A dispatch manager at a 3PL in Lawrenceville called us one Tuesday afternoon, ostensibly about adding two receiving associates. Halfway through the call she mentioned the facility was getting hit with a 4% carrier chargeback rate. We asked whether she had her on-time delivery rate in front of her. She didn't.
Those three things, the labor shortage, the chargebacks, and the OTD miss, were the same problem. A shortfall in receiving staff had pushed dock-to-stock out to 30-plus hours. Inventory positions were wrong because unconfirmed freight hadn't been put away and confirmed in the WMS. Orders were shipping against stale counts, some were short, some were late, and the carriers were billing back for it. She'd been managing three separate conversations when it was really one.
The core logistics KPIs for warehouse operations are on-time delivery rate (industry average 84–90%; world-class is 95%+), order pick accuracy (WERC DC Measures 2024 median: 99.30%), inventory accuracy (industry average 83%, per CAPS Research and ISM, March 2024), and labor cost as a percentage of revenue (28.59% average across 600+ warehousing operations, per The Fulfillment Advisor's 2024 survey). These four tell you whether product is moving on time, correctly, and without burning through labor budget.
Georgia warehousing is under unusual throughput pressure. The Port of Savannah processed 5.7 million TEUs in 2025, its second-busiest year on record, with 42 double-stack train departures weekly and average vessel-to-rail transfer times of 22 hours, down from 28 hours at the start of the year. That freight flows into distribution centers across Hall County, Conyers, Lawrenceville, and the Atlanta MSA. The operations managers receiving it are accountable for how fast it lands on shelves or ships back out.
U.S. business logistics costs hit $2.58 trillion in 2024, representing 8.8% of GDP, according to the CSCMP's 35th Annual State of Logistics Report, produced by Kearney and released June 2025. Getting it wrong inside the four walls has never been easier to measure, or harder to absorb.
On-Time Delivery and the Perfect Order Calculation
On-time delivery rate is the percentage of shipments that leave within the agreed window. In 2024, the industry average ran 84–90%. Organizations using advanced fulfillment platforms hit 95.4%. World-class is generally 95–98%+.
Those numbers look manageable until you run the perfect order calculation.
Perfect order rate is multiplicative, not additive. If your on-time delivery is 98%, your order accuracy is 90%, and your invoice accuracy is 95%, your combined perfect order rate is 0.98 × 0.90 × 0.95, which works out to about 84%. Every component compresses the result. APQC's Open Standards Benchmarking puts the industry average for perfect order rate at 85–90%, with world-class operations hitting 97–98%. Each percentage point below that reflects some combination of late shipments, wrong picks, short shipments, or billing errors, all generating rework cost inside your facility before they ever reach the customer.
The compounding math surprises most warehouse managers the first time they see it. A team proud of 98% OTD and 90% pick accuracy has a perfect order rate around 88% if invoice accuracy isn't clean. That's not a crisis, but it's the real number your customer is experiencing every week.
The Port of Savannah connection matters here: 3PLs and distribution centers receiving port freight directly work through demand that arrives in waves, not at a steady pace. Volume spikes around vessel arrivals don't accommodate staffing shortfalls. A short-staffed receiving dock means inbound freight isn't inducted promptly, inventory accuracy suffers, pick accuracy follows, and the perfect order rate is where all of it compounds.
Pick Accuracy and Inventory Accuracy
Pick accuracy is the percentage of orders filled without errors. The WERC DC Measures 2024 annual survey, covering more than 1,000 warehouse and distribution center operations, reported a median pick accuracy of 99.30%. Best-in-class operations run 99.5–99.9%. An accuracy rate below 99% means more than one error per 100 orders, which rolls into returns, reship labor, and customer credits faster than most managers expect.
More than 35% of warehouses run at 1% error rates or worse, according to industry survey data. At that level, errors aren't random events. They're a process signal: slot locations that haven't kept pace with inventory movement, labels that look similar at pick speed, or new operators still orienting to the floor.
Inventory accuracy is the upstream cause that pick accuracy reflects downstream. CAPS Research, the supply management research arm of the Institute for Supply Management, reported in March 2024 that the average inventory accuracy rate across surveyed companies was 83%. One in six SKU locations, on average, has either the wrong count or the wrong product. When a picker reaches that location, they either catch the discrepancy (which costs time) or don't (which costs more).
We run cycle counts at several warehouse accounts across Georgia, and the gap between WMS-stated inventory and physical count is almost always larger than the operations manager expected going in. It's not because the team is careless. Inventory accuracy degrades incrementally with every putaway shortcut, every receiving rush, every shift where a pallet lands outside its assigned location and gets confirmed to the wrong slot.
Inventory shrinkage compounds this further. WERC research flags anything above 0.46% as an alarm threshold, while the average shrinkage rate across 150 U.S. 3PLs surveyed by Red Stag Fulfillment in 2024 ran at 1.44%. These two numbers belong on the same dashboard because improving inventory accuracy requires labor-intensive cycle counting. That's a staffing and scheduling decision, not just a systems fix.
Labor Cost Per Order and Units Per Labor Hour
Labor cost as a percentage of revenue averaged 28.59% for U.S. warehousing operations in 2024, according to The Fulfillment Advisor's annual survey of more than 600 facilities. That's down from 31.70% in 2023. But average staff hourly wages rose from $15.78 to $16.95 during the same period, a 7.4% increase. The efficiency gain came from throughput improvement, not from paying people less.
As a share of total operating costs, labor runs closer to 45–57%. Extensiv's 4th Annual 3PL Warehouse Benchmark Report found that 53% of 3PLs report labor exceeding 40% of overall business costs.
For individual order economics: B2C pick-and-pack averaged $3.18 per order in 2024 and $3.20 in 2025. B2B pick and pack averaged $4.79 per order. Those are useful reference points when you're evaluating whether your cost per order is in line with operations of comparable size and product mix.
We used to report units per labor hour as the primary labor productivity metric for placed workers at our warehouse accounts. We still include it, but we've learned it tells an incomplete story on its own. A picker running 120 units per hour with a 1.5% error rate is generating more rework cost than a picker running 95 units per hour with a 0.2% error rate, once you account for returns, reships, and the labor required to correct mistakes. We now pair units per labor hour with pick accuracy on every account, because throughput at the cost of quality is a false efficiency.
If you're evaluating labor cost trends by shift, the denominator matters as much as the numerator. A shift where overtime is covering for absent associates will show a higher cost per order than a fully-staffed shift running at standard headcount, even if the absolute order volumes look similar.
Dock-to-Stock Time
Dock-to-stock is the time between a trailer arriving at your facility and its contents landing in a confirmed inventory location in your WMS. Best-in-class is 2–6 hours. The industry average for most warehouse types runs 6–12 hours. When dock-to-stock slides above 24 hours, it's a bottleneck signal, typically in receiving, labeling, or putaway, and it shows up in your inventory accuracy before it shows up in your OTD.
The Lawrenceville 3PL's chargeback problem traced back here. Dock-to-stock was running 30–36 hours on the days receiving was short-staffed. Inventory counts didn't reflect what was physically staged but not yet confirmed in the system. Picks went against stale counts. Some orders shipped short. The OTD miss followed, and the chargebacks followed that.
If you track dock-to-stock daily by shift, you'll usually catch this problem before it moves the OTD number. The pattern we see most often across Georgia accounts is that Monday is the worst day of the week. Freight that accumulated over the weekend comes in all at once, and staffing doesn't always anticipate it. A weekly review that checks dock-to-stock by day of week usually reveals a Monday pattern worth addressing in scheduling, not in a carrier dispute conversation three weeks later.
A Weekly Logistics KPI Framework
This is the review cadence we recommend to operations managers at Georgia warehouse and 3PL accounts. Set the dashboards once; the review itself doesn't need to take long.
Daily (shift-end, 5 minutes): Log any dock-to-stock times above 12 hours and note the cause. Count pick error tags or customer-facing discrepancies flagged that shift. Record attendance versus scheduled headcount in receiving and pick/pack.
Weekly (Monday review, 20 minutes): Calculate OTD for the prior week against your agreed threshold. Pull inventory accuracy from the most recent cycle count or perpetual inventory report. Check pick accuracy against your 99%+ target. Review cost per order and units per labor hour by shift, and flag any shift where overtime substituted for planned headcount.
Monthly (ops review, 45 minutes): Run the full perfect order calculation using your actual OTD, pick accuracy, and invoice accuracy. Trend labor cost as a percentage of revenue against the 28.59% industry average. Review dock-to-stock by day of week. For any associates placed in the prior 60 days, run a new-hire productivity curve: standard-hours actual versus standard at 30, 60, and 90 days in.
The monthly view is where floor-level numbers connect to financial results. If you're using a staffing partner to fill receiving or picking roles, that link needs to be explicit in your review. An agency that can't give you consistency on time-to-fill and first-30-day pick accuracy will show up in your logistics KPI dashboard before the conversation about staffing performance comes up.
For the broader KPI framework we use to evaluate staffing performance across our 27 Georgia accounts, including the 12 metrics we track with data tables from our own operations, the staffing KPI pillar guide covers each metric and what it predicts. For benchmark ranges specific to operations and warehouse management functions broken out by role, the operations KPI examples post has those. And for fill rate benchmarks specific to light industrial staffing in Georgia, the fill rate benchmarks post covers what we see across our accounts.
We staff warehousing, 3PL, recycling, and light industrial operations across 27 accounts in Lawrenceville, Conyers, Gainesville, Hall County, Smyrna, and the Atlanta MSA. If you're evaluating a Georgia staffing partner for warehouse and logistics roles and want to understand how we track pick accuracy and labor cost before and after placement, Schedule a Call and we'll walk through how we approach it.
