Connect with us

Non classé

The State of Transportation Systems: TMS Lessons from 2025

Published

on

The State Of Transportation Systems: Tms Lessons From 2025

Transportation management underwent steady but meaningful change in 2025. While dramatic innovation was limited, organizations made progress in modernization, connectivity, and decision support. The theme of the year was not transformation. It was alignment—aligning TMS capabilities with the realities of volatile markets, cost pressure, emissions requirements, and customer expectations for more reliable service.

As companies look toward 2026, the lessons of 2025 offer a clearer picture of how TMS platforms are evolving, where value is being created, and what operational constraints continue to limit performance.

Modernization Accelerated and Became More Practical

Organizations continued to migrate from legacy, on-premise systems toward cloud-native platforms. But 2025 marked a shift: modernization was not pursued for its own sake. Instead, companies moved strategically, often focusing modernization efforts on the most constrained, high-visibility transportation processes.

The winning modernization projects delivered:

Cleaner API connectivity for rates, tenders, and tracking

Modular configurations that avoided monolithic system redesign

Reduced onboarding time for carriers and brokers

Better data freshness across execution and visibility systems

Instead of implementing everything at once, most enterprises adopted incremental modernization—starting with visibility integration, rate automation, or fleet scheduling—and expanding gradually.

In 2026, modernization efforts will continue to focus on practical outcomes like reducing manual load, accelerating tender cycles, and improving ETA reliability rather than chasing sweeping transformations.

Continuous Insights Replaced Periodic Reporting

One of the most notable changes was the widespread adoption of continuous, event-driven transportation monitoring. Companies moved away from static weekly performance reviews toward ongoing visibility into network conditions.

The shift was driven by:

the rise of real-time visibility platforms

better quality location data

improved ETA prediction

more reliable carrier status updates

API-fed telemetry replacing batch uploads

Rather than planning once and reacting later, transportation teams used near-real-time insights to:

reroute shipments

adjust pickup windows

realign labor at docks

escalate exceptions before they reached the customer

This “continuous planning” model reduced the latency between data, interpretation, and action.

In 2026, continuous insights will become standard. Static reporting will remain important for strategic planning, but day-to-day operations will revolve around dynamic decision cycles supported by live data.

AI Provided Targeted, Not Transformational, Wins

AI added value in transportation, but only in narrow, well-defined workflows. The strongest results came from AI’s ability to help evaluate alternates and reduce manual decision time.

Routing and Contingency Recommendations

AI helped planners identify viable alternates during:

weather disruptions

port congestion

driver shortages

regional bottlenecks

sudden capacity changes

These recommendations did not replace planning expertise. They accelerated it. AI functioned as a scenario generator—offering options that humans could refine.

Load Matching and Asset Utilization

AI improved load matching for private and dedicated fleets by analyzing:

empty miles

driver hours

backhaul opportunities

dock availability

These gains helped companies squeeze more productivity from constrained assets.

Exception Prioritization

AI helped reduce noise in exception handling by:

filtering out low-impact alerts

grouping related exceptions

identifying root causes

recommending the best corrective action

In 2026, AI will integrate more deeply into TMS workflows, but its role will remain decision support—not autonomy.

API Integration Emerged as a Competitive Advantage

EDI still dominates transportation, but it showed clear limitations in 2025. Delays in status updates, inconsistent message quality, and slow onboarding pushed companies toward API-first connectivity.

Carriers with strong APIs gained share in:

live tracking

instant rate shopping

automated tender acceptance

more granular status updates

lane-specific performance scoring

Shippers discovered that API-enabled carriers delivered faster, more accurate insights and fewer manual interventions.

In 2026, the shift will continue. EDI will remain for large carriers and structured freight networks, but APIs will power high-volume, time-sensitive, and cross-border operations.

Carbon-Aware Planning Began Its Move Into Execution

Sustainability efforts shifted from reporting to operational decision-making. Transportation teams began using emissions as a planning variable.

Companies applied emissions scoring to:

mode selection

carrier procurement

consolidation decisions

routing choices

lane prioritization

Some organizations used TMS enhancements to compare emissions intensity between alternates during routing decisions.

Early adopters discovered that carbon efficiency often aligned with cost and reliability. Efficient lanes tended to be:

better utilized

more predictable

more consistent in transit times

In 2026, carbon-aware routing will expand as regulators tighten expectations and customer requirements evolve.

Planning Cycles Compressed Under Persistent Volatility

Transportation volatility—capacity swings, geopolitical shifts, weather disruptions, and rising energy costs—forced companies to shorten planning cycles.

Teams moved from:

quarterly → monthly carrier scorecards

weekly → daily lane performance checks

static → rolling forecasts

annual → quarterly bid refreshes for variable lanes

This shift required better tools, better data, and better coordination across planning, procurement, and execution.

In 2026, planning cadence will continue to compress as continuous planning becomes the norm.

Visibility Data Became More Actionable

Visibility tools matured in 2025. The strongest improvements included:

more accurate ETAs

simplified exception categories

more reliable location data

better integrations with telematics providers

higher consistency in stop-level information

Companies used this improved data to:

reduce detention

schedule labor more accurately

improve dock turn times

respond earlier to late pickups or missed connections

In 2026, visibility platforms will integrate deeper with TMS systems so planners can adjust execution directly from the exception screen.

Key Constraints That Persisted

Despite progress, several structural issues remained unresolved:

carrier fragmentation

inconsistent small-carrier data quality

limited multimodal synchronization

slow customs processes in certain regions

capacity uncertainty tied to extreme weather

energy price volatility

Technology softened these constraints but did not eliminate them.

What 2026 Will Require

Companies that want to improve transportation performance in 2026 will need to:

strengthen integration discipline

adopt real-time carrier connectivity

incorporate emissions and energy variables

improve scenario modeling

refine carrier scorecards

build continuous planning behaviors

embed AI into exception and routing workflows

The organizations that succeed will treat the TMS as an active operations platform, not a passive system of record.

Final Takeaway

TMS evolution in 2025 was steady and practical. The systems that delivered the most value improved connectivity, reduced latency, and made planning more responsive. In 2026, transportation management will center on real-time coordination, AI-assisted decisions, and cleaner integration across the entire planning-to-execution spectrum. The companies that modernize incrementally, rather than overhaul everything at once, will see the strongest and most reliable gains.

The post The State of Transportation Systems: TMS Lessons from 2025 appeared first on Logistics Viewpoints.

Continue Reading

Non classé

The Systems-Engineered Logistics Operation: From Transformation Projects to Continuous Design

Published

on

By

For years, logistics transformation has been organized as a succession of projects. Implement the platform. Build the control tower. Automate the facility. Add the AI layer. The problem is that logistics no longer changes on a project cadence.

That environment is disappearing. The future logistics will need to be designed continuously. The Autonomous Logistics Network is one expression of this end state, but reaching it requires continuous design rather than a one-time transformation project.

Stop Thinking in Technology Stacks

Modern logistics networks are becoming integrated combinations of physical assets, software, data, optimization, AI, robotics, people, partners, and automated decisions. Calling this a technology stack understates what is happening.

It is an operating system. The important design questions are no longer confined to which applications a company owns. Leaders have to consider how decisions flow, how data maintain continuity across systems, how automation interacts with people, how models are governed, how exceptions escalate, and how the organization behaves when components fail.

That is systems engineering territory. The companies that manage this architecture deliberately will have an advantage over those that continue adding capabilities one project at a time.

Intelligence Is Moving to the Point of Action

Logistics technology is moving from systems of record toward systems of decision. Traditional applications captured transactions and supported workflows. Analytical systems added prediction and optimization. The emerging layer increasingly combines real-time signals, AI, optimization, agents, and execution connectivity.

The result is intelligence closer to the point of action. A shipment delay can be identified, its impact evaluated, alternatives generated, and a response executed with limited human intervention. Transportation systems can continuously re-evaluate routes, capacity, and exceptions instead of waiting for manual replanning. Warehouse and yard systems can adjust priorities as conditions change.

This will make logistics faster. It will also make architecture and governance more consequential.

When software only reported information, a bad output could be ignored. When software acts, the operating envelope matters.

Human Work Moves Up the Decision Stack

More automation does not eliminate the human role. It changes it.

People will spend less time collecting information, reconciling spreadsheets, monitoring routine transactions, and making repetitive bounded decisions. They will spend more time dealing with novel exceptions, cross-functional tradeoffs, strategic choices, carrier and customer relationships, system design, and governance.

That is a better use of human capability. It is also a harder job.

The future planner, transportation manager, warehouse leader, or logistics executive will need to understand not only operations but the automated systems influencing operations. They will need to know when to trust a recommendation, when to challenge it, and how a decision in one part of the system affects another. Logistics expertise will become more architectural.

Continuous Design Requires Continuous Validation

If the system changes continuously, validation must become continuous as well.

AI models drift. Business priorities change. automation rules evolve. New interfaces are added. Local process changes accumulate. External conditions move.

The organization cannot wait for the next transformation program to determine whether the operating system still meets its requirements. Performance, model behavior, exception patterns, overrides, decision latency, data quality, and failure modes will need ongoing monitoring.

This creates a closed lifecycle: design, deploy, observe, validate, improve, and redesign. Transformation becomes less of an event and more of a management discipline.

Resilience Becomes an Architectural Property

The future of resilience is also likely to move beyond static buffers. Inventory and redundancy will remain important, but digital systems will make logistics more capable of sensing, simulating, and responding dynamically.

A disruption can trigger scenario analysis. A digital twin can estimate consequences. Optimization can evaluate alternatives. AI can interpret unstructured signals. Automated decision systems can act inside approved boundaries.

This does not eliminate the need for physical resilience. It allows physical resilience and decision resilience to work together.

The strongest logistics networks will not simply carry more protection. They will understand their dependencies and reconfigure faster when conditions change.

Architecture Becomes a Competitive Capability

For years, companies differentiated logistics through network scale, facility and transportation assets, carrier leverage, operational excellence, service design, and technology investment. Architecture is becoming another source of advantage.

Two companies may use similar software and still achieve very different results because one has better process integration, clearer decision rights, stronger data, more effective automation boundaries, better failure recovery, and tighter governance. The advantage does not come from owning the component. It comes from how the components have been engineered to work together.

Logistics Management Becomes Systems Management

That may be the larger lesson of this series. Logistics networks are already systems of systems. The technology is making them more connected, more autonomous, and more adaptive. That complexity cannot be managed indefinitely through functional optimization and periodic implementation projects.

The discipline has to evolve.

Define requirements before selecting solutions. Design the operating model. Architect processes, data, and decisions together. Engineer technology into the system rather than around it. Validate the outcome. Govern change. Design for failure. Improve continuously.

The competitive advantage will not come from owning the same AI, automation, TMS, WMS, visibility, and execution technologies everybody else can buy. It will come from how coherently those components have been engineered to work together. The future of logistics management is not simply more digital, more autonomous, or more intelligent. It is more engineered.

Related Logistics Viewpoints research

Systems Engineering in Logistics
The New Architecture of Logistics
2026 Supply Chain Decision Intelligence Market Map
Digital Transformation in Logistics
Previous in this series: Design for Failure: Resilience, Risk, and Failure Modes

Request the Systems Engineering in Logistics Client Edition

If your organization is evaluating a logistics transformation, technology strategy, automation program, or operating-model redesign, I would be glad to provide the complete client edition and discuss how the framework applies to your priorities, constraints, and operating environment.

Request the client edition

The post The Systems-Engineered Logistics Operation: From Transformation Projects to Continuous Design appeared first on Logistics Viewpoints.

Continue Reading

Non classé

Walmart and Symbotic: When Warehouse Automation Becomes a Network Strategy

Published

on

By

Warehouse automation has traditionally been discussed one facility at a time. A retailer installs an automated storage system, deploys mobile robots, adds robotic picking, or upgrades sortation. The business case is then measured against improvements within that particular building. Walmart and Symbotic are beginning to challenge that way of thinking.

On October 29, Walmart and Symbotic announced an expanded commercial agreement that will bring additional automation capabilities to 25 U.S. regional distribution centers. The agreement includes an initial commitment of approximately $6 billion, covering work over several years and multiple locations. Walmart says the initiative is intended to support upstream e-commerce inventory management, increase storage capacity, and improve the movement of products through its supply chain. Those numbers make the announcement noteworthy. But the more interesting story is what the scale of the commitment says about the next phase of warehouse automation.

From an Automation Project to an Operating Model

For years, warehouse automation investments were frequently justified around specific bottlenecks: reduced picker travel, increase storage density, improve sortation throughput, or offset labor requirements. Those are still important objectives. But Walmart is evaluating automation against something larger: the performance of an interconnected distribution network supporting stores, pickup and home delivery.

Rob Montgomery, executive vice president for Walmart U.S. Supply Chain Operations, tied the expanded agreement to improving service, growing capacity, simplifying work for associates and lowering costs. The company also expects the expansion to support broader assortment, greater speed and more reliable replenishment. That distinction matters.

Warehouse automation increasingly needs to be evaluated not simply by asking, “How much faster can this facility pick?” but by asking, “What does this investment change across the supply chain?” Does additional storage capacity improve inventory positioning? Does automation enable later ordering cutoffs? Can replenishment become more predictable? Can the same technology architecture be repeated across multiple facilities without redesigning the operation every time? Those questions take warehouse automation discussions much closer to business strategy.

Scale Is Becoming Part of the Business Case

The Walmart-Symbotic relationship is particularly interesting because this is not a new pilot. Reuters reported that Symbotic has been helping automate Walmart’s supply chain since 2017, while the latest agreement extends automation to another 25 regional distribution centers. There is another layer to the expansion as well. Supply Chain Dive reported that Walmart committed an additional $125 million toward research and development of racking technology and related picking, process-flow and inventory-management capabilities. That is important because it suggests the competitive discussion is moving beyond individual pieces of robotic hardware. Warehouse automation is increasingly about how storage, picking, inventory, material movement and software operate together.

Symbotic’s current portfolio illustrates that evolution. The company says its integrated offering includes BreakPack for each-picking and SymMicro for e-commerce micro-fulfillment, supported by proprietary software that uses AI to orchestrate product movement. The question for warehouse operators, therefore, becomes less about which robot performs an individual task and more about how multiple automation layers combine into a repeatable operating system.

Walmart Is Not the Only Signal

Developments elsewhere reinforce the same trend. Amazon reported in 2026 that it has deployed more than one million robots across its operations network. Its systems now span inventory handling, mobile robotics, robotic arms and packaging automation. The company also says its Sequoia system can identify and store inventory up to 75 percent faster at fulfillment centers.

Meanwhile, DHL Supply Chain and Locus Robotics reached another useful measure of scale in 2026: one billion warehouse picks using Locus AMRs. Locus says thousands of its robots now operate across more than 40 DHL-managed sites worldwide. These examples are different applications with different economics. That is precisely the point. The warehouse automation market is moving beyond the question of whether robotics can work. Leading operators are increasingly confronting the harder questions of where automation should be deployed, how quickly it can scale, how well it integrates with existing operations, and whether benefits survive replication across a network.

The Metrics That Matter After Go-Live

The risk in covering a $6 billion automation agreement is treating announced spending as though it were demonstrated return. It is not. The more valuable story will develop as the systems go live. The measures worth watching include throughput, storage utilization, replenishment performance, labor productivity, system availability, fulfillment speed, implementation cost and the ability to maintain performance during demand peaks. That distinction should matter to technology buyers. A compelling demonstration can show what automation can do. A network-scale deployment begins to show whether the technology can generate similar value repeatedly under different facility and operating conditions. For Walmart, that makes the 25 distribution centers as important as the $6 billion headline.

Takeaway

The next chapter of warehouse automation will not be defined simply by more robots. It will be defined by whether operators can turn automation into a repeatable, measurable and scalable operating capability.

Walmart’s expanded relationship with Symbotic provides an unusually large test of that idea. The announced objectives are ambitious: more capacity, faster product movement, better replenishment, broader assortment, simpler work and lower costs. Now comes the more important part: measuring what changes when those systems are operating across the network. For other warehouse operators considering automation, that may ultimately be the most useful lesson from Walmart. Do not evaluate the robot alone. Evaluate what the automation changes in the economics and performance of the supply chain around it.

The post Walmart and Symbotic: When Warehouse Automation Becomes a Network Strategy appeared first on Logistics Viewpoints.

Continue Reading

Non classé

Walmart and Symbotic: When Warehouse Automation Becomes a Network Strategy

Published

on

By

Walmart And Symbotic: When Warehouse Automation Becomes A Network Strategy

Warehouse automation has traditionally been discussed one facility at a time. A retailer installs an automated storage system, deploys mobile robots, adds robotic picking, or upgrades sortation. The business case is then measured against improvements within that particular building. Walmart and Symbotic are beginning to challenge that way of thinking.

On October 29, Walmart and Symbotic announced an expanded commercial agreement that will bring additional automation capabilities to 25 U.S. regional distribution centers. The agreement includes an initial commitment of approximately $6 billion, covering work over several years and multiple locations. Walmart says the initiative is intended to support upstream e-commerce inventory management, increase storage capacity, and improve the movement of products through its supply chain. Those numbers make the announcement noteworthy. But the more interesting story is what the scale of the commitment says about the next phase of warehouse automation.

From an Automation Project to an Operating Model

For years, warehouse automation investments were frequently justified around specific bottlenecks: reduced picker travel, increase storage density, improve sortation throughput, or offset labor requirements. Those are still important objectives. But Walmart is evaluating automation against something larger: the performance of an interconnected distribution network supporting stores, pickup and home delivery.

Rob Montgomery, executive vice president for Walmart U.S. Supply Chain Operations, tied the expanded agreement to improving service, growing capacity, simplifying work for associates and lowering costs. The company also expects the expansion to support broader assortment, greater speed and more reliable replenishment. That distinction matters.

Warehouse automation increasingly needs to be evaluated not simply by asking, “How much faster can this facility pick?” but by asking, “What does this investment change across the supply chain?” Does additional storage capacity improve inventory positioning? Does automation enable later ordering cutoffs? Can replenishment become more predictable? Can the same technology architecture be repeated across multiple facilities without redesigning the operation every time? Those questions take warehouse automation discussions much closer to business strategy.

Scale Is Becoming Part of the Business Case

The Walmart-Symbotic relationship is particularly interesting because this is not a new pilot. Reuters reported that Symbotic has been helping automate Walmart’s supply chain since 2017, while the latest agreement extends automation to another 25 regional distribution centers. There is another layer to the expansion as well. Supply Chain Dive reported that Walmart committed an additional $125 million toward research and development of racking technology and related picking, process-flow and inventory-management capabilities. That is important because it suggests the competitive discussion is moving beyond individual pieces of robotic hardware. Warehouse automation is increasingly about how storage, picking, inventory, material movement and software operate together.

Symbotic’s current portfolio illustrates that evolution. The company says its integrated offering includes BreakPack for each-picking and SymMicro for e-commerce micro-fulfillment, supported by proprietary software that uses AI to orchestrate product movement. The question for warehouse operators, therefore, becomes less about which robot performs an individual task and more about how multiple automation layers combine into a repeatable operating system.

Walmart Is Not the Only Signal

Developments elsewhere reinforce the same trend. Amazon reported in 2026 that it has deployed more than one million robots across its operations network. Its systems now span inventory handling, mobile robotics, robotic arms and packaging automation. The company also says its Sequoia system can identify and store inventory up to 75 percent faster at fulfillment centers.

Meanwhile, DHL Supply Chain and Locus Robotics reached another useful measure of scale in 2026: one billion warehouse picks using Locus AMRs. Locus says thousands of its robots now operate across more than 40 DHL-managed sites worldwide. These examples are different applications with different economics. That is precisely the point. The warehouse automation market is moving beyond the question of whether robotics can work. Leading operators are increasingly confronting the harder questions of where automation should be deployed, how quickly it can scale, how well it integrates with existing operations, and whether benefits survive replication across a network.

The Metrics That Matter After Go-Live

The risk in covering a $6 billion automation agreement is treating announced spending as though it were demonstrated return. It is not. The more valuable story will develop as the systems go live. The measures worth watching include throughput, storage utilization, replenishment performance, labor productivity, system availability, fulfillment speed, implementation cost and the ability to maintain performance during demand peaks. That distinction should matter to technology buyers. A compelling demonstration can show what automation can do. A network-scale deployment begins to show whether the technology can generate similar value repeatedly under different facility and operating conditions. For Walmart, that makes the 25 distribution centers as important as the $6 billion headline.

Takeaway

The next chapter of warehouse automation will not be defined simply by more robots. It will be defined by whether operators can turn automation into a repeatable, measurable and scalable operating capability.

Walmart’s expanded relationship with Symbotic provides an unusually large test of that idea. The announced objectives are ambitious: more capacity, faster product movement, better replenishment, broader assortment, simpler work and lower costs. Now comes the more important part: measuring what changes when those systems are operating across the network. For other warehouse operators considering automation, that may ultimately be the most useful lesson from Walmart. Do not evaluate the robot alone. Evaluate what the automation changes in the economics and performance of the supply chain around it.

The post Walmart and Symbotic: When Warehouse Automation Becomes a Network Strategy appeared first on Logistics Viewpoints.

Continue Reading

Trending