A Wegmans merchant analyst currently spends a significant amount of time accessing and collating historical product data. This data is used to make informed decisions about how much product needs to be moved, when it needs to be moved, and to which of the various Wegmans stores the product needs to go. A poor decision can result in significantly devalued or expired product that needs to either be sold at a loss or discarded entirely. By providing easily accessible data, our solution will help decision makers in the supply chain efficiently evaluate item data in order to purchase and push the right amount of product to the right store at the right time. This project aims to aid the decision making process. It will streamline this process by providing results calculated from the standard algorithms used in making these predictions and by allowing decision makers to spend more time analyzing relevant data. In addition, it will help increase decision accuracy by allowing analysts to manipulate the inputs for algorithms used to calculate projected inventory.