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Supply chain practitioners seeking the best way to speed decision intelligence, unify supply chain data, and increase operational efficiency can benefit from a supply chain data gateway. Here are 10 ways a supply chain data gateway can improve your performance across the end-to-end supply chain.
Supply chain practitioners seeking the best way to speed decision intelligence, unify supply chain data, and increase operational efficiency can benefit from a supply chain data gateway. Here are 10 ways a supply chain data gateway can improve your performance across the end-to-end supply chain.
The logistics and supply chain industry is a critical component of global trade, responsible for moving goods and materials efficiently to meet consumer and business demands. Addressing Energy Challenges in Logistics The logistics sector is a significant contributor to greenhouse gas emissions.
The company aims to change this with the expansion of its data fabric portfolio. A supply chain data fabric can help companies augment their supply chain processes. Those can include suppliers, contract manufacturers, logistics service providers, customs brokers, governmental agencies, and other participants.
Logistics Service Providers (LSPs) have a lot on their plate. In response to the growing complexity of the modern global supply chain, logistics service providers are embracing digital supply chain solutions powered by new IoT tracking technologies and data analytics. How can the modern LSP stay competitive in the age of IoT?
An organization with tens of thousands of different products may have to move them across many modes of transportation, IT systems, and third-party logistics partners, all adding to complexity, as well as loss of visibility and control. Optimizing fulfillment requires a series of steps to get a shipment from its source to the end customer.
Our daily lives are inundated with data. Supply chain teams face a similar dilemma – companies are overloaded with vast amounts of data, and the ability to sift through the noise and focus on relevant insights has become a critical capability. Why Context Matters Context transforms data into actionable insights.
In “2025’s Top 100 3PLs: How Logistics Giants are Confronting Uncertainty”, Joe Lynch and Seth Clevenger , Managing Editor of Features and Multimedia at Transport Topics, discuss the Top 100 logistics companies, 2024 performance, changes to the list, and the trends impacting the industry. is a native of northwest Ohio.
These are big data platforms that monitor news sources and assorted databases from governments, financial institutions, ESG NGOs, and other sources to detect when an adverse event has occurred or may be about to occur. Most argue that when the UI is trained with the companys own data, the risk of hallucination is small.
Supply Chain & Logistics News Round-Up (October 7th – 11th) This past week, I’ve been playing tourist in London, one of my favorite cities in Europe. The shortage has not impacted Charlottesville’s other major healthcare provider, Sentara Health as this organization sources its IV solutions from a different manufacturer.
Supply Chain & Logistics News January 2nd-6th 2025 The global supply chain never sleeps, and this weeks headlines reveal the fast-moving shifts shaping logistics, trade, and technology. Song of the week: The post Supply Chain & Logistics News January 2nd-6th 2025 appeared first on Logistics Viewpoints.
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.
Supply Chain & Logistics News February 2nd-6th 2025 The global supply chain never sleeps, and this weeks headlines reveal the fast-moving shifts shaping logistics, trade, and technology. Song of the week: The post Supply Chain & Logistics News February 2nd-6th 2025 appeared first on Logistics Viewpoints.
As logistics networks become increasingly complex, the volume of real-time data generated by devices, equipment, vehicles, and facilities is growing rapidly. Edge computing processing data locally, near the source has emerged as a method to address these challenges by reducing latency and improving resiliency.
As the logistics technology sector continues to mature, the number of tools, solutions and platforms that supply chain stakeholders are using (juggling?) This proliferation has made the need for – and lack of – industry data standards all the more acute. are growing too. future may hold.
Schneider Electrics new Environmental Data Program gives logistics professionals unprecedented access to carbon and sustainability metrics, covering over 70% of its product turnover. This move empowers companies to make more informed sourcing decisions, comply with ESG standards, and build greener operations.
Shippers, brokers, carriers, news organizations and industry analysts rely on DAT for trends and data insights based on a database of $150 billion in annual market transactions. He leads a team of market experts who study every facet of the logistics industry to bring the best available insight to customers.
More recently, demand planning applications based on machine learning have improved forecasting by incorporating competitor pricing data, store traffic, and weather data. ML techniques like clustering, data similarity, and semantic tagging can automate master data management.
While past efforts focused on meeting compliance requirements, organizations are now working to proactively embed environmental, social, and governance (ESG) principles into their sourcing, production, and distribution activities. Data collection and verification remain areas of concern. Cost pressures can complicate ESG efforts.
Geopolitical instability, extreme weather, labor shortages, and fluctuating consumer demand regularly impact global logistics. Traditional supply chain planning, which relies on historical data and reactive adjustments, is no longer adequate for managing these challenges. Amazon is a leader in AI-driven supply chain management.
SAP is embedding its generative Joule across the SAP Ariba source-to-pay solution portfolio to make it easier for their customers to manage routine inquiries, such as status updates, summarization, and frequently asked questions. The post Key Takeaways from SAP Spend Connect Live appeared first on Logistics Viewpoints.
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. Since then, supply chain disruptions and volatility have only increased. The Ukraine-Russia conflict is ongoing.
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. Integrate with External Tools and Data: AI Agents can augment their inherent language model capabilities with APIs and tools (e.g.,
Access to Unique Process and Asset Capabilities: Some suppliers offer unique skills, technologies, or processes that are not available in-house or through other sources. Ensuring that collaborative forecasts, VMI and OTIF data is captured through execution platforms and utilized as part of S&OP and S&OE is critical.
This added responsibility for companies will have lasting effects on business operations, corporate partnerships, supply chain logistics, compliance requirements, and data integrity. Regulations requiring Scope 3 emissions data from companies, create an end-to-end value chain reporting issue.
Reducing cost was the primary objective, and most operational decisionsfrom sourcing to fulfillmentreflected that mindset. Leading organizations are building supply chains that are less exposed to single points of failure, more informed by real-time data, and more able to adjust sourcing, inventory, and routing based on current conditions.
Data is the lifeblood of AI in the supply chain. Without sufficient data, AI models can’t uncover meaningful patterns, make accurate predictions, or provide valuable insights for informed decision-making in complex and dynamic environments. At the same time, feeding your AI models too much data can also be a problem.
Source: mainebiz.biz In today’s rapidly evolving logistics and supply chain sector, warehouses are increasingly turning to innovative technologies to gain a competitive edge. Overview of Warehouse Robotics Warehouse robotics represent a revolutionary advancement in the logistics and supply chain sector.
Its a rollercoaster for logistics and supply chain leaders operating in global markets. With deep-tier mapping of supply chains, companies can manage upstream supplier risk and downstream buyer exposure while optimizing alternative supplier sourcing and ensuring trade compliance. Intensifying geopolitical unrest.
Home Introducing Freightos Enterprise: End-to-End Procurement, Benchmarking, and Management Freightos Enterprise unifies market intelligence, tender management, and shipment operations into one solution, enhancing logistics efficiency for large import-export businesses.
“To improve,” the report rightly notes, “organizations should enhance supply chain visibility with robust data and analytics; use AI to foresee disruptions; keep business continuity plans current; and diversify supply sources, suppliers, manufacturing and logistics partners.”
They will handle providing accurate data across their operations, including product sourcing, procurement, and transactions, to name just a few. The post Navigating the Complex Landscape of ESG and Forced Labor Regulations: Insights from IBM’s Conference appeared first on Logistics Viewpoints.
Companies leaning heavily on global sourcing? manufacturer I know saw their import costs jump overnight, forcing a rethink of a decade-old sourcing strategy. Consequently, when shortages emerged, they had already secured alternative sources, thereby averting a significant disruption to production. For example, U.S.-based
Companies find it difficult to fully trust the data from suppliers, complicating efforts to ensure product authenticity, safety, and ethical sourcing. This will enable diamond jewelry consumers at scale to engage with the unique journeys their diamonds have taken from source.
Data fabrics, knowledge graphs, a digital thread, and digital twin technologies are critical. Those stakeholders include planners; supply chain, manufacturing, and logistics executives; sales and marketing; finance or regional or business unit leaders; and suppliers and other partners. Pradhan ex-claimed.
This year, a recurring theme that I saw was about using supply chain data to improve the customer experience across the entire value chain. Here are the ones that stood out to me, especially as it relates to supply chain data. The single data cloud runs on Snowflake, one of Blue Yonder’s partners.
Edge Hardware: The battle for edge hardware also intensified in 2024, as companies sought to deploy AI capabilities closer to the source of data. ChatGPT Search : This feature gives users a way to get answers from relevant web sources.
Businesses will need to ensure accurate data reporting across core operations such as sourcing, procurement, and transactions. For use cases like tariff calculation, a large data model can be implemented using public cloud architecture with proper permissions. Consequently, demand for robust GTC solutions will continue to rise.
Our daily lives are inundated with data. Supply chain teams face a similar dilemma companies are overloaded with vast amounts of data, and the ability to sift through the noise and focus on relevant insights has become a critical capability. While the abundance of data is seen as an asset, the real question is: What do you do with it?
A data-driven, technology-enabled approach is required to build resilience and efficiency. The COVID-19 pandemic and ongoing geopolitical shifts demonstrated the risks of relying on single-source suppliers and minimal inventory buffers. Walmart is also implementing AI-driven logistics and procurement.
It brings data that is stored in different silos across an organization all into one model. With the advent of true “single source of truth” inventory visibility , a digital twin is a more feasible goal than ever before. Are you a manufacturer wondering how best to leverage real-time data to elevate your business performance?
Supply chain and logistics functions have been one of the most volatile in the global economy of the last four years. Source: J.P. The World Trade Organization publishes lots of insightful data on global trade – including trade indexes. Output rose in 8 of the 29 nations for which data was available.
Home No More Black Swans: The Age of Supply Chain Uncertainty Freightos Enterprise unifies market intelligence, tender management, and shipment operations into one solution, enhancing logistics efficiency for large import-export businesses. What’s become increasingly clear is that there are no more black swans in global logistics.
That’s where data analytics comes in. It’s the key to transforming your supply chain from a source of frustration into a well-oiled, profit-generating machine. Modern supply chains thrive on real-time data, execution-focused applications, and dynamic decision-making. Ready to get started? Let’s dive in.
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