The Challenge
Pricing data lived in four separate places. Each with its own format. Its own naming conventions. Its own schedule for updates. To understand the complete picture, someone had to visit every source, translate between them, hold the patterns together mentally.
The hours went to gathering. Understanding came second.
People drowned in tabs while trends hid in plain sight. In an industry where yesterday's price movement shapes today's decision, that fragmentation carried real cost. Every hour between a market shift and a response was margin left on the table or margin quietly eroding.
Our Approach
We built a system that visits each source, gathers what it finds, and brings everything into a single view. Four vendors, normalized into one place, updated automatically.
When a source changes its format, the system notices, adapts, and continues. This happens quietly, usually overnight. The team wakes to current data without having to chase it.
The Results
Before: average response time to competitor price changes was 2.7 days. After: same-day.
We reconstructed twelve months of pricing events and measured the gap between when markets moved and when the business responded. The pattern was consistent: a $30 price increase missed for three days across 100 units is $3,000 that never reaches the books. Multiply across a year of movements in both directions.
The system caught a data anomaly in week two. A vendor had changed their export format without notice. Previously, this would have gone undetected for weeks, quietly corrupting decisions. The system flagged it overnight.
Annual margin impact: $47,000 in recovered opportunity and avoided loss.