Supply Chain Integration
Phil Simchi-Levi
Kaminsky
David
[email protected]
Philip Kaminsky
Edith Simchi-Levi
The Old Paradigm:
Push Strategies



Production decisions based on long-term
forecasts
Ordering decisions based on inventory &
forecasts
What are the problems with push strategies?
– Inability to meet changing demand patterns
– Obsolescence
– The bullwhip effect:



Excessive inventory
Excessive production variability
Poor service levels
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
A Newer Paradigm:
Pull Strategies

Production is demand driven
– Production and distribution coordinated with true customer
demand
– Firms respond to specific orders

Pull Strategies result in:
–
–
–
–

Reduced lead times (better anticipation)
Decreased inventory levels at retailers and manufacturers
Decreased system variability
Better response to changing markets
But:
– Harder to leverage economies of scale
– Doesn’t work in all cases
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
Push and Pull Systems
 What
are the advantages of push
systems?
 What are the advantages of pull
systems?
 Is there a system that has the
advantages of both systems?
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
A new Supply Chain
Paradigm

A shift from a Push System...
– Production decisions are based on forecast

…to a Push-Pull System
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
Push-Pull Supply Chains
The Supply Chain Time Line
Customers
Suppliers
PUSH STRATEGY
Low Uncertainty
PULL STRATEGY
High Uncertainty
Push-Pull Boundary
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
A new Supply Chain
Paradigm

A shift from a Push System...
– Production decisions are based on forecast

…to a Push-Pull System
– Initial portion of the supply chain is replenished
based on long-term forecasts
 For
example, parts inventory may be replenished
based on forecasts
– Final supply chain stages based on actual
customer demand.
 For
example, assembly may based on actual orders.
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
Consider Two PC
Manufacturers:

Build to Stock
–
–
–
–

Forecast demand
Buys components
Assembles computers
Observes demand and
meets demand if
possible.
A traditional push
system

Build to order
–
–
–
–
–

Forecast demand
Buys components
Observes demand
Assembles computers
Meets demand
A push-pull system
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
Push-Pull Strategies

The push-pull system takes advantage of
the rules of forecasting:
– Forecasts are always wrong
– The longer the forecast horizon the worst is the
forecast
– Aggregate forecasts are more accurate
 The

Risk Pooling Concept
Delayed differentiation is another example
– Consider Benetton sweater production
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
What is the Best
Strategy?
Demand
uncertainty
(C.V.)
Pull
H
I
II
Computer
IV
Push
III
Delivery cost
Unit price
L
L
Pull
H
Push
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
Economies of
Scale
Selecting the Best SC
Strategy




Higher demand uncertainty suggests push
Higher importance of economies of scale suggests
push
High uncertainty/ EOS not important such as the
computer industry implies pull
Low uncertainty/ EOS important such as groceries
implies push
– Demand is stable
– Transportation cost reduction is critical
– Pull would not be appropriate here.
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
Selecting the Best SC
Strategy

Low uncertainty but low value of economies
of scale (high volume books and cd’s)
– Either push strategies or push/pull strategies
might be most appropriate

High uncertainty and high value of
economies of scale
– For example, the furniture industry
– How can production be pull but delivery push?
– Is this a “pull-push” system?
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
Characteristics and Skills
Raw
Material
Customers
Push
Pull
Low Uncertainty
High Uncertainty
Long Lead Times
Short Cycle Times
Cost Minimization
Service Level
Resource Allocation
Responsiveness
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
Locating the Push-Pull
Boundary

The push section:
–
–
–
–

Uncertainty is relatively low
Economies of scale important
Long lead times
Complex supply chain structures:
Thus
– Management based on forecasts is appropriate
– Focus is on cost minimization
– Achieved by effective resource utilization – supply chain optimization

The pull section:
– High uncertainty
– Simple supply chain structure
– Short lead times

Thus
– Reacting to realized demand is important
– Focus on service level
– Flexible and responsive approaches
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
Locating the Push-Pull
Boundary

The push section requires:
– Supply chain planning
– Long term strategies

The pull section requires:
– Order fulfillment processes
– Customer relationship management

Buffer inventory at the boundaries:
– The output of the tactical planning process
– The input to the order fulfillment process.
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
Locating the Push-Pull
Boundary
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
Impact of the Internet –
Expectations Were High

E-business strategies were supposed to:
– Reduce cost
– Increase service level
– Increase flexibility
– Increase Profit
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
Reality is Different…..

Amazon.com Example
–
–
–
–
–

Founded in 1995; 1st Internet purchase for most people
1996: $16M Sales, $6M Loss
1999: $1.6B Sales, $720M Loss
2000: $2.7B Sales, $1.4B Loss
Last quarter of 2001: $50M Profit
 Total debt: $2.2B
Peapod Example
–
–
–
–
Founded 1989
140,000 members, largest on-line grocer
Revenue tripled to $73 million in 1999
1st Quarter of 2000: $25M Sales, Loss: $8M
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
Reality is Different….
 Furniture.com – launched in 1999, with
thousands of products

$22 Million in sales the first nine months

Over 1,000,000 visitors per month

Died November 6, 2000
– Logistics costs too high
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
Reality is Different….

Dell Example:
– Dell Computer has outperformed the competition in
terms of shareholder value growth over the eight years
period, 1988-1996, by over 3,000% (see Anderson and
Lee, 1999)
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
What is E-Business?


E-business is a collection of business models and
processes motivated by Internet technology, and focusing
on improving the extended enterprise performance
E-commerce is the ability to perform major commerce
transactions electronically
– e-commerce is part of e-Business
– Internet technology is the driver of the business change
– The focus is on the extended enterprise:




Intra-organizational
Business to Consumer (B2C)
Business to Business (B2B)
The Internet can have a huge impact on supply chain
performance.
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
The Book Selling
Industry

From Push Systems...
– Barnes and Noble

...To Pull Systems
– Amazon.com, 1996-1999
– No inventory, used Ingram to meet most demand
– Why?

And, finally to Push-Pull Systems
– Amazon.com, 1999-present

7 warehouses, 3M sq. ft.,
– Why the switch?


Margins, service, etc.
Volume grew
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
Direct-to-Consumer:Cost
Trade-Off
Cost ($ 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
Industry Benchmarks:
Number of Distribution Centers
Food Companies
Pharmaceuticals
Avg.
# of
WH
3
14
- High margin product
- Service not important (or
easy to ship express)
- Inventory expensive
relative to transportation
Chemicals
25
- Low margin product
- Service very important
- Outbound transportation
expensive relative to inbound
Sources: CLM 1999, Herbert W. Davis & Co; LogicTools
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
The Grocery Industry

From Push Systems...
– Supermarket supply chain

...To Pull Systems
– Peapod, 1989-1999
 Picks
inventory from stores
 Stock outs 8% to 10%

And, finally to Push-Pull Systems
– Peapod, 1999-present


Dedicated warehouses allow risk pooling
Stock outs less than 2%
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
Challenges for On-line
Grocery Stores

Transportation cost
– Density of customers
– Very short order cycle times

Less than 12 hours
– Difficult to compete on cost



Must provide some added value such as convenience
Is a push-pull strategy appropriate?
What might be a better strategy?
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
Less than 300,000
shoppers
Number of
customers
Average
order
Delivery charges
Webvan
21000
$71
Peapod
140000
$120
$4.95 for < $50
free for > $50
$7.95 per order
HomeGrocer.com
50000
$110
NetGrocer.com
60000
$70
ShopLink.com
3 30 0
$98
$9.95 < $75 free
fo r > $ 7 5
$2.99 for < $50
$4.99 for > $50
$25 monthly
Streamline.com
3 40 0
$100
$30
Source: D. Ratliff
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
A New Type of Home
Grocer

grocerystreet.com
– On-line window for retailers
– The on-line grocer picks products at the store
– Customer can pick products at the store or pay
for delivery
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
The Retail Industry

Brick-and-mortar companies establish virtual retail
stores
– Wal-Mart, K-Mart, Barnes & Noble, Circuit City

An effective approach - hybrid stocking strategy
– High volume/fast moving products for local storage
– Low volume/slow moving products for browsing and
purchase on line (risk pooling)

Danger of channel conflict
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
E-Fulfillment

How have strategies changed?
– From shipping cases to single items
– From shipping to a relatively small number of
stores to individual end users
What is the difference between on-line and
catalogue selling?
 Consider for instance Land’s End which has
both channels

© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
E-Fulfillment Requires a New
Logistics Infrastructure
Traditional Supply Chain
e-Supply Chain
Supply Chain Strategy
Push
Push-Pull
Shipment Type
Bulk
Parcel
Inventory Flow
Unidirectional
Bi-directional
Simple
Highly Complex
Destination
Small Number of Stores
Highly Dispersed Customers
Lead Times
Depends
Short
Reverse Logistics
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
E-business Opportunities:

Reduce Facility Costs
– Eliminate retail/distributor sites

Reduce Inventory Costs
– Apply the risk-pooling concept
 Centralized
stocking
 Postponement of product differentiation

Use Dynamic Pricing Strategies to Improve
Supply Chain Performance
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
E-business Opportunities:

Supply Chain Visibility
– Reduction in the Bullwhip Effect



Reduction in Inventory
Improved service level
Better utilization of Resources
– Improve supply chain performance



Provide key performance measures
Identify and alert when violations occur
Allow planning based on global supply chain data
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
Distribution Strategies
Warehousing
 Direct Shipping

– No DC needed
– Lead times reduced
– “smaller trucks”
– no risk pooling effects

Cross-Docking
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
Cross Docking

In 1979
– Kmart had 1891 stores and average revenues per store of $7.25
million
– Wal-Mart was a small niche retailer in the South with only 229
stores and average revenues under $3.5 million

10 Years later
– Wal-Mart had




highest sales per square foot of any discount retailer
highest inventory turnover of any discount retailer
Highest operating profit of any discount retailer.
Today Wal-Mart is the largest and highest profit retailer in the world
– Kmart ????
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
What accounts for Wal-Mart’s
remarkable success

A focus on satisfying customer needs
– providing customers access to goods when and where they want
them
– cost structures that enable competitive pricing


This was achieved by way the company replenished
inventory the centerpiece of its strategy.
Wal-Mart employed a logistics technique known as crossdocking
– goods are continuously delivered to 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.
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
Characteristics of CrossDocking:




Goods spend at most 48 hours in the warehouse
Cross Docking 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.
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
System Characteristics:




Very difficult to manage
Requires advanced information technology. Why? What
kind of technology?
All of Wal-Mart’s distribution centers, suppliers and stores
are electronically linked to guarantee that any order is
processed and executed in a matter of hours
Wal-Mart operates a private satellite-communications
system that sends point-of-sale data to all its vendors
allowing them to have a clear vision of sales at the stores
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
System Characteristics:



Needs a fast and responsive transportation
system. Why?
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.
© 2003 Simchi-Levi, Kaminsky, 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
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi
Transshipment
 What
is the value of this?
 What tools are needed?
 What if the system is
decentralized?
© 2003 Simchi-Levi, Kaminsky, Simchi-Levi