Table of ContentsIntroductionProblem IdentificationAnalysisRecommendationsBarilla SpA, one of the world's leading pasta manufacturers based in Italy, faces high variability demand which leads to additional costs and greater operational inefficiency. within its supply chain; as we move up the chain, uncertainty about the accuracy of the request increases. Maggiali, director of logistics, was in fact aware of this increasing burden imposed on the company's production and distribution system. To solve this problem, the key adequate formulation observed at the time was to implement “Just in Time Distribution” (JITD) which would mitigate the consequences of demand variability. A relatively new system, JITD challenges the current system used by Barilla by centralizing a common database between Barilla and its distributors. Such data transparency would help provide accurate demand forecasts, which would benefit both entities. However, the internal resistance encountered by Maggiali made it difficult to implement the just-in-time distribution system. Therefore, to begin our analysis of the problem, we will focus on providing appropriate solutions, for example avoiding multiple updates of demand forecasts, breaking up order batches, stabilizing prices and eliminating games in case of shortage. We will then discuss the feasibility of the program in our environment and finally the methodology behind the acquisition of targeted customers that we wish to include in the recommendations. Say no to plagiarism. Get a tailor-made essay on “Why Violent Video Games Should Not Be Banned”? Get the original essayIntroductionBarilla SpA is an Italian food company established in 1875 in Parma, Italy by Pietro Barilla. The company is currently known as the largest pasta manufacturer in the world and has 25 factories throughout Italy. Each factory focuses on a specific product segment such as pasta, flour mills, and other products the organization specializes in like cakes, croissants, and bread. The manufacturing company also has two distribution facilities that are responsible for delivering their products. Currently in the system, once the products are manufactured, they are sorted into two different categories, fresh and dry, which are then delivered to the central distribution centers (CDCs). Fresh produce is only stored for three days, while dry produce is transported either to central distribution centers or to depots managed by Barilla. Depots deliver dry goods to small independent stores, and central distribution centers oversee dry goods to two types of distributors: Grande Distribuzione, which is a distribution organization responsible for distribution to supermarket chains, and Distribuzione organizzata , which is made up of many other distributors. Giorgio Maggiali is the director of logistics for Barilla SpA and he faces a lot of resistance when he tries to implement a new manufacturing concept called Just-In-Time Distribution (JITD). Initially, this strategy was suggested by the previous director, Brando Vitali. However, Maggiali strongly supports this idea. Due to the current structure of the company, variations in customer demand cause the entire system to operate unfavorably. The consequence is a surplus of inventory at all levels of the supply chain, which generates additional costs. ThisThe result is commonly called the bullwhip effect. To resolve this issue, Maggiali must decide whether or not to pursue the JITD strategy and how best to implement it for Barilla SpA. Identifying the Problem From the described problems that Barilla was facing, it is evident that the company is facing the Bullwhip Effect. At every stage of the supply chain, Barilla has high inventory levels and recurring stock-outs at the distribution level. Additionally, they face: an exaggeration of demand variability up the chain, compounded by sales promotions that offer volume incentives such as full truckload (FTL), and a lack of data to predict demand. In addition, there is another factor that makes the problem even more serious: Barilla has a large variability of dry products (around 800 storage units). High inventory levels at the company's central distribution centers and at its distributors' distribution centers result in increased costs on both sides, for Barilla and its corresponding distributors. Barilla struggles to respond to wide variations and uncertainty in demand. Thus, manufacturing and distribution costs increase and the company is anxious about the fulfillment rate of customer orders. Although there is excess inventory in distributors' warehouses, stock-outs still occur frequently and distributors' order fulfillment rate is low. Additionally, end-consumer needs will not be met if supply chain dysfunction persists. The company's customers are segmented into three main categories: small retail stores, large independent supermarkets and large supermarket chains. Deliveries to small retail stores are made through the organization's depots, while deliveries to supermarkets go through intermediary distribution centers managed by a third-party organization representing several different or chain-owned supermarkets. Retailers send their orders to the distributor daily, however, the distributor places them once a week. Although all distributors have a computer system, a complex forecasting system or analytical tools to indicate order amounts is present in only a few. In Exhibits 12 and 14 (see original case for graphs), there is little effort to specify order quantities based on stock levels. For example, at Cortese DC, in week 29, the inventory level was 500 cwt., which is considered low compared to other orders of the year. Additionally, the order quantities from this distribution center during the same week were less than 200 quintals, which is lower than the average order quantity which is 300 quintals. This leads to a very high out-of-stock rate the following week, around 8.5%, as shown in Exhibit 13 (see original case for graphs). Cortese DC's case is not an isolated situation. Other Barilla distributors have not been effective in their ability to predict order quantities when arranging orders with Barilla. To combat variations in demand from their retailers, safety stock is used to solve the problem of demand uncertainty. However, this technique leads to a total inventory level much higher than it should be and tends to mask the weakness of their demand forecast. Which makes the situation even worse; Promotional programsBarilla's sales and marketing and various volume incentives motivate distributors to place huge orders in batches, further increasing fluctuations in demand to Barilla. On Barilla's side, to address issues related to demand uncertainty from distributors, Barilla increases the level of safety stocks, which ultimately leads to higher overall inventory levels. With sales information from its distributors unknown, Barilla faces many conflicts in forecasting demand for its products and planning accordingly. Additionally, Barilla's wide range of pasta products makes demand forecasting and inventory management more complex, leading to a more serious bullwhip effect. Thus, the main reason for the presence of the Bullwhip effect is the use of safety stock as the main expectation. to address the variability of demand at each level of the supply chain, the lack of sharing of demand information between distributors and Barilla and traditional sales promotion and marketing strategies aimed at increasing the volume of demand at the expense of manufacturing planning and inventory control. Analysis As previously stated, the main identified problem that Barilla was facing is a phenomenon called the Bullwhip effect. The symptoms of such an effect are numerous but are identified as follows in the Barilla framework. Lack of accuracy of information shared among supply chain members (across) and their independent decision-making processes regarding demand forecast updates, order consolidation, fluctuation prices and rationing and the game of shortages are the main reasons behind this phenomenon. inefficiencies observed within the company's supply chain. It is so common for each member of the supply chain to forecast the demand for their products in order to accommodate their production schedule, capacity plan and inventory control. Forecasts are usually made based on previous order history. Thus, the order that would be sent upstream of the supply chain, to the supplier, would be based on this forecast while taking into consideration the safety stock that each reseller would like to keep in order to avoid stock shortages. With this in mind, each dealer would contribute to the bullwhip effect by wanting to maintain their own level of safety stock. Additionally, when the time between replenishments is long, the bullwhip effect would be exacerbated. This is due to the dealer's desire to take into account this significant lead time and would therefore increase its product forecasts to account for any increase in demand from its customers. Variability in demand as each member of the supply chain exercises the same process to account for their own safety stock results in a colossal increase in inventory levels at each level and thus results in higher costs.1. Avoid Multiple Demand Forecast Updates – To avoid these demand forecast updates from one location to another and to circumvent repetitive data processing, both sides of the supply chain must unify their efforts to use the same raw data in the same system. This could be done by implementing the Electronic Data Interchange (EDI) system to facilitate the flow of information. However, this is not enough. In fact, different methods used to forecast using the same raw data would also result in variability in therequest. It is therefore necessary for the site upstream in the supply chain to be responsible for updating inventory levels and forecasting demand from its own downstream site. The downstream site would thus be transformed into a passive member of the supply chain. This is called a continuous replenishment program (CRP) or vendor managed inventory (VMI). Another remedy is to connect directly to customers and get demand information by hijacking the downstream site. This proves beneficial, not only in terms of accurate demand forecasting and low inventory levels, but also in terms of recognizing the demand structure for the company's products. Additionally, if just-in-time distribution and replenishment could be implemented, it could minimize the bullwhip effect and thus bring about operational improvements. 2. Broken order batches – Another concern Barilla faces is bulk orders within the supply chain. This means that the company accumulates requests before placing an order with its suppliers. In other words, suppliers receive orders periodically or once a month, they witness an irregular flow of requests, unbearable one time, and zero demand for the rest of the month. Additionally, this technique is used when the supplier is not able to accommodate small and frequent orders due to the lengthy processes and high costs encountered. Unless a company uses the EDI system to reduce costs, it will always find this method of frequent ordering impractical, not only because of the high costs of placing an order and replenishing it, but also because of the transport costs. Companies do not issue orders. unless they require full truckload (FTL) and less than truckload rates in an attempt to reduce their transportation costs and would even benefit from incentive discounts from suppliers. While waiting to fill a truck, companies would have long order cycles within the supply chain and therefore inefficiencies in the supply chain. However, having frequent orders when using the EDI system and long order cycles are not compatible unless the company acquires a third-party logistics company that would allow small replenishments to be made, while reducing costs on full loads. In fact, these third-party companies would be responsible for not just one company's inventory, but several of them in order to save money on full truckloads. In this way, the company would have acquired an effective approach that would once again mitigate the bullwhip effect.3. Stabilize Prices – One of the simplest and most cost-effective methods to control the bullwhip effect would be to “reduce both the frequency and level of wholesale price reductions.” In the past, Barilla's sales strategy relied heavily on the use of trade promotions as a means of getting its products into the food distribution network. This strategy played a central role in the company's sales; Little did they know they were directly fueling the Bullwhip Effect. Barilla used two strategies that were part of their “trade promotions.” Both were implemented using a "canvas" system whereby they divided the year into ten to twelve periods, which typically lasted four to five weeks. The end goal of such a divided schedule was to achieve..