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differentiated capabilities

Labor is your biggest variable cost. Start measuring it properly.

Labor accounts for 15–35% of manufacturing cost, yet most plants still rely on timesheets that can’t capture concurrent teams, multi-shift jobs, or operator-crewed machine cells. The Eyelit MES has been solving every complex labor tracking scenario, giving you true Overall Labour Effectiveness (OLE) from plant level down to individual operator and product — and a proven path from 30% to 80% labour productivity.

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The Problem

Why timesheets fail and why digitizing them is not enough

Labor accounts for 15–35% of manufacturing cost, higher still in complex, assembly-intensive environments. The productivity gap, the difference between paid hours and time actually spent producing, has a huge impact on profitability. Yet most plants either allocate labor as overhead or attempt measurement through timesheets completed at the end of a shift from memory. Some MES systems simply digitize that paper timesheet: that reduces paperwork, but still cannot model labor as the multi-dimensional concept it is. These scenarios are all common on real shop floors, and all break a simple timesheet:

shared job, staggered team

A team works collectively on one operation but members start at different times and some move to a different job mid-run. Whose time is charged, and how?

multi-shift operations

A single operation spans several shifts with different teams. One job, multiple crews, standard timesheets lose continuity entirely.

operator-crewed machine cells

One operator runs four machines concurrently. Labor time and machine time are not the same thing, and most systems cannot tell the difference.

flow-to-Work environments

An operator works in a different team or shift from one day to the next. Tracking individual productivity across dynamic assignments requires a system built for it.

ole Framework

Overall Labor Effectiveness (OLE) — the complete picture of workforce productivity

Most manufacturers can identify the overall gap between their labor cost and their output, but few can break it down into the specific, actionable losses that drive it. OLE is the single KPI that provides this breakdown, capturing the full impact of the workforce on productivity. Calculated as Net Recoveries ÷ Paid Working Labor Time, it decomposes into three independently measurable loss categories — Utilization, Performance, and Quality — each pointing directly to a different type of problem and a different corrective action.

utilization

Are people productively engaged during paid time? Measures the split between direct activity, indirect activity, and unbooked / unaccounted time. Poor utilization, not poor performance, is the most common drag on productivity.

performance

When operators are doing direct work, are they working at the expected rate? Speed Loss is the gap between what was produced and what should have been produced in that time.

quality

Of the output produced, how much is good product? Scrap loss is the time lost to items scrapped, rework loss is the time lost in reworking items. What remains is Fully Productive Time.

How it works

How Eyelit MES captures OLE — automatically, in execution

Step 1

Set labor standards

Define expected times per operation and product. Concurrent and multi-resource combinations configured once.

Step 2

Capture actuals in real time

Operators log on and off at workstations via touchscreen or barcode scanner. The MES timestamps every transition, no end-of-shift guessing.

Step 3

Calculate apportioned times

Labor and asset hours calculated independently. Concurrent operators, concurrent jobs, and shift handovers all handled automatically, each on its own basis.

Step 4

Surface OLE dashboards

Live utilization, performance, and quality metrics from plant level down to team, shift, and individual operator, in real time.

Step 5

Feed planning with real data

Actual labor times replace financial standard times in APS. Schedules are built on what the workforce can really achieve.

skills & qualification

Skills Matrix — define, enforce, and develop operator qualifications

Define required skills per operation

Every operation in Eyelit MES carries a defined skills requirement. Before an operator can be assigned to — or log on to — a task, the system verifies their qualifications against those requirements. Unqualified assignment is blocked at the point of execution, not discovered at audit. The availability of skilled operators is also taken into account during planning and scheduling, ensuring that plans are realistic and achievable rather than built on assumptions about who is available and qualified.

Skills can also be configured to distinguish between working on an operation and completing it. For example, an apprentice may be permitted to work on an operation under supervision, but only a fully qualified operator can sign it off as complete — giving manufacturers fine-grained control over quality and compliance without removing less experienced operators from productive work.

Skills are defined at multiple levels: skill type, proficiency grade, and expiry date. A welder certified to one standard cannot be auto-assigned to an operation requiring a higher grade. A certification that has lapsed is treated as absent.

How skills enforcement works in execution

skills defined on operations

Each operation specifies which skills, and at what proficiency, are required to perform it. Configured once, enforced every time.

operator qualification records

Each operator profile carries their current certifications, grades, and expiry dates. The system knows in real time who is qualified for what.

blocked at Book-On

An operator attempting to book on to an operation they are not qualified for is blocked before work begins, not flagged after the fact.

skills gap reporting

Cross-reference performance data against the skills matrix to identify where training is needed, by individual, team, or operation type.

Skills enforcement connects directly to scheduling and planning. Knowing which operators are qualified for which operations means the scheduler can make realistic, constraint-aware assignments, rather than discovering a qualification gap after a work order has been released to the floor.

scheduling accuracy

The Eyelit APS uses live qualification data to optimize operator assignments, allocating the right skills to the right operations to maximize throughput, rather than discovering a qualification gap after a work order has been released to the floor.

expiry management

Certifications with expiry dates are tracked automatically. Planners are alerted before a qualification lapses, not after it has affected a work order.

training prioritization

Identify which skills are constraining throughput. Focus training investment where it removes real bottlenecks rather than across the board.

continuous improvement

Correlate operator skill level with actual performance data. Identify who excels at specific operations, and codify their approach as best practice for others.

attendance & pay

Paid Hours & Attendance — a capable alternative to time & attendance

Track attendance and hours worked in MES

The Eyelit MES captures the hours operators are present and working, giving you an accurate, real-time record of attendance and paid time. For many manufacturers, MES covers the core time and attendance capabilities they need without a separate system. MES integrates with door access control systems so attendance is recorded automatically at entry. Payroll integration passes verified hours to external systems for pay calculation and tax processing.

The Eyelit MES integrates with door access control systems so attendance is recorded automatically at entry, no manual clock-in required. Payroll integration passes verified hours to external systems for pay calculation and tax processing, keeping the source of truth in manufacturing where the data originates.

door access integration

Real-time attendance captured via access control. Site entry automatically opens an attendance record, no separate clock-in step for operators.

payroll integrator

Verified hours passed to payroll systems for pay and tax calculation. The Eyelit MES is the source of truth; external systems consume it.

pay management

Define pay rules by shift and work pattern, what rates apply, when, and under what conditions. Manage holiday and absence records and exception reporting for late attendance and unapproved overtime. Verified hours pass directly to payroll for pay and tax calculation.

overtime approval

Overtime is managed through a controlled approval workflow, requested, reviewed, and authorized in the Eyelit MES before hours are committed and passed to payroll.

From attendance to productivity gap — in one system

attendance

Who is on site, when they arrived, and when they left, captured automatically via door access or manual login.

paid hours

Hours worked recorded per operator, per shift. Basis for payroll export and the denominator in every productivity calculation.

productive hours

Direct, indirect, and unaccounted time all categorized in real time. The productivity gap calculated automatically against paid hours.

overtime Control

Overtime requests managed through an approval workflow. Authorized hours flow directly to payroll, no manual amendment.

capabilities

Module capabilities

separate labor & Asset Standard times

Most systems define standard times as a single value covering labor or asset hours, not both independently. Eyelit defines them separately, handling scenarios where one operator crews many machines, or many operators work a single large assembly. Labor and asset actuals are each calculated and reported on their own basis.

paid hours & attendance

Attendance tracked via door access integration or workstation book-on. Paid hours recorded per operator per shift based on configurable shift patterns and pay rules. Overtime managed through an approval workflow. Integrates with payroll for pay and tax calculation.

labor productivity analysis

Live dashboards expose utilization, performance, and quality from plant level to individual operator. Drill into any dimension, department, shift, team, work center, to identify where losses are occurring and take targeted action. Tracking labor productivity losses also gives valuable insight into machine idle time, providing a knock-on improvement to OEE.

labor loss categorization

Operators log reason codes in real time. Losses hidden in overhead buckets, waiting for materials, tooling delays, machine setup, become quantified, manageable line items that management can act on.

skills matrix & enforcement

Skills requirements defined per operation and enforced at book-on. Qualification records, proficiency grades, and expiry dates maintained per operator. Unqualified assignment blocked before work begins.

digital work instructions

Push SOPs, quality checklists, and best-practice guidance, including tips and how-to videos from experienced operators, directly to the workstation. New starters reach proficiency faster.

accurate actual labor cost

Actual labour times tracked per product, not per overhead bucket. Understand the true cost of labour at part number level, enabling accurate quotes, better sequencing, and defensible make-vs-buy decisions.

optimized labor scheduling

Live actuals feed directly into the Eyelit APS. Realistic labor constraints replace theoretical assumptions. Sub-minute replanning triggers automatically when shop floor conditions change.

why it matters

Labor visibility drives improvements far beyond headcount

What accurate labor tracking reveals
Once you measure labour properly, problems that were always there, but never quantified, become visible and fixable.

Planning & Material Problems

Under-utilized labor is rarely a people problem. It exposes scheduling gaps, late materials, or machine downtime that no one had connected to lost labor hours.

OEE Root Cause

Labor data adds the “why” to OEE. A machine logged as idle tells you nothing; an operator reason code tells you everything needed to fix it.

Labor Not Equal to Asset Time

Most systems conflate the two. The Eyelit MES tracks them separately, so a machine running for 8 hours crewed by one operator for 2 is costed and reported correctly on both dimensions.

Performance Culture

Sharing live productivity data with operators drives immediate improvement. Teams operating at 50% efficiency have reached 70–80% simply through visibility of their own performance.

Quote We’ve seen an instant improvement in productivity. Just by communicating individual and group productivity data with operators, we’ve seen people who were operating at 50% efficiency get up to 70–80%. — Rupert Pearson, Managing Director, Olicana Tubular Metal Products

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