Supplier price lists
Turn a scanned supplier price list into a usable Excel table
A repeatable procedure for preserving SKUs, units, currencies, and price breaks when a supplier sends a scan.
Define the table before converting
A supplier price list is useful only if each amount stays attached to the right product and selling unit. Before opening a converter, decide which fields you need: supplier, source date, SKU, description, unit, currency, price, and any quantity break. Keep these separate rather than treating a page-shaped worksheet as the final deliverable.
Request a native spreadsheet when the supplier can provide one. If a scan is the only available source, retain the original file and work on a copy. Record which edition of the price list is being processed so that old and new prices cannot silently merge into a single unexplained dataset.
Prepare a representative sample
Inspect the first, middle, and last pages. Look for repeated headings, page-specific notes, several currencies, and product descriptions that wrap across lines. Choose a small sample that includes these conditions. The aim is to expose the difficult parts before committing the whole document to one conversion setting.
Wondershare's official extraction guide describes an OCR-to-Excel route for scanned PDFs. That establishes a possible method, not a quality result for your supplier. Whatever tool you use, compare the sample with a small answer table prepared from the source. Verify the critical fields before processing the remaining pages.
Normalize product rows deliberately
Create one row for each actual price record. If a product has several quantity breaks, retain each break and its condition, or create clearly named columns with the same meaning throughout the workbook. Do not allow a note such as case of twelve to disappear while the price remains, because that can change how the amount is interpreted.
Keep SKU fields as text and distinguish a missing price from a zero price. Preserve the supplier's original value in a raw field when conversion needs interpretation. Microsoft's Power Query documentation explains that type conversion depends on locale. Set a suitable numeric interpretation for the source instead of relying on the workstation's default.
Validate relationships, not just totals
Compare each sampled SKU, unit, and price together. Correct-looking prices attached to neighboring products can survive a simple sum check. Check the first and last data rows of every page and every change of table layout. Count expected records and investigate unexplained gaps or extra entries.
Use the previous price list to flag unusually large changes, but do not overwrite the new value automatically. A change might reflect a new pack size, currency, discount structure, or legitimate revision. Return to the source before deciding whether the issue is conversion or a supplier change.
Save an auditable working version
Keep three distinct files: the original PDF, the untouched extraction, and the approved table. Add a source-page reference to the working data and note any manual decisions. This makes the next update easier because a colleague can understand why a row was changed without reconstructing the entire job.
The finished table should support filtering and price comparison without relying on visual page layout. Before sharing it, check the intended import process as well as the workbook display. A file that looks correct when opened can still lose identifiers or interpret decimals differently when imported into another system.
Sources
Evidence status: methodology. No unverified accuracy, savings or traffic claim is made.