Retail Case Study
Farnley Retail Group
A demand forecasting system that reduced excess seasonal inventory.
-20%Reporting Time Saved
The Challenge
Where things stood before
Before working with us, Farnley Retail Group was dealing with systems that didn't talk to each other, making basic reporting a manual chore, and it was starting to cost them real business.
Competitors and peers seemed to have this figured out already, which only made it more frustrating.
The Solution
What we built
We started by getting a clear picture of exactly where things were breaking down before proposing anything.
What we ultimately delivered was a demand forecasting system that reduced excess seasonal inventory, built specifically around what Farnley Retail Group needed.
- Benchmarked against clear, agreed-upon success metrics from day one
- Delivered within a 7-week timeline without cutting scope
- Tested thoroughly before launch to avoid post-launch surprises
- Built using Node.js and PostgreSQL for a stable, maintainable foundation
Results
The impact, by the numbers
-20%
Reporting Time Saved
+25%
Data Accuracy
-28%
Inventory Discrepancies
91.5%
Team Adoption
Tech Stack
Built with
Node.jsPostgreSQLREST APIEDI
Greystone Distribution
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