Essay About Demand Fluctuation And Barilla Spa

Barilla Operating Environment Case Study
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Module 1Written Case Study 1 : Barilla SpA (A)Tracy FinchMember ID # 10067861February 13th, 2018Instructor: Romeo CallegaroTable of ContentsExecutive Summary3Issue Identification4Operating Environment7Root Cause Analysis4Alternatives And/Or Options1Recommendations4Implementation1Monitor and Control4Appendix A4EXECUTIVE SUMMARYISSUE IDENTIFICATIONThe main issue facing Barilla is operational inefficiencies due to demand fluctuation, magnified at the source,  also known as the Bullwhip Effect.  Because of the large fluctuations in demand , Barilla is unable to meet the actual demands of the end customer effectively which ultimately result in increased costs across the board in inventory, distribution and manufacturing.  There are several contributing factors to this demand fluctuation that must be addressed:Lack of forecasting from distributors is the largest and most important of the external factors and one that is both short and long term in nature.  Unsophisticated methods of inventory control and little or no data on which to forecast, make it nearly impossible to gauge or anticipate actual demand. This lack of POS data results in large variations in weekly orders as seen in Exhibit A.Internally, there is a lack of centralized data for order processing that leads to distributors maintaining a higher than necessary inventory.  Distributors have full control over their orders which is a long term issue negatively impacting  Barillas ability to effectively manage their inventory, production and distribution.Orders placed by distributors weekly typically take an average of 10 days to be shipped.  This long lead time causes the distributors to order additional product adding to the higher inventory contributing to the fluctuating demand isses.Barilla’s heavy use of promotional activities such as price, transportation and volume discounts also contributed to the fluctuating demand of product.  By offering discounts for full truck loads and price discounts, demand for the product was inflated. Without any real time data or forecasting tools, distributors were simply taking advantage of discounts without factoring in any supported data for future needs.Without a maximum/minimum order limit, distributors took full advantage of these discount. This created additional inventory build up and subsequently measures to reduce the inflated inventory.  Because the internal sales compensation system rewarded sales throughout these promotion periods on specific SKUs, the sales force contributed to the issue by pushing certain products during promotional periods to increase their bonuses.  They also fold volume discounts which would significantly add to the fluctuation or demand and inflated inventory.Finally, the sheer number of SKUs leads an inability to forecast accurately.  With over 800 “dry goods” SKUs, Barilla would need a complex system to be able to accurately predict demand.OPERATING ENVIRONMENTBased in Italy, Barilla is a very large, vertically integrated corporation.  It is the largest pasta manufacturer in the world with at 35% market share in Italy and a 22% market share in Europe.  Growth was expected to continue as the overall economic outlook was promising and pasta consumption was on the rise globally.The company was organized into seven divisions, three of them being pasta.  Over the past number of years, they have experienced amplified levels of inefficiencies and rising costs due to the unstable and fluctuating demand from it’s distributors despite the fact that pasta consumption was relatively stable throughout the year.Barilla owns and operates its own network of plants throughout Italy.  In addition to the pasta plants, they also had plants for their fresh and specialty products.  It followed a very strict and controlled production sequence to ensure a high quality of product.They operate through their own central distribution centres (CDCs) as well as a chain of distributors including Grand Distributors (GDs) which are owned by large supermarket chains, and Organized Distributors (DOs) which are third-party independent suppliers. Nearly 2/3rds of their dry products are destined for Supermarkets which are shipped to them via the distributors.