Supported a team of 3 people on warehouse optimization and ad-hoc projects.
Analyzed data for warehouse optimization, resulting in 5% increase in picking and replenishment efficiency.
Resolved error in the database regarding product information by writing SQL query to extract, load, and transform (ELT) data from database. Then using both SQL and PowerBI DAX to manipulate data before finding deviations.
Improved internal inventory platform by converting product images from a source folder into binary data (Base64Encoder) with Python query and uploaded on PowerBI, resulting in faster inventory research for employees and faster response times to customer service requests.
Re-addressed product storage locations in the warehouse based on the product footprints to minimize damages when packing and delivering that can cause product crushing.
Established Minimum Order Quantity (MOQ) for different customers based in California, which are wholesales, retails, and restaurant customers, by utilizing sales, distance, gas price, truck capacity, and customer data.
Improved warehouse capacity by analyzing product movements, products, storage locations, sales data to recommend items to discontinue which gaining additional available storage locations.
Evaluated Rate of Return using Time Series and dashboard to illustrate abnormal returning behaviors and conducted interviews for root causes. The new return policy was constructed to reduce return abusers.
