Diagnose and Optimize Inventory for a Milan Cosmetics Brand
Overview
What this challenge is about.
Diagnose and Optimize Inventory for a Milan Cosmetics Brand. Intermediate challenge in analysis. Analyzing real datasets and building models that drive decis...
The Brief
What you'll do, and what you'll demonstrate.
Stockouts of bestsellers and overstock of slow movers are simultaneously costing Luminosa Milano lost sales and excess holding costs, and the company has no data-driven way to set inventory levels.
This is not a data exercise. It is the work an analyst or data scientist does when stakeholders need answers from messy data. That distinction matters to every hiring manager who has seen candidates describe statistical methods and none who have extracted insight from messy, incomplete, real-world data.
When you finish, you will have something most graduates do not: a real-world deliverable, verified by Ewance, that you can show to a hiring manager and say "I did this. Here is the proof."
When you finish, you will have something most graduates do not: a real-world deliverable, verified by Ewance, that you can show to a hiring manager and say "I did this. Here is the proof."
Earning criteria — what you'll demonstrate
- Diagnose demand behavior from raw transaction data, distinguishing steady from intermittent demand and spotting stockout-distorted history.
- Apply exponential smoothing to forecast demand and quantify forecast quality with mean absolute percentage error.
- Translate service-level targets and lead times into safety stock, reorder points, and order quantities.
- Automate repetitive inventory calculations with a robust, user-friendly VBA macro.
- Communicate analytical findings and trade-offs clearly to a non-technical operations audience.
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Aligned coursework coming soon.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
- Excel Modeling
Apply excel modeling to solve real industry problems and demonstrate production-level capability.
- Vba Programming
Apply vba programming to solve real industry problems and demonstrate production-level capability.
- Demand Forecasting
Apply demand forecasting to solve real industry problems and demonstrate production-level capability.
- Inventory Optimization
Apply inventory optimization to solve real industry problems and demonstrate production-level capability.
- Data Analysis
Analyze real datasets, build models, and communicate findings that drive decisions.
Careers
Career paths this challenge builds toward
Completing this challenge demonstrates skills that transfer directly to these roles:
Supply Chain Analyst
This challenge mirrors the daily work of a supply chain analyst: turning messy sales history into forecasts and inventory policies that balance availability against cost. You leave with a defensible, reusable model and the vocabulary to justify reorder decisions to operations leaders.
This challenge sharpens
- demand-forecasting
- inventory-optimization
- data-analysis
Demand Planner
Demand planners forecast product-level sales and set replenishment parameters under service-level constraints. By building per-product exponential-smoothing forecasts and tying them to safety stock and reorder points, you practice the exact modeling loop a demand planner runs every cycle.
This challenge sharpens
- demand-forecasting
- inventory-optimization
- excel-modeling
Operations / Business Analyst
Operations analysts automate recurring spreadsheet processes and present trade-offs to decision-makers. Automating reorder calculations with VBA and proving cost and stockout improvements on a dashboard builds directly toward the analytical and tooling skills this role rewards.
This challenge sharpens
- excel-modeling
- vba-programming
- data-analysis