Warehouse Receiving: Convert Delivery Notes into Google Sheets in Seconds

Warehouse receiving is one of those processes that should be simple: a truck arrives, you verify quantities, and inventory gets updated. In reality, it often turns into a slow loop of paper delivery notes, manual data entry, typos, and “we’ll fix it later” spreadsheets.

With Img2Sheet, you can turn delivery notes (paper or PDF screenshots) into clean, structured rows in Google Sheets—using AI extraction, not just basic OCR. You define the exact columns you want once, then every new delivery note follows that same structure automatically.

Privacy note: Img2Sheet removes uploaded files immediately after extraction. We don’t store your delivery notes.

The receiving problem (and why OCR alone isn’t enough)

A classic delivery note can include:

  • Supplier name + address
  • Delivery number / reference
  • Date
  • Purchase order number
  • A table of SKUs, quantities, unit types, batch/lot numbers
  • Notes like “backorder” or “partial delivery”
  • Messy scans, stamps, handwriting, skewed photos

Traditional OCR may “read text,” but receiving needs structured data:

  • “This value goes into PO Number”
  • “These values are line items”
  • “Quantities must be numbers”
  • “SKU must be extracted even if the layout changes a bit”

That’s where AI extraction with a predefined structure makes the difference.

How Img2Sheet fits warehouse receiving

Img2Sheet works in two steps:

1) Create your receiving structure (once)

You define your columns with:

  • Label (e.g., PO Number)
  • Type (text or number)
  • Prompt (what data should be extracted exactly)

This structure becomes your “receiving template.”

2) Upload a delivery note

Upload a photo or scan, and Img2Sheet extracts data according to your structure, then inserts it into your Google Sheet in the same consistent format every time.

A practical Google Sheets structure for delivery notes

Here’s a strong starting structure for warehouse receiving. You can tweak it based on your operation:

Header fields (one row per delivery)

  • Supplier Name (text) — “Extract the supplier/company name”
  • Delivery Note Number (text) — “Extract delivery note / delivery number / DN number”
  • Delivery Date (text) — “Extract the delivery date as written”
  • PO Number (text) — “Extract purchase order number / PO reference”
  • Warehouse / Location (text) — “Extract delivery location if present”
  • Total Items (number) — “Extract total number of line items if shown”
  • Notes (text) — “Extract any comments like partial delivery, backorder, damaged, etc.”

Line-item fields (multiple rows or grouped output depending on your setup)

  • SKU / Item Code (text) — “Extract product code / SKU”
  • Item Name (text) — “Extract the product description/name”
  • Quantity Delivered (number) — “Extract delivered quantity”
  • Unit (text) — “Extract unit (pcs, box, kg, etc.)”
  • Batch / Lot (text) — “Extract batch/lot number if present”
  • Expiry Date (text) — “Extract expiry date if present”

If your delivery notes vary by supplier format, you can create multiple structures (one per supplier or per document type) and route documents to the right one.

What “in seconds” looks like in real warehouse workflows

Once your structure is set, a receiving clerk can:

  1. Snap a photo of the delivery note (or upload a scan)
  2. Upload it to Img2Sheet
  3. Get a ready-to-use Google Sheets row (or rows for line items)

Instead of typing, copy-pasting, or reformatting, the sheet is instantly usable for:

  • Inventory receiving logs
  • GRN tracking
  • Supplier performance tracking (late/partial deliveries)
  • Discrepancy reports
  • Reconciliation with purchase orders

Common use cases (beyond just “logging”)

✅ 1) Faster inventory updates

Your sheet becomes the source of truth for what actually arrived—clean, consistent, searchable.

✅ 2) Discrepancy tracking

Create columns like Expected Qty and Delivered Qty, then calculate variance automatically.

✅ 3) Receiving audit trails

Keep a structured log of who received what, when, from which supplier, under which reference numbers.

✅ 4) 3PL / multi-client warehouses

Use separate structures per client, or add a Client Name column as a required field.

Why AI extraction beats “text recognition” for delivery notes

Delivery notes are tricky because:

  • Layouts change by supplier
  • Tables are inconsistent
  • Some documents are low quality
  • Critical values appear in different places (“PO” might be top-left, top-right, or mid-page)

AI extraction lets you describe what you want:

  • “Extract the PO Number near labels like PO / Purchase Order”
  • “Extract each line item with SKU, description, and delivered quantity”
  • “Return quantity as a number (not text)”

That’s not just reading text—it’s understanding which text matters and where it belongs.

Data consistency: the biggest hidden win

Most warehouse spreadsheets fail because data is inconsistent:

  • “PO#” vs “PO Number” vs “PurchaseOrder”
  • Quantities stored as text
  • Missing columns
  • Line items pasted in weird formats

By enforcing a structure, every row matches your format:

  • Same columns
  • Same meaning
  • Same types
  • Ready for formulas, filters, pivots, dashboards, and automation

Security & privacy by design

Receiving documents can contain sensitive details (supplier pricing, references, customer info in some cases). That’s why:

  • Uploaded files are removed immediately after extraction
  • No “file links” to worry about
  • You keep control of your data in Google Sheets

Tips to get the best extraction results

  • Use clear photos (avoid heavy shadows)
  • Keep the whole document in frame
  • If the note has multiple pages, upload the page that contains the table + key references
  • For recurring suppliers, create a dedicated structure tailored to their layout

What to write in your Google Sheet next (simple automation ideas)

Once data is structured, you can:

  • Auto-flag missing PO numbers
  • Calculate supplier fill-rate (% delivered vs expected)
  • Detect repeated partial deliveries
  • Build a weekly receiving dashboard
  • Export to your ERP later (cleaner than manual entry)

Wrap-up

If your team is still manually typing delivery notes into Google Sheets, you’re paying twice: once in time, and again in mistakes.

With Img2Sheet, you set a receiving structure once, then every new delivery note becomes structured data automatically— using AI extraction, not just OCR—while uploaded files are removed immediately after extraction.