Demand forecasting across 140 stores
A forecasting engine and planning dashboard that tells each store what to order, and why.
- Client
- Specialty retail chain
- Industry
- Retail
- Timeline
- 4 months
- Year
- 2025
The challenge
Store managers ordered by gut feel. Some stores ran out of best-sellers while others wrote off unsold stock every month.
Our approach
We unified sales, inventory and promotions data in a warehouse, trained per-SKU forecasting models and built a planning dashboard with explainable recommendations managers can accept or adjust.
Results
- Less write-off stock
- 23%
- Fewer stock-outs
- 17%
- Forecast accuracy
- 92%
- Recommendations explained in plain language
- One trusted set of numbers for every store
- Buyers plan weeks ahead instead of reacting
Services
Technology
- Python
- dbt
- Snowflake
- scikit-learn
- Power BI
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Next project
Invoice processing that runs itself
Let's build something remarkable.
Tell us where you want to be in twelve months. We'll show you how software, AI and automation can get you there.