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Your Supply Chain Isn’t Broken. Your Supply Chain Data Is.

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Your Supply Chain Isn’t Broken. Your Supply Chain Data Is.

Walk into any supply chain war room and you’ll hear the same frustrations on repeat: delays, stockouts, excess inventory, missed forecasts, rising costs. The natural instinct is to blame the network: suppliers, transportation, labor, or global disruption. But that diagnosis misses the real issue.

Your supply chain isn’t broken. Your data is.

Modern supply chains are more connected than ever before. They span continents, integrate hundreds of partners, and rely on increasingly sophisticated technology. Supply chain data is the collection of real-time and historical information from every touchpoint of a product’s journey. On paper, they should be faster, smarter, and more resilient. Yet many organizations are operating with less confidence and visibility than they had a decade ago. Why? Because the foundation (data) has quietly eroded.

Key components of supply chain data include product, logistics, financial, inventory, and demand data. As technology and sophistication increase, big data and digital transformation play a critical role in enabling modern supply chain analytics. Data sources now include structured and unstructured data from IoT, social media, traditional business tools, and external sources like weather alerts and alternative datasets, all of which are vital for comprehensive supply chain analysis.

The Illusion of Visibility

Most companies believe they have visibility into their supply chain. Dashboards are everywhere. Reports are automated. Data is constantly flowing in from ERP systems, warehouse management tools, transportation platforms, and supplier portals. However, effective data collection and data processing are crucial for ensuring that supply chain data is reliable and actionable. Supply chain data analytics and data visualization tools are essential for transforming raw data into actionable insights that drive better decision-making.

But visibility isn’t about having more data—it’s about trusting it. Diagnostic analytics can help organizations identify the root causes of supply chain issues, such as delayed shipments or missed forecasts, by analyzing underlying factors. Organizations use supply chain analytics to optimize operations, and end-to-end visibility enables better, faster decision-making in supply chain management.

When inventory data is delayed by hours (or days), when supplier updates are inconsistent, and when demand signals are fragmented across systems, what you’re left with is a distorted picture of reality. Real-time data allows companies to track, monitor, and identify bottlenecks quickly, reducing the impact of disruptions. Decisions made on top of that picture are inherently flawed.

This is how organizations end up expediting shipments they didn’t need, over-ordering inventory “just in case,” or missing critical shortages that were hiding in plain sight.

The Fragmentation Problem

The core issue isn’t that companies lack data. It’s that their data lives in silos.

Procurement sees one version of demand while operations sees another. Finance has its own numbers and suppliers operate on entirely different datasets. Each system is optimized for its own function, but none are aligned around a single, real-time version of the truth. Data integration is essential for aligning supply chain data and ensuring consistency across the organization.

This fragmentation creates friction at every handoff point in the supply chain. Forecasts don’t match orders. Orders don’t match shipments. Shipments don’t match receipts. With increased data from sources like IoT devices, social media, and B2B platforms, organizations can enhance their analytical capabilities and support data driven decisions. However, without proper integration, the benefits of this increased data are lost. Organizations that deploy AI-powered analytics and end-to-end supply chain visibility tools can significantly improve their ability to anticipate and respond to disruptions, enhancing operational efficiency.

In this environment, even the best supply chain strategies fail; not because they’re wrong, but because they’re built on unreliable inputs.

Data Access: The Hidden Bottleneck

In today’s global supply chains, data access is often the silent culprit behind stalled progress. Supply chain analytics depends on the ability to collect, process, and analyze massive volumes of data from a dizzying array of sources – everything from supplier portals and logistics systems to IoT sensors and customer orders. Yet, as the volume and variety of data grow, so do the challenges.

Unstructured data, like emails, PDFs, shipment documents, and social media, can overwhelm traditional systems, making it difficult for supply chain managers to extract meaningful insights. When data is locked away in disparate systems or arrives in inconsistent formats, the result is a fragmented view of supply chain performance.

The solution lies in robust data management platforms that enable real-time data access and automatically assess data quality and relevance. By integrating data across the supply chain and applying advanced analytics, organizations can identify patterns and trends that would otherwise remain hidden. Predictive analytics and artificial intelligence further enhance this capability, allowing teams to anticipate disruptions, optimize inventory, and streamline operations.

Ultimately, organizations that prioritize seamless data access and invest in modern supply chain analytics tools gain a decisive competitive edge. They move from reactive firefighting to proactive, data-driven decision making, transforming their supply chain operations and eliminating bottlenecks to set a new standard for performance.

Why More Technology Isn’t the Answer

When faced with these challenges, many organizations respond by adding more tools, such as another analytics platform, another dashboard, or another AI model. However, effective supply chain management relies on robust data analysis and data analytics to extract actionable value from supply chain data.

But layering new technology on top of bad data doesn’t solve the problem. It amplifies it.

Supply chain data analytics, as a discipline, leverages cognitive analytics and machine learning to process large datasets and generate data-driven insights that support better decision-making. Prescriptive analytics can recommend specific actions to improve operational processes, such as inventory management and logistics planning, based on analytical insights. The wide range of benefits provided by supply chain analytics includes more efficient management, reduced operational costs, improved planning, and better risk management.

AI-driven forecasts trained on flawed historical data will produce flawed predictions. Optimization engines working with incomplete inputs will generate suboptimal plans. The result is faster, more confident decision-making, but in the wrong direction. Before companies can become “data-driven,” they need to become “data-trustworthy.”

Artificial Intelligence in Supply Chain: Hype vs. Reality

Artificial intelligence is everywhere in the supply chain conversation, promising to revolutionize everything from demand forecasting to warehouse operations. But while the potential is real, the reality is more nuanced.

AI excels at analyzing data, identifying patterns, and predicting future demand – capabilities that can dramatically improve supply chain performance and operational efficiency. The effectiveness of AI in supply chain management depends on the quality and integration of the underlying data. Without clean, connected, and governed data, even the most sophisticated AI models will struggle to deliver actionable insights. Data security and data integration are not optional, they are foundational.

AI is not a magic wand, but when deployed thoughtfully, on top of a solid data foundation, it can provide a genuine competitive advantage. The organizations that succeed will be those that combine advanced analytics with robust data management, empowering their teams to make smarter, faster decisions in an increasingly complex global economy.

Rebuilding the Foundation

Fixing supply chain data isn’t about a single system or initiative. It requires a fundamental shift in how data is managed, governed, and used.

It starts with integration: connecting data across systems, partners, and functions so that everyone operates from the same foundation. But integration alone isn’t enough. Data must also be standardized, cleansed, and continuously updated to reflect real-world conditions. Identifying and mitigating supply chain risks and disruptions is critical, and effective risk management relies on analytics to assess vulnerabilities and respond proactively.

Equally important is context. Raw data doesn’t drive decisions; interpreted data does. Organizations need to align on definitions, metrics, and business rules so that insights are consistent across teams. Supply chain analytics enables organizations to track supplier performance using metrics such as on-time delivery, lead times, defect rates, and contract compliance. These data-driven performance metrics allow businesses to evaluate suppliers objectively, fostering better negotiation and supporting risk management.

Finally, there’s the need for real-time intelligence. In a world where disruptions happen daily, yesterday’s data is already outdated. The ability to sense, analyze, and respond in real time is what separates reactive supply chains from resilient ones.

From Supply Chain Data Analytics Chaos to Decision Confidence

When data is accurate, connected, and timely, something powerful happens: decision-making accelerates. Descriptive analytics plays a key role here, analyzing supply chain data to identify current trends and relationships within operations, helping professionals understand the present state of logistics, inventory, and performance as a foundation for more advanced analytics.

Planners stop second-guessing forecasts. Operations teams trust inventory levels. Executives gain a clear view of risks and opportunities. Accurate, connected, and timely data provides just that – exactly what supply chain teams need for real-time visibility and analytics. Instead of reacting to problems, organizations can anticipate and prevent them.

The supply chain doesn’t just become more efficient, it becomes a competitive advantage.

The Bottom Line

For years, companies have tried to fix supply chain performance by optimizing the physical network. This includes adding suppliers, rerouting logistics, and increasing buffer stock. But these are symptoms, not solutions. The real bottleneck isn’t in your warehouses or your transportation lanes. It’s in your data.

Until that foundation is fixed, every improvement will be incremental at best, and counterproductive at worst. Staying updated with industry news is essential to remain informed about the latest trends and developments in supply chain data and analytics, ensuring your strategies are always relevant.

Your supply chain isn’t broken. Your data is.

Chris Cunnane is the Global Product Marketing Manager for Supply Chain at InterSystems. In this role, he is responsible for developing and executing marketing strategy and content for the InterSystems supply chain technology suite. Chris has 20+ years of supply chain expertise, leading the supply chain practice at ARC Advisory Group, as well as holding various sales, marketing, and operations roles in the wholesale, retail, and automotive parts markets. He holds a BA in Communications from Stonehill College and an MA in Global Marketing Communications from Emerson College.

The post Your Supply Chain Isn’t Broken. Your Supply Chain Data Is. appeared first on Logistics Viewpoints.

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From Deluges to Dry Beds: How Extreme Weather is Rewriting Logistics Strategy

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From Deluges To Dry Beds: How Extreme Weather Is Rewriting Logistics Strategy

Historically, supply chain managers viewed extreme weather as a series of isolated, unlinked headaches, a temporary detour here, a delayed container vessel there. But recent events are proving that climate-driven disruptions are no longer isolated events; they are systemic, compounding risks occurring simultaneously. Right now, global logistics are caught in a bizarre paradox of water volatility: inland waterways are concurrently shutting down due to both catastrophic flooding and severe drought.

The Current Snapshot:

In the United States, flash flooding across Missouri and the wider Ohio and Tennessee river valleys has completely knocked out regional road networks, forced emergency evacuations, and pushed the Black River to a projected record crest of 28 feet. Thunderstorms piled on top of each other to dump between 6 and 12 inches of rain across southern Missouri, with some areas near Miaoli receiving nearly 31 inches (80 cm) of downpour. The deluge tore a woman’s home entirely from its foundation, claiming her life, while the Army National Guard had to deploy Black Hawk helicopters to rescue more than 200 children and staff trapped at a summer camp in Lesterville. These slow-moving storms have brought regional last-mile and freight networks to a halt.

Across the Pacific, Typhoon Bavi just battered Taiwan and East China, forcing massive evacuations of over 2 million people and completely disrupting cargo handling and air freight at major hubs like Shanghai, where airlines canceled more than 680 flights. Yet, while parts of the world are drowning, Europe’s most critical commercial artery is choked by a severe mid-summer heatwave. On July 13th, water levels at the critical Kaub chokepoint on the Rhine plummeted to 53cm, well below the 81cm threshold where standard low-water surcharges apply. Freight barges are currently restricted to carrying just 20% of their total capacity, forcing operators to move volumes by individual agreement only. This near-standstill has triggered a massive, expensive migration of freight onto an already maxed-out rail and road infrastructure.

The Strategic Shift: Redundancy is Dead, Dynamic Flex is In

This dual reality underscores a massive trend shaping supply chain management: the shift from static risk planning to dynamic execution. When a primary inland waterway fails, you cannot simply rely on a fixed backup plan, because your backup mode (whether it is rail hubs restricted by local congestion or trucking lanes blocked by flash floods) is likely facing its own climate or operational constraints.

To endure this era of unforeseen climate events, logistics leaders are focusing on three main areas:

Mode Elasticity: Building contractual agility into carrier agreements so that switching from barge to rail, or air to ocean, can happen in hours rather than weeks.
Predictive Visibility Beyond Tier 1: Moving past simple track-and-trace. True resilience requires mapping out how weather events three states over will impact infrastructure, labor availability, and warehouse productivity downstream.
Climate as a Network Design Parameter: Historically, networks were designed almost purely around labor costs, tax incentives, and transit times. Network optimization models must now ingest historical climate data and predictive models as core constraints when choosing warehouse locations and routing strategies.

As the current El Niño cycle threatens to further scramble global rainfall and temperature patterns, the old playbook of waiting out the storm is officially obsolete. Volatility is the new baseline, and the competitive advantage belongs to the networks built to flex.

The post From Deluges to Dry Beds: How Extreme Weather is Rewriting Logistics Strategy appeared first on Logistics Viewpoints.

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Defense Drones Are Becoming an Industrial Supply Chain Race

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Ondas’ acquisition of DZYNE shows why competitive advantage in autonomous systems is shifting from technical demonstrations toward component security, modular design, manufacturing scale, and supplier integration.

The defense-drone market is moving from technical experimentation to industrialization.

Companies still need better aircraft, autonomy software, sensors, communications systems, and counter-drone technologies. But as governments prepare to purchase autonomous systems in much larger quantities, competitive advantage will increasingly depend on a different set of capabilities: securing components, expanding production, integrating acquired technologies, and supporting rapidly changing products at scale.

Ondas Holdings’ acquisition of DZYNE Technologies is an indication of that shift.

Ondas announced on July 6 that it had acquired DZYNE, a developer and manufacturer of autonomous aerial systems, surveillance platforms, and counter-UAS technologies. The transaction expands an Ondas portfolio that already includes automated drone operations, autonomous platforms, and systems designed to detect and counter unauthorized aircraft.

The immediate story is one of defense-technology consolidation. The more consequential story is industrial.

As demand for lower-cost autonomous systems grows, success will depend on more than which company develops the most advanced drone. It will depend on which companies can construct resilient supplier networks, standardize components, increase production volumes, manage product complexity, and adapt designs as technologies and operating requirements change.

The defense-drone race is becoming an industrial supply chain race.

From Technical Demonstration to Industrial Production

Defense technology companies have become highly effective at demonstrating new capabilities.

A startup can design a sophisticated autonomous aircraft, complete successful flight tests, and secure an initial government contract. That does not necessarily mean the company can produce thousands or tens of thousands of systems reliably and economically.

Scaling production introduces a different set of challenges.

Manufacturers must secure motors, batteries, cameras, processors, communications modules, navigation systems, electronic assemblies, composite materials, permanent magnets, and specialized sensors. Defense applications may also require component traceability, cybersecurity controls, approved suppliers, domestic-content compliance, and production processes that differ substantially from those used in commercial markets.

A technically successful platform can therefore encounter the same constraints seen across automotive, aerospace, electronics, and industrial-equipment supply chains: long lead times, limited supplier capacity, single-source dependencies, inconsistent quality, and inadequate visibility below the first tier.

Those risks become more serious when demand increases quickly.

The proposed fiscal year 2026 defense budget requested $13.4 billion for autonomy and autonomous systems, including $9.4 billion for unmanned and remotely operated aerial vehicles. The request illustrates the size of the potential demand signal now forming around autonomous defense systems.

Large procurement budgets, however, do not automatically create the industrial capacity required to fulfill them.

A Drone Is Also a Network of Supply Chain Dependencies

The relative simplicity and low unit cost of some small drones can obscure the complexity of the industrial base behind them.

Compared with a conventional military aircraft, an individual drone may be inexpensive and comparatively easy to assemble. Yet its components may come from a globally dispersed and highly concentrated supplier network.

Dependencies can include battery materials, electric motors, rare-earth magnets, semiconductors, carbon-fiber materials, communications equipment, cameras, circuit boards, and lower-level electronic assemblies.

These dependencies create both commercial and strategic risks.

A manufacturer may be able to obtain components economically under normal market conditions but lose access when export controls, trade restrictions, geopolitical tensions, or competing domestic demand intervene. The unavailability of a relatively inexpensive motor, magnet, sensor, or battery component can delay delivery of an entire system.

Research from the Center for Strategic and International Studies has identified rare-earth magnets, carbon-fiber materials, lithium-ion inputs, semiconductors, and other upstream materials as potential chokepoints in the drone industrial base. The analysis also highlights the lack of visibility below many first-tier defense contractors.

The implication is significant.

The strategic value of a drone manufacturer is not limited to its aircraft designs, software, or patents. It also includes its qualified supplier base, access to critical materials, manufacturing processes, contract-production relationships, testing infrastructure, and ability to replace unavailable components without redesigning the entire system.

These capabilities are harder to see than a successful flight demonstration, but they may ultimately determine which companies can deliver at scale.

M&A as Industrial Integration

The Ondas-DZYNE transaction reflects a broader effort to assemble complementary autonomous-system capabilities within larger corporate platforms.

DZYNE adds long-endurance aircraft, smaller autonomous systems, surveillance capabilities, counter-UAS technologies, modular airframe expertise, and established defense-customer relationships. Ondas brings additional autonomous platforms, drone infrastructure, security applications, and corporate resources.

The strategic logic extends beyond expanding the product catalog.

An integrated company may be able to combine engineering teams, share software architectures, consolidate suppliers, increase purchasing leverage, coordinate manufacturing investment, and offer customers a broader group of interoperable systems.

It may also be able to spread the costs of compliance, testing, cybersecurity, government contracting, and business development across a larger revenue base.

These potential advantages are especially important in a market where individual products may change rapidly.

The successful autonomous-defense company may not be the one with a single dominant aircraft. It may be the company with an industrial architecture capable of supporting several types of systems while reusing common components, software, communications technologies, manufacturing processes, and supplier relationships.

That begins to resemble a supply chain platform rather than a traditional aerospace program.

Modular Architecture Becomes a Supply Chain Capability

Autonomous systems are evolving much faster than conventional defense platforms.

New processors, sensors, communications technologies, electronic-warfare systems, navigation capabilities, and software functions can emerge within months. A design optimized for one operating environment may quickly require a different payload, communications module, navigation system, or method of avoiding interference.

Manufacturers therefore need product architectures that support rapid change.

A modular design can allow a company to replace a sensor, processor, battery, motor, or communications module without redesigning the entire aircraft. Standardized interfaces can also make it easier to qualify alternative suppliers when a component becomes unavailable or fails to meet cost, security, or performance requirements.

This is both an engineering strategy and a supply chain strategy.

Modularity can reduce dependence on individual components, support multisourcing, simplify product upgrades, and separate stable elements of a platform from technologies that will change frequently.

It can also reduce the disruption created by export restrictions, obsolescence, supplier failures, and sudden increases in demand.

Companies that manage this effectively will be better positioned to balance technological innovation with manufacturability. Those that do not may find themselves repeatedly redesigning products around unavailable components or operating separate, inefficient supply chains for every platform they develop or acquire.

Consolidation Does Not Automatically Create Scale

Acquisitions can create the appearance of industrial scale without delivering it.

Combining several autonomous-system companies may produce a broad technology portfolio, but it can also create duplicated suppliers, incompatible software, fragmented engineering practices, overlapping products, and multiple low-volume manufacturing processes.

The most important post-acquisition work will therefore occur well below the level of the corporate announcement.

Management will need to determine which components can be standardized, which suppliers can support higher volumes, which manufacturing processes can be shared, and which products should remain operationally independent.

It will also need to decide where vertical integration provides a meaningful advantage.

Some components may be strategically important enough to manufacture internally. Others may be better obtained from specialized suppliers. Still others may require domestic or allied capacity that does not yet exist at an acceptable cost or volume.

The strongest consolidators will not simply accumulate technologies. They will rationalize the industrial systems behind them.

That will require common product-development standards, shared supplier data, coordinated sourcing, manufacturing visibility, and disciplined decisions about which platforms continue to receive investment.

Without that integration, a larger portfolio may simply create a larger collection of low-volume supply chains.

Procurement Must Change Alongside Manufacturing

Manufacturers are only one side of the industrial equation.

Government procurement systems must also adapt to a market in which technologies change quickly and production volume may matter as much as the performance of an individual platform.

Traditional defense purchasing can take years to define requirements, evaluate contractors, select a platform, and establish a long-term program. That approach is difficult to reconcile with autonomous systems that may require frequent software updates, component substitutions, or redesigns based on operational feedback.

The fiscal year 2026 budget discussion itself acknowledged the need for more agile funding across unmanned systems, counter-UAS, and electronic warfare because the technologies and available industry capabilities are evolving rapidly.

The challenge is to increase speed without abandoning security, quality, traceability, interoperability, and operational reliability.

That may require shorter purchasing cycles, continuous testing, modular requirements, larger pools of qualified suppliers, and contracts that allow systems to evolve after initial deployment.

It may also require buyers to evaluate vendors differently.

A successful technical demonstration remains important. But procurement decisions may need to place greater weight on production readiness, supplier resilience, component provenance, manufacturing yield, workforce capacity, and the ability to sustain deliveries over time.

The ability to build 100 systems is not evidence that a company can build 10,000.

Domestic Production Is Both an Economic and Security Objective

U.S. policy increasingly treats domestic drone manufacturing as both a commercial-industrial priority and a national-security concern.

A June 2025 executive order called for expanding domestic drone production, reducing reliance on foreign sources, strengthening critical supply chains, prioritizing compliant American-made systems, and securing the supply chain against foreign control or exploitation.

The objective is clear. Execution will be difficult.

Rebuilding domestic capacity involves more than opening final-assembly plants. A drone assembled in the United States may still depend on imported batteries, motor magnets, semiconductor devices, imaging systems, circuit boards, or raw materials.

A durable domestic strategy must therefore look several tiers into the supply chain.

It must identify which dependencies create unacceptable risk, where allied sourcing is sufficient, where domestic production is economically feasible, and where strategic inventories or long-term purchasing commitments may be necessary.

Demand visibility will be essential.

Suppliers are unlikely to invest in new factories, tooling, automation, and specialized labor based on a sequence of small or uncertain contracts. Government customers may need to provide clearer multiyear demand signals while preserving enough flexibility to avoid locking procurement into technologies that become obsolete.

This creates a difficult balance between scale and adaptability.

Manufacturers need stable demand to invest in capacity. Buyers need enough flexibility to incorporate new technology. The industrial model must support both.

The Emerging Competitive Model

The next generation of autonomous-defense companies will compete across several dimensions simultaneously.

They will compete on technology, but also on cost, speed, manufacturability, component availability, software integration, supplier resilience, and production capacity.

They will need to manage product development like technology companies while operating supply chains more like automotive, electronics, or industrial-equipment manufacturers.

That combination will favor companies capable of building common architectures across multiple systems.

It will also favor companies that can convert acquisitions into operational integration rather than allowing each acquired business to remain a separate collection of products, suppliers, engineering standards, and manufacturing processes.

The Ondas-DZYNE transaction is unlikely to be the last of its kind.

As autonomous systems move from specialized programs toward broader deployment, larger companies will continue acquiring technologies, engineering talent, production capabilities, and supplier relationships that would take years to build internally.

But assembling a portfolio is not the same as building an industrial system.

The winners will be the companies that standardize components, rationalize suppliers, design for substitution, integrate manufacturing, and convert rapidly changing technology into reliable production volume.

The next phase of the defense-drone market will not be determined by innovation alone.

It will be determined by who can industrialize it.

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Logistics Viewpoints Expands Its Supply Chain Resource Library

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The growing collection now includes strategic white papers, market-research executive summaries, advisory guides, and supplier visibility programs spanning AI, energy, cybersecurity, transportation, warehousing, and global trade.

As of July 2026, Logistics Viewpoints offers more than two dozen downloadable resources for supply chain executives, technology providers, and industry professionals.

The library has expanded beyond traditional market research to include strategic white papers on emerging operating issues, executive summaries covering major supply chain technology markets, guides to ARC Advisory Group research and advisory services, and commercial programs designed to help suppliers reach a targeted industry audience.

Together, these materials provide a practical starting point for organizations evaluating new technologies, assessing market opportunities, strengthening supply chain resilience, or building greater visibility in the market.

Strategic Supply Chain White Papers

The strategic white-paper collection focuses on issues that are reshaping how supply chains are designed, managed, and governed.

AI in the Supply Chain: Architecting the Future of Logistics with A2A, MCP, and Graph-Enhanced Reasoning

This paper examines the emerging architecture behind enterprise AI systems, including agent-to-agent communication, Model Context Protocol, knowledge graphs, and graph-enhanced reasoning.

Download the AI architecture white paper

AI in the Supply Chain: From Architecture to Execution

The second AI paper moves from architecture to deployment. It explores the decision intelligence layer needed to connect AI systems with enterprise data, workflows, governance, and supply chain execution platforms.

Download AI in the Supply Chain: From Architecture to Execution

Oil & Gas in the Supply Chain

Oil and gas remain critical inputs across transportation, manufacturing, agriculture, chemicals, and industrial production. This paper examines how organizations can build more resilient and responsible supply chains amid geopolitical risk, price volatility, infrastructure constraints, and environmental pressure.

Download Oil & Gas in the Supply Chain

Cyber Resilience in the Supply Chain

This paper examines how organizations can strengthen supply chain resilience against cyber threats that extend across internal systems, connected equipment, suppliers, logistics partners, and technology providers.

Download Cyber Resilience in the Supply Chain

Sustainability in the Supply Chain

The sustainability paper explores how companies can balance environmental goals with operational efficiency, resilience, supplier management, and regulatory compliance.

Download Sustainability in the Supply Chain

Energy in the Supply Chain

Energy cost, availability, and reliability influence transportation, manufacturing, warehousing, and network design. This paper considers how supply chains can better manage energy volatility and changing infrastructure requirements.

Download Energy in the Supply Chain

Connected Vehicles and V2X in the Supply Chain

This paper examines how connected vehicles, infrastructure, devices, and logistics platforms may improve transportation visibility, coordination, and responsiveness.

Download the Connected Vehicles and V2X white paper

Market-Research Executive Summaries

The Logistics Viewpoints library also includes executive summaries of major supply chain software and automation markets. These downloads provide concise introductions to market structure, technology capabilities, adoption patterns, and competitive dynamics.

Available summaries include:

Supply Chain Planning Global Outlook

Transportation Management Systems

Transportation Execution Systems

Warehouse Management Systems

Automated Storage and Retrieval Systems

Autonomous Mobile Robots

Omnichannel Order Management Systems

Global Trade Management Solutions

Global Trade Compliance Systems

Supply Chain Management Market Opportunity

These resources are particularly useful for executives seeking a concise overview before beginning a more detailed technology evaluation or market assessment.

Research and Advisory Guides

Organizations that require deeper analysis can also download guides describing ARC Advisory Group research and advisory services.

Custom Market Research Guide

This guide explains how tailored research can support market sizing, competitive analysis, customer research, technology assessments, and strategic planning.

Download the Custom Market Research Guide

Annual Contract Advisory Service Overview

The annual advisory service provides ongoing access to analysts, market insight, research, and strategic guidance.

Download the Annual Contract Advisory Service Overview

Voice of the Customer Survey Guide

This guide explains how structured customer research can help suppliers understand buyer priorities, customer satisfaction, market perception, and unmet needs.

Download the Voice of the Customer Survey Guide

Standard Market Research Report Guide

This guide outlines the structure, methodology, and business applications of ARC Advisory Group’s standard market research reports.

Download the Standard Market Research Report Guide

Sponsorship and Supplier Visibility Programs

Logistics Viewpoints also offers several programs for technology providers and service companies seeking greater visibility among supply chain executives.

Available program guides include:

Logistics Viewpoints Sponsorship Program

Sponsored Webinar Program

Sponsored Podcast Program

Supplier Spotlight Program

ARC Industry Forum Sponsorship

These programs combine industry content, analyst participation, and targeted audience access to help suppliers communicate their market position and expertise.

A Broader Supply Chain Knowledge Platform

The expansion of the Logistics Viewpoints resource library reflects a broader shift in the publication’s role.

Logistics Viewpoints remains an editorial platform covering supply chain technology, market developments, and operating strategy. The growing download library extends that role by giving readers access to more structured research, strategic frameworks, market summaries, and practical service guides.

Executives can use the library to explore emerging issues such as artificial intelligence, cyber resilience, energy, and connected transportation. They can also access established research on planning, transportation, warehousing, automation, order management, and global trade.

Technology suppliers can use the commercial guides to evaluate available research, advisory, webinar, podcast, sponsorship, and supplier visibility opportunities.

The collection will continue to expand as new white papers, market summaries, and program materials are published.

Readers can visit the Logistics Viewpoints White Papers library for the latest additions.

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