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Data & Scraping

Turning Supplier Documents Into Structured Data

Delivery notes, certificates and spec sheets arrive as PDFs in a hundred formats. What extraction can handle, and how to fail safely.

Updated 2 min readBy SpiderHunts Technologies

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Quick answer — TL;DR

Extraction works well where the same supplier sends a consistent format and less well across a long tail of one-off layouts. Handle the top suppliers by volume first, keep a manual path for the rest, and never let a low-confidence extraction post silently.

The paperwork nobody can use

Supplier documents arrive constantly - delivery notes, certificates of conformity, test reports, specification sheets, safety data. Each contains information the business needs, in a layout chosen by the supplier.

Most of it is filed and never used analytically. When a question arises - which batches came from which source, which certificates expire this quarter - it means opening files.

Concentrate on the top suppliers

Document formats follow a steep distribution. A handful of suppliers usually account for most of the volume, and each sends a consistent layout.

  1. Count documents by supplier over a representative period.
  2. Take the suppliers covering most of the volume and handle their formats specifically.
  3. Use a general approach for the remainder, with lower expectations.
  4. Keep a straightforward manual path for genuinely one-off documents.
  5. Revisit the distribution periodically as the supply base changes.

Trying to handle every format equally well from the start is how these projects overrun. The long tail is genuinely hard and rarely worth the same effort per document.

What makes documents hard

  • Scans and photographs rather than digital PDFs
  • Tables spanning pages, with headers repeated or not
  • Multiple deliveries on one note, or one delivery across several
  • Units and formats differing by supplier - kg against lb, dates in either order
  • Handwritten annotations that change the meaning
  • The same field named differently on each supplier's template

The date format issue causes quiet, serious errors. A date read day-first when it was month-first produces a plausible wrong answer rather than a failure, which is the worst kind of bug. Pin the expected format per supplier rather than guessing per document.

Validate against what you already know

Extraction accuracy improves substantially when checked against your own records. You usually know what you ordered, so an extracted quantity or part number can be validated rather than trusted.

ExtractedCheck against
Part numberPurchase order lines
QuantityExpected delivery, with tolerance
SupplierSupplier master
DatePlausible window around the order
Batch or serialFormat rules for that supplier

Mismatches become exceptions rather than errors, which is the right outcome. An extraction disagreeing with the order is exactly what someone should look at.

Fail loudly

The dangerous failure is a confident wrong value posting into a system. A low-confidence extraction must go to a person rather than defaulting, and the original document should always be one click away.

Store the source document reference with every extracted value. When something looks wrong six months later, being able to see the page it came from turns an investigation into a glance.

A misread date does not throw an error. It just quietly puts the wrong month in your system.

FAQ

Frequently asked questions

The questions readers ask us after this guide.

Still have a question?

Ask us directly — a senior engineer will get back to you.

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Do we need a different model per supplier?

Not necessarily a different model, but format-specific handling for high-volume suppliers usually performs much better than one general approach.

What accuracy is realistic?

High for consistent digital documents from known suppliers; considerably lower for poor scans and unfamiliar layouts. Measure by supplier rather than overall.

Is OCR good enough now?

For clean scans, generally yes. Poor-quality faxed or photographed documents remain difficult and always will.

Should extracted data post automatically?

Only above a confidence threshold and after validation against your own records. Everything else should go to review.

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