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4 Value Of Information
 

4 Value Of Information

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  • Each of the firms along the supply chain are producing at a constant rate because demand is easily forecasted; the supply chain is in equilibrium. Each of the firms are forecasting demand accurately.
  • In this example, demand has increased by 10 units over equilibrium. To meet the demand, the distributor doubles inventory to meet production and to meet any other demand fluctuations. The producer further up the chain also notices the increased demand of the distributor and doubles their demand forecast to 40 units and hold 80 units in inventory to meet demand and hedge against any other demand fluctuations. The supplier (or top of the supply chain) receives the blunt of the whip effect. Costs for individual firms, in this example, increase the further you move up the supply chain,
  • What if there are promotional activities, no transportation discounts and no inflated order? Are we still going to see an increase in variability? Consider a simple supply chain with a single retailer and a single manufacturer
  • 零售商向制造商发出的订单需求的方差 Var(Q) 与顾客需求的方差之比满足:
  • 供应链上第 k 阶段发出订单的方差 Var(qk) 相对于顾客需求的方差 Var(D) 的关系,
  • Some keys to reducing costs to your firm: stabilize prices along the supply chain and be sure your information along the supply chain is timely and accurate. This will enhance decision making and allow your company to be responsive to customer demand.
  • Every firm should look to reduce costs and help them gain competitive advantage. Reducing costs along the supply chain is a new phenomenon. Perhaps your firm can gain a competitive edge by reducing fluctuations in the information along your supply chain.

4 Value Of Information 4 Value Of Information Presentation Transcript

  • VALUE OF INFORMATION -BULLWHIP EFFECT-
  • Value of Information
    • “ In modern supply chains, information replaces inventory” (True or False 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.
  • The Bullwhip Effect and its Impact on the Supply Chain
    • Consider the order pattern of a color television model sold by a large electronics manufacturer to one of its accounts, a national retailer.
    Fig 1. Order Stream
  • The Bullwhip Effect and its Impact on the Supply Chain Fig 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
  • Increasing Variability of Orders Up the Supply Chain
  • We Conclude ….
    • Order variability is amplified up the supply chain; upstream echelons face higher variability.
  • Consequences….
    • Increased safety stock
    • Reduced service level
    • Inefficient allocation of resources
    • Increased transportation costs
    • Excess inventories
    • Problems with quality
    • Increased raw material costs
    • Overtime expenses
    • Lengthened leadtime
    • Lost sales
  • Cause of BW: 1.Demand Forecasting
    • One day, the manager of a retailer observed a larger demand (sales) than expected.
    • He increased the inventory level because he expected more demand in the future (forecasting).
    • The manager of his wholesaler observed more demand (some of which are not actual demand) than usual and increased his inventory.
    • This caused more (non-real) demand to his maker; the manager of the maker increased his inventory, and so on. This is the basic reason of the bull whip effect.
  • Cause of BW: 2. Lead time
    • With longer lead times, a small change in the estimate of demand variability implies a significant change in safety stock, reorder level, and thus in order quantities.
    • Thus a longer lead time leads to an increase in variability and the bull whip effect.
  • Cause of BW: 3. Order Batching
    • When using a min-max inventory policy, then the wholesaler will observe a large order, followed by several periods of no orders, followed by another large order, and so on.
    • The wholesaler sees a distorted and highly variable pattern of orders.
    • Thus, batch ordering increases the bull whip effect.
    • Takes care of promotional aspects also.
  • Cause of BW: Variability of Price/Forward Buying
    • Retailers (or wholesalers or makers) offer promotions and discounts at certain times or for certain quantities.
    • Retailers (or customers) often attempt to stock up when prices are lower.
    • It increases the variability of demands and the bull whip effect.
  • Cause of BW: 5. Rationing & Shortage Gaming
    • When retailers suspect that a product will be in short supply, and therefore anticipate receiving supply proportional to the amount ordered (supply allocation).
    • When the period of shortage is over, the retailer goes back to its standard orders, leading to all kinds of distortions and variations
  • Supply Chain in Equilibrium
    • Customer demand forecast = 10 units
    Suppliers Producers Distributors Retailers Products & Services Products & Services Products & Services Information Cash Key: = Inventory Levels 10 Units 10 Units 10 Units 10 Units 10 Units 10 Units
    • Retailers are selling product at a constant rate and price. Firms along the supply chain are able to set their inventory to meet demand.
  • Supply Chain Disrupted
    • Customer Demand forecast = 20 units
    Suppliers Producers Distributors Retailers Products & Services Products & Services Products & Services Information Flow Cash Flow Key: = Inventory Levels 160 Units 80 Units 40 Units 80 Units 40 Units 20 Units
    • As demand increases, the distributor decides to accommodate the forecasted demand and increase inventory to buffer against unforeseen problems in demand. Each step along the supply chain increases their inventory (double in this example) to accommodate demand fluctuations. The top of the supply chain receives the harshest impact of the whip effect.
  • Consider a simple supply chain…
    • Single retailer, single manufacturer.
      • Retailer observes customer demand, Dt.
      • Retailer orders q t from manufacturer.
    Retailer Manufacturer D t q t L
  • Quantifying the Bullwhip Effect
    • Suppose a P period moving average is used.
    • If the variance of the customer demand seen by the retailer is Var(D), then the variance of the orders placed by that retailer to the manufacturer, Var(Q), relative to the variance of customer demand satisfies:
  • Var(q)/Var(D): For Various Lead Times L=5 L=3 L=1 0 2 4 6 8 10 12 14 0 5 10 15 20 25 30 L=5 L=3 L=1 P A lower bound on the increase in variability given as a function of p
    • Figure shows the lower bound on the increase in variability as a function of p for various values of the lead time,L. When p is large, and L is small, the bullwhip effect due to forecasting error is negligible.
    • The bullwhip effect is magnified as we increase the lead time and decrease p.
    • Assume p=5, L=1
    • The variance of the orders placed by the retailer to the manufacturer will be at least 40 percent larger than the variance of the customer demand.
  • Multi stage SC systems
  • Multi-Stage Supply Chains
    • Consider a multi-stage supply chain:
      • Stage i places order q i to stage i+1 .
      • L i is lead time between stage i and i+1 .
    Retailer Stage 1 Manufacturer Stage 2 Supplier Stage 3 q o =D q 1 q 2 L 1 L 2
  • SC with centralized Demand Information
    • Centralized: each stage bases orders on retailer’s forecast demand.
    • The retailer observes customer demand, forecasts the mean demand using a moving average with p demand observations, finds his target inventory level based on the forecast mean demand, and places an order to the wholesaler.
    • The wholesaler receives order along with the retailer’s forecast mean demand, uses this forecast to determine his target inventory level, and place an order to the distributor.
    • Similarly, the distributor
    • places order to the factory.
  • SC with centralized Demand Information (cont’)
    • In this centralized SC, each stage of the SC receives the retailer’s forecast mean demand and follows and order-up-to inventory policy based on this mean demand.
    • The variance of the orders placed by the kth stage of the SC, Var(Q k ), relative to the variance of the customer demand, Var(D), is just:
  • SC with centralized Demand Information (cont’)
    • For example, if the lead time from the retailer to the wholesaler is two periods, then L1=2. Similarly, if the lead time from the wholesaler to the distributor is two periods, then L2=2, and if the lead time from the distributor to the factory is also two periods, then L3=2.
    • The total lead time from the retailer to the factory is L1+L2+L3=6
    • This expression for the variance of the orders placed by the kth stage is very similar to the expression in the previous section, with the single stage lead time.
  • Decentralized Demand information
    • Decentralized: each stage bases orders on previous stage’s demand.
    • The retailer does not make its forecast mean demand available to the remainder of the SC. Instead, the wholesaler must estimate the mean demand based on the orders received from the retailer.
    • The variance of the orders placed by the k th stage of the SC, Var(Q k ),relative to the variance of the customer demand, Var(D) satisfies:
    The variance increases multiplicatively at each stage of the SC.
  • Multi-Stage Systems:Var(q k )/Var(D) Dec, k=5 Cen, k=5 Dec, k=3 Cen , k=3 k=1
    • Increase in variability for centralized and decentralized system
  • Effect of Information Sharing
    • It is now clear that by sharing demand information with each stage of the SC, we can significantly reduce the bullwhip effect.
    • When demand information is centralized, each stage of the SC can use the actual customer demand data to estimate the average demand.
    • When demand information is not shared, each stage must use the orders placed by the previous stage to estimate the average demand. These orders are more variable than the actual customer demand data, thus, the forecasts created using these orders are more variable, leading to more variable orders.
  • 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 .
    • Centralized demand information can significantly reduce the bullwhip effect, but will not eliminate it.
  • Coping with the BW Effect 1. Demand uncertainty
    • Adjust the forecasting parameters , e.g., larger p for the moving average method.
    • Centralizing demand information ; by providing each stage of the supply chain with complete information on actual customer demand ( POS: Point-Of-Sales data )
    • Continuous replenishment
    • VMI ( Vender Managed Inventory: VMI )
  • Coping with the BW Effect 2. Lead time
    • Lead time reduction
    • Information lead time can be reduced using EDI ( Electric Data Interchange ) or CAO ( Computer Assisted Ordering )
    • Cross docking
  • Coping with the BW 3. Order Batching
    • Reduction of fixed ordering cost using EDI and CAO
    • 3PL ( Third Party Logistics )
    • VMI
    • Shipping in LTL sizes by combining shipments
    • The supplier—usually the manufacturer but sometimes a reseller or distributor—makes the main inventory replenishment decisions for the consuming organization.
        • The supplier monitors the buyer’s inventory levels (physically or via electronic messaging) and makes periodic resupply decisions regarding order quantities, shipping, and timing.
        • Transactions customarily initiated by the buyer (like purchase orders) are initiated by the supplier instead.
        • The purchase order acknowledgment from the supplier may be the first indication that a transaction is taking place; an advance shipping notice informs the buyer of materials in transit.
    The VMI Partnership
      • The manufacturer is responsible for both its own inventory and the inventory stored at is customers’ distribution centers.
  • Coping with the BW Effect 4. Variability of Price
    • Stabilize pricing
      • Eliminate promotions & variation in prices
      • Limit quantity purchased during a promotion
  • Coping with the BW Effect 5. Rationing & Shortage Gaming
    • Allocate the lacking demand due to sales volume and/or market share instead of order volume. ( General Motors , Saturn, Hewlett-Packard )
    • Share the inventory and production information of makers with retailers and wholesalers. ( Hewlett-Packard , Motorola )
  • Reducing BW effect in your firm
    • Are prices in your supply chain stable?
    • Is information between firms along the supply chain accurate and timely?
    • Is sales being forecasted on projected data?
    • Are you forecasting sales using data from EDI or Point of Sale computer systems.
    • Are incentives for sales representatives along the supply chain at minimum?
    • Are orders being placed in small increments?
    • Are batch orders reduced to minimum levels?
  • Reducing BW effect in your firm
    • If you answered no to any of the previous questions regarding your firm and the bullwhip effect, then you may have an opportunity to reduce costs to your individual firm.
  • 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.
  • 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
  • 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?
  • 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.
  • 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
  • THANK YOU