Barilla Case Study
What are the reasons for the increase in variability in Barilla’s supply chain?
Barilla gave volume reductions for the merchants ordering capacity fully loaded quantities, in turn causing merchants to place more supply orders than necessary leaving their inventory levels high. This meant that the retailers did not have to order as often due to high inventory rates on hand. There is also a weekly change in customer demand for the pasta produce. The lack of information to customer demand data in the supply chain forced each supply chain participant in the supply chain to make their own demand forecast and place their own orders, causing an increase in inventory levels at both facilities at Barilla.
This cause and effect is known as the Bull-Whip effect. The retailers were hesitant to communicate customer demand because they feared that Barilla would lower its inventory and sales. Each level in the supply chain kept its own inventory level and placed their order with Barilla weekly. Most of the distributors used a recurrent inventory model to handle their inventory and placed orders when the supply levels were below the ordering point. This type of model works well for smaller manufacturing companies but not for larger companies such as Barilla. The model tracked the number of merchandise sold, but it did not track the kind of items that were sold. Barilla also failed to use forecasting methods to analyze customer demand.
How can the firm cope with the increase in variability?
Creating a strong strategic alliance with the suppliers and buyers can help to produce a positive change in the performance of the supply chain. Using Vendor Management Inventory will help the supplier understand the demand in every level of the supply chain, and will help to produce the necessary amount of products, in turn lower inventory levels and help reduce the likely hood of being left out of stock on a product. A key factor of using the VMI work is the risk shared impact.
Barilla gave volume reductions for the merchants ordering capacity fully loaded quantities, in turn causing merchants to place more supply orders than necessary leaving their inventory levels high. This meant that the retailers did not have to order as often due to high inventory rates on hand. There is also a weekly change in customer demand for the pasta produce. The lack of information to customer demand data in the supply chain forced each supply chain participant in the supply chain to make their own demand forecast and place their own orders, causing an increase in inventory levels at both facilities at Barilla.
This cause and effect is known as the Bull-Whip effect. The retailers were hesitant to communicate customer demand because they feared that Barilla would lower its inventory and sales. Each level in the supply chain kept its own inventory level and placed their order with Barilla weekly. Most of the distributors used a recurrent inventory model to handle their inventory and placed orders when the supply levels were below the ordering point. This type of model works well for smaller manufacturing companies but not for larger companies such as Barilla. The model tracked the number of merchandise sold, but it did not track the kind of items that were sold. Barilla also failed to use forecasting methods to analyze customer demand.
How can the firm cope with the increase in variability?
Creating a strong strategic alliance with the suppliers and buyers can help to produce a positive change in the performance of the supply chain. Using Vendor Management Inventory will help the supplier understand the demand in every level of the supply chain, and will help to produce the necessary amount of products, in turn lower inventory levels and help reduce the likely hood of being left out of stock on a product. A key factor of using the VMI work is the risk shared impact.