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Las Vegas, NV – May 2025 I had the opportunity to attend Momentum 2025 in Las Vegas, Manhattan’s annual user conference focused on supplychain and commerce innovation. The environment supports emerging interoperability standards, such as A2A and MCP, and integrates with third-party platforms, including Google Agentspace.
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.
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.
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.
As supplychains adapt to rising complexity, automation has moved from an optional investment to a core operational strategy. Among the most impactful technologies supporting this shift are Automated Guided Vehicles (AGVs) and Autonomous Mobile Robots (AMRs). AGVs vs. AMRs: What’s the Difference?
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.
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.,
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.
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.
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.
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.
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.
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.
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.
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.
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.
Many large organizations have multiple systems for order, warehouse, or transportation management that are barely integrated frequently not at all. These steps include sourcing and receiving inventory, storing inventory, order processing, picking and packing an order, shipping the order, and returns management.
Against a backdrop of US tariff uncertainty and geopolitical instability, European supplychains are backing technology as a key response, with supplychain management software and forecastingtechnologies found to be deployed most widely and the capabilities most likely to generate resilience.
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.
His keynote address highlighted the company’s recent accomplishments, such as the introduction of a new inventory planning solution, substantial investments in research and development, and advancements in artificial intelligence. The company has also focused on AI integration, with AI agents now available on their platform.
If you’re managing inventory with spreadsheets , you’re not alone—but you might be falling behind. In this dynamic environment, inventory management powered by spreadsheets is no longer a viable strategy. Why Spreadsheets Are Failing Inventory Management Excel feels familiar. But familiarity doesn’t equal effectiveness.
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.
Historically, supplychain leaders managed supplychains in a world of abundance. There are many factors: war, supply shortages, climate change, labor (knowledge and availability), and shifts in governmental regulation. The waste included: Negative Forecast Value Added (FVA) in demand planning.
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.
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.
Download Executive Summary Automated Storage & Retrieval Systems (AS/RS) – Cube-based storage, shuttles, unit-loads — we break down the systems revolutionizing storage efficiency. Download Executive Summary Global Trade Compliance (GTC) Systems – Navigate compliance with smarter tech.
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.
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.
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.
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.
In the competitive industrial landscape, efficient spare parts inventory management is crucial to maintaining seamless operations and driving profitability. Spare parts supplychains, however, come with their own set of complexities, requiring targeted strategies and specialized tools to meet these unique demands effectively.
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%.
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.
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
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).
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.
For years, supplychains were engineered to be lean. Recent years have brought a series of disruptions that exposed vulnerabilities in how supplychains are designed. Recent years have brought a series of disruptions that exposed vulnerabilities in how supplychains are designed.
QKS Group , a global advisory and research firm, evaluates vendors for its SPARK Matrix™ based on two key criteria: technology excellence and customer impact. We are honored to be recognized by QKS as a technology leader in their analysis of the retail and supplychain markets,” said Inna Kuznetsova, CEO of ToolsGroup.
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.
Technology can change or even improve work. Companies today making a fundamental mistake: they are attempting to automate current processes with AI versus challenging and redefining work. Today, in supplychain planning, this could not be further from reality. Most companies forecast a single stream with a focus on error.
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