Code
Optimizing Inventory for a Barcelona D2C Cosmetics Brand
Overview
What this challenge is about.
You are given a CSV file with 6 months of daily sales data for 20 SKUs, including product name, date, units sold, and current stock level. Your task is to write a Python program that: (1) loads and cleans the data, (2) calculates daily average demand and demand variability for each SKU, (3) computes a suggested reorder point and safety stock using a basic formula (e.g., ROP = avg demand * lead time + safety stock), and (4) outputs a summary table ranking SKUs by risk of stockout. Success means delivering a working script and a one-page report with your recommendations. Constraints: use only standard Python libraries (csv, statistics) and no external APIs.
The Brief
What you'll do, and what you'll demonstrate.
How can Glow Naturals use historical sales data to set inventory levels that minimize stockouts and overstock?
Earning criteria — what you'll demonstrate
- Write a Python script to load and clean structured data from a CSV file
- Apply basic statistical functions (mean, standard deviation) using standard libraries
- Implement a simple business logic (reorder point formula) in code
- Generate a formatted output (table) and interpret results for decision-making
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Skills you'll demonstrate.
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