Freight operations has a dirty secret: the numbers we report with confidence are often stitched together from partial truths.

ETAs that were never confirmed. Tender acceptance timestamps that don’t match what the carrier remembers. PODs that show up days late. Accessorials that land on an invoice with no photo, no geofence, no reference other than Trust us.

And then we wonder why our meetings turn into debates instead of decisions.

The data looks clean, but it isn’t

Most organizations don’t have a freight problem. We have a data lineage problem.

Here’s what’s broken, and why it keeps happening:

• Too many systems of record. The ERP has the cost view, the TMS has the plan view, the WMS has the execution view, and the carrier has the reality. None of them fully agree.
• Too many “soft” events. Arrived, loaded, departed, delivered, attempted. If those events aren’t captured the same way across carriers and facilities, they aren’t comparable.
• Too many manual touchpoints. Someone updates a load in the TMS after a phone call. Someone else keys detention into a spreadsheet. A third person disputes it with an email chain. The audit trail is weak by design.
• Documents are treated like attachments, not data. BOLs, rate confirmations, lumper receipts, PODs. We store them, but we don’t extract consistent fields and tie them to events.

The result is predictable: we spend hours reconciling what happened instead of preventing the next miss.

If you’ve ever had to argue whether a carrier was really checked in at 13:12 or 15:40, you’ve lived this.

Why it keeps happening in our industry

We’re operating in a world where variability is the norm, and our tech stack still assumes it’s the exception.

A few shifts are making the cracks wider:

• Accessorials are climbing because dwell time is climbing. Detention and layover don’t feel like edge cases anymore, especially in tight dock schedules and peak seasons. FMCSA’s 2020 detention and demurrage guidance pushed shippers and ocean stakeholders toward fairer practices, but it also increased scrutiny and disputes when proof is thin.
• Visibility expectations are higher than the data quality. Customers expect near real-time ETAs like they’re tracking a pizza. Meanwhile, many loads still rely on EDI 214s that arrive late, inconsistent carrier API updates, or driver check calls.
• More mode mixing means more handoffs. Intermodal plus drayage, cross-dock transfers, pool distribution, final-mile. Every handoff is a new chance to lose timestamps, documents, and accountability.
• Fraud and compliance pressure are real. Double brokering and identity issues have made many teams tighten onboarding and documentation. That’s necessary, but it adds steps and increases the cost of bad data.

And here’s the uncomfortable part: we often incentivize speed over accuracy. If the team’s goal is to close loads fast, invoices get paid before exceptions are fully validated. The errors don’t disappear. They just show up later as margin leakage.

The path forward is boring, and it works

We don’t fix this with another dashboard. We fix it by making events and documents defensible.

A practical path forward looks like this:

Decide what the truth is for each event

Pick 10-15 operational events that actually drive cost and service, then define them like you mean it.

Examples:

• Arrival at shipper: geofence ping within X meters OR gate timestamp OR signed check-in sheet
• Loaded: weight ticket or dock release timestamp OR driver app confirmation plus facility confirmation
• Detention start: appointment time plus grace period OR check-in timestamp, depending on contract
• Delivery: POD timestamp plus receiver signature OR photo with GPS and time

Then assign a hierarchy. If we have geofence plus driver app confirmation, that wins. If we don’t, fall back to EDI. If EDI is missing, fall back to manual, but flag it as low confidence.

This one change turns arguments into auditability.

Stop treating documents like dead PDFs

Every BOL, rate confirmation, POD, and accessorial receipt should be searchable and tied to the load in a structured way: reference numbers, dates, locations, quantities, and who approved what.

If we can’t answer these questions in under 60 seconds, we’re vulnerable:

• Which rate confirmation was the carrier paid against?
• Does the POD match the consignee name and delivery date we billed?
• Is the lumper receipt tied to the right stop and approved threshold?

Tools that use OCR and automation can help here. For example, Debales.ai can pull key fields from logistics documents and align them to load records so teams spend less time chasing paperwork and more time resolving exceptions.

Build exception workflows that match the way ops really runs

Most teams have plenty of data. What they lack is a clean path from signal to action.

Set up three lanes:

• Green lane: no missing docs, events match definitions, invoice auto-approves
• Yellow lane: minor gaps, route to a queue with a 24-48 hour SLA
• Red lane: high-risk exceptions like detention over threshold, accessorials without proof, POD mismatch, or rate confirmation discrepancies

You’d be surprised how quickly margin improves when 70-80 percent of loads flow through green without human touches.

What we can do this week (without a big IT project)

If you’re running a brokerage desk, a 3PL ops team, or a shipper transportation group, here are actions you can take in the next five days.

1) Audit the last 50 accessorials you paid

Pick detention, layover, lumper, TONU, and re-delivery.

Track:

• How many had a supporting document?
• How many had a timestamp trail?
• How many were approved by policy versus approved by habit?

If more than 20 percent are missing proof, you’ve found a real cost lever.

2) Standardize your detention language in rate confirmations

Detention disputes often start with vague terms.

Add specifics:

• Appointment time definition
• Grace period
• Required proof (check-in, check-out, signed timestamp, or geofence)
• Billing increment rules

Even tightening this on your top 10 lanes can cut back-and-forth emails fast.

3) Make carriers send one thing consistently

We ask carriers for five different updates across email, EDI, portals, and texts. Then we blame them for inconsistency.

Pick one standard channel per carrier tier:

• Strategic carriers: API or EDI with performance monitoring
• Mid-tier: driver app check calls through a single portal
• Spot: structured email template with required fields

The goal isn’t perfection. It’s reducing randomness.

4) Add a confidence score to ETAs

Not all ETAs are equal.

Label them:

• High confidence: live GPS plus recent movement
• Medium: last ping older than X hours or EDI only
• Low: manual entry or no updates

Then train customer service and sales to speak accordingly. A low-confidence ETA should trigger proactive outreach, not blind optimism.

5) Create one shared “stop profile” per facility

Facilities create most of our variability: check-in process, lumper rules, dock hours, restrooms, gate bottlenecks.

Build a simple stop profile in your TMS notes or shared knowledge base:

• Appointment rules
• Average dwell by day of week
• Detention proof requirements
• Contact info that actually works

When we reduce facility surprise, we reduce detention.

The shift that matters

We’ve spent years chasing visibility. The next competitive edge is credibility.

When our timestamps are defensible, our invoices are cleaner, our ETAs stop being fiction, and our teams get hours back every week. Not because we worked harder, but because we stopped arguing with ourselves.

If your freight data can’t stand up to a dispute, it’s not operational intelligence. It’s a story we tell until the invoice arrives.