Barilla: Poor Forecasting by Retailers and Distributors

Topics: Economic order quantity, Supply chain management, Sales Pages: 7 (2269 words) Published: December 8, 2012
Barilla is facing several problems throughout their supply chain, and also some problems internal to the company. The biggest problem is the fluctuating demand and the number of stock-outs that are occurring throughout the supply chain. Barilla is facing problems with the way that information is being passed up the supply chain, problems with promotions, internal problems, and problems with getting the entire supply chain onboard for change. Promotions and Sales Representatives:

The sales strategy of Barilla included enormous discounts and promotions, in terms of volume, transportation and cost. One year was divided into 10-12 canvass periods, during each of which, there would a promotional sale offered by the company. The promotion varied between 1-10% of discount. Sales Representatives were being paid on a commission basis, which is not a right way. They were paid based on the amount of product they sell. So when a promotion goes on, the Sales Representatives try to push that particular product to make more money. This is causing the stores to hold on to more inventory, during a promotion period. But during a non-promotional period,the order quantity would fall down vigorously, which increases the chances of stock-outs, as shown in Figure 3. This practice in changing the order quantitiestends the distributors to rapidly change their weekly ordersto Barilla, leading to a change in Barilla’s overall manufacturing orders. Poor Forecasting by Retailers & Distributors:

The store manager in the retail outlet controls the ordering review process. He checks the inventory level, and if they are in need of a particular product, he places the daily order instantaneously to the distributor. This is not an accurate model of forecasting. The distributor follows a simple periodic review system, without any sophisticated or computerized forecasting tools, which leads to poor forecasts, resulting in high inventory at all the levels throughout the supply chain.

Figure 3 Sales and Stock-outs at Cortese Northeast DC, for the year 1989 Problems with the Lead Times:
Barilla’s lead times are also causing large amounts of variability in the supply chain. Barilla had a set time of 8 to 14 days for fulfilling their distributor orders with an average lead time of 10 days. This lead time is relatively long, and the time difference of 6 days between shortest lead time and longest lead time could increase the amount of variability throughout the supply chain. The lead times between the distributors and the supermarkets could fluctuate anywhere from 24 to 48 hours. In terms of hours, this is a very wide range and is a cause of variability between the supermarket’s orders and the distributor’s orders. Ordering Behaviour and Limits for Order Quantity:

The distributors used to have full control over the orders. They ordered for different quantities in different periods, based on promotions and demand fluctuations from supermarkets. Furthermore, there are no specified limits for the order quantities. The distributors ordered low quantities more often which increases the operational difficulty and production cost. Sometimes they ordered as high as possible during promotional periods, which leads to false demand. The fluctuating demand caused by the above factors led to various inefficiencies for Barilla which are listed below 1.Frequent orders, High Production Cost and High Transportation Cost 2.Stock-outs and Customer dissatisfaction

3.Bullwhip effect
4.Out-of-control of the ordering process
5.Operational difficulties and inefficiencies
6.Inflexibility of the supply chain operations
The JIT-D strategy, which is similar to the JIT (in Toyota Production System), but instead of implementing within the organization, when implemented for the whole supply chain, would positively eliminate the demand variability. But the distributors strongly oppose this strategy for the following reasons. Controversy over POS data sharing:

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