Operations platform review, aviation catering
An independent review of the software running day-to-day operations at an aviation catering business — meals produced in a kitchen and delivered to private aircraft at UK airports. Every screen and module walked through, then two documents: a plain-English user guide, and a costed modernisation proposal.
What I delivered
- A system overview and user guide written to be read before anyone logs in for the first time, so that when they do, every screen already makes sense. Covers the business, the vocabulary, the order lifecycle, every module, and the workflows someone new will hit in their first week.
- An improvement analysis and modernisation proposal — around forty findings grouped into seven themes, each with a business reason, an implementation approach and an effort estimate, then banded into a twelve-month roadmap.
- A separate strategic section on where AI actually fits, with five concrete use cases grounded in data the platform already holds.
Leading with what already works
The proposal opens by being explicit about what the existing system gets right — a well-modelled six-stage order lifecycle, correct domain vocabulary rather than forced generic language, proper handling of amendments, recipe composition, consolidated invoicing, and a deep accounting integration.
Findings worth naming
- No single view of where an order is. An order sits in exactly one stage at a time, but nothing shows its journey — so staff assemble the timeline mentally, every time.
- Data quality drifting quietly. Duplicate part numbers, placeholder descriptions never replaced, test records mixed into live data, and stock levels showing zero across the board — meaning either the module isn’t used or it is silently broken. Worth establishing which.
- Integration failures visible but passive. A warning icon appears on the row, but with no retry action, no filter for unsynced records and no health indicator anywhere. Knowing something failed is not the same as being able to fix it.
- Reporting stops at quantity and value. No margin, no period-on-period comparison, no customer profitability — despite both cost and sale price already living on the record. The data to answer commercial questions was there; nothing asked them.
- Desktop-first throughout. Drivers airside, chefs on the pass and account managers on the road were all second-class users of a system built for a desk.
Where AI actually fits
Kept deliberately separate from the general improvements, and argued from the shape of the business rather than from the technology: orders arrive by email and PDF and get re-typed, amendments happen constantly, the data is structured and repetitive, and margins are thin enough that errors are expensive.
How the roadmap was sequenced
Quick wins sit at the front deliberately, and the document says why in plain terms: they are not the highest-value items. The strategic overlay is.