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Barilla Case Study

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What is causing the distributor’s order pattern to look this way?

  • 预测

产品包装规格、类型

信息

订货方式?

促销

  • 系统缺乏柔性

生产设备调整慢

提前期较长

运输折扣

数量折扣

促销行为

没有最大或最小的订货量

产品分散

订货提前期长

客户服务率低


Barilla is currently experiencing a high rate of fluctuation in the demand generated from their customer. There are multiple underlying factors that contribute to this sporadic demand pattern.

  • Too many kinds of products

Dry products were offered in about 800 different packages SKUs. Pasta was made in 200 different shapes and sizes and was sold in over 470 different packaged SKUs. Due to regional preferences and differences in retail requirements, a typical distributor might distribute 150 of Barilla’s 800 dry-product SKUs.

  • The lead-time period is too long

Barilla product would then be shipped to the distributor over the course of the week that started 8 days after the order was placed and ended fourteen days after the order. The average lead time was ten calendar days.

  • No order restrains for retailers and distributors

Barrier's appraisal plan for salesmen encourages salesmen to make more purchases, and then encourages distributors to hold more inventory through promotion, which deviates from the real demand. The services of the sales department are directed at distributors. At present, 90% of the time is spent in stores without knowing the real needs of consumers.

  • Transportation discount and volume discount

Barilla divided each year into 10 or 12 “canvass” periods, typically four to five weeks in length, each corresponding to a promotional program. In addition, Barilla pays for transportation and offers a discount of 2-3% for full car orders. As for sales representatives, they can offer buyer a 1000 lire/carton discount (representing a 4% discount) if the buyer purchased a minimum of three truck-loads of Barilla egg pasta.

  • Lack of communication

This includes a lack of forecasting system and communication to ensure that demand needs are met. It is apparent that there is lack of coordination of objectives and demand between central distribution center (CDC) and the grand distributor (GD). For instance, the distributor purchases dry products in higher volumes when a promotion or discount in given to decrease their inventory purchasing cost. They don’t consider the potential consequences this may generate in the long term for the supply chain. This decentralized decision-making results in high and unpredictable fluctuations in demand.

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