Class Project Report

Class Project Report - Technical Report for Dominicks...

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Technical Report for Dominick’s Problem Dominick’s is a retail outlet and they are trying to predict the sales of Coke and Pepsi in their stores from data for a 210 week period. Companies are always trying to forecast their sales in the upcoming quarters to get a feel for how many sales they are going to have. Sales are the number one thing for any company and they want them to be as high as they can possibly be. So, we have been hired to run these models to figure out what other products significantly affect and drive up the sales of Coke and Pepsi. Importance It is important for companies to do this analysis so they can predict their inventory. They need to know how much to buy or not to buy based on these models of forecasting. The elasticities of the other product besides Coke and Pepsi determine how many of Coke and Pepsi will be sold with a given price. Depending on the prices of their other beverages are going to affect how many of Coke and Pepsi that you sell. If Dominick’s wants to sell a lot of Pepsi and Coke than they will need to look at these models and find out which products are significant to the sales of Coke and Pepsi. So, if Canada Dry Ginger Ale is a significantly significant factor to the sales of units of Coke than they are going to want to raise the price of Ginger Ale to raise the sales of Coke. Objectives Our objectives in this analysis as Dominick’s retail stores are to determine what has an effect on our mission to raise the sales of Coke and Pepsi. In order to fulfill our objectives we will need to complete multiple models that make up our analysis, which are comprised of various information we have gathered on products that will have a strong effect on the sales of Coke and
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Pepsi. Using SAS, we are completing models in which we will be obtaining the majority of our information; some of the models we will be evaluating are the multiplicative model and seasonality model. A multiplicative model uses all the elasticities of the products and their prices; by multiplying these two numbers and adding them to the other products, this process allows us to forecast sales. The seasonality model is similar to the multiplicative in that it uses the prices and elasticities of the products that affect our analysis, in addition to dummy variables whose values consist of 0 and 1. By completing this model we are able to show and predict when our sales of Coke and Pepsi will sky-rocket immediately before they decline. For example all retail stores experience this effect during the holiday season when sales are peaking and then as they plummet when this season comes to a close. The elasticities in themselves are another helpful tool that we will use to help us make a decision in the end, because they will show us which products will be substitutes or compliments, in relation to that of our products in question (Coke and Pepsi). Also, as we complete our evaluation the SAS output will be issuing p-values to each of our product variables. By using these p-values we are able to find out which products
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This note was uploaded on 12/11/2011 for the course AGEC 317 taught by Professor Staff during the Fall '08 term at Texas A&M.

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Class Project Report - Technical Report for Dominicks...

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