What Is Indirect Labor in a Warehouse

If you’ve ever stared at your UPH numbers thinking your team is crushing it, then looked at your total payroll and wondered where all the money went, indirect labor is almost certainly the answer. Most DC managers have a clear picture of their pick rates and pack throughput. Very few have an equally clear picture of what their workforce is doing the other 20–30% of the time they’re on the clock. That gap is where labor budgets quietly fall apart.

What Is Indirect Labor in a Warehouse, and Why Can’t You Ignore It?

Direct labor is straightforward: picking an order, receiving a pallet, packing a carton, loading a truck. These activities move product and generate measurable output. Indirect labor is everything else. Supervision, team huddles, safety training, equipment pre-checks, forklift charging and maintenance, cleaning, and any time a worker spends walking between assignments without being engaged in a direct task.

The distinction matters because most Labor Management Systems (LMS) measure productivity only against direct labor activities. If an associate spends 90 minutes of an 8-hour shift in indirect time and that time gets lumped into direct labor buckets, your productivity metrics look better than they actually are. You think you have a high-performing team. What you actually have is a measurement problem.

Here’s the operational reality: you can’t reduce what you’re not measuring accurately. A DC running 25% indirect labor when they believe they’re running 17% is making headcount decisions, staffing decisions, and budget decisions based on false data. The variance doesn’t show up in your pick rate dashboard. It shows up in your P&L at the end of the month when actual labor hours blow through the plan.

How Do You Calculate Indirect Labor Costs Separately from Direct Labor?

The calculation itself isn’t complicated. The hard part is getting clean input data, which requires your time-tracking infrastructure to actually differentiate between activity types.

Start with your LMS or WMS time clock records. Every major WMS supports indirect labor codes — predefined categories that workers clock into when they shift away from productive work. Common indirect codes include supervision, training, safety, equipment maintenance, cleaning, meetings, and idle/unassigned time. If your operation doesn’t have these codes configured and actively used, that’s the first problem to fix before any calculation is meaningful.

Once you have separated hours, the formula is simple:

Indirect labor cost = (Total indirect hours ÷ Total hours worked) × Total payroll

So if your DC logs 10,000 total labor hours in a week, 2,500 of which are coded as indirect, and your total weekly payroll is $280,000, your indirect labor cost is 25% of $280,000, or $70,000 for that week. Annualized, that’s $3.64 million in labor spend that produces no direct throughput output.

A more granular approach breaks indirect cost down by category, which is where the analysis becomes actionable. Here’s a sample framework:

The categories in the “Yes” column are where your reduction work happens. The categories that are partially or not controllable still need to be measured, because they set a floor below which your indirect percentage can’t realistically go.

What Activities Are Getting Misclassified as Direct Labor in Your Warehouse?

This is where most DC managers get it wrong, and the reason is almost never malicious. It’s usually a combination of poorly designed time codes, operator self-reporting bias, and cultural pressure to show strong pick rates.

You’d think the biggest classification problem is supervisors logging their time wrong. But in most operations I’ve seen, the real issue is front-line workers absorbing indirect minutes into surrounding direct task windows because nobody set up the codes to make it easy to do otherwise.

The most common misclassified activities across operations are:

• Travel time between pick zones: If workers are moving from one area of the building to another without scanning product, that’s indirect. Many WMS systems default to assigning travel time to the prior direct task, inflating the time-per-unit calculation.
• Label scanning and quality verification: A quick scan or visual check before putting product away is not picking. In high-SKU environments with tight FIFO requirements, this can quietly add 8–12 minutes per pallet and never gets coded separately — which means it never gets managed.
• Short breaks and personal time under 5 minutes: These rarely get logged. Workers don’t bother clocking into an indirect code for a 3-minute water break. They just pick up where they left off, and the dead time shows up as reduced direct productivity instead of legitimate indirect time.
• Equipment troubleshooting: When a conveyor jams or a scanner battery dies, the worker fixing it or waiting for it to be fixed is on indirect time. Frequently this gets absorbed into the surrounding direct task window.
• FIFO rotations and replenishment staging: In grocery and healthcare distribution especially, repositioning product for date compliance is nearly always direct-coded even though it produces no outbound throughput.

The pressure to show high UPH numbers drives self-reporting distortion. When workers know their performance is being evaluated against engineered standards for direct tasks, they have every incentive to keep clocking direct time even when they’re doing something indirect. Fix the code structure and remove that incentive by making indirect coding culturally normal and expected.

Why Is Your Indirect Labor Percentage Stuck at 20–30% When Industry Benchmark Is 15–18%?

The MHI industry data puts target indirect labor in the 15–18% range for well-run distribution operations. If you’re sitting at 22–28% and can’t seem to move it, the root causes usually fall into four buckets.

Excessive meeting load. Daily shift huddles, supervisor check-ins, weekly all-hands safety briefings — in aggregate, these can consume 30–45 minutes per worker per day across a large operation. That’s not a trivial number. A 300-person DC losing 35 minutes per person per day to meetings is giving up roughly 175 labor hours daily in indirect time. Every day.

Over-supervision ratios. Industry norms suggest one supervisor per 12–15 associates in active picking operations. Operations running at 1:8 or 1:9 are paying supervisor wages, often $55,000–$75,000 annually, for headcount that doesn’t generate throughput. That overhead is entirely indirect, and it compounds with management layers above it.

Inadequate cross-training. When volume shifts from one zone or department to another and workers can’t flex to follow the work, you get idle pockets of headcount waiting for assignments. Idle time is indirect time. Cross-training reduces it, but most operations under-invest because the training itself adds short-term indirect hours. It’s a false economy, and it’s one of the more frustrating patterns to watch play out in real time.

Equipment and slotting inefficiency. Slotting — the strategic placement of SKUs within a DC to minimize picker travel — directly affects how much time workers spend moving versus picking. Poor slotting forces longer travel paths, which drives up indirect travel time. This is one of the few indirect drivers that’s almost entirely within your control to fix without adding headcount.

A 5 percentage point improvement in indirect labor (moving from 23% to 18%) in a 200-person operation translates to roughly 10 full-time equivalents in annual payroll savings. At current warehouse wages, that’s $350,000–$500,000 per year, and that’s before you account for the 15–20% wage increases that have hit the industry since 2020.

Can You Lower Indirect Labor Without Cutting Headcount — And Should You?

Yes, and this is actually the more sustainable approach. Cutting indirect headcount directly — eliminating supervisors, reducing training staff — creates short-term budget relief and long-term operational degradation. In my experience, the operations that try to solve this by cutting people first are the same ones calling me six months later trying to figure out why their error rates spiked and their overtime costs doubled. I’ve watched too many DCs gut their training programs to hit a quarterly labor target and then spend twice as much on overtime and error correction shortly after.

The better path is identifying low-value indirect activities and either eliminating them or converting them into productive time:

• Consolidate daily meetings into a single structured 10-minute shift-start huddle. Use digital displays or mobile messaging for mid-shift updates instead of pulling people off the floor.
• Automate manual indirect tasks where possible. Automated label printing and application systems remove a full indirect category entirely.
• Redesign zone boundaries to reduce travel time. If your top-velocity SKUs are slotted in a way that forces pickers to travel the full length of the building multiple times per hour, that’s a layout problem, not a people problem.
• Use scheduling precision to eliminate wait-time indirect — workers clocking in before their assigned area has work to process are generating pure indirect time. Better labor planning, meaning you actually know when each work center needs labor and schedule arrivals accordingly, eliminates this category without a single headcount change.

Platforms like CognitOps take a different approach to this scheduling problem by forecasting labor needs across all DC activities continuously, rather than relying on static staffing models that create wave-start idle time. When you know precisely when volume is hitting each work center, you can schedule labor to match instead of defaulting to “everyone in at 6 AM.”

The trap to avoid: indirect labor isn’t inherently wasteful. Safety meetings exist because people get hurt when they don’t happen. Training exists because turnover, running at 35–50% annually in roughly 6 in 10 DCs, means you’re constantly onboarding new workers. Measure indirect by category and cut low-value activities, not necessary ones.

Honestly, there’s no clean answer on where to draw that line. What counts as “low-value” indirect depends heavily on your product mix, your workforce tenure, and how close you are to your engineered rate ceilings. A newer operation with high turnover has a legitimate reason to run higher training indirect than a mature one. Context matters.

Should You Track Indirect Labor with Standards or Time Studies?

Both methods have their place, and most DC managers use neither consistently. That’s the actual problem.

Engineered standards for indirect labor — preset indirect hour targets per 100 units processed, per shift, or per headcount — work well for budget forecasting and trend reporting. If your operation is stable and your indirect codes are consistently applied, you can set expected indirect rates by department and flag variances weekly without running a single time study. Fast, scalable, and sufficient for 80% of monitoring needs.

Time studies are more accurate and significantly more labor-intensive to conduct. They’re the right tool when your indirect percentage spikes unexpectedly, after you’ve made major process changes (new WMS go-live, layout redesign, new product lines), or when you’re trying to redesign an indirect-heavy workflow and need precise data to set new standards. Don’t use them as your primary tracking mechanism — the observation burden makes it unsustainable at scale.

According to the Bureau of Labor Statistics, industrial engineering and work measurement roles in distribution have grown alongside DC complexity, which reflects exactly this tension. As e-commerce has increased the number of distinct DC tasks by 3–4x since 2018, older set-it-and-forget-it standards have become increasingly inaccurate without regular validation.

So which should you use? Use standards for ongoing budget management and trend monitoring. Run time studies when your indirect costs spike, when you redesign processes, or roughly every 12–18 months as a calibration check. Neither method alone is enough.