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In most industries, supplychains have become increasingly complex. This complexity has introduced gaps in visibility and responsiveness that traditional systems werent designed to handle. As a result, many organizations are moving toward supplychain orchestration as a structured method for improving coordination.
Jack Fiedler, the vice president for digital transformation of the global supplychain at Lenovo Lenovo is ranked tenth by one leading analyst firm among a list of global companies with exceptional supplychains. Jack Fiedler : We’re unique in the technology industry. That has worked out well for us.
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.
In the rapidly evolving world of global supplychains, interoperability—the ability of systems, devices, and organizations to work together seamlessly—has become a critical factor for operational efficiency. Here’s how each layer translates to the supplychain context: 1. These seven layers are: 1.
Speaker: Brian Dooley, Director SC Navigator, AIMMS
Is your demand forecasting process evolving with the times? Are you satisfied with your level of forecast accuracy? This webinar shares research findings from a recent survey among supplychain planning professionals and delves into the following: Who is typically responsible for forecasting?
The adoption of AI in supplychainautomation is enabling companies to make more accurate decisions, reduce cycle times, and better manage complexity. These capabilities are now being integrated into mainstream TMS, WMS, and ERP platforms.
The industrial sectorparticularly supplychain management, is facing unprecedented complexity. Volatile markets, global disruptions, and the need for real-time insights are pushing traditional systems to their limits. Typically, these systems consist of standard-task agents (e.g.,
I laugh when business leaders tell me that they are going to replace their current supplychain planning technologies with “AI.” Each supplychain planning technology at the end of 2024, went through disruption–change in CEO, business model shift, layoffs, re-platforming and acquisitions.
Why Transformation Is a Boardroom Priority Supplychain management is now a core strategic concern for business leaders. Companies that fail to modernize face supply shortages, revenue loss, and regulatory risks. A data-driven, technology-enabled approach is required to build resilience and efficiency.
Speaker: Eva Dawkins - Senior Consultant, Supply Chain
The last three years have been a rollercoaster ride for most supplychains, filled with volatile unpredictability and frequent disruptions. We know technology improvements can improve supplychain operations and add significant value for companies even in turbulent times.
Frederic Laluyaux, the CEO of Aera Technology, agrees with this assessment. In the supplychain arena, the need to make course corrections is exploding. Masson of ARC points out, “Each AI use case requires specific datasets and may necessitate different tools and techniques.” Business cycles are compressing.
We spoke with CTSI-Global to learn more about their approach to transportation management and the solutions they provide for businesses navigating the complexities of supplychain operations. In summary, CTSI-Global described its approach as a combination of advanced technology, customizable service models, and industry expertise.
In the fast-paced world of modern supplychains, traditional forecasting methods fall short. Advanced supplychain planning is being transformed by probabilistic forecasting , which revolutionizes demand forecasting, supply planning, and inventory optimization.
At ToolsGroup, we’ve long championed probabilistic demand forecasting (also known as stochastic forecasting) as the cornerstone of effective supplychain management software. However, most modern product portfolios aren’t this predictable.
In the fast-paced world of modern supplychains, traditional forecasting methods fall short. Probabilistic forecasting is revolutionizing demand forecasting, supply planning, and inventory optimization by significantly improving forecast accuracy and decision-making across distribution networks.
The supplychain industry is no stranger to uncertainty. 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.
When one thinks of supplychainsoftware vendors, the name InterSystems may not spring to mind. A supplychain data fabric can help companies augment their supplychain processes. They aim to achieve the same success in supplychain management that they have achieved in the healthcare sector.
Enterprise procurement leaders are under more pressure than ever—juggling cost control, compliance, supplier risk, and internal complexity, all while trying to modernize outdated systems. AI, automation, and generative tools are redefining efficiency, allowing procurement teams to move from reactive to proactive decision-making.
It has led supplychain vendors to discuss how they currently use artificial intelligence. Further, virtually every supplier of supplychain solutions is eager to explain the ongoing investments they are making in artificial intelligence. The forecast can be compared to what actually shipped or sold.
However, as carbon taxes and emissions reporting requirements continue increasing, supplychain professionals face mounting pressures from inside and outside their organizations to measure and improve performance against new, nebulous sustainability metrics. Sustainability is high on the list of favorite corporate buzzwords.
The logistics and supplychain industry is a critical component of global trade, responsible for moving goods and materials efficiently to meet consumer and business demands. Retrofitting existing infrastructure with energy-efficient technologies further enhances sustainability efforts.
As artificial intelligence (AI) becomes more integrated into supplychains, companies are focusing on how it can support human workers. 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.
Supplychain disruptions have become a persistent operational risk. Traditional supplychain planning, which relies on historical data and reactive adjustments, is no longer adequate for managing these challenges. Amazon is a leader in AI-driven supplychain management.
I find that most companies’ understanding of supplychain planning is immature, and that next week, at the Gartner SupplyChain Summit in Orlando, that many will don their Mickey ears to discuss what I consider outdated supplychain planning models. How can I improve the process of software selection?
During the two-day event, I participated in various sessions covering a range of topics, including Warehouse Management Systems, Labor Management, Agentic AI, and Warehouse Automation. He highlighted Manhattan’s unified cloud-native platform, which allows for faster innovation and better customer solutions.
Imagine a world where supplychains run with complete transparency, efficiency, and automationwhere every transaction, shipment, and payment are executed seamlessly without intermediaries slowing things down. For decades, supplychain management has encountered bureaucratic bottlenecks, inefficiencies, and trust issues.
Manhattan joins a select group of supplychainsoftware suppliers generating over $1 billion in annual revenue. Manhattan Associates is a leader in two markets, warehouse management systems and omnichannel systems. The company also sells supplychain planning and transportation management solutions.
As global supplychains 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.
Harvard Business Review recently published an article, “ To Build Resilience, CEOs Need to Become Supply-Chain Experts ”. In this article, we wanted to discuss one aspect of supplychain that is often not given enough attention – building strategic relationships and shared value with direct spend suppliers.
They are focusing on how Infor creates value through insights, automation, and process. Automate: utilizes technologies such as RPA, IDP, and IPaaS. RPA automates manual and repetitive tasks. IDP converts paper-based documents into automated digital processes. Infor calls this the Value Void.
Balancing forecast accuracy with inventory management gets more challenging every day. Artificial intelligence (AI) and rapidly developing generative AI tools provide complex, real-time, and in-depth insights specific to supplychain management. This makes it hard to reach agreement.
Demand forecasting has evolved dramatically in recent years. Businesses have shifted from supply-focused approaches to demand-driven models, yet many still struggle to balance accuracy with agility. Traditional forecasting methods often fail under high variability, leading to excess costs, stockouts, and obsolescence.
Demand forecasting has evolved dramatically in recent years. Businesses have shifted from supply-focused approaches to demand-driven models, yet many still struggle to balance accuracy with agility. Traditional forecasting methods often fail under high variability, leading to excess costs, stockouts, and obsolescence.
The global supplychain landscape is undergoing significant transformations, influenced by rapid technological advancements, shifting consumer expectations, and the intricacies of international commerce. Developing Analytical Skills Data analysis is at the heart of effective supplychain management.
As technologies like artificial intelligence (AI) gain traction, the focus has remained on practical applications that yield incremental improvements rather than wholesale infrastructure change. AI is playing an increasingly pragmatic role in optimizing supplychain operations.
Procurement and supplychain management are often used interchangeably—but in practice, the lines between them can blur in ways that create real friction. Misaligned priorities, siloed systems, and unclear ownership can directly impact key performance indicators like cost savings percentage and procurement cycle time.
Gartner predicts that by 2026, 95% of data-driven decisions will be at least partially automated. In fact, Gartner also found that only 10% of CEOs say their business uses AI strategically, and just 9% of technology leaders report having a clearly defined AI vision statement. Yet, many companies struggle to harness AIs full potential.
CONA Services Provides a Common Platform for SupplyChain Collaboration CONA Services LLC is an IT services company owned and governed by the 11 largest Coca-Cola bottlers in North America. CONA is a strategic partner that provides its bottlers with a common set of processes, data standards, and technologyplatforms.
Based on this, a multiple-month financial, supplychain, and capital expenditure plan is produced. A supplychain planning application is the core technology that enables robust planning. Historically, the supplychain plan that resulted from the IBP process was too static. More than 5.6 More than 5.6
Safety Stock: Navigating SupplyChain Volatility Through Strategic Inventory Planning Demand volatility represents a critical challenge for supplychain executives today, with safety stock emerging as a key strategic tool to mitigate market uncertainties.
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 supplychain environment.
Machine learning (ML)a specialized field within artificial intelligence (AI)is revolutionizing demand planning and supplychain management. According to McKinsey , organizations implementing AI-driven demand forecasting solutions can reduce forecast errors by 30% to 50%.
This requires a thorough readiness assessment, selection of appropriate technology, and careful integration with existing business processes. This assessment helps identify whether existing systems can support DPP integration and what upgrades or changes are necessary.
The pace of technological evolution is pushing organizations to the brink. This is more evident in supplychain, where time-tested methods are being replaced with new ones. The groundbreaking technology is transforming how companies manage sales and operations planning (S&OP). Enter Generative AI (GenAI).
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