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Champions Radar – Decarbonization Technologies for the Chemical Industry

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Champions Radar – Decarbonization Technologies For The Chemical Industry

As the pressure mounts yearly for the chemical industry to become more sustainable, more companies are defining net-zero objectives and clear decarbonization plans. Major chemical companies have set clear plans to heavily reduce their carbon footprint by 2030 and reach net-zero by 2050. The industry will certainly go through deep changes in the upcoming decade to achieve this. In this context, companies are looking for trusted solution providers that can help them design the most efficient plan and support them in the transition to ensure adoption of the new technologies.

To address this complex challenge, ARC has explored the requirements of the market and mapped it with the solutions that leading automation companies are providing. The aim of this study is to understand how well these companies are fulfilling the need for increased sustainability in the chemical industry.

More than twenty companies were analyzed. Three are the leaders in the market as they cover most of the challenges facing chemical companies to achieve their decarbonization objectives. There are also other leaders focused on specific solutions which we believe are critical as well.

Value and process of Champions Radar

The Champions Radar aims to map solutions provided by companies to meet specific market needs, helping end users identify suitable providers and highlighting market leaders. For solution providers, it offers insights into their market position, strengths, weaknesses, and growth opportunities. The study starts by discussing challenges with end users, understanding their needs, and mapping those to the offerings of solution providers.

After gathering and validating information, the solutions are evaluated against key indicators, combining capabilities, experience, and revenue to create the final Champions Radar.

Champions Radar for Decarbonization Technologies in Chemical Industry

The study covered topics related to decarbonization roadmap, energy efficiency, fugitive leaks, by-product treatment, energy transition, carbon capture, alternative feedstocks and treatment at the end of life. Major automation companies were considered in the analysis by exploring their value proposition in terms of what hardware, software, and services they provide to the industry. The following are some quick reflections:

Three leaders in the industry: Siemens, Schneider Electric and Emerson.

Aspen Technology is very well established in the chemical industry as a software provider for process optimization.

Most of the companies covered in the scope are focusing on process efficiency and many on energy efficiency

The challenges with the largest impact

In order to reach net-zero, companies in chemical industry are focusing on Scope 1 and 2 for the next 5 years. These emissions are related to those directly emitted in the facility and the ones emitted by the energy that is purchased, which was generated through fossil fuels. But in reality, more than 75% of the emissions linked to this industry is related to Scope 3, which includes all the sources not included in the Scope 1 and 2, and that are involves the whole value chain of the product.

Two applications were considered in the scope of the study which are related to Scope 3: utilization of alternative feedstocks, and treatment at the end of life.

Companies like Schneider Electric through AVEVA, or Siemens through its software solution GProm are offering digital tools that enable companies to model new feedstocks and anticipate the effect of the usage of recycled resins or bio feedstocks in their process.

Solutions related to advanced recycling were also found. Honeywell UOP, for example, offers their own advanced OpCycle Process, which introduces a revolutionary plastics recycling technology to drive a circular economy. Software company Aspen Technologies has plenty experience in the chemical industry and offers specific models related to advanced chemical recycling, which helps end users to simulate pyrolysis processes, accelerate design and increase performance of plants.

Concluding Thoughts

Plastic circularity is a complex challenge by itself and it will have the largest impact on reaching net-zero. Digital circularity tools are needed to help companies move forward: green supply chain, digital passports and blockchain are some of the technologies that will enable companies to accelerate the adoption of this new approach.

At ARC, we are planning to develop a new champions radar focused on Plastic Circularity, and those digital tools that end users are looking for. We encourage everyone that is interested in this topic (end users and solution providers) to contact us and explore together how can you contribute to this study.

Do you want to receive more detailed information related to the Champions Radar on Decarbonization Technologies for the Chemical Industry? Don’t hesitate to contact us!

Luciano is part of the European process team at ARC, covering topics related to sustainability and is located in ARCs offices in Germany.

At ARC, Luciano assists companies in enhancing their asset performance while emphasizing sustainability. His responsibilities involve leading market research focused on sustainability and supporting asset owners in identifying optimal technologies to address their decarbonization challenges.

The post Champions Radar – Decarbonization Technologies for the Chemical Industry appeared first on Logistics Viewpoints.

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

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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.

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Walmart and Symbotic: When Warehouse Automation Becomes a Network Strategy

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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.

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Walmart and Symbotic: When Warehouse Automation Becomes a Network Strategy

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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.

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