RetailNDA-safe case study

Demand Forecasting and Assortment Optimization — Apparel

Built Python-based demand forecasting and assortment optimization models for a global retailer, paired with executive dashboards.

Client

Global Apparel Retailer (NDA-Protected)

Duration

8 months

Stack

PythonBigQueryPower BITime Series

01. The Problem

Client needed to forecast demand across thousands of SKUs and optimize store-level assortment — existing methods relied on spreadsheets and manual analysis.

02. The Approach

Designed a hybrid ML pipeline combining time-series forecasting with assortment optimization. Built a Power BI layer so regional managers could explore forecasts interactively.

03. The Outcome

Improved forecasting accuracy compared to baseline; decision cycles shifted from monthly to weekly. Adopted by multiple regional teams.

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