Supply Chain Analysis: Case Study

Download the dataset below to solve this Data Science case study on Supply Chain Analysis.

Supply chain analytics is a valuable part of data-driven decision-making in various industries such as manufacturing, retail, healthcare, and logistics. It is the process of collecting, analyzing and interpreting data related to the movement of products and services from suppliers to customers.

Here is a dataset we collected from a Fashion and Beauty startup. The dataset is based on the supply chain of Makeup products. Below are all the features in the dataset:

  1. Product Type
  2. SKU
  3. Price
  4. Availability
  5. Number of products sold
  6. Revenue generated
  7. Customer demographics
  8. Stock levels
  9. Lead times
  10. Order quantities
  11. Shipping times
  12. Shipping carriers
  13. Shipping costs
  14. Supplier name
  15. Location
  16. Lead time
  17. Production volumes
  18. Manufacturing lead time
  19. Manufacturing costs
  20. Inspection results
  21. Defect rates
  22. Transportation modes
  23. Routes
  24. Costs

You are required to perform Supply Chain Analysis to find data-driven approaches to optimize the supply chain performance and improve customer satisfaction while reducing costs and maximizing profits for all stakeholders involved.

References to Solve this Data Science Case Study