Supply Chain Integration

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					Supply Chain Integration

          Ranjan Ghosh
 Indian Institute of Management
              Calcutta
     Outline of the Presentation

The Bullwhip Effect

Distribution Strategies and Information
 Systems

Supply Chain Management: Pitfalls and
 Opportunities
          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
        The Bullwhip Effect
and its Impact on the Supply Chain


                            Figure 2. Point-of-sales
                                      Data-Original




 Figure 3. POS Data After
    Removing Promotions
         The Bullwhip Effect
and its Impact on the Supply Chain




 Figure 4. POS Data After Removing Promotion & Trend
   Higher Variability in Orders Placed by
Computer Retailer to Manufacturer Than Actual
                    Sales




     Lee, H, P. Padmanabhan and S. Wang (1997), Sloan Management Review
Increasing Variability of Orders
     Up the Supply Chain




Lee, H, P. Padmanabhan and S. Wang (1997), Sloan Management Review
            We Conclude ….



• Order Variability is amplified up the supply
  chain; upstream echelons face higher
  variability.

• What you see is not what they face.
        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
         What are the Causes….
• Single retailer, single manufacturer.
  – Retailer observes customer demand, Dt.
  – Retailer orders qt from manufacturer.



    Dt                qt
           Retailer         Manufacturer
                      L
         What are the Causes….

• Promotional sales
• Volume and Transportation Discounts
• 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
         What are the Causes….

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



    Dt                qt
           Retailer         Manufacturer
                      L
            Var(q)/Var(D):
       For Various Lead Times
• Lead time of the manufacturer = L so that an
  order placed by the retailer at the end of period t
  is received in the beginning of period (t+L).
• In every period, the retailer calculates a new
  mean and standard deviation, based on the p
  most recent observations of demand. If the
  variance of the customer demand seen by the
  retailer is Var(D), then the variance of the orders
  placed by the retailer to the manufacturer,
  Var(q), relative to the value of the customer
  demand, satisfies
•      Var(q)/Var(D) ≥ 1 + ( 2L/p ) + ( 2L2/p2 )
      Var(q)/Var(D):
 For Various Lead Times
14
         L=5
12

10

 8       L=3
 6

 4       L=1
         L=1
 2

 0
     0         5   10   15   20   25   30
          Consequences….
• Increased safety stock

• Reduced service level

• Inefficient allocation of resources

• Increased transportation costs
         Consequences….
• Single retailer, single manufacturer.
  – Retailer observes customer demand, Dt.
  – Retailer orders qt from manufacturer.



    Dt                qt
           Retailer         Manufacturer
                      L
          Consequences….
• Increased safety stock

• Reduced service level

• Inefficient allocation of resources

• Increased transportation costs
   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              q1
       Retailer        Manufacturer   q2   Supplier
       Stage 1    L1    Stage 2            Stage 3
                                      L2
             Multi-Stage
        Systems:Var(qk)/Var(D)
• Supply Chain with Centralized Demand
  Information
The variance of the orders placed by the kth stage
  of the supply chain, Var(qk), relative to the
  variance of the customer demand, Var(D), is
                              k             k
 Var(qk) / Var(D) ≥ 1 + (2 Σ Li ∕ p) + 2( ∑ Li )2 ∕ p2
                             i=1           i=1

 where Li is the lead time between stage i and
 stage (i+1).
             Multi-Stage
        Systems:Var(qk)/Var(D)
• Supply Chain with Decentralized Demand
  Information
  The variance of the orders placed by the kth
  stage of the supply chain, Var(qk), relative to the
  variance of the customer demand, Var(D), is
                      k
 Var(qk) / Var(D) ≥ Π [1 + (2 Li ∕ p) + 2( Li2 ∕ p2)]
                     i=1

 where Li is the lead time between stage i and
  stage (i+1).
              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
            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.
Coping with the Bullwhip Effect
    in Leading Companies
• 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
         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.
         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.
    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
       Distribution Strategies
• Warehousing
• Direct Shipping
  – No DC needed
  – Lead times reduced
  – “smaller trucks”
  – no risk pooling effects
• Cross-Docking
                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.
     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.
      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.
 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.
     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 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
     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.
        Distribution Strategies
  Strategy          Direct         Cross         Inventory at
  Attribute        Shipment       Docking        Warehouses
    Risk                                           Take
   Pooling                                       Advantage
Transportation                     Reduced         Reduced
    Costs                       Inbound Costs   Inbound Costs
   Holding       No Warehouse    No Holding
    Costs           Costs          Costs
  Demand                          Delayed         Delayed
 Variability                     Allocation      Allocation
      Supply Chain Integration –
     Dealing with Conflicting Goals

•   Lot Size vs. Inventory
•   Inventory vs. Transportation
•   Lead Time vs. Transportation
•   Product Variety vs. Inventory
•   Cost vs. Customer Service

				
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posted:6/18/2012
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