1The business problem
Are you an operations or quality manager in a manufacturing business?
Answering a simple question, such as which batch of material went into a product shipped last week, means opening several spreadsheets and a filing cabinet.
Paper at the door
Delivery details are written down, then typed up later, if at all.
Records in different places
Stock, batches and test results live in separate systems.
Audit preparation by hand
Pulling evidence together for an audit takes far longer than it should.
2What we would advise
Start with the record, not the AI. We would design one reliable trail from incoming material to finished product, then consider AI for jobs such as reading supplier delivery notes.
- Discovery. Collect the forms, map who fills them in and time how long audit preparation takes today.
- One small piece first. Capture incoming material digitally and link it to batches. Trial it with real jobs.
- Attach the evidence. Link quality test results and inspection records to the batch record.
- Review and expand. Measure against the baseline, then decide what comes next.
3The proposed solution
| Capability | What it does | Status |
|---|---|---|
| Point-of-work capture | Existing stock system, a simple form app or a tablet checklist | To evaluate |
| Delivery note reading | Document extraction, with a person checking each result | To evaluate |
| Final decision | Quality sign-off | Human decision |
4Starting point and aim
| Area | Typical starting point | What we would work towards |
|---|---|---|
| Incoming material | Paper delivery notes | Captured once, at the door |
| Batch record | Stock and tests in separate places | One record with its tests attached |
| Audit evidence | Gathered by hand | Ready to export |
5Evidence and how we would measure it
This is an illustrative approach, so there are no results to report. In a real engagement we agree the measures first and report against your own baseline.
- MeasureAudit preparation time and record completeness against your own baseline
- ReviewResults reviewed with you at 30, 60 and 90 days
Expert insight
Most traceability problems are record problems. Fix the record first, and AI has something reliable to work with.
Questions we are often asked
Do we need AI for traceability?
Often not at first. Good data capture and one batch record do most of the work. AI helps later with reading documents or spotting unusual results.
Most relevant for: Manufacturers with paper-based records, separate stock and quality systems, or audit preparation that takes too long.