When International Roadcheck pulls thousands of trucks off the road over three days, capacity can tighten fast. A carrier that confirmed a pickup on Monday may be unavailable by Wednesday. Yet the load still has to move, and the customer still expects a solution.

What determines the outcome is whether a team sees the problem with enough time to act or hears about it when the truck doesn’t show.

For many trucking and logistics teams, the answer often comes too late.

The problem often isn’t a lack of freight data. It’s that the data needed to manage a disruption — carrier capacity, appointment windows, detention clocks, truck locations — is scattered across transportation management system platforms, carrier portals, spreadsheets, an ERP screen, or an email only one person opened. Pulling it together can take hours the situation doesn’t allow.

This is one of the biggest gaps in transportation today. Teams are data-rich and insight-poor. They have more information than ever, but it is scattered and not always reliable when you need it. What’s missing is the connective layer that turns that information into timely, actionable decisions.

This isn’t a problem limited to one side of the transaction. Carriers managing capacity through a disruption such as Roadcheck are making decisions with the same fragmented picture. When both sides of a load are working from incomplete information, the gap between what’s expected and what actually happens widens quickly.

For shippers managing freight across multiple carriers and modes, that gap shows up as added cost, missed commitments, and decisions made too late to matter.

There’s a name for this problem: the data constraint. Until that data is connected, teams remain a step behind.

Why Fragmented Freight Data Leads to Firefighting

For too many freight teams, the week opens with an accounting of what went wrong over the weekend: shipments that slipped, detention and demurrage charges that accumulated while no one was watching, equipment out of position, and customer commitments now at risk.

The team spends the day chasing status updates, calling carriers, reconciling numbers that don’t match from one system to the next, and passing information along manually.

This is a structural problem. The teams are capable. But the systems they work in often don’t share information in real time, leaving them to react after the fact.

The work still gets done, but it depends on long hours, institutional knowledge, and constant follow-up. When a key person leaves, much of that knowledge can walk out the door as well, and rebuilding it can take months or longer.

The industry has spent heavily trying to change this. Freight operations have invested in transportation management systems, tracking tools, and carrier connections, but the investments have not ended the firefighting.

PwC's 2026 Digital Trends in Operations Survey found that 87% of operations and supply chain leaders said poor data quality had limited their ability to realize value from digital initiatives.

The tools may add more information without necessarily connecting it. A team can own a TMS, three carrier portals, and a stack of reports that don’t talk to each other and still struggle to say where a given load stands.

How Poor Freight Visibility Drives Up Costs

Fragmented data costs freight teams one charge at a time, across hundreds of shipments, often with no single failure to point to. An operation can accumulate significant detention, demurrage, and accessorial charges and only see the full impact when the invoices arrive.

In bulk and break-bulk freight, a single shipment may move by both truck and rail before reaching the customer, so the meter can be running in more than one place at once.

Detention is the version most trucking teams know: a truck held beyond its allotted free time at a facility, with charges adding up appointment by appointment. On the rail side, demurrage can run somewhere between $75 and $300 per railcar per day. A shipper moving 50 cars a month that loses a day on each can incur thousands of dollars in charges before anyone flags the problem.

The same fragmentation affects carrier relationships.

When a freight team can’t measure on-time performance, transit times, or late pickups with confidence, carrier conversations take place without solid evidence. It becomes harder to hold a partner to a commitment, resolve a dispute, or identify lanes that consistently underperform.

There is a market signal here as well. Freight that could move by either rail or truck has been shifting toward truck, and a 2025 Oliver Wyman shipper survey put rail’s share of that flexible freight at just 19% and falling. Shippers cited visibility, responsiveness, and demurrage among their concerns.

Where freight moves increasingly depends in part on which mode a team can effectively see and manage.

Connecting TMS and Freight Data for Better Visibility

The teams best positioned to stay ahead of disruption tend to have one thing in common: their data is connected well enough to surface problems while there is still time to act.

That connective layer — usually a multimodal TMS or a purpose-built integration — brings rail and truck status, carrier portals, and order and appointment data into one place. It reconciles that information into a common view and can trigger alerts when something needs attention.

When those systems feed into a single view instead of separate portals, tracking becomes operational visibility.

A lane where capacity is tightening can reveal which loads still depend on a single carrier, allowing a backup to be lined up before capacity disappears. A carrier account drifting below its rebate threshold can be identified while there is still time to correct it. A facility with chronic dwell becomes visible as a pattern, allowing scheduling or routing changes before the costs repeat.

The handful of loads with problems developing become easier to spot rather than remaining buried in systems someone has to search manually.

That’s exception management, and it is a meaningful step beyond firefighting. Teams can respond earlier, while they still have options.

Predictive capabilities go one step further by identifying early signals that build over hours or days and allowing teams to act before an exception develops at all. A temperature-sensitive load trending toward a delay, for example, could be flagged early enough to reroute it before the cargo or delivery is at risk.

That is where many teams want to be. Few are fully set up to get there yet.

From Real-Time Alerts to Predictive Freight Analytics

What does it take to move from spreadsheets to predictive freight analytics? The capability tends to build in stages, with each level depending on the one below it:

1. Spreadsheets, email, and knowledge carried in people’s heads
2. A core system of record for shipment execution
3. Consolidated reporting and carrier scorecards
4. Real-time alerts and threshold monitoring
5. Predictive insight and optimization that anticipates problems before they form

Those levels are difficult to skip. Put an advanced tool on top of an operation still working largely from spreadsheets and email, and it may not deliver much value because the data and processes it depends on are not yet in place.

The first step is getting a clear picture of where the operation stands today. A team whose network data remains scattered across systems may still be early on that curve, regardless of how sophisticated some of its individual tools are.

Knowing where the team stands points to the right next step — the capability the operation can build on now rather than simply the one that sounds most advanced.

Most trucking operations already have more data than they can use. The advantage over the next few years will go to teams that connect it well enough to act on it in time.

Connected, reliable freight data also provides the foundation for AI and predictive analytics. Without it, AI risks automating decisions based on the same fragmented information teams struggle with today.

For teams that are data-rich and insight-poor, the real opportunity is catching small problems early enough to keep them from becoming bigger ones.

About the Author: Brian Cupp is vice president of operations, enablement, and strategic initiatives at IntelliTrans, a transportation management system provider for bulk and break-bulk shippers. He has more than 25 years of experience with the company in operations, service delivery, carrier network management, rate procurement, fleet sizing, and logistics analytics.

This contributed guest article was authored and edited according to Heavy Duty Trucking’s editorial standards and style to provide useful information to our readers. Opinions expressed may not reflect those of HDT.