Supply Chain Integration
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
Outline of the Presentation
 The Bullwhip Effect
 Distribution Strategies and Information
Systems
 Supply Chain Management: Pitfalls and
Opportunities
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. 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 1999 D. Simchi-Levi, P. Kaminsky & E. 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 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
The Bullwhip Effect
and its Impact on the Supply Chain
Figure 4. POS Data After Removing Promotion & Trend
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. 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 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
Increasing Variability of Orders
Up the Supply Chain
Lee, H, P. Padmanabhan and S. Wang (1997), Sloan Management Review
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. 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 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
What are the Causes….
• Promotional sales
• Inflated orders
- IBM Aptiva orders increased by 2-3 times
when retailers though that IBM would be out
of stock over Christmas
- Same with Motorola’s Cellular phones
• Demand Forecast
• Long cycle times
• Order Batching
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
What are the Causes….
• Single retailer, single manufacturer.
– Retailer observes customer demand, Dt.
– Retailer orders qt from manufacturer.
– Lead time + 1 = L.
Dt
Retailer
qt
L
Manufacturer
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
The Bullwhip Effect
2
Var (Q)
2L 2L
 1
 2
Var ( D)
P P
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
Var(q)/Var(D):
For Various Lead Times
14
L=5
12
10
L=3
8
6
L=1
L=1
4
2
0
0
5
10
15
20
25
30
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
Consequences….
•
•
•
•
Increased safety stock
Reduced service level
Inefficient allocation of resources
Increased transportation costs
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. 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 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
Formula
k
K
Var (Q )
 1
Var ( D)
2( Li )
i 1
p
k

2( Li )
2
i 1
p
2
 2 Li 2 Li 
Var (Q )
  1 
 2 
Var ( D)
p
p 
i 1 
K
k 1
2
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
Multi-Stage
Systems:Var(qk)/Var(D)
30
Dec, k=5
25
20
15
Cen, k=5
10
Dec, k=3
Cen, k=3
5
k=1
0
0
5
10
15
20
25
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
The Bullwhip Effect:
Managerial Insights
• Exists, in part, due to the retailer’s need to
estimate the mean and variance of demand.
• The increase in variability is an increasing
function of the lead time.
• The more complicated the demand models
and the forecasting techniques, the greater
the increase.
• Centralized demand information can reduce
the bullwhip effect, but will not eliminate it.
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
Coping with the Bullwhip Effect
• Reduce Variability and Uncertainty
- POS
- Sharing Information
- Year-round low pricing
• Reduce Lead Times
- EDI
- Cross Docking
• Alliance Arrangements
– Vendor managed inventory
– On-site vendor representatives
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
Example:
Quick Response at Benetton
• Benetton, the Italian sportswear manufacturer, was
founded in 1964. In 1975 Benetton had 200 stores
across Italy.
• Ten years later, the company expanded to the U.S.,
Japan and Eastern Europe. Sales in 1991 reached 2
trillion.
• Many attribute Benetton’s success to successful use
of communication and information technologies.
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
Example:
Quick Response at Benetton
• Benetton uses an effective strategy, referred to
as Quick Response, in which manufacturing,
warehousing, sales and retailers are linked
together. In this strategy a Benetton retailer
reorders a product through a direct link with
Benetton’s mainframe computer in Italy.
• Using this strategy, Benetton is capable of
shipping a new order in only four weeks, several
week earlier than most of its competitors.
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
How Does Benetton
Cope with the Bullwhip Effect?
1. Integrated Information Systems
• Global EDI network that links agents with
production
and inventory information
• EDI order transmission to HQ
• EDI linkage with air carriers
• Data linked to manufacturing
2. Coordinated Planning
• Frequent review allows fast reaction
• Integrated distribution strategy
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
Distribution Strategies
and Information Systems
Pull Vs. Push Strategies
Push Strategies
• Production decisions based on forecasts
• Manual purchase orders and invoices are
employed
• Ordering decisions based on inventory &
forecasts.
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
Push Strategies
• Single retailer, single manufacturer.
– Retailer observes customer demand,
Dt.
– Retailer orders qt from manufacturer.
Dt
Retailer
qt
L
Manufacturer
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
Distribution Strategies
and Information Systems
Problems with Push Strategies:
• Excess finished goods inventory
• Inefficient production
• Inefficient operations, high costs, low service
levels
- Excess capacity
- Low utilization of resources
- High transportation cost
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
Pull Strategies
• Single retailer, single manufacturer.
– Retailer observes customer demand, Dt.
– Retailer orders qt from manufacturer.
POS Data
Dt
Retailer
qt
L
Manufacturer
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
Distribution Strategies and
Information Systems
•
•
•
•
•
Pull Strategies
Production is demand driven
Faster information flow mechanisms are used
Inventory levels are reduced
Distribution facilities are transformed from
storage points to coordinators of flow.
But:
– Harder to leverage economies of scale
– Doesn’t work in all cases
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
Push and Pull Systems
• To take advantage of both
• How can this be accomplished?
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
Distribution Strategies
• Warehousing
• Direct Shipping
– No DC needed
– Lead times reduced
– “smaller trucks”
– no risk pooling effects
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
Cross Docking
In 1979, Kmart was the king of the retail industry
with 1891 stores and average revenues per store of
$7.25 million
• At that time Wal-Mart was a small niche retailer in
the South with only 229 stores and average revenues
about half of those Kmart stores.
• Ten years later, Wal-Mart transformed itself; it has
the highest sales per square foot, inventory turnover
and operating profit of any discount retailer. Today
Wal-Mart is the largest and highest profit retailer in
the world.
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
What accounts for Wal-Mart’s
remarkable success
• The starting point was a relentless focus on satisfying
customer needs; Wal-Mart goal was simply to provide
customers access to goods when and where they
want them and to develop cost structures that enable
competitive pricing
• The key to achieving this goal was to make the way
the company replenished inventory the centerpiece of
its strategy.
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
What accounts for Wal-Mart’s
remarkable success?
• This was obtained by using a logistics technique
known as cross-docking. Here goods are continuously
delivered to Wal-Mart’s warehouses where they are
dispatched to stores without ever sitting in inventory.
• This strategy reduced Wal-Mart’s cost of sales
significantly and made it possible to offer everyday
low prices to their customers.
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
Characteristics of Cross-Docking:
• Goods spend at most 48 hours in the
warehouse,
• Avoids inventory and handling costs,
• Wal-Mart delivers about 85% of its goods
through its warehouse system, compared to
about 50% for Kmart,
• Stores trigger orders for products.
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
System Characteristics:
• Very difficult to manage,
• Requires linking Wal-Mart’s distribution
centers, suppliers and stores to guarantee
that any order is processed and executed in a
matter of hours,
• Wal-Mart operates a private satellitecommunications system that sends point-ofsale data to all its vendors allowing them to
have a clear vision of sales at the stores
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
System Characteristics:
• Need a fast and responsive transportation
system:
• Wal-Mart has a dedicated fleet of 2000 truck
that serve their 19 warehouses
• This allows them to
– ship goods from warehouses to stores in
less than 48 hours
– replenish stores twice a week on average.
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
Distribution Strategies
Strategy
Attribute
Direct
Shipment
Cross
Docking
Risk
Pooling
Take
Advantage
Transportation
Costs
Holding
Costs
Demand
Variability
Inventory at
Warehouses
Reduced
Inbound Costs
No Warehouse
Costs
Reduced
Inbound Costs
No Holding
Costs
Delayed
Allocation
Delayed
Allocation
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
Transshipment
• What is the value of this?
• What tools are needed?
• What if the system is decentralized?
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
Supply Chain Integration - Dealing
with Conflicting Goals
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Lot Size vs. Inventory
Inventory vs. Transportation
Lead Time vs. Transportation
Product Variety vs. Inventory
Cost vs. Customer Service
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
Supply Chain Management:
Pitfalls and Opportunities
Conflicting Objectives in the Supply
Chain
1. Purchasing
• Stable volume requirements
• Flexible delivery time
• little variation in mix
• large quantities
2. Manufacturing
• Long run production
• High quality
• High productivity
• Low production cost
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
Supply Chain Management:
Pitfalls and Opportunities
3. Warehousing
• Low inventory
• Reduced transportation costs
• Quick replenishment capability
4. Customers
• Short order lead time
• High in stock
• Enormous variety of products
• Low prices
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
Symptoms of Supply Chain Problems
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•
•
•
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Stock-outs and High Inventory
Long Cycle Times
High Returns
High Costs
Poor Service Level
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
Common Pitfalls
1. Information and Management
• No Supply Chain Metrics
• Inadequate Definition of Customer Service
• Inaccurate Delivery Status Data
• Inefficient Information Systems
2. Operational Control
• Ignoring the Impact of Uncertainties
• Simplistic Inventory Stocking Policies
• Discrimination against Internal Customers
• Poor Coordination
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi
Common Pitfalls
3. Design and Strategy
• Incomplete Shipment Methods Analysis
• Incorrect Assessment of Inventory Costs
• Product and Process Design without SC
Consideration
• Focus on Incomplete Supply Chain
©Copyright 1999 D. Simchi-Levi, P. Kaminsky & E. Simchi-Levi