Starting Semester: Fall 2021
Location: Atlanta; GA
The Home Depot
Client ProfileToday, The Home Depot is the world's largest home improvement retailer with approximately 500,000 orange-blooded associates and more than 2,200 stores in the U.S., Canada and Mexico. The typical store today averages 105,000 square feet of indoor retail space, interconnected with an e-commerce business that offers more than one million products for the DIY customer, professional contractors, and the industry's largest installation business for the Do-It-For-Me customer.
Project DescriptionThe Home Depot has tremendous scale in home improvement, delivering tens of millions of customer orders across online, store and appliance networks. The company is making significant investments to create the fastest, most efficient, and reliable delivery in the industry. A key focus of this strategy is providing shorter delivery lead times for items purchased online and in-store. THD would like to understand the impact of delivery date availability on customer likelihood to purchase across delivery channels. Currently THD offers a variety of delivery experiences based on product type and inventory stocking location. This project will explore the relationships between delivery lead time and propensity to purchase. The team will first evaluate the current model in use for measuring online sales conversion. The team will then construct new models to evaluate different factors like price, competitive speed, product mix, and delivery date and time window scheduling across all delivery networks. The team will leverage findings from its research to recommend specific opportunities to increase sales and improve the delivery experience. The findings of this project will help inform strategic direction within Supply Chain and identify potential new areas of investment. The team is expected to provide THD with tools and methodologies that will measure the economic opportunity of delivery speed and identify opportunities to bolster the company's competitive advantage within product categories
SkillsThe team will analyze large datasets and construct models that leverage data science techniques. Strong quantitative skills and a knowledge of statistics and data analysis is preferred. Supply Chain, Analytics, Engineering, or a related field of study is ideal. Experience with SQL, python, R, Tableau or similar tools is also preferred.