This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
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.
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.
What is needed is a practical, scalable way to unify supply chain data across systems, make it useful in real time, and apply intelligence, whether from algorithms, machine learning models, or a trained human eye, to act on it quickly. Using Data Fabric Studio, the team: Mapped and validated key identifiers (like DUNS numbers) across systems.
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.
This GEP-sponsored report will show you how to leverage data for a collaborative supply chain that delivers results and how to future-proof supply chain management strategies. The C-suite is laser-focused on supply chain performance.
If your systems are disjointed and you lack the ability to analyze masses of data in real time, you will struggle to deliver on-time, in-full and your reputation and revenue will be negatively impacted. A good fulfillment strategy can help businesses boost customer satisfaction (CSAT), reduce inefficiencies, and increase sales.
manufacturer I know saw their import costs jump overnight, forcing a rethink of a decade-old sourcing strategy. A Fortune 500 retailer, for instance, reduced its procurement cycle time by 30% by leveraging an AI-driven tool to analyze supplier data efficiently.
Home Making Logistics Data Actionable: Insights from Freightos and Gryn July 7, 2025 Blog Data is the backbone of efficient decision-making. However, transforming raw data into actionable insights remains a significant challenge for many logistics organizations. That’s the reason why you are collecting data.”
Strategies that worked just a few years ago are now too rigid, manual, or disconnected to keep up. But what does it actually take to regain control and build a procurement strategy that’s both resilient and scalable? How do you begin developing a procurement strategy?
Karan delves into two critical areas: material waste and data waste. He discusses how material waste impacts costs and efficiency, and the often-overlooked issue of data waste—where valuable data is not captured, leading to inefficiencies in managing inventory and operations.
Strategies that worked just a few years ago are now too rigid, manual, or disconnected to keep up. But what does it actually take to regain control and build a procurement strategy that’s both resilient and scalable? How do you begin developing a procurement strategy?
Are you still relying on outdated data to guide your inventory decisions? Gartner reports that companies using data-driven strategies can achieve a 20% increase in sales by aligning inventory with current market trends. Is this the strategy you want to pursue? Are you ready to transform your inventory strategy?
To stay ahead, you need a clear strategy for understanding and forecasting these charges. That's why a fuel surcharge strategy is crucial for shippers. If Carrier A consistently charges less than Carrier B for the same routes, use that data in your next rate negotiation. With so many variations, you can't afford to guess.
These sensors capture precise data on factors like location, speed, fuel usage, and driver behavior, transforming fleet management from reactive to data-driven decision-making. The IoT data allows managers to detect inefficiencies, predict maintenance needs, and even assess driver performance.
Speaker: Karan Talati: CEO and Co-Founder of First Resonance
Join Karan Talati, CEO of First Resonance and former SpaceX Manufacturing Engineer, in this on-demand webinar to learn how leading manufacturers are: Navigating tariffs with data-driven supply chain strategies Leveraging automation and AI to eliminate bottlenecks Building resilience with predictive supplier management Adapting flexible strategies to (..)
Data collection and verification remain areas of concern. Legacy procurement systems pose challenges, as they were not designed to capture and manage ESG-related data. Addressing the Challenge: Practical Approaches Organizations making progress on ESG-driven supply chains are employing several practical strategies.
Kara is the Founder and CRO of LeadCoverage , the premier B2B marketing and PR firm dedicated to helping logistics companies increase lead generation through targeted marketing strategies and media coverage. Kara’s new book “The Revenue Engine” offers readers a guide to effective revenue-generating strategies.
From geopolitical instability to labor shortages and sustainability demands, supply chain leaders must continuously evolve their strategies to stay competitive. Logility embeds AI directly into its solutions, helping businesses to go beyond basic data analysis, and enables those businesses to take actions they might not have anticipated.
That’s where data analytics comes in. Modern supply chains thrive on real-time data, execution-focused applications, and dynamic decision-making. In this post, we’ll explore how data analytics can revolutionize your supply chain. Demand Forecasting: Analyze past data to predict future needs.
Speaker: Jason Chester, Director, Product Management
In today’s manufacturing landscape, staying competitive means moving beyond reactive quality checks and toward real-time, data-driven process control. But what does true manufacturing process optimization look like—and why is it more urgent now than ever?
Key strategies include: Electrification of Transport: The use of electric vehicles (EVs) for freight and last-mile delivery reduces emissions and operational costs. Blockchain also facilitates collaboration by sharing verified data across stakeholders. Immutable records enable accountability throughout the supply chain.
Resilience is the ability to respond to disruption while maintaining core operations, and more companies are shifting their strategies accordingly. Sudden tariff increases can quickly make a cost-optimized procurement strategy untenable, leaving companies scrambling to adjust. Finally, rigid fulfillment networks compound the problem.
By developing strategies for design, supply, production, distribution, and inventory, planning provides a foundation for product innovation and plays a key role in product simplification and SKU rationalization. Traditional supply chain infrastructures, built to serve brick-and-mortar markets, are being strained by e-commerce.
Traditional supply chain planning, which relies on historical data and reactive adjustments, is no longer adequate for managing these challenges. AI as a Predictive Tool AI-driven supply chain planning integrates machine learning, real-time data analytics, and external risk monitoring to anticipate disruptions before they materialize.
From new pricing strategies and material substitutability to alternative suppliers and stockpiling, a new GEP-commissioned Economist Impact report reveals that enterprises are adopting a variety of approaches underpinned by data and technology.
Treating suppliers as essential partners in the field of direct spend management—almost like customers—can be a key component of a successful company strategy. Market Intelligence: Suppliers often have access to valuable business and supply market intelligence, which can inform a company’s strategy especially in the area of direct spend.
As supply chains adapt to rising complexity, automation has moved from an optional investment to a core operational strategy. 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?
Physical Layer: Transmits data over a physical connection. Data Link Layer: Handles data transfer between connected nodes. Network Layer: Manages data routing. Transport Layer: Ensures dependable data transfer. Presentation Layer: Translates between data formats. These seven layers are: 1.
With companies importing raw materials, components, and finished products, rising tariff rates and customs duties can erode profit margins and disrupt business strategies, especially given the reliance of U.S. By Jackson Wood , Director of Industry Strategy, Global Trade Intelligence at Descartes.
Learn from historical examples and modern approaches to innovation while uncovering how AI and real-time data can automate processes, strengthen supply chain operations, and ensure scalability. This session offers practical strategies to optimize operations, mitigate disruptions, and achieve industrial excellence.
Others had already pressure-tested their supply chain strategies for moments like this. Scenario modeling, running what-if simulations to stress-test sourcing, pricing, and inventory decisions, has become a cornerstone of supply chain strategy. When the latest wave of U.S. tariffs hit, some companies scrambled. They’re the norm.
To truly build resilience across the entire organization — including supply chain and logistics — businesses need to remove the internal silos that can lead to restricted data flow and collaboration. AI allows suppliers to review data in real time, so they can stress-test scenarios, make changes and tweak their responsiveness.
Their use reflects, and reinforces, a shift toward more agile, data-driven logistics in food retail. From a supply chain perspective, pricing becomes more than a marketing lever, it becomes a live data signal. This can lead to a reevaluation of warehouse strategy. Others may increase buffer stock for high-turnover items.
In an age where supply chains stretch across continents and rely on increasingly complex data streams, the ability to present data clearly and effectively is no longer a luxury—it’s a strategic necessity. Yet, even with the right data, poor communication often leads to poor execution.
Behind every AI breakthrough lies a battle for resources: data centers, compute hardware, power, and telecom infrastructure. And right now, even tech giants are hitting a wall. Our latest white paper reveals the six critical supply chain elements that are increasingly separating AI leaders from the rest.
Backup Data & Systems: Use a 3,2,1, strategy to back up data. Have 3 copies of your data, in 2 geographically dispersed locations, and 1 location off of your network. When that does happen, you’ll want to do anything to restore your data. Just as you are.
The increasing frequency of disruptions, whether due to natural disasters, pandemics, or geopolitical tensions, underscores the urgent need for robust supply chain strategies. This includes the adoption of cloud product lifecycle management (PLM) technology for enhanced data visibility and flexibility.
Machine learning improves the vehicle’s performance by analyzing data from past deliveries and refining its operations. Cloud Computing: The data collected by ADVs is processed through cloud platforms, enabling real-time communication, route adjustments, and fleet management.
The law mandates the Forced Labor Enforcement Task Force to develop strategies for enforcement and requires importers to provide clear evidence that their supply chains are free from forced labor. They will handle providing accurate data across their operations, including product sourcing, procurement, and transactions, to name just a few.
This eBook highlights how data-driven strategies empower marketing campaigns through personalization tactics. Here’s what’s covered: How data-driven marketing drives the customer experience. Understanding marketing strategy & performance. The most challenging obstacles to data-driven marketing success.
Given the companys position in the market, the company is capable of executing the business strategy that delivers their vision to customers. The products and services were focused around the idea of cognitive solutions delivered by the Blue Yonder Platform that is built on Snowflakes AI data cloud.
Edge Hardware: The battle for edge hardware also intensified in 2024, as companies sought to deploy AI capabilities closer to the source of data. These developments help enable real-time data processing, reduce the reliance on cloud connectivity, and democratize access to advanced AI technologies in industrial and robotic contexts.
In “Navigating the Numbers: Tariffs, AI, and The Future of Supply Chains”, Joe Lynch and Corey DeSantis , BDO’s Logistics and Transportation Subject Matter Expert, discuss the evolving landscape of global trade, the transformative power of artificial intelligence, and strategies for building resilient supply chains for tomorrow.
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 is responsible for driving strategy, customer engagement, and industry analysis.
It's quite a process for marketing teams to develop a long-term data management strategy. It involves finding a data management provider that can append contacts with correct information — in real-time. Not just that, but also ongoing data hygiene efforts to keep the incoming (and existing) information fresh.
We organize all of the trending information in your field so you don't have to. Join 102,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content