“Three gaps on the early shift. Who can I call?”
Behind it: Confirmations went out the afternoon before, and nobody checked who had replied.
This agency isn't a client. It's put together from patterns that come up again and again in agencies placing temporary workers at volume.
Places: Warehouse and light industrial workers
Size: About 60 staff, 22 of them recruiters
On assignment: About 900 workers in a typical week
Clients: One large client brings in about two fifths of revenue
Holding it together: A duty manager, a payroll lead and two senior recruiters
The review read one month of records and talked to three people. Here's what it found, ranked by what each cost.
“Three gaps on the early shift. Who can I call?”
Behind it: Confirmations went out the afternoon before, and nobody checked who had replied.
“Fifty timesheets still missing, and payroll closes at six.”
Behind it: Timesheets arrive by text, email and paper, and nobody chases them until closing day.
“She left after eight days. That's the second this month.”
Behind it: Nobody checks in with a new starter once day one is over.
“Placed four people today. Spent the evening on paperwork.”
Behind it: Worker documents and expiry dates live in spreadsheets, so recruiters check them by hand.
Two smaller leaks: invoice lines that didn't match the client's hours, and the same candidate sent by two recruiters.
AI could help with the first three. Choosing which worker suits which site stays with the recruiters. The renewal conversation stays with the owner.
“That's the third short shift this month. We need to talk about the contract.”
Largest client, 11:40 AM
Everyone wanted better candidate matching. But short shifts were costing the most, and they were putting the largest client at risk. Progress would also show within a week. So that's where it started, and matching came third.
Used to call down a list at 5 AM.
Now starts with two gaps flagged and replacements suggested.
Used to confirm their own workers every evening.
Now spend that time with candidates and clients.
Used to chase timesheets on closing day.
Now works from a short list, two days early.
The result: shifts started full far more often, fewer people left in their first fortnight, the largest client renewed, and nobody's job was cut.
A fifth of worker phone numbers were out of date. Two weeks of cleanup came before anything went live.
Some workers found the check ins too frequent. After asking them, it changed to one message the evening before, and none at dawn unless they hadn't replied.
One site supervisor kept his own list. Rather than replace it, the workflow reads it.
Timesheet collection was added once shift confirmation had held for a quarter. New starter check ins followed.