The consumer products sector faces volatility in demand on a high scale and level of complexity, thereby posing challenges in the area of inventory management. Economic volatility and demand variability present challenges that simple models of demand forecasts are not equipped to handle. An important method of tacking demand variability is an effective way to improve the inventory control policy, which should be designed to smoothen stocking response to demand variation arising from the customers.

Problem Description - Representing the hypermarket, the objective of our forecasting is to reduce the spoilage of vegetables in the hypermarket by accurately forecasting sales on a daily basis. By using historical data of the last year we plan to forecast daily demand for two SKU's 'Exotic Vegetables' and 'Beans' under the vegetable sub-class.

Our analysis aims to reveal insights from monthly international passenger traffic data in the three major U.S. Airways hubs, Charlotte (CLT), Philadelphia (PHL), and Phoenix (PHX), to predict future implications at the newest international hub, Phoenix. Operations in PHX international hub began more recently (2007) than the other two hubs (2000), leading us to focus on creating a forecasting model to predict the monthly flow of international passengers to and from the PHX hub with fuller accuracy using the combination of insights.

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