Does Your Carrier's Data Have a Conflict of Interest?

If a pitcher got to call the strike zone, every borderline pitch would somehow catch the corner.

Freight has built a surprisingly similar system around carrier data.

The carrier tells you where the truck is, whether it's late, what temperature the trailer held, and whether anything unusual happened in transit. Then your team uses that same information to judge the carrier's performance, protect a six-figure load, answer a customer, or decide whether a pharmaceutical shipment is still viable.

That should make you uncomfortable.

Not because carriers are sitting in the cab inventing temperatures. The problem is more basic than that. You're asking one party to both perform the work and provide much of the evidence used to prove the work was done correctly.

When the shipment is frozen food, biologics, electronics, or precious metals, that's quite a lot of trust to place in somebody else's version of events.

To clarify, we're not saying that carrier data is useless. Quite the contrary, actually. It just shouldn't be the referee, the replay booth, and the official record.

Who's Keeping Score on Your Carrier?

Usually, your carrier is.

They report the arrival time, that timestamp becomes an on-time percentage, and a few weeks later 96.4% lands in the QBR deck looking wonderfully scientific. Rarely does anybody stop to ask where the original number came from.

Your customers aren't nearly that trusting. Walmart uses its own clock, and a missed window can mean a 3% COGS charge. Across deductions, the average supplier gives back about 5.8% of invoice value. Your customer grades you with independent data while you're grading the carrier using carrier data.

Detention makes the contradiction even harder to ignore. ATRI found it at 39.3% of stops, and carriers increasingly arrive with timestamped dwell records while shippers are reconstructing the afternoon from a clipboard.

Visibility platforms recognize the problem, too. Some now grade data availability separately from data quality, because receiving a feed and knowing what happened aren't the same thing. That's exactly where visibility programs start losing their value.

Where Do Excursions Mostly Happen?

Often where one set of hands gives the shipment to another.

Your product can spend hours in a tightly controlled cold room, then lose that protection during a transfer nobody thinks twice about. A pallet sits on the ramp at a transit hub while ground crews sort out custody, paperwork, or the next move. Researchers have found that this ground-transfer window can be riskier than the flight itself, and air cargo operators in fact have coined it "the tarmac problem."

The even rougher part is that your data can go quiet at exactly the same moment.

EDI 214 tells you that something happened. It doesn't tell you what the shipment endured between those events, and one carrier's visibility often ends when custody changes. So 90 minutes on hot asphalt can disappear into a perfectly innocent-looking gap between "departed" and "arrived."

That helps explain why temperature excursions so often begin around handoffs, especially on multimodal shipments, and why pharma still loses roughly $35 billion a year to cold-chain failures. The riskiest part of the trip is often the same part your carrier data sees least clearly.

What Does a "Where's My Truck" Call Really Cost?

Start with the obvious answer: somebody's time.

Every "where's my truck?" call is a visibility system admitting it didn't get there first. The carrier update didn't arrive, the portal is stale, or nobody knows whether that 4:00 p.m. status is really a 9:00 a.m. scan. So a person starts chasing the load instead.

Multiply that across a network, and it gets expensive quickly. You're paying operations to call carriers, customer service to relay the answer, and managers to clean up whatever happened while everyone was waiting. Detention runs on the same lousy information loop: 94.5% of carriers bill for it, while fewer than half get paid.

The bigger hit comes from finding out too late. A delay discovered at the dock can become an OTIF failure: catch it three hours earlier, and you may still have time to move the appointment.

That's the practical value of ending load chasing: the alert comes to you while there's still something you can do about it.

Whose Data Wins When You File a Freight Claim?

The record with the fewest holes.

Carmack gives shippers a path to recovery, but it doesn't give you a free pass. You still have to prove the freight was in good condition at pickup, damaged at delivery, and worth what you're claiming before the carrier has to start defending itself.

Sounds straightforward until the damage is concealed. Now the carrier can say it happened after delivery, and even shock or tilt indicators can get waved off as normal road movement. Suddenly, everybody has a version of events, and you wind up trying to reconstruct Tuesday from paperwork.

Cargo theft is even less forgiving. Verisk CargoNet recorded 677 incidents and $304.6 million in losses in Q2 2026. When the insurer asks where the load was, who had custody, or when the seal broke, "this is what the carrier sent us" doesn't carry much weight.

A seal that reports tampering itself gives you your own record. In a claims fight, that difference can be the whole ballgame.

Why Can't You Automate on Data You Can't Verify?

Because automation turns bad information into action.

Real-time shipment visibility has a natural progression: track the load, flag the problem, decide what to do, then automate the response. The trouble starts when those decisions still depend on carrier check-ins, manually entered milestones, or location data that went stale somewhere along the way. 

After all, nobody wants to reroute a shipment or book emergency cold storage because a third-party status said something happened five hours ago.

Once teams get burned by unreliable data a few times, they get cautious. Alerts get double-checked, exceptions get chased down manually, and automation stops at the exact point where it should be saving time.

That problem gets even bigger once AI starts making decisions. Gartner's 2026 trends put provenance and decision governance alongside agentic AI for good reason. An agent can move faster than your team, but it can't magically tell whether a carrier-reported milestone deserves to be trusted.

Reliable observability has to come before automation. Otherwise, you've taken the same questionable input and taught software to act on it faster.

So What Can You Do About It?

Give yourself a second witness.

Carrier data still has value, but it shouldn't be the only record you have when a load runs late, warms up, gets opened, or disappears between handoffs. Tive puts the real-time tracking device on the freight itself, so location and condition keep reporting even when the truck changes, custody changes, or somebody else's feed goes dark.

That changes what visibility can actually do for you. You can catch a temperature excursion while there's still time to save the product, escalate an exception through Tive's optional 24/7 monitoring team should you need their assistance, and walk into a claim with a timestamped record that didn't come from the carrier you're filing against.

See why shippers switch to Tive, how it works across the cold chain, and what that looks like in your industry.

Better yet, test it. Put Tive on the lane you trust least and compare the device record with the carrier feed for 30 days. Then run the ROI on what you find.