OT Leakage Benchmarks in Indian Factories: How Much Are You Losing?

Key finding: Overtime leakage in Indian factories — the gap between hours actually worked and hours correctly compensated — is a larger and more systematic problem than most finance and HR teams realise. InOps data shows that manual OT reconciliation processes produce material discrepancies every payroll cycle, in both directions: workers underpaid on legitimate OT, and factories billed for OT that did not occur.

This report defines OT leakage, quantifies it across InOps-monitored sites, identifies the three root causes, and documents the closure patterns that best-performing plants use.

Defining OT leakage: three distinct failure modes

Unauthorised OT: Workers stay beyond shift end without formal approval. Line supervisors allow it informally; HR and payroll are not aware until the worker claims it or the contractor invoices for it. This is the most common leakage type.

Ghost OT: Overtime claimed on contractor invoices for hours that biometric records do not support. This is straightforward fraud in some cases, but more commonly the result of manual data entry errors at the contractor level.

Unclaimed legitimate OT: Workers owed overtime pay who do not claim it — common among contract workers who are unaware of their entitlement or who cannot navigate the claims process. This is a compliance liability for the principal employer under the Factories Act.

What the data shows

Among InOps-monitored sites that migrated from manual to automated OT tracking, average monthly OT discrepancy dropped significantly after integration — with the largest reductions seen in sites where biometric punches feed payroll directly, eliminating the manual extraction step entirely.

Sites with automated shift-rule enforcement (OT requires manager approval in the system before it becomes payable) show the lowest ghost OT rates. Sites still using paper-based OT registers show the highest.

The financial impact scales with headcount. For a 1,000-contractor workforce at ₹15,000 average monthly wages with a 10% OT rate, even a 20% discrepancy in OT tracking represents a six-figure monthly exposure.

Root causes of persistent OT leakage

The primary root cause is system fragmentation: biometric data in one system, shift rosters in a spreadsheet, and OT approvals via WhatsApp. Reconciliation happens at month-end, by which point the evidence for any given dispute — who was on site, when, under whose approval — is inaccessible.

The secondary cause is the contractor invoice gap. Principal employers receive bulk invoices from staffing agencies that bundle regular and overtime hours. Without a worker-level attendance record to verify against, invoice reconciliation is effectively impossible.

The tertiary cause is policy ambiguity. Many plants have written OT policies that differ from actual shop-floor practice. The gap is tolerated until an audit or a labour dispute forces a reckoning.

How top-performing plants close the gap

Plants with the lowest OT leakage rates share a common architecture: biometric punch data is the system of record for shift start, shift end, and overtime threshold crossing. Every minute of potential OT triggers an automated notification to the line manager and requires digital approval before it becomes payable.

Invoice reconciliation is automatic: the contractor-submitted invoice is compared line-by-line to the biometric record, and discrepancies are flagged before payment is released. Finance does not need to trust the invoice — they verify it.

The result is OT leakage approaching zero in both directions: workers get paid for every legitimate overtime hour, and factories do not pay for hours that did not happen.