The Value of Information

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The Value of Information

• Phil Kaminskykaminsky_at_ieor.berkeley.edu

David Simchi-Levi Philip Kaminsky Edith
Simchi-Levi
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Value of Information

• In modern supply chains, information replaces
  inventory
• Why is this true?
• Why is this false?
• Information is always better than no information.
  Why?
• Information
• Helps reduce variability
• Helps improve forecasts
• Enables coordination of systems and strategies
• Improves customer service
• Facilitates lead time reductions
• Enables firms to react more quickly to changing
  market conditions.

3
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
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The Bullwhip Effect and its Impact on the Supply
Chain
Figure 2. Point-of-sales Data-Original
Figure 3. POS Data After Removing Promotions
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The Bullwhip Effectand its Impact on the Supply
Chain
Figure 4. POS Data After Removing Promotion
Trend
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Higher Variability in Orders Placed by Computer
Retailer to Manufacturer Than Actual Sales
Lee, H, P. Padmanabhan and S. Wang (1997), Sloan
Management Review
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Increasing Variability of Orders Up the Supply
Chain
Lee, H, P. Padmanabhan and S. Wang (1997), Sloan
Management Review
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We Conclude .

• Order variability is amplified up the supply
  chain upstream echelons face higher variability.
• What you see is not what they face.

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What are the Causes.

• Promotional sales
• Forward buying
• Volume and transportation discounts
• Batching
• Inflated orders
• IBM Aptiva orders increased by 2-3 times when
  retailers thought that IBM would be out of stock
  over Christmas
• Motorola cell phones

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What are the Causes.

• Single retailer, single manufacturer.
• Retailer observes customer demand, Dt.
• Retailer orders qt from manufacturer.

Dt
qt
Retailer
Manufacturer
L
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What are the Causes.

• Promotional sales
• Volume and transportation discounts
• Inflated orders
• Demand forecasting
• Order-up-to points are modified as forecasts
  change orders increase more than forecasts
• Long cycle times
• Long lead times magnify this effect

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What are the Causes.

• Single retailer, single manufacturer.
• Retailer observes customer demand, Dt.
• Retailer orders qt from manufacturer.

Dt
qt
Retailer
Manufacturer
L
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How big is the increase?

• Suppose a P period moving average is used.

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Var(q)/Var(D)For Various Lead Times
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L5
L5
12
10
L3
L3
8
6
L1
4
L1
2
0
0
5
10
15
20
25
30
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Consequences.

• Increased safety stock
• Reduced service level
• Inefficient allocation of resources
• Increased transportation costs

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Multi-Stage Supply Chains

• Consider a multi-stage supply chain
• Stage i places order qi to stage i1.
• Li is lead time between stage i and i1.

qoD
q1
q2
Retailer Stage 1
Manufacturer Stage 2
Supplier Stage 3
L1
L2
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Multi stage systems

• Centralized each stage bases orders on
  retailers forecast demand.
• Decentralized each stage bases orders on
  previous stages demand

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Multi-Stage SystemsVar(qk)/Var(D)
Dec, k5
Cen, k5
Dec, k3
Cen, k3
k1
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The Bullwhip EffectManagerial Insights

• Exists, in part, due to the retailers 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 significantly
  reduce the bullwhip effect, but will not
  eliminate it.

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Coping with the Bullwhip Effect in Leading
Companies

• Reduce uncertainty
• POS
• Sharing information
• Sharing forecasts and policies
• Reduce variability
• Eliminate promotions
• Year-round low pricing
• Reduce lead times
• EDI
• Cross docking
• Strategic partnerships
• Vendor managed inventory
• Data sharing

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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 Benettons success to successful
  use of communication and information technologies.

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ExampleQuick 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
  Benettons 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.

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How Does BenettonCope 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

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Information for Effective Forecasts

• Pricing, promotion, new products
• Different parties have this information
• Retailers may set pricing or promotion without
  telling distributor
• Distributor/Manufacturer might have new product
  or availability information
• Collaborative Forecasting addresses these issues.

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Information for Coordination of Systems

• Information is required to move from local to
  global optimization
• Questions
• Who will optimize?
• How will savings be split?
• Information is needed
• Production status and costs
• Transportation availability and costs
• Inventory information
• Capacity information
• Demand information

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Locating Desired Products

• How can demand be met if products are not in
  inventory?
• Locating products at other stores
• What about at other dealers?
• What level of customer service will be perceived?

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Lead-Time Reduction

• Why?
• Customer orders are filled quickly
• Bullwhip effect is reduced
• Forecasts are more accurate
• Inventory levels are reduced
• How?
• EDI
• POS data leading to anticipating incoming orders.

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Information to Address Conflicts

• Lot Size Inventory
• Advanced manufacturing systems
• POS data for advance warnings
• Inventory -- Transportation
• Lead time reduction for batching
• Information systems for combining shipments
• Cross docking
• Advanced DSS
• Lead Time Transportation
• Lower transportation costs
• Improved forecasting
• Lower order lead times
• Product Variety Inventory
• Delayed differentiation
• Cost Customer Service
• Transshipment