Move information from documents into workflows, not spreadsheets.

What the process looks like today

Illustrative example: a wholesale team receives supplier invoices by email, purchase orders from purchasing and scanned delivery orders from the warehouse. Staff re-key references and line items into a spreadsheet or accounting system, then compare quantities and totals across documents. A missing delivery reference or partial shipment leaves an item waiting in an inbox, with little visibility into who must resolve it.

How the improved workflow works

Illustrative workflow: receive the document, extract agreed fields, match available records, route exceptions, update an approved destination and retain an audit record. Extraction is only one step: the process must also define duplicate handling, mismatch ownership and what happens when a downstream update fails.

• Receive agreed document types from an authorised inbox or upload location and assign a processing reference.
• Extract supplier or customer names, document numbers, dates, line items, quantities, units and totals into a defined schema.
• Match invoices to purchase orders and delivery records where the required references are available; apply agreed rules for duplicates and discrepancies.
• Place unreadable fields, missing records and mismatches into an exception queue with source documents available for review.
• Send staff-approved records to the agreed accounting, purchasing or operations destination; distinguish a prepared record from a successful system update.
• Record corrections, approval status and processing outcomes with agreed log access and retention boundaries.

Capabilities, limits and financial approval

Use straightforward validation for required fields, arithmetic and matching rules. Document extraction tools and AI can help with varied layouts where appropriate, but a plausible extracted value is not evidence that a transaction is valid.

• Can help: classify agreed document types, extract fields, normalise formats, identify potential duplicates, compare records and prepare structured imports.
• Cannot assume: that a scan is complete, that a supplier is legitimate, that goods were received or that a missing PO should be created automatically.
• Human approval: authorised staff resolve quantity and value mismatches, confirm exceptions and approve consequential financial record changes.
• Out of scope unless separately agreed: payment execution, supplier bank-detail changes and autonomous financial approval. Extraction does not replace accounting judgement or fraud controls.
• Low-quality scans, handwriting, multi-page tables and unexpected formats require explicit tests and a fallback review path.

Documents and systems to assess

Typical inputs include PDF invoices, scanned delivery orders, purchase-order exports, receiving records and structured forms. Existing destinations may include accounting software, ERP, procurement tools, spreadsheets or an internal database. These are examples, not certified connector claims; available permissions and supported interfaces determine feasibility.

• Confirm document versions, supported languages and formats, required fields, supplier identifiers and authoritative matching records.
• Review whether the destination supports a sandbox, API, validated import or controlled export; direct posting is not a default assumption.
• Define which records can be read, which approved fields can be written and who owns reconciliation when a system rejects an update.

A scoped pilot: deliverables and prerequisites

Choose a bounded document family and matching scenario, such as invoices against available POs and delivery records. Include difficult cases as well as clean samples so the pilot tests the real review burden rather than extraction on ideal documents alone.

• Deliverables: a current-state map, field schema, extraction and validation workflow, matching rules, an exception queue and an agreed export or test integration.
• Validation: staff-checked expected values, representative test scenarios, documented failure paths and acceptance criteria for fields and downstream updates.
• Handover: processing and reviewer instructions, access boundaries, measurement findings and a recommendation on production readiness.
• Prerequisites: authorised document samples and corresponding records, agreed tolerances and duplicate rules, a finance or operations owner and staff available to verify results.
• Integration access: permission from the accounting or ERP owner, appropriate test credentials or export access, agreed retention and a clear prohibition on unapproved live postings.
• Production is separately scoped for deployment, training, monitoring, exception ownership and ongoing maintenance as formats or systems change.

Measurement goals for the pilot

Measure the whole process, including corrections and exception handling, against a representative manual baseline. The aim is to identify a useful improvement, not to claim error-free extraction or guaranteed savings.

• Processing time per document: receipt to approved structured record, with waiting time and active handling effort distinguished.
• Extraction exception rate: the share requiring review, broken down by document type, field and error reason.
• Re-entry effort: staff time spent copying and correcting data, including any work introduced by the new review queue.
• Reconciliation cycle time: time to resolve invoice, PO and delivery mismatches, with unresolved exception age visible.
• Record quality: field-level agreement with staff-checked values and successful destination updates, assessed separately from extraction speed.