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Mastering Disruption: A Smarter, More Connected Approach

Published

10 mois ago

27 mars 2025

Mastering Disruption: A Smarter, More Connected Approach

Five years ago, we all thought the COVID-19 pandemic resulted in the most disrupted supply chain landscape we would ever see. We were wrong. Since then, supply chain disruptions and volatility have only increased.

Three months into 2025, we have seen a barrage of on-again, off-again tariffs that have supply chain and logistics teams reeling, as they must rethink everything from next week’s shipping route to their foundational network models. From wildfires and flooding to tornadoes and hurricanes, climate change contributes to more frequent and powerful disasters. The Ukraine-Russia conflict is ongoing. Tensions flare in the Middle East without warning.

A disruption at any point in the global logistics network — including the average of 12 touch points from shipment packaging to final delivery — can prove disastrous for profits, service levels, customer loyalty, and other key metrics. With the global e-commerce market predicted to reach $8.1 trillion next year, omnichannel revenues may be increasing — but so are the chances that something, somewhere, will go wrong on the journey of getting orders to the customer.

Today the question is not just “When is the next disruption coming?” but also “How well can we proactively avoid the damage it may cause?”

Most supply chain and logistics teams have recognized that the only way to combat today’s incredible level of uncertainty is by adopting and applying digital tools. The pace and scope of supply chain disruption are beyond human cognition, manual analysis, and consumer-grade spreadsheet tools. With its ability to monitor conditions across the supply chain — at every node and touch point — digitalization provides the only practical solution.

Kudos to the supply chain and logistics teams that have already adopted transportation management systems (TMS), warehouse management systems (WMS), and other digital solutions. They can ingest large volumes of functional data and leverage advanced intelligence to recognize broad trends and specific disruptive events. They are applying predictive analytics and data science to choose an optimal response quickly, driven by facts and pre-defined business outcomes.

It is not surprising that the TMS market will nearly double in size between 2024 and 2029, increasing from $11.75 billion to $23.07 billion. Similarly, the WMS market is expected to grow from $3.9 billion in 2023 to $13.3 billion by 2030, more than tripling in size.

As the Stakes Get Higher, Technology Is Growing in Reach and Capability

While having a TMS or a WMS is a great place to start, many supply chain and logistics teams may not realize that they are only scratching the surface of modern supply chain digitalization. The logistics domain’s and industry’s leading software providers recognize that supply chain disruptions and volatility are growing — and they have responded with some powerful innovations.

Supply chain and logistics teams owe it to themselves to learn about the new generation of advanced digital solutions— and associated best practices— that are changing the nature of logistics networks today. Generally, next-gen innovations fall into a few main categories, discussed below.

Enabling an immediate and synchronized response

Ideally, supply chain and logistics teams would respond to every disruptive event immediately — making the best, most informed decision and then orchestrating it across thousands of miles of supply chain. That may sound impossible, but new technology places this capability within the reach of every organization. There are two components involved here: making the right decision and executing it in a synchronized manner.

Artificial intelligence (AI) is not just a buzzword; it has become a critical competency for supply chain and logistics teams today. Its value is recognized by shippers as they choose logistics partners. In a recent study, almost three-quarters (74%) of shippers reported they would switch to 3PL providers based on their AI capabilities.

Why? Because only AI is capable of ingesting real-time data from across functions, facilities, fleets, trading partners and the outside world — then using data science and pattern recognition — see disruptions at the earliest moment. AI is also making it possible to define a response that balances multiple outcomes, such as cost, service, profitability, and sustainability, applying pre-defined rules and guardrails. It is no wonder that the AI in the supply chain market will grow more than 10x between 2024 and 2030, from $5 billion to $51 billion.

AI is only the beginning of generating the most effective response to disruptions. Leading supply chain and logistics teams can drive an automated, collaborative response to exceptions by uniting interoperable solutions — like WMS, TMS, planning, order management, and yard management systems — on a shared platform. Wherever the disruption occurs in the end-to-end supply chain, a platform approach and interoperable solutions guarantee shared awareness of the event and a broad, cross-functional response that intelligently balances all outcomes. The responses are more effective, and response time is much quicker, with fewer buffer stocks.

Just as a single solution, like a TMS, can autonomously reroute a shipment when a port closes, the end-to-end supply chain can act immediately, in synchronization, with little to no human intervention. More broadly, AI can be deployed across functions to shift inventory, switch transportation modes, find new carriers, communicate across functions and regions with customers and partners, and otherwise deliver a smart, collaborative response. That is the beauty of a platform enabled by AI.

Adopting a platform-based approach can be a game-changer for today’s embattled supply chain and logistics teams — creating a seamless and effective way to recognize a disruption and pull a single execution lever in response.

Redefining the concept of a logistics network

The capabilities of AI in recognizing disruptions and changes and fueling synchronized planning and execution are limitless. For most supply chain and logistics teams, their execution options are not limitless. Teams are constrained by their physical resources, like trucks, inventory, and labor capacities, as they seek to resolve a disruption. They are also limited by their supplier, carrier, and trading partner networks.

One of the most exciting innovations happening in logistics today is eliminating these constraints via digitalization of the supply chain ecosystem. Real-time connectivity empowers the existing logistics network and opens the door to limitless opportunities for collaboration and partnership beyond the existing supply chain footprint.

By partnering with the right solutions provider, supply chain and logistics teams can connect with as many as 150,000 trading partners that can instantly and seamlessly extend the logistics network on demand. Whether supply chain and logistics teams are looking for new sources of inventory, transportation or warehousing, a full-service logistics software partner can seamlessly connect them with the right partners.

Even as the logistics network expands, digitalization guarantees all collaborators share the same data and awareness. They have real-time visibility into inventory levels, movements and purchase orders across all trading partners in the multi-tier network — from raw materials to warehouse to retail shelf or consumer doorstep.

The shift from a traditional, linear, constrained supply chain to a dynamic, interactive network has emerged as one of the smartest and most effective ways of managing logistics disruptions. After all, who does not want more options and greater agility when the unexpected happens?

Executing flawlessly at the task level

While the first two innovations described here focus on optimized end-to-end execution, enabled by AI and digitalization, today’s next-gen technology is changing how users complete every task and handle every item. In a recent interview published by Logistics Viewpoints, Blue Yonder CEO Duncan Angove highlighted the groundbreaking developments in agentic AI that are transforming the supply chain at a granular level.

The power of agentic AI lies in creating a new digital workforce that interacts directly with human associates. A team of interactive, AI-enabled optimization engines, or agents, are trained in specific logistics tasks like order prioritization, warehouse picking or load-building.

Supply chain and logistics teams can complement their human workforce with these specialized agents, each complete with their numeric algorithms, to accelerate and optimize key tasks. Human workers at the warehouse, for example, are guided by these AI agents, or co-pilots, as they complete their daily work via a user-friendly interface. Text and voice interactions are

possible, and these agents generate summaries and reports that allow associates to see both macro and micro-level performance results. Not only can agentic AI reduce warehouse labor costs by 25% and improve productivity by 15%, but it also increases employee satisfaction and retention.

Agentic AI is an easily learned and accessible way for many companies to derive quick returns from next-gen technologies. Blue Yonder has seen 5x growth in agentic AI applications year-over-year, and this emerging technology area is just getting started.

It is Clear: Supply Chains Must Exert Greater Control Over Disruptions

Industry statistics demonstrate clearly that the world’s supply chain and logistics teams are embracing the power of advanced technology and digitalization. As supply chain disruptions increase in frequency and scale, software providers are doing their part by investing in even more impactful technology innovations every day.

That is why supply chain and logistics teams need to see technology adoption not as a one-time event but as an ongoing journey. Companies that continuously explore and apply the newest innovations, like AI agents, will realize a significant edge over competitors who still rely on older technologies and highly manual work processes.

Looking back at the COVID-19 pandemic, who could have predicted that the world’s supply chains would only become more disrupted and challenged? Fortunately, from tariffs to extreme weather, today’s advanced technology allows supply chain and logistics teams to be far better prepared for the future — no matter what that future looks like.

About the Author

Terence Leung is Global Senior Director of Solution and Industry Marketing at Blue Yonder. With a keen interest in AI and digitalization and the benefits they generate, Terence is passionate about Blue Yonder’s industry-leading supply chain platform, which spans warehouse management, warehouse execution, yard management, transportation management, planning, and commerce solutions. He works closely with Blue Yonder customers to understand their challenges and requirements, helping them adopt best practices in their digital journeys.

Prior to joining Blue Yonder, Terence was the leader in product marketing and value engineering at One Network. He held previous leadership positions in industry management at Savi Technology and solution management and management consulting at i2 and Deloitte Consulting, respectively. Terence earned an MBA from the University of Texas, Austin, and an Electrical Engineering degree from MIT.

The post Mastering Disruption: A Smarter, More Connected Approach appeared first on Logistics Viewpoints.

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India–U.S. Trade Announcement Creates Strategic Options, Not Executable Change

Published

10 heures ago

3 février 2026

India–u.s. Trade Announcement Creates Strategic Options, Not Executable Change

The announcement by Donald Trump and Narendra Modi of an India–U.S. “trade deal” has drawn immediate attention from global markets. From a supply chain and logistics perspective, however, the more important observation is not the scale of the claims, but the lack of formal detail required for execution.

At this stage, what exists is a political statement rather than a completed trade agreement. For companies managing sourcing, manufacturing, transportation, and compliance across India–U.S. trade lanes, uncertainty remains the defining condition.

What Has Been Announced So Far

Based on public statements from the U.S. administration and reporting by CNBC and Al Jazeera, several points have been asserted:

U.S. tariffs on Indian goods would be reduced from an effective 50 percent to 18 percent

India would reduce tariffs and non tariff barriers on U.S. goods, potentially to zero

India would stop purchasing Russian oil and increase energy purchases from the United States

India would significantly increase purchases of U.S. goods across energy, agriculture, technology, and industrial sectors

Statements from the Indian government have been more limited. New Delhi confirmed that U.S. tariffs on Indian exports would be reduced to 18 percent, but it did not publicly confirm commitments related to Russian oil, agricultural market access, or large scale procurement from U.S. suppliers.

This divergence matters. In supply chain planning, commitments only become relevant when they are documented, scoped, and enforceable.

Why This Is Not Yet a Trade Agreement

From an operational standpoint, the announcement lacks several elements required to support planning and execution:

No published tariff schedules by HS code

No clarification on rules of origin

No definition of non tariff barrier reductions

No implementation timelines

No enforcement or dispute resolution mechanisms

Without these components, companies cannot reliably model landed cost, supplier risk, or network design changes.

By comparison, India’s recently announced trade agreement with the European Union includes detailed provisions covering market access, regulatory alignment, and investment protections. Those provisions are what allow supply chain leaders to translate trade policy into operational decisions. The U.S. announcement does not yet meet that threshold.

Implications for Supply Chains

Tariff Reduction Could Be Material if Formalized

An 18 percent tariff rate would improve India’s competitive position relative to regional peers such as Vietnam, Bangladesh, and Pakistan. If implemented and sustained, this could support incremental sourcing from India in sectors such as textiles, pharmaceuticals, and light manufacturing.

For now, however, this remains a scenario rather than a planning assumption.

Energy Commitments Are the Largest Unknown

The claim that India would halt purchases of Russian oil has significant implications across energy, chemical, and manufacturing supply chains. Russian crude has been a key input for Indian refineries and downstream industrial production.

A shift away from that supply would affect energy input costs, tanker routing, port utilization, and U.S.–India crude and LNG trade volumes. None of these impacts can be assessed with confidence without confirmation from Indian regulators and implementing agencies.

Agriculture Remains Politically and Operationally Sensitive

U.S. officials have suggested expanded access for American agricultural exports. Historically, agriculture has been one of the most protected and politically sensitive sectors in India.

Any meaningful liberalization would raise questions around cold chain capacity, port infrastructure, domestic political resistance, and regulatory compliance. These factors introduce execution risk that supply chain leaders should consider carefully.

Compliance and Digital Trade Issues Are Unresolved

Several areas remain undefined:

Whether India will adjust pharmaceutical patent protections

Whether U.S. technology firms will receive exemptions from digital services taxes

Whether labor and environmental standards will be linked to market access

Each of these issues influences sourcing strategies, contract terms, and long term cost structures.

Practical Guidance for Supply Chain Leaders

Until formal documentation is released, a measured approach is warranted:

Avoid making structural network changes based on political announcements

Model tariff exposure using multiple scenarios rather than a single assumed outcome

Monitor customs and regulatory guidance rather than headline statements

Assess exposure to potential energy cost changes in Indian operations

Track implementation of the India–EU agreement as a near term reference point

Bottom Line

This announcement suggests a potential shift in the direction of India–U.S. trade relations, but it does not yet provide the clarity required for operational decision making.

For now, it creates strategic optionality rather than executable change.

Until tariff schedules, regulatory commitments, and enforcement mechanisms are formally published, supply chain and logistics leaders should treat this development as informational rather than actionable. In trade, execution begins only when the documentation exists.

The post India–U.S. Trade Announcement Creates Strategic Options, Not Executable Change appeared first on Logistics Viewpoints.

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Winter weather challenges, trade deals and more tariff threats – February 3, 2026 Update

Published

15 heures ago

3 février 2026

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Winter weather challenges, trade deals and more tariff threats – February 3, 2026 Update

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Published: February 3, 2026

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Weekly highlights

Ocean rates – Freightos Baltic Index

Asia-US West Coast prices (FBX01 Weekly) decreased 10% to $2,418/FEU.

Asia-US East Coast prices (FBX03 Weekly) decreased 2% to $3,859/FEU.

Asia-N. Europe prices (FBX11 Weekly) decreased 5% to $2,779/FEU.

Asia-Mediterranean prices(FBX13 Weekly) decreased 5% to $4,179/FEU.

Air rates – Freightos Air Index

China – N. America weekly prices increased 8% to $6.74/kg.

China – N. Europe weekly prices decreased 4% to $3.44/kg.

N. Europe – N. America weekly prices increased 10% to $2.53/kg.

Analysis

Winter weather is complicating logistics on both sides of the Atlantic. Affected areas in the US, especially the southeast and southern midwest are still recovering from last week’s major storm and cold.

Storms in the North Atlantic slowed vessel traffic and disrupted or shutdown operations at several container ports across Western Europe and into the Mediterranean late last week. Transits resumed and West Med ports restarted operations earlier this week, but the disruptions have already caused significant delays, and weather is expected to worsen again mid-week.

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The resulting delays and disruptions could increase congestion levels at N. Europe ports, but ocean rates from Asia to both N. Europe and the Mediterranean nonetheless dipped 5% last week as the pre-Lunar New Year rush comes to an end. Daily rates this week are sliding further with prices to N. Europe now down to about $2,600/FEU and $3,800/FEU to the Mediterranean – from respective highs of $3,000/FEU and $4,900/FEU in January.

Transpacific rates likewise slipped last week as LNY nears, with West Coast prices easing 10% to about $2,400/FEU and East Coast rates down 5% to $3,850/FEU. West Coast daily prices have continued to slide so far this week, with rates dropping to almost $1,900/FEU as of Monday, a level last seen in mid-December.

Prices across these lanes are significantly lower than this time last year due partly to fleet growth. ONE identified overcapacity as one driver of Q3 losses last year, with lower volumes due to trade war frontloading the other culprit.

And trade war uncertainty has persisted into 2026.

India – US container volumes have slumped since August when the US introduced 50% tariffs on many Indian exports. Just this week though, the US and India announced a breakthrough in negotiations that will lower tariffs to 18% in exchange for a reduction in India’s Russian oil purchases among other commitments. President Trump has yet to sign an executive order lowering tariffs, and the sides have not released details of the agreement, but once implemented, container demand is expected to rebound on this lane.

Recent steps in the other direction include Trump issuing an executive order that enables the US to impose tariffs on countries that sell oil to Cuba, and threatening tariffs and other punitive steps targeting Canada’s aviation manufacturing.

The recent volatility of and increasing barriers to trade with the US since Trump took office last year are major drivers of the warmer relations and increased and diversified trade developing between other major economies. The EU signed a major free trade agreement with India last week just after finalizing a deal with a group of South American countries, and other countries like the UK are exploring improved ties with China as well.

In a final recent geopolitical development, Panama’s Supreme Court nullified Hutchinson Port rights to operate its terminals at either end of the Panama Canal. The Hong Kong company was in stalled negotiations to sell those ports following Trump’s objection to a China-related presence in the canal. Maersk’s APMTP was appointed to take over operations in the interim.

In air cargo, pre-LNY demand may be one factor in China-US rates continuing to rebound to $6.74/kg last week from about $5.50/kg in early January. Post the new year slump, South East Asia – US prices are climbing as well, up to almost $5.00/kg last week from $4.00/kg just a few weeks ago.

China – Europe rates dipped 4% to $3.44/kg last week, with SEA – Europe prices up 7% to more than $3.20/kg, and transatlantic rates up 10% to more than $2.50/kg, a level 25% higher than early this year.

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Judah Levine

Head of Research, Freightos Group

Judah is an experienced market research manager, using data-driven analytics to deliver market-based insights. Judah produces the Freightos Group’s FBX Weekly Freight Update and other research on what’s happening in the industry from shipper behaviors to the latest in logistics technology and digitization.

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Microsoft and the Operationalization of AI: Why Platform Strategy Is Colliding with Execution Reality

Published

1 jour ago

2 février 2026

Microsoft And The Operationalization Of Ai: Why Platform Strategy Is Colliding With Execution Reality

Microsoft has positioned itself as one of the central platforms for enterprise AI. Through Azure, Copilot, Fabric, and a rapidly expanding ecosystem of AI services, the company is not merely offering tools, it is proposing an operating model for how intelligence should be embedded across enterprise workflows.

For supply chain and logistics leaders, the significance of Microsoft’s strategy is less about individual features and more about how platform decisions increasingly shape where AI lives, how it is governed, and which decisions it ultimately influences.

From Cloud Infrastructure to Operating Layer

Historically, Microsoft’s role in supply chain technology centered on infrastructure and productivity software. Azure provided scalable compute and storage, while Office and collaboration tools supported planning and coordination. That boundary has shifted.

Microsoft is now positioning AI as a horizontal operating layer that spans data management, analytics, decision support, and execution. Azure AI services, Microsoft Fabric, and Copilot are designed to work together, reducing friction between data ingestion, model development, and business consumption.

The implication for operations leaders is subtle but important: AI is no longer something added to systems; it is increasingly embedded into the platforms those systems rely on.

Copilot and the Question of Decision Proximity

Copilot has become a focal point of Microsoft’s AI narrative. Positioned as an assistive layer across applications, Copilot aims to surface insights, generate recommendations, and automate routine tasks.

For supply chain use cases, the key question is not whether Copilot can generate answers, but where those answers appear in the decision chain. Insights delivered inside productivity tools can improve awareness and coordination, but operational value depends on whether recommendations are connected to execution systems.

This highlights a broader pattern: AI that remains advisory improves efficiency; AI that is embedded into workflows influences outcomes. Microsoft’s challenge is bridging that gap consistently across heterogeneous enterprise environments.

Microsoft Fabric and the Data Foundation Problem

Microsoft Fabric represents an attempt to simplify and unify the enterprise data landscape. By combining data engineering, analytics, and governance into a single platform, Microsoft is addressing one of the most persistent barriers to AI adoption: fragmented and inconsistent data.

For supply chain organizations, Fabric’s value lies in its potential to standardize event data across planning, execution, and visibility systems. However, unification does not eliminate the need for data discipline. Event quality, latency, and ownership remain operational issues, not platform features.

Fabric reduces friction, but it does not resolve governance by itself.

Integration with Existing Enterprise Systems

Microsoft’s AI strategy assumes coexistence with existing ERP, WMS, TMS, and planning platforms. Integration, rather than replacement, is the dominant pattern.

This creates both opportunity and risk. On one hand, Microsoft can act as a connective tissue across systems that were never designed to work together. On the other, loosely coupled integration increases dependence on interface stability and data consistency.

In execution-heavy environments, even small integration failures can cascade quickly. As AI becomes more embedded, integration reliability becomes a strategic concern.

Where AI Is Delivering Value, and Where It Isn’t

AI deployments tend to deliver value fastest in areas such as demand sensing, scenario analysis, reporting automation, and exception identification. These use cases align well with Microsoft’s strengths in analytics, collaboration, and scalable infrastructure.

Where value is harder to realize is in autonomous execution. Closed-loop decision-making that directly triggers operational action requires tighter coupling with execution systems and clearer decision ownership.

This reinforces a recurring theme: platform AI accelerates insight, but execution still depends on operating model design.

Constraints That Still Apply

Despite the breadth of Microsoft’s AI portfolio, familiar constraints remain. Data quality, security, compliance, and organizational readiness continue to limit outcomes. AI platforms do not eliminate the need for process clarity or decision accountability.

In some cases, the ease of deploying AI services can outpace an organization’s ability to absorb them operationally. This creates a risk of insight saturation without action.

Why Microsoft Matters to Supply Chain Leaders

Microsoft’s relevance lies in its ability to shape the default environment in which enterprise AI operates. Platform decisions made today influence data architectures, governance models, and user expectations for years.

For supply chain leaders, the key takeaway is not to adopt Microsoft’s AI stack wholesale, but to understand how platform-level AI affects where intelligence sits, how it flows, and who ultimately acts on it.

The next phase of AI adoption will not be defined solely by model performance. It will be defined by how effectively platforms like Microsoft’s translate intelligence into operational decisions under real-world constraints.

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