Barilla Spa Case Report

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Promotional Activities - The use of promotions in the form of price, transportation, and volume discounts was the main strategy to sell more products to the distributors. The year is divided into 10-12 periods, during which different products are used for the promotions at discounts of anywhere between 1.4% and 10% which caused a major impact to demand variations. These fluctuations are the main cause of the supply issues, Barilla had to overproduce during these times creating higher demand and inventory buildup in their distribution centers. The DC’s would then take measures to try and clear out the inventory buildup such as pushing the discounted product to distributors which started the cycle all over again as the price was driving the demand up.

Transportation Incentives – Barilla would offer discounts to distributors/customers based on full truckloads of product. The downside to this is that the distributors would invest heavily on product, overloading them on certain items that may not be hot sellers and force them to carry excess inventory for some time, forcing them to buy different products the next time the truckload incentives were used, and again, may be carrying excess inventory on that product. This is a vicious cycle that will eventually catch up to the distributor. Since Barilla controls the product shipping from their plant to the distribution centers, their transportation costs would have been reduced however other costs would have gone up such as inventory holding costs, transportation, and extra labor. (See attached Exhibit 8 from Barilla SpA Case Study)

Order Lead Times – The distributors would place order with Barilla once per week, and the average time it takes Barilla to ship the product is 10 calendar days from the date the order is received. This longer lead time causes distributors to place orders for more product than they actually need knowing that it takes 10 business days until they get their next one.

Sales Representatives – Similar to the transportation incentives where distributors would get discount pricing on truckloads, the sales reps would push more products out during promotional periods in order to up their compensation; however this would also lead to a lower need from distributors when outside the promo periods as they would be all stocked up. This would cause a wide variation in demand patterns for Barilla and would be almost impossible to forecast.

Environmental and Root Cause Analysis

Pasta is a staple in Italy and very significant on the food chain. “Per capita pasta consumption in Italy averaged 18 kilos per year, greatly exceeding that of other western European countries.” (pg. 2, Barilla SpA case study) Because of this, the consumers who would be purchasing these products would be very cost conscience and would be prepared to go a little further out of their way to save a few dollars. Also, quality is very important, again, the customer is willing to travel a bit further in order to get the best possible tasting product for their money. Based on the fact that Barilla has the market share they do, we have to assume they would be recognized as an industry leader and favorite among their customers. This is why forecasting the consumer demand is extremely important and a necessity with JITD. Currently, the traditional way of filling orders is leading to stock out or excess inventory, neither is benefiting anyone in the supply chain. With Barilla’s current process to make pasta, they cannot change production at a moment’s notice. The plant needs to keep the kiln’s humidity and temperature at precise levels for the different types of pasta that it produces. Based on those requirements, sequential production would be hugely beneficial to Barilla to reduce downtime of production and keep their costs low throughout the process. Implementing the JITD system would give them the top down perspective for production/inventory decisions instead of the bottom to top reactionary system they have currently.

In the case study, there is a mention that competition is a factor, with over 2000 Italian pasta manufacturers. This means that even though Barilla has a huge share in the area and has the name behind the product, they are constantly competing or have competitors going after more and more shelf space in supermarkets, small chain stores, and restaurants. Success in this market place is going to depend on pricing, brand recognition, brand availability, and customer service. Recognition is something they already have, however in the past, having control of their pricing and availability was out of their hands. By implementing a JITD system, they would have the ability to bring production back into their hands and gaining control over distribution. Adding to the fluctuating demand is also a strain on raw materials, meaning that if Barilla cannot get a handle on their own raw material needs, they may find it impossible to get what they need, when they need it. For example, if they continue to allow distribution to set production, they will have weeks where quantities needed can be 100, and then next week that can skyrocket to 1000, then back to 400 the week after. There is no forecasting model that can keep them on track for raw materials if this variation continues, especially in a perishable food market. If they decide to stock up on raw materials to prevent stock outs, they could find themselves with capital tied up in raw materials and no orders to sustain, or in inventory holding costs.

If they can have their sales representatives working more closely with people placing the orders and the end users themselves, they would find they would have an “ear on the ground” that may assist them in forecasting more accurately as well.

Alternatives or Options

Alternative 1 – While a JITD system is relying on external numbers, this alternative would be solely based on internal operations. If Barilla is unable to convince distributors to share their information, they can move to a strategy that would set their forecasting to match their sales history. They would also need to incorporate a growth percentage as well as safety stock to ensure they are being as accurate as possible with production. For example, if they example a product that sold 1000 units in January of last year, they would have to assume the same production would be needed this year, along with a safety stock, say 10%, plus a year over year growth percentage, again 10%. They would also take in consideration if there are promotions on that product currently or upcoming shortly, another 10% for promotions. This would give them a monthly total of 1300 units, or 325 units per week. That should be their determined production schedule