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Home Making Logistics Data Actionable: Insights from Freightos and Gryn July 7, 2025 BlogData 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.”
D rayage carriers and brokers face the following challenges: Operational Inefficiencies & Lack of Real-Time Visibility:Difficulty managing complex drayage processes and tracking critical information (containers, status, appointments) leads to wasted time, errors, and increased costs.
If youve followed our blog over the years, youll know that weve shared lots of information about distribution network design, why its vital to get it right, how long it should take, the importance of reviewing the network every so often, and various elements of design such as determining the number of warehouses and where to locate them.
Modern Communication: Replacing Outdated Systems with Agile Tools For years, logistics ran on Electronic Data Interchange (EDI), a system built on rigid standards that required every trading partner to use the same technical language. Looking Ahead The future of logistics will revolve around data, speed, and intelligence.
This is the concept behind Lean Logistics, an approach focused on eliminating waste and increasing efficiency : What is Lean Logistics? Optimization: An important goal is continuous improvement and being attentive to correcting errors. Standardization: Investing in efficient practices to eliminate waste, rework, and delays.
Solution: Use data-driven forecasting to predict demand as accurately as possible. By leveraging predictive analytics and a just-in-time (JIT) inventory model, you can maintain optimal stock levels, which reduces storage costs and cuts down on waste from unsold items. Ready to optimize your supply chain?
Successfully navigating the shift to onshoring or nearshoring requires transparent communication throughout supply networks as well as data-driven decision-making processes and an organizational culture that embraces change rather than resists it.
For third-party logistics (3PL) providers, this shift presents a valuable opportunity to help clients turn returns into revenue through smarter operations, better data, and strategic partnerships. Data-Driven Return Management Technology plays a major role in unlocking the revenue potential of reverse logistics.
Real-time data With technologies such as the Internet of Things (IoT) , data creation is happening at an exponential rate, meaning that manufacturing in the 21st Century isnt so much based on gut-driven decisions anymore but rather on data. It eliminates duplicate work and ensures everyone works from the same accurate data.
In this blog, we break down the real benefits of TMS automation, and why it’s a game-changer for brokers looking to grow faster, operate leaner, and deliver a better customer experience. Instead of chasing down documents or checking multiple systems, your team is focused on moving freight and solving problems in real time.
Bayer invested in a logistics platform that integrates supply chain data and communication across internal teams and developed a catalog of strategies to be deployed in the event of a range of disruption scenarios.
Strategic moves like bulk buying, closer supplier partnerships, and syncing procurement with supply chain planning can tighten inventory, cut waste, and free up cash. A Fortune 500 retailer, for instance, reduced its procurement cycle time by 30% by leveraging an AI-driven tool to analyze supplier data efficiently.
AI systems get better and more accurate as they collect and analyze more data. ML is a form of AI that enables a system to learn from data rather than through explicit programming. ML is a form of AI that enables a system to learn from data rather than through explicit programming.
Manufacturers have started implementing features of the Fourth Industrial Revolution (4IR) to be more flexible and responsive and make more intelligent, data-driven decisions. Supply chain optimization IoT data can be used to optimise supply chain operations, including transportation, warehousing, and distribution.
Imagine an e-commerce company running a Black Friday sale and running out of a top-selling item due to outdated stock data. Real-time inventory tracking ensures that as soon as an order comes in, your team has accurate data on product availability, streamlining the entire fulfillment process.
This blog provides tips and resources on how to lay the foundation for a long-term, productive and cost-effective 3PL freight services partnership! Make data-backed decisions using real-time shipping insights. What are your recommendations for cutting shipping costs or reducing waste?
The 2023 data shows road carriers handled the turbulence better than any other mode , yet booking a truckload often still means phoning four brokers before lunch, four more after, and a few more before the shifts over. The post The Domestic Freight Wave&Why Instant FTL Quotes Matter appeared first on Freightera Blog.
A good 3PL provides transparent pricing and detailed analytics so you can: Understand your cost drivers Uncover areas to cut waste Budget with greater accuracy Real-time risk monitoring Your 3PL should track global news, weather and supply chain trends daily.
It’s the freight shipping platform that allows you to: Make informed decisions based on real data Significantly reduce operational costs Improve your customers’ experience with more efficient deliveries Ready to transform your logistics? No more wasted time. Get your first free quote in less than 2 minutes.
In our previous blog, we explored how matrices enhance supply chain efficiency, from inventory management to logistics. By leveraging these technologies, businesses can optimize operations, reduce costs, and make smarter, data-driven decisions. Now, were taking it a step further. In case you missed it! Read More In case you missed it!
Turning food and beverage challenges into opportunity For food and beverage manufacturers, success comes down to getting the right food products to the right place at the right time, all while reducing waste and despite wafer-thin margins.
Route Optimization Overview AI-powered route optimization analyzes multiple factors, like traffic patterns, weather forecasts, and delivery data, to create the most efficient routes in real time. Demand Forecasting Overview Accurate demand forecasting is key to reducing wasted resources and cutting last-mile delivery costs.
That said, most brokers won’t have the time or team to consistently publish blogs or case studies—and that’s okay. CRM Data and Old Contacts Revisit old quotes, inactive accounts, and partially worked leads. CRM Data and Old Contacts Revisit old quotes, inactive accounts, and partially worked leads. Follow through.
This integration enables automated order processing workflows, reducing manual data entry and expediting fulfillment. Integration with eCommerce Platforms: The fulfillment operations are seamlessly connected with major eCommerce platforms like Shopify , WooCommerce, and BigCommerce.
Their CEOs agreed, and technology leaders began channeling new resources into the data foundations necessary not only for supply chain analytics, but for the artificial intelligence surge now upon us. This “never waste a crisis” mentality has created a growing divide between the corporate data haves and have-nots.
The Benefit: Faster clearance, reduced delays for time-sensitive shipments, and reliable transit data. The Dedola Advantage: We integrate with digital port systems and leverage real-time data feeds, ensuring your shipments benefit from smart infrastructure efficiencies with timely updates.
To meet this moment, health systems must adopt a more resilient, transparent, and data-driven approach, powered by digital transformation. It is the strategic reinvention of how a health system operates, how it collects and uses data, how it integrates across departments, and how it delivers care in a dynamic environment.
It enables manufacturers to make decisions about production schedules, inventory management, quality control and more, all based on live data. AI facilitates real-time decision making by processing and analyzing data at a speed that far surpasses human capability. Powering growth through smart, data-driven manufacturing.
An effective ERP strategy will help to leverage AI and machine learning so that manufacturers can better analyze real-time data to streamline processes, cut down on waste and boost overall productivity. The post ERP Strategies for Manufacturers appeared first on SYSPRO Blog.
With an extensive background in technology and social media dating back to 1991, Tom has co-founded an Irish software development company, a social media consultancy, and the hyper energy-efficient data center, Cork Internet eXchange.
Editor’s Note: This is a guest blog post from end-to- end global supply chain services company, Flash Global. The company focuses on high tech industries such as telecome , data storage, data centers, bio-medicine, and any company who needs supply chain visibility and proactive supply chain services for replacement parts and more.
This means faster deliveries, lower costs, and less wasted space for everyone involved. Eliminating Inefficiencies: Onward’s data-driven platform tackles the inefficiencies of traditional big and bulky delivery. Their platform optimizes routes and matches loads efficiently, reducing empty miles and fuel consumption.
We continue our "Most Popular Blog Posts of 2015.So So Far" series today highlighting supply chain blog posts. On the Cerasis blog, our goal is to offer tips, news, best practices, and trends so you, the reader, find a lot of value in our expertise. Most Popular Supply Chain Blog Posts from the Cerasis Blog for 2015 So Far.
Editor's Note: Today's blog comes from Katie Cruze at considerdigital.com who give us the top 5 reasons why data quality is important. Data, for most companies, is often collected for record-keeping purposes. For many companies, managing the quality data can seem like an overwhelming task.
What is Machine Learning ML is the computing engine behind AI and gives computers the ability to make sense of, and learn, from data to perform specific tasks without manual interference. Nine areas where AI can help manufacturers There are several ways in which data and AI can be applied in the manufacturing industry. The Industry 4.0
The manufacturing industry is currently undergoing a rapid digital transformation, and as a result, companies are generating vast amounts of data. Unfortunately, without proper processing and analysis, this data is of little use to the organization. This can lead to improved quality, reduced waste, and optimized production processes.
Wasting resources and assets cost managers a pretty penny. Fortunately, smart data utilization can help reduce deadheading occurrences and make the entire supply chain more profitable. Waste matters in the shipping industry because every instance leads to higher freight costs. And it’s essential to understand why. .
What you will learn in this blog: Leveraging Data Analytics For Invaluable Insights Implementing Lean Principles for Waste Reduction Effective Management Of Supply Chain Costs As companies navigate market fluctuations and challenges, effectively managing supply chain expenses becomes pivotal for success.
Businesses are continuously trying to find ways to maximize productivity and reduce waste to remain competitive in the global marketplace. Lean manufacturing is a production process that is based on maximizing productivity while simultaneously minimizing waste within the manufacturing operation. What is lean manufacturing?
Data-driven analytics enables you to make cost-effective transportation decisions. However for most shippers, parcel spend is poorly understood because shipping data is often locked up in point solution silos, such as carrier-provided systems and websites, in a variety of different formats. But no longer.
Small but meaningful at scale: Sometimes orders are canceled, and if you pick a method and print the label up stream, you are wasting money on canceled orders. The importance of data. But a key insight for us in the ecommerce supply chain domain was the importance of data.
Big data and predictive freight rates in the digital supply chain are nothing new. Nearly all shippers, brokers and carriers collect and use data to derive insights, including predictive rates. Unfortunately, the most robust applications of that data will quickly diminish in value as data ages. Download the White Paper.
Reporting requires businesses to collect and track data on their ESG performance and report this information in a transparent and consistent manner. This involves implementing processes and systems for collecting and reporting on data, and some businesses may need to ensure that the information is verified by a third party.
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