Your 3PL claims 99.9% fulfillment accuracy. But here’s what they’re not telling you: they’re mostly counting errors that get reported - customer complaints, obvious returns, maybe their own QA catches. The mispicks that slip through? Those don’t make it into their metrics.

A mispick is when your 3PL ships the wrong item. Customer ordered SKU-A but got SKU-B in the box. Most of these go unreported. Customer gets a $50 item instead of their $30 order? They’re not calling you. That error vanishes into thin air. Meanwhile, you’re eating the cost difference and your inventory counts are screwed.

Here’s how to catch those silent mispicks using data you already have.

The Weight Discrepancy Signal

Every time UPS or FedEx scans your package, they log its actual weight and dimensions. When that doesn’t match what your system says should have shipped, you’ve probably got a mispick.

Example: Your WMS says Order #12345 contains SKU-A (ships at 5 lbs). UPS bills you for 15 lbs. Unless your packer stuffed 10 pounds of bubble wrap in there, you’ve got the wrong item in that box.

This works because:

Carriers measure every single package (they need to bill you)
Weight variances of 2+ pounds are rarely packaging differences
The data already exists in your carrier portal

How to Actually Pull This Data

Step 1: Get Your Carrier Discrepancy Reports

UPS:

Log into ups.com → Billing → Invoice Download
Look for “Weight and Dimension Corrections”
Export as CSV (includes tracking number, billed weight, actual weight)

FedEx:

FedEx Billing Online → Reports → Weight Exceptions
Download the “Package Level Detail” report
Shows original vs. corrected weight for each tracking number

Heads up: These reports typically lag 3-7 days behind shipping date.

Step 2: Match Against Your Expected Weights

Pull your shipment data with these fields:

Order number
Tracking number
SKU(s) shipped
Expected package weight

Now compare:

If carrier weight > expected weight by 2+ lbs: possible wrong item
If carrier weight < expected weight by 2+ lbs: possible missing item
Weight matches but customer complained: possible wrong variant (same weight, different color/size)

Step 3: Calculate Your Real Accuracy Rate

Here’s the formula that actually matters:

True Accuracy = 1 - ((Weight Discrepancies + Customer Complaints) / Total Paid Shipments)

Not the fantasy number your 3PL reports.

The ERP Double-Check

Want even better data? Cross-reference with “no cost orders” in your ERP.

When customers report wrong items, most systems create replacement orders flagged as $0.00. These are confirmed mispicks. Combine them with weight discrepancies to get:

Reported errors: No-cost orders in ERP
Unreported errors: Weight mismatches with no complaint

Together, these paint the real picture.

Red Flags in Your Data

Watch for these patterns:

SKU confusion: Same product, different sizes consistently swapped (Small shirts shipped as Medium)

Weight difference might be minimal
Check dimension corrections too

Warehouse location issues: Errors cluster around specific SKUs

Usually means bins are mislabeled or too close together
Your heaviest SKUs getting mixed with light ones

Time-based spikes: Accuracy tanks during peak hours

3PM-5PM errors mean rushed end-of-day picks
Monday errors mean weekend inventory movements weren’t updated

Turning This Into Leverage

With real accuracy data, you can:

1. Enforce SLA Penalties

Some 3PL contracts include penalties like 1% invoice reduction per 0.1% below target accuracy. For example, if you’re at 98.7% against a 99.9% target:

1.2% below target
12 × 0.1% increments
12% invoice reduction

Having carrier data makes this defensible. Not your word against theirs.

2. Demand Process Improvements

Show them exactly which SKUs cause problems. Push for:

Barcode scanning at pick AND pack
Weight verification before shipping
Pick-to-light systems for high-error SKUs

3. Know When to Switch 3PLs

If accuracy stays below 99% after showing them the data, you’ve got a 3PL that either can’t or won’t improve. Time to find one that doesn’t suck.

The Manual Version (What Most Brands Do Now)

Export carrier weight corrections (weekly)
Export order/shipment data from WMS
VLOOKUP tracking numbers to match weights
Flag variances over 2 lbs
Send CSV to 3PL
Argue about each line item
Maybe get a credit

This works but it’s painful. Most ops teams give up after a month.

Automating This Mess

The smart play is piping this data automatically:

Carrier API → weight/dimension data
WMS/OMS API → expected weights by SKU
Match on tracking number
Flag discrepancies over threshold
Daily/weekly error reports

That’s where 3PL Pulse helps - we pull carrier weight data directly from APIs, plus we grab tracking events from Shopify to match everything up automatically. No CSV exports, no VLOOKUP hell. We even catch the cases where tracking numbers get reused or orders ship in multiple packages. But honestly, even the manual version beats flying blind.

Bottom Line

Your 3PL’s self-reported accuracy is fantasy. Carrier weight data is reality.

Start pulling those weight correction reports. Match them against your shipments. Calculate your real accuracy rate. Then use that data to either fix your current 3PL or find one that doesn’t suck.

Your customers might not complain about mispicks, but your carriers never lie about weight.

Got a clever way to catch 3PL errors? Drop us a note at hello [at] 3plpulse.com

The Carrier Weight Hack That Catches 3PL Mispicks