For years, visibility brought reassurance to freight operations. If a team could open a system and see where the shipment was located, they could answer the customer, inform the warehouse, and feel confident that execution was on track. In a more predictable supply chain environment, that level of transparency created real value. A tracking update signaled control. A status notification implied stability.
That definition of visibility no longer holds up.
Freight now moves through a network defined by congestion, labor variability, weather disruption, geopolitical shifts, capacity swings, and rising cargo risk. Under those conditions, knowing where a shipment is does not automatically tell you whether it is safe, on time, or aligned with the original plan. As Mark Baxa explains, “It was really location alone. It wasn’t actionable. It wasn't enough.” The industry has reached a point where visibility must evolve beyond location and into interpretation.
Traditional freight visibility relies heavily on milestones. A pickup confirmation, a departure scan, an arrival notice. Those data points are useful, but they describe events that have already occurred. They do not predict what will happen next. Baxa captures this limitation directly: “Milestones are more of a rearview mirror. Look what happened.”
Rearview information supports reporting and accountability. It does not prevent disruption. In an environment where customer tolerance for surprises has collapsed and expectations for proactive communication have risen, organizations need more than historical confirmation. They need signals that allow intervention before service failure becomes inevitable.
That shift changes the role of data. Instead of simply confirming movement, freight data must surface warning patterns. Baxa describes the new operational standard clearly: “Modern operations now really need to focus more on warning signals… so you can intervene while there's still time to do that.” This is the transition from tracking to anticipation. Visibility becomes meaningful when it informs action.
The difference between first generation visibility and modern freight intelligence lies in interpretation. A shipment may appear normal inside a tracking system while quietly trending toward delay or risk. That distinction matters.
Baxa frames it succinctly: “Seeing freight and then interpreting freight behavior are different things. One is at present and one is more prediction.” Present tense visibility answers what is happening. Predictive visibility answers what is likely to happen. When organizations analyze shipment patterns across lanes, carriers, facilities, and regions, they begin to identify signals that extend beyond individual loads. Dwell time anomalies, route deviation trends, congestion patterns, and carrier reliability metrics become indicators of future performance.
The practical result is fewer surprises. Instead of reacting to missed pickups or late arrivals, teams can intervene earlier. Instead of explaining what went wrong, they can redirect before disruption materializes.
As expectations rise, the Transportation Management System has expanded in responsibility. It can no longer function solely as a transactional system that records routing decisions and stores shipment history. It must become a platform that evaluates whether the plan remains viable as conditions change.
Baxa notes that “TMS platforms… have obviously become much more robust and perhaps all encompassing… versus what they were, say, five years ago.” That evolution reflects a deeper need. Companies are measured not only in cost efficiency but also in reliability, responsiveness, and customer experience. A system that sets expectations is not enough. It must also measure whether those expectations remain achievable.
This is why early awareness carries so much weight. Baxa articulates the operational imperative clearly: “We'd much rather know that it's not going to be there before we hit our promise date.” The moment a promise date is missed, options narrow and costs rise. Premium freight, service credits, production disruptions, and strained relationships follow. Intelligent systems aim to preserve flexibility by surfacing risk earlier, while alternative actions are still available.
One of the most dangerous aspects of freight execution is that risk often presents itself quietly. A shipment may show minor pauses or routing adjustments that appear routine. Without context, those updates can be misinterpreted as harmless. With context, they can signal serious operational exposure.
Baxa illustrates this dynamic with a scenario that resonates across industries. “The TMS tells you that there's a pause and rerouting is in process. You don't know what that is… and all of a sudden… it's on the rail… and it was needed tomorrow. It's now going to be there in five days.” The issue is not simply the change in transit time. It is the disconnect between the shipment’s operational importance and the modified execution plan.
Risk extends beyond timing. Security and integrity demand similar vigilance. Baxa warns that “Somebody's keeping an eye on your freight that shouldn't be… and it's stolen.” Theft and fraud rarely begin with dramatic alerts. They often begin with subtle anomalies that only become visible when systems are designed to detect patterns, not just events.
Modern visibility must therefore connect data to context. It must understand what a shipment requires, how it is behaving, and whether surrounding conditions introduce new exposure.
As freight systems grow more sophisticated, artificial intelligence naturally becomes part of the conversation. AI excels at processing large volumes of data, identifying patterns across thousands of shipments, and flagging anomalies faster than manual review ever could. Yet its effectiveness depends entirely on human understanding.
Baxa emphasizes the foundational requirement: “You must know and understand how supply chains work and the functions that enable supply chains to exist.” Without domain expertise, AI output lacks meaningful validation. With expertise, it becomes a powerful extension of human capability.
Decisional accountability remains human. Baxa is clear on this point: “The human mind makes those decisions… not a machine.” Technology can surface options and recommendations, but supply chain leaders must weigh contractual obligations, regulatory constraints, customer priorities, and financial risk before acting. The organizations that gain advantage will be those that combine intelligent systems with well-developed operational judgment.
Despite widespread agreement that freight must become more predictive, adoption is not automatic. Organizations operate under budget constraints, competing priorities, and varying appetites for risk. Baxa describes the practical reality: “What might be holding back progress… there's a limited amount of cash… People are trying to figure out their true cost position.”
In that environment, intelligent freight initiatives must be tied to clear business impact. Technology for its own sake will not sustain executive support. Baxa advises leaders to identify where value will be most meaningful. “You got to figure out… where you're going to make the most meaning. What's the So, what factor.” Whether the priority is preventing line down risk, reducing premium freight, mitigating theft exposure, or improving customer retention, the starting point must be clarity around outcomes.
When intelligent visibility is applied to the most consequential gaps in the operation, it transitions from a technology investment to a strategic advantage.
At its core, intelligent freight is not about dashboards or automation for its own sake. It is about uncovering insight that would otherwise remain hidden and acting on it in time to protect service and performance.
Baxa defines it in a way that captures both its technical and human dimensions. “It means the ability to see where the naked eye of the human can't see… truly helping us uncover what we cannot see, for the benefit of making better decisions.” That definition moves visibility beyond status and into foresight. It reframes freight management as a discipline grounded in anticipation rather than reaction.
Visibility was a breakthrough. Intelligence is now the expectation.
The transition from visibility to intelligent freight is reshaping how Shippers and 3PLs think about execution, technology, and risk. To explore these themes further, Banyan Technology launched a dedicated Intelligent Freight mini-series on its Tire Tracks podcast.
The series examines how freight data evolves from passive reporting into proactive signal detection. Episodes feature industry leaders discussing predictive analytics, behavioral shipment modeling, AI driven decision support, fraud prevention, and the expanding role of the TMS inside connected freight ecosystems.
Rather than focusing on abstract innovation, the discussions center on practical application. Listeners gain insight into how organizations are strengthening decision support, identifying operational risk earlier, and building more resilient freight strategies in a volatile environment.
Listen to the latest episode and subscribe to the Intelligent Freight mini-series.
Stay tuned for upcoming conversations covering predictive visibility, cargo risk management, AI enabled execution, and the future of intelligent freight operations across the supply chain.