Why Google Sheets Automation Breaks So Often for Remote Teams

1. Basic Google Sheets triggers will silently fail on shared accounts

You’d think a remote team living in a shared Google Drive would be the ideal setup for automating Sheets. But no — if two team members install the same script-based automation or use apps like Zapier or Make to trigger on edits, Google might just… not fire the trigger. Or worse, fire it twice.

One Tuesday I built a Sheets-to-Slack notifier using a simple Edit trigger. Worked perfectly. Wednesday, I added a second user to the Sheet, and suddenly Slack was blowing up with duplicate messages. Turns out, both users had authorized the same automation, and Google fired the onEdit hook for both accounts’ tokens. This isn’t in the UI. There’s no obvious warning, not even in the Apps Script logs unless you dig under Stackdriver in GCP.

It’s 2024 and this still happens. Best prevention: centralize all automation ownership in ONE Google account (ideally a service account or automation-only user) and make all Sheets contributors view-only where possible. If they must edit, use a custom sidebar UI so edits don’t count as edits, or separate the data enrichment step from the display Sheet entirely.

2. Conditional formatting can block automation writes with no warning

This one wasted hours. I had a script that writes values into specific columns, based on workflow status. It always died silently halfway. No error, no toast, nothing in Stackdriver either. After disabling pieces line-by-line, I realized the Sheet had conditional formatting rules applied with custom formulas that referenced the same range being written to.

Google Sheets doesn’t throw warnings when a script tries to overwrite a cell that’s conditionally locked by custom logic. It just… fails. Sometimes it writes, sometimes not. It depends on whether the formula inside the conditional formatting conflicts with the edit at runtime.

If your script isn’t writing what you expect, open the Format → Conditional formatting pane and audit every little rule. Delete anything complex or dynamic. Better yet, apply visual formatting through Apps Script directly (e.g., setBackgrounds, setFontWeights) to avoid this edge case entirely.

3. Zapier skips Sheets triggers after timezone shifts or daylight saving

This isn’t theoretical. We had an onboarding workflow tied to a weekly Google Sheets row creation, which then triggered a Zap to send sequences — it worked until Europe switched to summer time and one team member’s local clock changed, altering the Sheet’s perceived edit time.

The Zap was set to only trigger on new rows, not older rows being updated. But that didn’t help. Zapier looks for timestamp differences to detect changes, and the Google Sheet used NOW() as the timestamp. After the DST switch, NOW() updated late, and Zapier de-duped the trigger, assuming it was the same event—but it wasn’t.

Use this instead if you need reliable temporal signals:

=ARRAYFORMULA(IF(A2:A<>"", TEXT(NOW(), "yyyy-mm-dd hh:mm:ss"), ""))

…and freeze the timestamp right when the row is created. Make can also help here, since it uses webhooks better. But even that’s fragile. If human input triggers the NOW() function refresh (e.g. opening the Sheet), it can falsely mark the row as new. Test with different timezones logged in.

4. Google Sheets API limits resurface in weird ways during batch updates

Ran into this two days ago: pushing multi-row updates via the Sheets API in a Make scenario, using batchUpdate across a 1500-row dataset. Everything looked fine until row 638, where the batch quietly truncated.

No error message, no failure log. Just a partially updated Sheet. Turns out Google limits the batchUpdate payload size not just by the number of rows/columns, but by total cell character count — and if your data fields contain large JSON blobs, nested HTML, or long Markdown notes, you’ll silently hit the boundary around row 600 or so.

A quick workaround is to chunk data into smaller payloads, ideally 200 rows per request, and insert a brief wait (like 300ms) between calls to avoid throttling. Also: log the updated row count after every write cycle and check if it matches expectations. If not, assume silent failure and log the delta.

5. Formula results don’t count as changes for webhook triggers

If you’re playing with Make or Zapier watching for changes in a Sheet cell, here’s a brutal catch: formula results aren’t considered edits. Even if the cell visibly changes, Google doesn’t mark it as modified. That means any automation watching for changes will quietly do nothing.

Had a client trying to trigger SMS notifications when flight prices dropped. The Sheet used IMPORTXML to scrape prices. Worked fine on screen — but the automation never triggered. That’s because IMPORTXML changed the cell value without changing the cell itself.

Fix option 1: add a companion column where someone manually re-types or confirms the value. Fix option 2: use Apps Script to detect formula result changes via polling (not recommend for large data). Fix option 3: write a separate service that watches the Sheet and hashes values to detect changes over time.

6. Sheet protection prevents edits only if you remember to enable warnings

Setting up range protection rules doesn’t stop automation from editing sheets — unless you configure warning prompts and enable them for scripts. By default, script-based edits and Zapier writes ignore protection completely.

That’s fine until someone accidentally builds an automation that overwrites manually entered data. I’ve done this twice: once overwriting a budget Sheet with historical roll-up totals I thought were stored elsewhere, and once inserting rows mid-Sheet because an automation didn’t respect the protected range limits.

The trick is to set up not just protected ranges, but a separate validation column, where scripts check for a lock signal before writing. Here’s a quick Apps Script pattern I use now:

function isRowLocked(row) {
  var status = sheet.getRange("Z" + row).getValue();
  return status === "LOCKED";
}

Then wrap your logic so only rows not marked LOCKED get touched.

7. Inter-sheet references break when collaborators duplicate the file

Collaboration loves friction. Especially when someone makes a copy of the Sheet and forgets that IMPORTRANGE-style formulas don’t carry over intact. The copied sheet will still reference the original Sheet unless they manually re-link the import data permissions — and there’s no pop-up about this.

Last month, someone duplicated our inventory Sheet to experiment with layout. They didn’t realize the stock numbers were still live-linked to production. They deleted rows, thinking it was sandboxed. Guess what happened? The live source Sheet emptied half its rows before I caught the damage in version history.

Always wrap your sync process with validation signals. I now prefix every live data tab with “📡_” and all experimental ones with “🧪_” so at least it’s obvious in a dropdown. Also helps to use IMPORTDATA from a published CSV instead of cross-Sheet formulas — just enough abstraction to force rechecking before edits.

8. Apps Script time triggers don’t always run on the minute

This is deep-cringe territory. I set up a script using ScriptApp.newTrigger().timeBased().everyMinutes(5) and assumed it would run at :00, :05, :10, etc. Instead, it ran whenever the scheduler felt like it, often :06, :12-ish, with ±30 seconds of swing.

That completely messed with a downstream reporting pipeline that assumed 5-minute mark snapshots. Ended up with overlapping log entries, missed deltas, and confusing anomalies in the analytics output.

There’s no fix to make time-based triggers land on exact minutes unless you poll from an external cron or scheduler. Even then, if the Google server is under load (and it often is), it’ll delay or skip the function call entirely. I eventually moved the time-critical part to a Cloud Function triggered by Cloud Scheduler — annoying but at least precise. If sub-minute accuracy isn’t critical, just round the timestamps post-capture and move on.

9. Airtable inserts break randomly when sheet columns are re-ordered

Tiny change, major fallout. Sheets lets collaborators drag columns freely. But if you’re using Zapier, Make, or API pulls into tools like Airtable, they often reference columns by index, not header.

Last week I added a new column to a shared people tracker. Seemed harmless. Within 12 minutes, 28 Airtable records were updated with mismatched birthdays and project IDs. Turns out Make’s module was using a hardcoded column C, which is now no longer the birthday column. Imagine explaining that in your retro.

Fix this with named ranges or enforce header checks inside the automation. Tools like Rows or Coda help by treating tables more schema-like, but if you’re stuck in Sheets, write a config Sheet that maps expected column headers to current positions and validate before every run.