170 hours a year recovered from a single automation

The problem

This firm had been running for 12 years. They'd accumulated a workflow that worked - just not efficiently. Every new job started with a message on WhatsApp. Someone would then copy the job details into a shared spreadsheet. Then, when the job was complete, they'd create an invoice in FreeAgent by copying the same details again.

It took roughly 15 minutes per job. At 14 jobs a week, that was 3.5 hours - every week - on pure data entry. No one had questioned it because it had always been that way.

What the audit found

During the workflow session, it became clear that all three tools - WhatsApp Business, Google Sheets, and FreeAgent - had API access available. The data entry was happening manually because no one had connected them. There was no technical barrier; it simply hadn't been set up.

The audit report identified this as the highest-priority item: high frequency, low technical complexity, complete elimination possible.

What was built

A Make.com scenario that watches the WhatsApp Business inbox for messages containing job keywords, parses the job details, creates a new row in the spreadsheet, and drafts an invoice in FreeAgent ready to review and send. The whole scenario runs in under 30 seconds from message receipt.

The team reviews each invoice before it goes out - the automation drafts, a human approves. That was important to them, and it was the right call.

The result

3.5 hours a week became roughly 20 minutes of review time. That's 170 hours a year back - the equivalent of four full working weeks. At a conservative admin rate of £20/hour, that's around £3,400 in recovered time annually. The audit cost £500.

The scenario has been running for four months without any manual intervention. When the team gets a new job type, they update the keyword list themselves.