Business Analytics Inventory Model Barilla Pasta Case Background (This case was taken from an article that appears in The Economist Nov. 2020) Barilla Pasta is the largest pasta maker in the world. The organization has a modern high-tech facility located at its world headquarters in Parma, Italy. Barilla exports 60% of its products; mainly to Europe and the U.S. Because of the COVID pandemic, people around the world are staying home and cooking for themselves. As a result, pasta sales world wide have increased. Likewise, pasta sales for Barilla have increased around 30% from 2019 to 2020. One of Barilla's most important markets is Germany. Since March of 2020, Barilla has supplied 22% of the pasta and 39% of the pasta sauces and pestos eaten in Germany (The Economist, Nov. 2020). Global sales for Barilla were $4.2 billion for 2019. The Problem Because of the international growth in pasta sales, Barilla may be experiencing problems with its inventory management. You are an executive with Barilla and you are a member of a team responsible for inventory and supply chains. You need to evaluate whether there is a problem with the optimization methods of the company's analytics unit. So, you, being the thorough professional that you are, decide to analyze the inventory numbers on your own: Given that demand in Germany for pasta is 490 tons per day and demand for sauce and pesto is 110 tons a day, the holding cost rate is 7%, the ordering cost is $500 per order, the cost for pasta is $413,892 per shipment per year, the cost for sauce and pesto is $411,460 per shipment per year, the working days are 363 and the lead time is 3 shipments per week (7 day work week), perform following analyses: a) EOQ model; b) Reorder Point; c) Cycle Time; and d) Total Inventory Costs for all information.