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The Barilla company, a major pasta producer located in Italy provides a demonstrative of issues resulting from the bullwhip effect.
Barilla offered special discounts to their customer who ordered full truckload of their goods. Such marketing deals created customer demand-patterns were highly peaked and volatile. The supply chain costs were so high that they outstripped the benefits from full truckload transportation.
The Barilla case was one of the first published cases that empirically supported the bullwhip phenomenon. The 5 major reasons leading to the bullwhip effect according to Lee: Demand signal processing is the is the practice of decision makers adjusting the parameters of the inventory replenishment rule.
Target stock levels, safety stocks and demand forecasts are updated in view of information or deviations from targets. Another major cause of the bullwhip problem is the lead-time, which is caused by two components.
The physical delays and also delays in cause of information. The lead-time is a key parameter to calculate safety stocks.
The third bullwhip creator is the practice of order batching. Economies of scale in ordering, production set-ups or transportation will quite clearly increase order variability. The fourth major cause of bullwhip is highlighted by Lee has to do with price fluctuations. Price discounts and quantity discounts are often offered by retailers. So the retailers buy goods in advance and quantities and store them.
This do not reflect their immediate needs. The fifth cause of bullwhip is connected with rationing and shortage gaming. Inflated orders placed by supply chain occupants during shortage periods tend to boost the bullwhip effect. Possibilities to minimize the bullwhip effect (in order to avoid costs): improve communication in the supply chain simultaneousness of actions (therefore time delays and reaction times can be avoided) centralization of disposition establish strategic alliances reduce the variability
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