The challenge: five days lost, every single month
Each month-end, the finance team pulled data from a freight management system, an accounting package, fuel-card statements, and a tangle of supplier spreadsheets — then reconciled it all by hand. The process swallowed five working days, introduced copy-paste errors that took even longer to chase down, and left no time for the analysis leadership actually wanted: margin by route, cost per shipment, where money was quietly leaking.
It wasn't a people problem. It was a plumbing problem. The data existed; it just lived in disconnected systems with no reliable way to bring it together.
The approach: a short discovery, then a fixed-scope build
We started with a paid discovery sprint: two weeks to map every data source feeding the close, assess data quality, and agree exactly what "done" looked like. That produced a costed, fixed-scope plan — no open-ended retainer, no surprises. The client knew the price and the outcome before a line of the build began.
Then we built to that scope:
- Integrated the freight system, accounting package, and fuel-card feeds through their APIs, replacing manual exports.
- Automated the reconciliation logic — matching transactions, flagging exceptions, and surfacing only the items a human actually needs to review.
- Shipped a governed Power BI "close pack": a single, trusted view of the month with drill-downs by route, client, and cost centre.
- Added access controls and an audit trail so every number could be traced back to its source.
"The first month we ran it, the close was done before lunch. The team spent the afternoon actually looking at the numbers instead of assembling them."
— Finance Lead, logistics SMBThe outcome: an afternoon, not a week
The monthly close dropped from five days to a single afternoon. Reconciliation that once relied on manual matching now runs automatically, with exceptions flagged for review rather than hunted down. Most importantly, the finance team got roughly a week of capacity back every month — capacity that now goes into forecasting and margin analysis instead of data wrangling.