What’s inside: monitoring · access rules
The question this file answersHow many overtime hours do we approve each month simply because the payroll run is in an hour?
Fits: plants where daily reporting and plant admin are rebuilt by hand.
Typical pattern, not a measured plant — the manufacturing playbook publishes no volume for time approval, so none is claimed here. Clock data arrives late and incomplete; supervisors chase the gaps, then wave everything through because payroll closes at noon. It hurts most the Monday after a weekend of unplanned shifts.
On payroll morning the supervisor opens a list of the shifts that need a decision — a spike, a gap, a swap — not the whole plant's hours. The approvals that used to be a rubber stamp are already drafted; the person spends the hour on the lines that could be wrong.
Typical, not a measured client result. Every figure here comes from the playbook source named below.
hours drafted from the clocks, anomalies to a supervisor — the same build as our timesheet file; no published figure for plant time
Before: supervisors approve everything because payroll closes in an hour. After: in-policy hours are drafted from the clocks and the odd lines wait for a name. This desk gets no percentage of its own until a source exists for it.
Overtime approval on a plant has no benchmark of its own. Toggl/Harvest (2023) report 40–60% less manual time entry from suggested entries — a professional-services figure that stays on the timesheet file and is not carried over to plant time. Not a payroll KPI.
Your time system and ERP stay where they are — SAP S/4HANA, Dynamics, Infor, whichever you have. We reuse the suggest-and-flag build from our timesheet file for professional firms, pointed at the shop floor:
Genuine overtime and why it happened. Shift swaps agreed on the floor. The story the clock did not record.
Not a payroll KPI.
If the rota is not maintained in the ERP, every deviation looks like an anomaly and the supervisor's list is long for the first pay cycles. Where the time system has no export, hours arrive as a spreadsheet drop, which is slower and needs IT. Clocks that miss breaks or floor-agreed swaps produce hours that look wrong but are not — those lines stay a conversation, not a rule. The Toggl/Harvest figure on the parent file is about consultancy time entry and is not transferred to plant time.
The path: free 60-second estimate → free 20-minute review → paid audit of this one process (€1.5–3K, typically two weeks) → pilot with your people in the loop (€10–20K, weeks, not quarters). No transformation programme. Prices are public, on the services page →
Scoped in the audit — the playbook has no estimate for this exact desk.
That depends on your volumes and wage costs — this page will not invent the number. The free 60-second estimate runs that calculation from your answers, with every multiplier sourced.
Not a named Aperanda client. Process file · Manufacturing.
Short process file. Same build as its parent file; the playbook has no separate volume or benchmark for this desk.