Stephanie Spinella
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Practicum project - analytics in supply chain management

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(In progress) Practicum team project for Associated Grocers on how to incorporate analytics into Logistics and Supply Chain management, specifically disaster management. My team is analyzing past inventory data provided by Associated Grocers, along with historical hurricane data collected after 2004, to derive the optimal quantity and basket mix of disaster items for the company to deliver to its independent retail grocers to keep up with the demand before, during, and after a hurricane. The following picture is a screen shot of the Tableau dashboard we are currently working on for the project:

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supply chain management - linear programming

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Using Microsoft Excel Solver, I completed a project that involved using optimization techniques to find the best supply chain management options with the given data. There are four hypothetical offices located in Los Angeles, Tulsa, Denver, and Seattle and by applying linear programming methods I found what combination of closed offices would produce the best costs for the company. 

SCM_LinearProgramming.pdf
File Size: 543 kb
File Type: pdf
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Search Engine Marketing ROI

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My team and I , the D.A.T.A. Miners, were approached with a challenge to reduce the amount of advertising costs for online retailer Shopper's Choice through Web Analytics, which included Google Analytics and AdWords. We created and simulated a few search term criteria that was show to save $700,000+ in advertising. Our main focus was reducing costs by eliminating keywords with low quality scores, eliminating unproductive items, and by evaluating bounce and conversion rates.  

SearchEngineMarketing_Presentation.pdf
File Size: 812 kb
File Type: pdf
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multivariate final project

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This project consisted of four business questions that each could be answered by a certain multivariate analysis. I used SAS Enterprise Guide to find what factors influenced customer satisfaction and customer commitment, as well as if there were any segments present in the customer base group. The four analyses that I used for this project were Factor Analysis, Cluster Analysis, Multiple Regression, and Logistic Regression. 

MultivariteFinalProject
File Size: 931 kb
File Type: pdf
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