Labor Productivity and the Dreaded Timesheet

There is significant discussion in the manufacturing industry around overall equipment effectiveness and how digitization can improve performance. However, when it comes to overall labor effectiveness, the conversation is noticeably quieter.

Labor typically accounts for between 10% and 20% of total manufacturing costs. In more complex and assembly-based industries, the share can reach 25–35% or higher. It represents a major opportunity, but one that many manufacturers struggle to address.

Why Measuring Labor is so Difficult

One reason may be that labor effectiveness is difficult to measure accurately. Instead of quantifying real labor costs and performance, many manufacturers allocate overhead to labor because it is simply too complex to track in detail.

When labor measurement is attempted, it often takes the form of the dreaded timesheet. Almost everyone in manufacturing has encountered it. A shopfloor operator may be asked to manually record their activities alongside their normal work. In reality, production always takes priority, and timesheets are completed at the end of a shift, often from memory. On the other side, a process engineer or production manager may request timesheets to better understand output or validate cost variances, knowing they may be returned incomplete or illegible. The data then must be manually entered into spreadsheets before it can be analyzed, adding more effort without necessarily improving accuracy.

Some Manufacturing Execution Systems (MES) have replaced paper with digital timesheets. While this reduces paperwork, it does not fully solve the problem. Manufacturing labor productivity is multi-dimensional and far more complex than simple time tracking.

Why Simple Time Tracking Falls Short

Basically, manufacturing environments rarely operate in neat, isolated blocks of work. Teams may work collectively on the same job but start and finish at different times. Operators may move between tasks during a run. A single operation may span multiple shifts with different teams involved. One operator may oversee several machines simultaneously, or individuals may move between teams from day to day, depending on workload. These realities make simple time allocation insufficient for understanding true labor performance.

When labor productivity is measured in a way that reflects how work happens, it can reveal insights that extend beyond labor itself.

A Real-World Example: The “Waiting for Crane” Problem

Let’s use an example to explain this better. Think of a large machining facility. After implementing MES with a focus on manufacturing labor productivity, the organization quickly identified a significant loss category repeatedly reported by operators: “Waiting for crane.” The facility relied on a crane to move parts between machines, and in a large site footprint, coordinating crane availability was challenging. Operators regularly experienced delays, but the issue had long been accepted as part of daily operations.

Once labor utilization was tracked properly, the scale and cost of this delay became visible. What had been seen as a routine inconvenience turned out to represent a substantial productivity loss across the entire site.

With clear data available, the problem became easier to address. Live dashboards were installed in the crane driver’s office, and text alerts from shopfloor workstations improved coordination. The result was a dramatic reduction in crane-related delays, almost eliminating the loss entirely. In solving the labor issue, the facility also improved asset utilization and overall flow.

What Labor Visibility Really Reveals

This example illustrates a broader point. When labor is properly measured and understood, it often highlights planning gaps, process inefficiencies, or material flow issues that would otherwise remain hidden. Underutilized labor may signal upstream supply problems. Idle machines may be linked to labor constraints rather than equipment faults. More accurate visibility of labor costs can also improve product costing and margin analysis. Therefore, when both labor and machine constraints are clearly defined, production plans become more realistic and achievable.

Addressing the Human Side of Labor Tracking

There is sometimes concern that detailed labor tracking may feel intrusive or create resistance among operators. In practice, the opposite is often true. Most operators take pride in their work and appreciate systems that make their jobs easier. Clear instructions, reduced manual paperwork, and the ability to surface recurring frustrations can improve both morale and performance. When daily obstacles are finally visible and addressed, it reinforces the value of measuring the right things.

Manufacturing labor productivity may be harder to quantify than equipment effectiveness, but as the machining facility discovered, it can uncover some of the most impactful opportunities for improvement across the plant.