# How to clean a worker spreadsheet before you import it A short clean-up routine for an existing worker roster before it goes into a system: one row per worker, dates as dates, consistent names and a plan for missing facts. By Worker Vault · Published 1 October 2026 · 5 min read URL: https://workervault.com/blog/clean-worker-spreadsheet-before-import **Key points** - One row per worker and one column per fact makes an import predictable. - Dates must be real dates, not text, and names must follow one format. - Decide what to do with missing facts before you import, and keep a list of them. - Check the preview before confirming, then work the gaps from one list. Most agencies that move to a system already have a worker roster in Excel. That is an asset. It also contains years of small inconsistencies that did not matter when a person read each row, but matter a great deal when software has to read them all. An hour of clean-up before import saves many hours afterwards. This routine covers what to fix, in the order that tends to pay back fastest. ## Step 1: make a copy and freeze the original Work on a copy. Keep the original untouched, with the date in its file name. If a clean-up step goes wrong, you can return to the starting point, and you will be able to show later what the roster looked like before it was changed. ## Step 2: one row per worker Look for workers who appear on several rows because each document has its own row. Merge them so each worker has exactly one row, and each fact has its own column. If a worker has two work permits in history, do not add a second row. Keep the current one in the main row and note the earlier one separately, so you can attach it as a document after import. ## Step 3: one column per fact Split columns that hold more than one fact. "Passport A1234567 exp 03/27" should be a passport number column and a passport expiry column. Remove merged cells, blank spacer rows and notes typed into data cells. Put notes in a notes column, which can travel with the record. ## Step 4: make dates real dates Dates are where imports most often fail quietly. Check that every date column holds actual dates, not text that looks like dates. Signs of trouble are left-aligned dates, a mix of formats such as 03/04/2026 and 3 April 2026, and a month and day that have swapped. Choose one format, convert the column, then spot-check ten rows against the source documents. If a date cannot be read with confidence, leave the cell blank and mark the worker for follow-up rather than guessing. ## Step 5: one format for names and identifiers Pick a single rule for names: for example, full name as in the passport, in capitals or in normal case, but not both. Remove double spaces and trailing spaces. Check identifiers, such as passport numbers, for letters that look like digits and for lost leading zeros. Look for duplicates by name and by passport number. Two rows for the same person are an import problem. One row for two people with the same name is worse. ## Step 6: decide what to do with missing facts Not every cell will be filled. Decide in advance what counts as acceptable for the import: - **Required to identify the worker:** name and a unique identifier. Do not import without them. - **Needed soon:** expiry dates and employer client. Import with the gap, and put the gap on the follow-up list. - **Nice to have:** everything else. Leave it empty. Keep a separate list of workers with gaps and the missing fact for each. It becomes your first work list after import. ## Step 7: import in steps and read the preview A good import runs in four steps: upload, validate, preview and confirm. Do not skip the preview. Read the first twenty rows, then check three or four workers you know well against their paper records. Fix the spreadsheet and run it again if anything looks wrong. ## After the import Attach documents to each record, starting with the soonest expiry dates. Have someone review each document before it is treated as evidence. Close each gap on your list by fixing the record, not by editing the list. Then set up a [permit expiry tracking routine](https://workervault.com/blog/foreign-worker-permit-expiry-tracking-routine) so the dates you have just imported are reviewed every week. ## A quick pass for the usual suspects Before you upload, run a final five-minute pass for the problems that cause most failed rows. Filter each date column for blanks and for values far outside the expected range, such as years that are clearly wrong. Sort names alphabetically and look for near-duplicates side by side. Check that no column mixes numbers and text where it should be one kind only. If you find a pattern, fix it for the whole column in one step, not row by row. Then save a new copy with a version note in the file name, so you can tell which file was imported if a question comes up later. ## Where Worker Vault fits Worker Vault imports existing workers from XLSX or CSV templates. The steps are Upload, Validate, Preview and Confirm, with a limit of 5,000 rows and 10 MiB per file. Imported workers get a worker record like any other, with documents, expiry dates and a place in the [Work Queue](https://workervault.com/solutions/compliance). For the wider picture, see [spreadsheet or system](https://workervault.com/blog/spreadsheet-vs-system-foreign-worker-records), [how to keep worker records and document expiry in order](https://workervault.com/blog/keep-worker-records-and-document-expiry-in-order) and the [worker records page](https://workervault.com/solutions/worker-records). To see an import with your own roster, [Book a Demo](https://workervault.com/book-a-demo). This post provides general information only. It is compiled from information publicly available on the web and is not an official source or legal or professional advice. Rules and requirements change over time, so check the facts with the relevant official authority before acting. Worker Vault accepts no responsibility for how this content is used.