600,000
500,000
400,000
300,000
200,000
100,000
0
60
00
70
00
80
00
90
00
10
00
0
11
00
0
12
00
0
13
00
0
14
00
0
15
00
0
16
00
0
17
00
0
18
00
0
Manufacturer Profit
700,000
Production Quantity
©Copyright 2004 D. Simchi-Levi
Manufacturer Profit
(Wholesale Price $70, RS 15%)
600,000
500,000
$481,375
400,000
300,000
200,000
100,000
0
60
00
70
00
80
00
90
00
10
00
0
11
00
0
12
00
0
13
00
0
14
00
0
15
00
0
16
00
0
17
00
0
18
00
0
Manufacturer Profit
700,000
Production Quantity
©Copyright 2004 D. Simchi-Levi
Supply Contracts
Strategy
Sequential Optimization
Buyback
Revenue Sharing
Retailer Manufacturer
470,700
440,000
513,800
471,900
504,325
481,375
©Copyright 2004 D. Simchi-Levi
Total
910,700
985,700
985,700
Supply Contracts
Fixed Production Cost =$100,000
Variable Production Cost=$35
Wholesale Price =$80
Selling Price=$125
Salvage Value=$20
Manufacturer
Manufacturer DC
Retail DC
Stores
©Copyright 2004 D. Simchi-Levi
Supply Chain Profit
1,000,000
800,000
600,000
400,000
200,000
0
60
00
70
00
80
00
90
00
10
00
0
11
00
0
12
00
0
13
00
0
14
00
0
15
00
0
16
00
0
17
00
0
18
00
0
Supply Chain Profit
1,200,000
Production Quantity
©Copyright 2004 D. Simchi-Levi
Supply Chain Profit
$1,014,500
1,000,000
800,000
600,000
400,000
200,000
0
60
00
70
00
80
00
90
00
10
00
0
11
00
0
12
00
0
13
00
0
14
00
0
15
00
0
16
00
0
17
00
0
18
00
0
Supply Chain Profit
1,200,000
Production Quantity
©Copyright 2004 D. Simchi-Levi
Supply Contracts
Strategy
Sequential Optimization
Buyback
Revenue Sharing
Global Optimization
Retailer Manufacturer
470,700
440,000
513,800
471,900
504,325
481,375
Total
910,700
985,700
985,700
1,014,500
©Copyright 2004 D. Simchi-Levi
Supply Contracts: Key Insights
• Effective supply contracts allow supply
chain partners to replace sequential
optimization by global optimization
• Buy Back and Revenue Sharing contracts
achieve this objective through risk
sharing
©Copyright 2004 D. Simchi-Levi
Supply Contracts: Case Study
• Example: Demand for a movie newly released video
cassette typically starts high and decreases rapidly
– Peak demand last about 10 weeks
• Blockbuster purchases a copy from a studio for $65
and rent for $3
– Hence, retailer must rent the tape at least 22 times before
earning profit
• Retailers cannot justify purchasing enough to cover
the peak demand
– In 1998, 20% of surveyed customers reported that they
could not rent the movie they wanted
©Copyright 2004 D. Simchi-Levi
Supply Contracts: Case Study
• Starting in 1998 Blockbuster entered a revenue sharing
agreement with the major studios
– Studio charges $8 per copy
– Blockbuster pays 30-45% of its rental income
• Even if Blockbuster keeps only half of the rental income,
the breakeven point is 6 rental per copy
• The impact of revenue sharing on Blockbuster was
dramatic
– Rentals increased by 75% in test markets
– Market share increased from 25% to 31% (The 2nd largest
retailer, Hollywood Entertainment Corp has 5% market share)
©Copyright 2004 D. Simchi-Levi
What are the drawbacks of RS?
• Administrative Cost
– Lawsuit brought by three independent video retailers who
complained that they had been excluded from receiving the
benefits of revenue sharing was dismissed (June 2002)
– The Walt Disney Company has sued Blockbuster accusing
them of cheating its video unit of approximately $120 million
under a four year revenue sharing agreement (January 2003)
• Impact on sales effort
– Retailers have incentive to push products with higher profit
margins
– Automotive industry: automobile sales depends on retail effort
©Copyright 2004 D. Simchi-Levi
What are the drawbacks of RS?
• Retailer may carry substitute or
complementary products from other
suppliers
– One supplier offers revenue sharing while
the other does not
• Substitute products: retail will push the product
with high margin
• Complementary products: retailer may discount
the product offered under revenue sharing to
motivate sales of the other product
©Copyright 2004 D. Simchi-Levi
Other Contracts
• Quantity Flexibility Contracts
– Supplier provides full refund for returned
items as long as the number of returns is
no larger than a certain quantity
• Sales Rebate Contracts
– Supplier provides direct incentive for the
retailer to increase sales by means of a
rebate paid by the supplier for any item
sold above a certain quantity
©Copyright 2004 D. Simchi-Levi