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In the rapidly evolving world of global supply chains, interoperability—the ability of systems, devices, and organizations to work together seamlessly—has become a critical factor for operational efficiency. Technologies like RFID (Radio Frequency Identification) and Bluetooth facilitate data exchange between devices. •
Customs and Border Protection’s systems not fully validating duty calculations on complex lines (which now describes virtually all transactions), brokers face heightened audit risks and potential penalties. When tariff changes happen overnight, brokers need technology that can adapt just as quickly. Compliance Risks : With U.S.
Ted Krantz, CEO of Interos Interos , a company providing supply chain resilience and risk management software, emailed me to say that there was a supply chain risk everyone seemed to be ignoring – AI-related risks. The AI-related risks include data poisoning and model corruption. It is well known that ChatGPT can hallucinate.
The current AI landscape can be viewed as a series of wars,” where companies and organizations are battling for dominance across various technological and market battlefronts. Datacenter Hardware: The demand for powerful computing to train ever larger and more accurate AI models is insatiable.
How Market-Leading Companies Are Navigating Tariff Chaos with GEP’s AI-Powered Procurement Platform breaks down how procurement teams are staying ahead of the chaos with real-time insights, smarter sourcing moves and AI-powered agility.
Frederic Laluyaux, the CEO of Aera Technology, agrees with this assessment. Masson of ARC points out, “Each AI use case requires specific datasets and may necessitate different tools and techniques.” Warehouse management systems rely on RF scans of locations and products. trillion rows of data into the platform. “So
As global supply chains grow more complex and customer expectations skyrocket, Transportation Management Systems (TMS) have become a strategic linchpin for companies aiming to stay competitive. The post Transportation Management Systems: The Digital Backbone of Modern Logistics appeared first on Logistics Viewpoints.
During COVID, this more agile and resilient model allowed the firm to grow their market share. Jack Fiedler : We’re unique in the technology industry. We’ve taken the same hybrid approach from a supply chain technology perspective. I’m responsible for the overall digital transformation, including technology.
I laugh when business leaders tell me that they are going to replace their current supply chain planning technologies with “AI.” Each supply chain planning technology at the end of 2024, went through disruption–change in CEO, business model shift, layoffs, re-platforming and acquisitions. You are right.
Multiple legacy systems prevent procurement from standardizing processes and tracking what they’re spending with each supplier. For global manufacturers, managing direct and indirect material spend can get very complicated very quickly.
Similarly, UPS uses its ORION system, which integrates real-time and historical data to optimize delivery routes, saving fuel and enhancing delivery reliability. Enhanced Efficiency Through Real-Time Data Connected vehicle technology drives efficiency improvements across route planning, driver safety, maintenance, and fuel management.
This complexity has introduced gaps in visibility and responsiveness that traditional systems werent designed to handle. It is not a technology on its own, but rather a process that combines planning, execution, and monitoring through integrated tools and workflows.
CTSI-Global operates at the intersection of logistics and technology, focusing on solutions that address the challenges of transportation management. Designed to integrate seamlessly with enterprise resource planning (ERP) systems through APIs and batch processes, the TMS facilitates smooth data flow and operational efficiency.
Most effective AI implementations today are designed to improve decision-making, reduce routine tasks, and increase operational efficiency through human-in-the-loop systems and decision support tools. Human-in-the-Loop Systems: AI as a Support Layer In supply chain operations, AI is rarely deployed to act independently.
This whitepaper details the following: Key phrases for closed-loop AI software automation The characteristics and impact of the foundation model Core timelines for the implementation of AI-enabled automation
Volatile markets, global disruptions, and the need for real-time insights are pushing traditional systems to their limits. Understanding AI Agents At its core, an AI Agent is a reasoning engine capable of understanding context, planning workflows, connecting to external tools and data, and executing actions to achieve a defined goal.
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 weeks shipping route to their foundational network models. That may sound impossible, but new technology places this capability within the reach of every organization.
AI Deployment in Operational Context Artificial intelligence has become a common feature in supply chain systems, though the depth of adoption varies widely. Smaller enterprises, however, often remain limited to off-the-shelf forecasting tools or point solutions without broader system integration.
Logility, a conservative company supply chain planning technology, historically had no debt and cash reserves of more than 80M, is undervalued in this deal. Aptean is orchestrating the Blue Yonder/E2open/Infor playbook of buying undervalued assets and milking the maintenance and Software-as-a-Service contracts with existing customers.
Drawing on our work with global companies across manufacturing, automotive, pharmaceuticals, semiconductors, software, technology, financial services, and a range of service industries, we outline the key strategic and tactical actions companies are taking to navigate this period of heightened uncertainty.
The sessions provided clear insights into the company’s strategic direction, technology roadmap, and leadership transition—highlighting a focus on platform unification, practical AI deployment, and long-term operational alignment.
Manhattan joins a select group of supply chain software suppliers generating over $1 billion in annual revenue. Manhattan Associates is a leader in two markets, warehouse management systems and omnichannel systems. Manhattan has been on a journey to get all their products on their microservices cloud-native Active Platform.
At this years keynote, Manhattan Associates outlined its current strategic direction, underscoring platform unification, AI integration, and leadership transition. His comments reflected a long-term orientation: technology and strategy are expected to evolve in parallel with shifts in the global supply chain environment.
For professionals in logistics and supply chain management, understanding the implications of this technology is crucial, as it has the potential to fundamentally change the way goods are transported and delivered. These technologies ensure that the vehicle can avoid obstacles, follow traffic rules, and make decisions about its environment.
For decades, operations research professionals have been applying mathematical optimization to address challenges in the field of supply chain planning, manufacturing, energy modeling, and logistics. Are evaluating tools and implementation approaches. Want a high level understanding of typical use cases for mathematical optimization.
In response, many organizations have shifted toward decentralized and regionalized supply chain models, distributing production and sourcing across multiple regions. However, recent disruptions including health crises, trade disputes, logistics bottlenecks, and climate-related events have exposed significant vulnerabilities in this model.
This involves the use of new technologies on their platform. Data fabrics, knowledge graphs, a digital thread, and digital twin technologies are critical. The Need for Speed When you talk to supply chain planning software suppliers, they identify similar trends. The technology is more advanced than the business process.
Among the most impactful technologies supporting this shift are Automated Guided Vehicles (AGVs) and Autonomous Mobile Robots (AMRs). These systems are increasingly used to improve internal logistics, address labor challenges, and support responsive, data-driven operations. AGVs vs. AMRs: What’s the Difference?
When one thinks of supply chain software vendors, the name InterSystems may not spring to mind. They offer softwaresystems and technology for complex integration, rapid application development, and advanced analytics and sell those solutions to companies that need to accelerate optimized business outcomes.
Scenario modeling is emerging as a key capability. To help you start 2021 strong, we updated our popular Buyer's Guide for Supply Chain Network Design Software with research insights and learnings. The Current Technology Landscape: Perceptions on network design technology. What’s inside?
From balancing cost-efficiency with ethical sourcing to enhancing transparency and integrating corporate social responsibility (CSR), businesses face mounting pressure to align their operations with sustainability, technology, and energy practices. The energy sector provides a compelling example of CSR-driven compliance.
One essential tool used by the supply chain team is supply chain design. Building automation is similar to industrial automation, except that instead of controlling a factory, the systems control a building’s entry, power consumption, and lighting. Initially, regions generating lower revenue were modeled.
As I write about the need to rethink how we make decisions with new forms of technology and the definition of a good decision, I turn to the Cynefin model advocated by my friend Trevor Miles. The more I use the model, the more I like it. Let me explain the model counterclockwise. This is the world of best practices.
I find that most companies’ understanding of supply chain planning is immature, and that next week, at the Gartner Supply Chain Summit in Orlando, that many will don their Mickey ears to discuss what I consider outdated supply chain planning models. Business leaders see the open sharing of feedback on software as too risky.
Explore the most common use cases for network design and optimization software. This eBook shares how supply chain leaders leverage their supply chain design software to tackle a variety of challenges and questions. Modeling your base case. Modeling carbon costs. What's inside? Scenario analysis and optimization defined.
Venture capitalists are high on Artificial Intelligence (AI), and over-exuberant professors with shiny new models are jockeying into position to get rich. Building a software company is hard work. Try to gain an understanding of how technological advancements can improve work. I am speaking to many that are ill equipped.
Enter the next generation of warehouse optimization – intelligent systems powered by artificial intelligence (AI) and machine learning (ML). Intelligent systems are fundamentally reshaping the way modern warehouses operate by constantly learning, adapting, and optimizing processes in real time. These arent just buzzwords.
Autonomous systems are becoming an integral part of modern logistics infrastructure. The convergence of robotics, artificial intelligence, and sensor technologies is enabling new levels of automation in both warehouse operations and last-mile delivery. Robotics-as-a-Service (RaaS) models further reduce capital investment barriers.
AI is not a new technology in the supply chain realm; it has been used in some cases for decades. Machine Learning occurs when a machine takes the output, observes its accuracy, and updates its model so that better outputs will occur. Customs uses the same technology to determine which shipments should be denied entry.
This report explores how the state of supply chain network design has changed – including how the tools, maturity models, and market demands are transforming the network design practice. Advanced analytics & Scenario Modeling. This report is useful if you are interested in: Exploring new network design insights and capabilities.
From sourcing and bid evaluation to warehouse slotting and dynamic routing, AI tools support faster and more consistent outcomes by processing large volumes of operational data and identifying patterns that human decision-makers may overlook. These capabilities are now being integrated into mainstream TMS, WMS, and ERP platforms.
Unexpected challenges like shifts in global markets, economic upheaval, commodity shortages, advancements in technology, or environmental changes can send shockwaves through operations in unexpected ways. With the right demand forecasting software and technology, businesses can transform volatility into an advantage.
The global supply chain landscape is undergoing significant transformations, influenced by rapid technological advancements, shifting consumer expectations, and the intricacies of international commerce. These platforms enable learners to engage in collaborative projects that mimic real-world supply chain challenges.
Organizations examine past sales trends, apply seasonal adjustments, and make forecasts based on historical models. When unexpected disruptions occura factory shutdown, a shipping delay, or a supply shortagethese models provide little flexibility. Executives are left making high-stakes decisions with incomplete information.
If the last few years have illustrated one thing, it’s that modeling techniques, forecasting strategies, and data optimization are imperative for solving complex business problems and weathering uncertainty. Experience how efficient you can be when you fit your model with actionable data. Don't let uncertainty drive your business.
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