Last-mile 3PL · Singapore
A Singapore last-mile 3PL operator was running performance analysis across four major retailer accounts, each delivering data in a different Excel format on a different cadence. The GM wanted year-on-year, store-by-store, SKU-level views. The team produced them. Eventually. We rebuilt the data pipeline and dashboard in 5 weeks. Now the GM asks; the system answers in seconds.
The GM ran a 3PL operation moving parcels across four major retailer accounts. Each retailer pushed performance data — delivery rates, exceptions, SLA breaches, return volumes, SKU mix — in a different Excel template on a different schedule. One was daily. One was weekly. One was monthly. One was "when they remember."
To answer something like "How are we doing on Retailer A's frozen-goods SKUs in the West region year-on-year?" the team had to compile from four sources, normalise the categories, line up the dates, and rebuild the pivot. Two days, sometimes three. By the time the answer landed, the GM had already moved on.
The data was there. It was the compilation that was killing visibility.
"By the time I had the answer, the question had aged out."
Five weeks. Foundation Build plus two Function Cycles. The AI agent was the second cycle, added once the data layer was solid.
Most operations teams accept multi-source manual compilation as the cost of doing business with multiple partners. It isn't. The compilation is a piece of software you haven't built yet. The longer you live with it, the more decisions you make on stale answers.
No pitch. No proposal. We talk about your business, identify the leverage, and tell you honestly whether we can help.