Cost-Minimization-during-Expansion

This is a personal project dealing with a business problem statement where the goal is cost minimization during expansion.

Problem Statement: The client is a fast-growing company selling merchandise across the US. Their team believes that as the company expands, they may benefit from moving from a single distribution warehouse (currently located in Syracuse, NY) to multiple distribution points.

Their sales are growing at a rate of 15% a year, so their spend with their parcel service is exploding. We have been given the following information:

1. The company pays the following rates:

• $5.60 / package for shipments < 500 miles
• $8.70 / package for shipments < 1250 miles
• $11.90 / package for shipments > 1250 US within the continental US $18.00 / package for shipments requiring air freight

2. The company ships packages in equivalent size and weight (you may assume all packages have the same price)

3. Shipments also have surcharges – the client has very little visibility into the reasons for these so they cannot share any information with you.

4. Their current warehousing spend is $150K a year.

Data Exploration, Findings and Analysis:

• The current grand total of annual warehouse costs - shipment and maintenance costs combined - was $1,533,482.64
  • Shipping costs made up about 90% of these total annual warehouse costs.
  • The company was spending a total of $1,383,482.64 on shipments each year.
• The state with the most shipping costs was California, with a whopping $429,255.84 spent on shipments to California, annually.
• Shipments to CA from the warehouse location in Syracuse, NY made up approximately 31% of our annual shipping costs, and 28% of total annual costs.

Solutions and Final Conclusions:

• In 5 years from now, another warehouse in CA is likely to save money. A single additional warehouse would save costs and hold long-term benefits.
• By opening a second warehouse, the company would save a grand total of $1.1M over the next 5 years.
  • That's 9.62% in total savings.
  • They would save $1.85M on shipping costs alone.
• Warehouse costs would be $1.5M over the next 5 years.
• Their net savings would be $654,309.64.
• They would be saving 17.29% on shipping, yearly.

To run the code:

Set your file path by running the following line (replace with your repo location and folder name):

file_path = 'data/Shipping_Data.xlsx' shipping_data = pd.read_excel(file_path)

Structure of Repo:

• data/: This includes our data file, Shipping_Data.xlsx.
• states/: Includes all files for the states.shp file used for mapping.
• images/: Includes all data visualizations created using our .ipynb file.
• presentation/: Includes powerpoint presentation, .pdf file of Python notebook and .pdf of slide deck of final analysis, visualizations, and conclusions.
• Cost-Minimization-during-Expansion.ipynb: Python Jupyter .ipynb file for running all data analysis and visualizations.