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Supply Chain Management
Supply Chain Design and Planning
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Chapter 5: The value of information
1. Bullwhip effect
1.1 Operational causes
− Demand Forecasting
• Estimates about demand are regularly modified
− Lead Time
• Small changes in demand estimates are magnified and increase variability
− Batch Ordering
• A large order followed by several periods of no order
− Price Fluctuations
• Discounts or promotions cause forward buying
− Order gaming
• Inflated orders when there is shortage
If all operational causes are removed à the effect persists
, 1.2 Behaviour causes
− Overreaction to backlogs
• Panic ordering reactions after unmet demand
− Decision-makers under-weight the supply line
• Misperceptions of feedback and time delays
− Lack of trust
• Perceived risk of other players’
− Bounded rationality
• Misuse of inventory policies
1.3 Quantifying the bullwhip
− Retailer follows a simple periodic review policy
• Base-stock (order-up-to) policy with r=1, and known lead time L
• Simple moving average for forecast (p number of periods)
− The variance of the customer demand seen by the retailer is Var(D)
− The variance of the orders placed by that retailer to the manufacturer, Var(Q)
L: lead time + review point
P: observations (weeks/ months)
− If p=5 and 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 seen by the
retailer
− When p is large and L is small, the bull whip effect due to forecasting error is negligible
− The bull whip effect is magnified as we increase the lead time and decrease p
− By increasing the number of observations used in the moving average forecast, the
retailer can significantly reduce the variability of the orders it places to the
manufacturer
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