Aerospace shop floors don’t really lack people to do the work, they lack visibility into the work that needs doing. To date, time and attendance data is used to estimate labor needs and track performance. Imagine if labor requirements were exactly defined by the work to be done.
1\. Capture time where the work happens, not where the door is
Badge swipes only indicate that someone was there at 6 a.m. and left at 2:30 p.m. They do not tell you what that person worked on, how long it took, or whether half the shift was devoted to material handling rather than direct labor. That is the hole through which labor utilization rate calculations crumble, because they are taking a proxy for productive time and dividing it by a number for which you do not and cannot actually measure reality.
Point-of-engagement time capture alone can save you from this conundrum, because you need only log those hours that relate directly to a work order and operation. Start a task on operation 10 of work order 12345? You are assigned to that part number as of the moment you log in for that task, whether it is a rush job or not. If the auditor wants to be able to trace labor back to part numbers on a rush job, you can help him out after the fact.
2\. Split direct labor from indirect labor before you try to fix either
Utilization improves when you can see the difference between touch time and everything else eating into a shift, setup, inspection, rework, and moving material between stations. Lump it all together and every improvement conversation turns into guesswork.
This is where a lot of manual tracking systems quietly fail. A supervisor logging hours on a spreadsheet at the end of the day isn’t going to reconstruct that an operator spent forty minutes waiting on a fixture and twenty minutes on actual value-added work. Workforce management platforms like AutoTime capture that breakdown automatically at the point of engagement, so indirect time gets coded separately from direct touch labor without anyone having to remember or estimate it after the fact. Once that split exists, you can actually see whether your utilization problem is a scheduling issue, a tooling issue, or a training issue – three very different fixes that all look identical on a generic time report.
3\. Put a real-time labor dashboard in front of team leads, not just managers
Data on utilization that is available in a report only after three days of the shift has ended is not useful for that particular shift. The benefit of collecting shop floor data is acting on it when operators are still at their workstations.
For example, a team lead who can, in real time, notice that one operator is idle while another work center is backed up, can move that labor before the bottleneck costs an hour instead of ten minutes. This is especially true in high-mix, low-volume production, where the next job on the schedule might need a completely different setup and skill set than the last one. Real time location systems and floor dashboards give leads the same kind of situational awareness that a dispatcher has over a fleet. Without this, reallocation must happen reactively, usually after a supervisor walks the floor and notices a problem that’s been sitting there for half a shift.
4\. Tie your skill matrix directly into scheduling
Aerospace work isn’t interchangeable labor. An operator without the right certification can’t legally touch certain operations, and putting someone unqualified on a job creates both a compliance risk and a training record gap that will surface in an audit.
The solution is to directly connect the skill matrix to planning and reallocating tools, so that the system provides only qualified operators when a particular job requires a work center. This will solve two problems at the same time: nobody gets a job assignment without the right certification, and the team leads don’t need to spend their time checking across the spreadsheet all certificates before reassigning work. Cross-training programs also become more useful because you can see in real time where certification is scarce and bottlenecking, compared to guessing at your training priorities at the end of every year.
5\. Compare actual hours to standard hours, then feed it back into your estimates
Checking actual labor hours against standard labor hours is important to understand where the problem lies. For example, if actual captured hours are consistently greater than standard hours for a specific operation, then there’s a problem; it could be due to the standard being incorrect, tooling degradation, or a necessary process change for that operation. If this discrepancy is not addressed, it will impact the accuracy of every quote on future jobs using the same routing.
This is, perhaps, one of the most underrated components of good labor management. Productivity improvements in labor of 30-50% are common once operation digitalization occurs. And while rewards will go to the early winners for the big shiny breakthroughs, there’s a slow, steady stream of upside available to nearly anyone from all the companies that aren’t today checking actual labor hours against standard labor hours on a work order right now.
It doesn’t require any bond-breaking technology investment to capture that value. You’ve already got most of the tech you need installed on the factory floor – you just need to point that effort at a different problem. Get this interaction right, and the obvious hidden factory answers don’t hide behind the budget conversation; they’re there on the time card, telling you when you’re busier and less busy than you know you should be.
