Connect with us

Non classé

Making Logistics Data Actionable: Insights from Freightos and Gryn

Published

on

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. In a recent webinar, Freightos’ Oliver Esch and Oliver Ritzmann from Gryn shared their expertise on overcoming data challenges and leveraging technology to drive smarter logistics operations. Below, we dive into their key takeaways and explore five practical ways to make your logistics data actionable, with insights grounded in industry trends and high-authority sources.

The Logistics Data Challenge

The logistics sector is awash with data, from shipment volumes and freight rates to sustainability metrics and supplier performance. Yet, as Esch highlighted, even global companies struggle with data harmonization. Disparate systems, such as Warehouse Management Systems (WMS), Transportation Management Systems (TMS), and Enterprise Resource Planning (ERP) platforms, often operate in silos, resulting in inconsistent data formats and poor data quality. For example, variations in country codes (e.g., “UK” vs. “GB”) or port codes for cities like Shanghai create confusion and erode trust in data reliability.

“The challenges are to harmonize different logtech or systems they are using today, especially in the world of WMS, TMS, ERP, and real-time visibility solutions. So there are so many standalone solutions in different companies.”

– Oliver Esch, VP Commercial, Enterprise Shippers | Freightos

Ritzmann echoed this sentiment, noting that even large enterprises with robust data lakes often fail to utilize them effectively due to low data quality or complex systems.

“You really need to make [data] actionable… use it to manage your suppliers, to drive supply chain improvements. …strive for cost savings and to increase supply chain performance. That’s the reason why you are collecting data.”

– Oliver Ritzman, Founder & CEO | Gryn

According to a 2023 McKinsey survey, 87% of shippers have maintained or increased their technology investments since 2020 to address challenges such as cost management and data integration, underscoring the critical role of technology in enhancing logistics efficiency. Freightos and Gryn are tackling these challenges head-on, with Freightos processing over 200 million data sets monthly for air and ocean freight and Gryn enabling scope 3 emissions reporting aligned with ISO 14083 and the GLEC framework.

Five Ways to Make Logistics Data Actionable

Esch and Ritzmann outlined five key strategies to transform logistics data into a strategic asset. These approaches, rooted in their extensive experience, can help organizations streamline operations, reduce costs, and enhance sustainability.

1. Define a Clear Purpose for Your Data

Collecting data without a clear objective is inefficient. Ritzmann emphasized the need to align data collection with specific business goals, such as procurement optimization, sustainability reporting, or supplier performance management. For instance, Freightos Terminal enables shippers to benchmark rates and track market trends, while Gryn’s platform supports decarbonization by aligning with regulatory standards, such as the Greenhouse Gas Protocol. By focusing on purpose-driven data, companies can avoid wasting resources on metrics that are not utilized.

2. Prioritize Critical Data Sets

Not all data is equally valuable. Esch cited a study by a U.S. university, presented at an FNL freight forwarder event, which found that 80% of the data collected in procurement events goes unused. To avoid this, companies should identify critical data points, such as transit times, supplier ratings, or carbon emissions, and streamline collection processes. Freightos Enterprise streamlines this process by offering modules for procurement, market intelligence, and booking, ensuring that only relevant data is prioritized.

3. Ensure Data Quality and Consistency

Poor data quality undermines decision-making. Ritzmann highlighted common issues, such as inconsistent country codes, date formats, or missing weights, which AI can help address by cleaning and structuring the data. According to Gartner, poor data quality costs organizations an average $12.9 million annually. Freightos and Gryn leverage AI to harmonize data, ensuring accuracy for tasks like invoice verification, where Esch noted that nine out of ten invoices contain errors.

4. Connect Data Sources for Actionable Insights

Fragmented data sources hinder visibility. Esch advocated for integrating systems, such as benchmarking tools, visibility solutions, and sustainability platforms, to create a single source of truth. For example, Freightos integrates with real-time visibility providers to track shipments and validate supplier performance, while Gryn connects shipment data to sustainability metrics. This holistic approach enables real-time decision-making, such as issuing spot requests when market trends shift, as supported by Freightos’ procurement tools.

5. Measure and Communicate Success

Data is only valuable if it drives results. Ritzmann stressed the importance of measuring outcomes, such as whether booked volumes align with tender awards or if sustainability initiatives deliver promised carbon reductions. Gryn’s upcoming AI-based supply chain optimization tool, set to launch in September 2025, will provide recommendations for cost and carbon savings, accompanied by clear metrics to demonstrate success. Communicating these results through executive dashboards or shareable reports ensures stakeholder buy-in and drives continuous improvement.

The Role of AI in Logistics Data

AI is transforming logistics by enabling data cleansing, predictive analytics, and automated workflows. However, both speakers cautioned that AI’s effectiveness depends on high-quality data.

Ritzmann shared that Gryn’s next release will include an AI-based report and chart builder, allowing users to generate performance reports or hotspot analyses with simple prompts.

Freightos, meanwhile, utilizes AI to enhance its rate management capabilities, enabling shippers to make informed decisions about procurement.

However, Esch noted that reluctance to share data remains a barrier, underscoring the need for secure, private cloud solutions like those offered by Freightos and Gryn.

Data-Driven Logistics in 2025 and Beyond

The logistics industry is at a turning point, with regulatory changes such as the EU Data Act and e-invoicing laws mandating improved data sharing and transparency. These developments align with Freightos and Gryn’s mission to simplify data flows and empower organizations to act swiftly on market trends. As Esch noted, “Just start now. Whatever data you have can be improved over time.” This pragmatic approach, combined with advanced platforms, positions companies to navigate volatility and achieve long-term success.

By embracing these five strategies and leveraging platforms like Freightos and Gryn, logistics professionals can harness data as a powerful tool to enhance efficiency, sustainability, and cost savings. Start your data journey today and unlock the full potential of your supply chain.

Jude Abraham

Jude Abraham is Freightos’ Content Marketing Lead, a seasoned high-tech storyteller and marketing strategist who has created award-winning content for global brands. Off the clock, Jude revels in the complex flavors of spicy curries, savors the balanced notes of an Old Fashioned, and spends countless hours indulging his fascination with ancient esoteric books.

Put the Data in Data-Backed Decision Making

Freightos Terminal helps tens of thousands of freight pros stay informed across all their ports and lanes

The post Making Logistics Data Actionable: Insights from Freightos and Gryn appeared first on Freightos.

Continue Reading

Non classé

Last Chance: Join the Webinar on AI, Component Sourcing, and the Future of Procurement

Published

on

By

Electronic component sourcing is becoming one of the most important cost and risk challenges facing manufacturers.

Pricing remains opaque. Supplier quotes do not always reflect true market pricing. Internal purchase history may show what a company paid, but not whether that price was competitive.

At the same time, chips and components are increasingly tied to geopolitics, tariffs, AI infrastructure, defense demand, electrification, industrial automation, and supply chain resilience.

The webinar is tomorrow at 11 AM ET. Register now to join ARC Advisory Group’s discussion, The Hidden Cost of Component Sourcing — and How AI Is Fixing It, featuring Jim Frazer in conversation with Lytica CEO Martin Sendyk.

This is a practical conversation for procurement, supply chain, engineering, operations, and executive leaders who are trying to understand how component sourcing is changing.

Manufacturers need to control cost, protect supply, support product launches, and manage risk in a market where visibility is often limited. Overpayment can remain hidden. Component risk can appear too late. Engineering and procurement decisions can become locked in before teams have enough market intelligence to make the best sourcing choices.

Tomorrow’s webinar will examine why traditional approaches to component sourcing are under pressure and how manufacturers can use better intelligence to identify hidden cost, improve benchmarking, and manage sourcing risk more effectively.

Attendees will learn:

Why electronic component pricing remains difficult to benchmark

How hidden overpayment can persist inside normal procurement activity

Why supplier quotes, list prices, and internal history are not enough

How real transactional data can improve pricing visibility

Why geopolitics, AI demand, tariffs, electrification, and defense demand are changing the sourcing risk equation

How AI and sourcing intelligence can help procurement teams make better cost and risk decisions

The issue is no longer only whether a company can secure supply.

The issue is whether it can secure the right components, at the right price, with the right risk profile, early enough to influence the business outcome.

For many manufacturers, that requires a more transparent, data-driven, and intelligence-led sourcing model.

Register now for the ARC Advisory Group webinar with Jim Frazer and Lytica CEO Martin Sendyk before the session begins tomorrow at 11 AM ET.

Register for the Webinar

The Hidden Cost of Component Sourcing — and How AI Is Fixing It
Date: June 23, 2026
Time: 11:00 AM ET
Location: Online
Speakers: Jim Frazer, Vice President, ARC Advisory Group, and Martin Sendyk, CEO, Lytica

If your organization manages a significant electronic component spend, this webinar will help you understand how AI and transactional market data can expose hidden sourcing costs and turn procurement into a more proactive system of intelligence.

Register now to reserve your spot.

The post Last Chance: Join the Webinar on AI, Component Sourcing, and the Future of Procurement appeared first on Logistics Viewpoints.

Continue Reading

Non classé

Weekly Supply Chain and Logsitics News Round Up (June 15th-18th 2026)

Published

on

By

Weekly Supply Chain And Logsitics News Round Up (june 15th 18th 2026)

This week in logistics, the industry faces a pivotal shift as Transportation Management Systems evolve into ‘decision intelligence’ hubs, moving beyond basic routing to become the core operating brain of the supply chain. Meanwhile, operational complexity reaches new heights with the massive logistical undertaking of the 2026 FIFA World Cup, even as trade tensions show signs of cooling following the European Parliament’s approval of a landmark EU-US tariff relief deal. From record-breaking automation at Nestlé’s new California hub to the fluctuating volatility of global air freight rates, these developments underscore a sector increasingly defined by high-tech integration and rapid adaptation to global market forces.

The Leading Supply Chain and Logistics Stories of the Week:

TMS Is Becoming Less of a Routing Tool and More of a Decision Intelligence Layer Beyond Execution

The role of the Transportation Management System (TMS) is undergoing a major paradigm shift. While traditional evaluations still focus heavily on execution-level metrics—like route optimization, automated tendering, and freight audit capabilities—these features have essentially become table stakes. Moving forward, the true strategic value of a TMS lies in its evolution from execution software to “transportation decision infrastructure.” Rather than just completing transactions, next-generation platforms serve as the continuous decision-making layer of the supply chain. By drawing data from across the entire network, integrating external market signals, and resolving multi-functional bottlenecks, modern TMS solutions are transitioning into the core operating brain that synchronizes movement, cost, and service levels in real time.

The Logistics Issue: The Supply Chains Behind the World Cup

While most fans focus entirely on the action on the pitch, supply chain professionals are watching what might be the most complex logistical undertaking in sporting history: the 2026 FIFA World Cup. Spanning three host nations—the United States, Canada, and Mexico—the sheer scale of the tournament requires moving more than twenty million pounds of equipment, coordinated across 5,000 vehicles and millions of square feet of warehouse space. The challenge isn’t just massive volume; it’s the absolute lack of tolerance for delay or error across highly regulated international borders. Industry experts point out that success hinges on establishing a unified ecosystem in which freight forwarders, customs officials, and vendors collaborate in real time. Crucial to this effort are standardized product identification and cloud-based labeling networks, which ensure that every critical piece of equipment, food shipment, and medical supply is fully traceable and compliant with differing regional mandates—proving that at this scale, elite collaboration is the only way to avoid catastrophic bottlenecks.

Transatlantic Trade Relief: European Parliament Greenlights EU-US Tariff

In a major relief to transatlantic supply chain operators, the European Parliament has officially voted to implement the long-awaited trade agreement with the United States. Under the newly approved legislation, the EU will eliminate tariffs on all American industrial goods and grant preferential market access to key U.S. agricultural and seafood shipments. In return, the U.S. has agreed to cap import tariffs on European products at 15%—effectively averting threatened 25% tariff hikes on European-built vehicles. Importantly for logistics planners, the deal incorporates a “defensive toolbox” to mitigate long-term trade volatility, including a sunset clause set for late 2029, a safeguard mechanism to protect EU markets from disruptive import surges, and strict conditions that allow the EU to suspend tariff preferences by the end of 2026 if the U.S. fails to lower existing duties on European steel and aluminum derivatives.

Nestlé Opens Its Largest and Most Technologically Advanced Distribution Center in the U.S.

Nestlé USA has officially unveiled its new 700,000-square-foot distribution hub in Arvin, California. Equipped with a $330 million price tag, the state-of-the-art facility represents a critical step in the company’s broader $25 billion U.S. infrastructure upgrade, emphasizing a pivot toward leaner, automation-first supply chain workflows. The Arvin facility houses the largest Automated Storage and Retrieval System (ASRS) in Nestlé’s global network, operating alongside laser-guided vehicles, automated crane systems, and layer-picking robotics. This build marks a major shift from retrofitting existing spaces to intentionally designing high-tech capabilities directly into greenfield logistics layouts from day one. Designed to mitigate peak-season labor bottlenecks, upskill the frontline workforce, and run on 100% renewable electricity as a zero-waste site, the facility showcases how global leaders are leveraging heavy automation to establish flexible, resilient distribution networks that protect margins against ongoing labor and capacity constraints.

Air Freight Spot Rates Spike 41% YoY in May, but Relief Is Expected Soon

Global air cargo spot rates surged by 41% year-over-year in May, averaging $3.40 per kilogram, driven by persistent geopolitical disruptions, carrier fuel surcharges, and localized demand booms like semiconductor and data center equipment shipments. According to Xeneta data, spot rates from Northeast and Southeast Asia to North America jumped nearly 40% compared to earlier this year. However, the pricing pressure isn’t uniform; transatlantic lanes from Europe to North America actually saw a 26% decline over the same period. For procurement teams battling these elevated costs, there is a glimmer of light on the horizon. Long-term contract rates appear to have peaked in April, and as carriers restore capacity and the market enters its traditional summer lull, analysts predict that year-over-year spot rate comparisons will finally begin to cool down, offering much-needed breathing room for shippers who have been relying on short-term contract extensions.

Song of the week:

The post Weekly Supply Chain and Logsitics News Round Up (June 15th-18th 2026) appeared first on Logistics Viewpoints.

Continue Reading

Non classé

Why Octave’s Austin Event Matters: From Asset Lifecycle Software to Intelligence at Scale

Published

on

By

Octave Live OnTour Austin takes place at a consequential point in the evolution of the industrial software market. Asset-intensive organizations are under sustained pressure to improve capital project execution, asset reliability, operational resilience, safety, quality, cybersecurity, and workforce productivity. At the same time, they are being asked to make better use of data and apply AI in ways that are practical, governed, and operationally relevant.

This is the context in which Octave’s Austin event should be evaluated.

Octave, the software spin-off from Hexagon AB, brings together software assets across engineering, construction, geospatial intelligence, asset operations, quality, public safety, physical security, and industrial cybersecurity. Its Design, Build, Operate, and Protect framework provides a clear structure for organizing those capabilities around the industrial asset lifecycle.

However, the strategic significance of the event is not limited to Octave’s portfolio structure. The more important issue is what Octave’s positioning indicates about the broader direction of industrial software.

The market is shifting from digitized workflows toward intelligence at scale.

Industrial Software Is Moving Beyond Functional Digitization

For much of the past two decades, industrial software investment has centered on functional digitization. Engineering teams adopted design, modeling, analysis, and engineering information management tools. Construction teams deployed project controls and field execution systems. Operations teams invested in EAM, APM, optimization, and reliability applications. Quality, safety, physical security, and cybersecurity functions developed their own specialized technology environments.

These investments created meaningful value within individual domains. But they also reinforced a long-standing structural problem: industrial work is highly interconnected, while the supporting software environment often remains fragmented.

A design change can alter construction cost and schedule. Construction execution quality can affect commissioning performance. Poor handoff from construction to operations can increase maintenance burden. Maintenance backlog can elevate safety and compliance risk. A cybersecurity incident can become an operational disruption. A public safety event may require geospatial, security, asset, and operational context at the same time.

This is the gap that lifecycle intelligence seeks to address.

Lifecycle Intelligence Requires Context Across the Asset Lifecycle

Octave’s Design, Build, Operate, and Protect framework is meaningful because it reflects how industrial assets are planned, built, used, maintained, protected, and improved over time.

In the Design domain, Octave can address engineering, modeling, analysis, information management, and geospatial intelligence. In Build, the portfolio extends into construction, supply chain management, and project performance. In Operate, the focus expands to operations optimization, asset performance, enterprise asset management, quality, compliance, and risk. In Protect, Octave’s positioning includes public safety, physical security, and industrial cybersecurity.

Individually, these are established industrial software categories. Collectively, they suggest a broader strategic direction: the use of software to preserve, connect, and operationalize context across the asset lifecycle.

That is where the Austin event becomes important. Customers and partners should look for evidence that Octave is moving beyond portfolio aggregation toward a more integrated model of lifecycle intelligence.

Intelligence at Scale Depends on Integration, Data, and Workflow Relevance

The phrase “intelligence at scale” should be interpreted operationally, not rhetorically. In industrial environments, intelligence at scale means that software can connect relevant data, apply domain context, and support better decisions across complex workflows.

This requires more than analytics dashboards. It requires software that can help users understand the implications of decisions across functions. It also requires a data foundation that connects engineering data, project execution status, asset histories, maintenance records, geospatial information, quality events, safety incidents, and cybersecurity signals.

AI increases the importance of this foundation. AI capabilities will have limited enterprise value if they are disconnected from operational systems and industrial context. The more material opportunity is AI that is embedded in real workflows and supported by trusted domain data.

For Octave, the strategic question is whether its portfolio can support AI-enabled decision-making across the asset lifecycle, rather than isolated AI features within individual applications.

The Event Should Be Assessed as a Roadmap Signal

Buyers should treat Octave Live OnTour Austin as a roadmap signal.

The first area to assess is integration. Octave’s portfolio breadth creates potential value, but customers will need clarity on how the company intends to connect products and workflows over time. Important indicators include shared data models, workflow orchestration, user experience consistency, API strategy, and cross-domain analytics.

The second area is AI. Customers should listen for specific use cases, not general AI messaging. Relevant examples could include project risk identification, asset performance optimization, maintenance prioritization, quality exception management, safety response, cyber risk monitoring, or engineering decision support. The key issue is whether AI is being tied to operational outcomes.

The third area is ecosystem fit. Industrial organizations rarely standardize on a single vendor across the full technology landscape. Octave will need to clarify how its offerings interact with ERP, EAM, APM, MES, PLM, project controls, cybersecurity, and analytics environments. The value proposition must be additive without increasing architectural complexity.

The fourth area is sequencing. Broad portfolios require disciplined execution. A credible roadmap should identify where Octave will focus first, what integration steps matter most, and how customers should think about value realization over time.

Broader Market Implications

Octave’s Austin event matters because it reflects a larger shift in industrial software.

The next stage of the market will not be defined solely by applications that digitize individual workflows. It will be defined by platforms and architectures that connect operational context across functions. This does not mean every customer will consolidate around a single software suite. Industrial technology environments will remain heterogeneous. But the strategic requirement for connected data, workflow continuity, and decision support will continue to intensify.

AI will accelerate this trend. Effective AI depends on relevant context. If industrial data remains trapped in disconnected systems, AI will be limited to narrow productivity assistance. If data and workflows are connected, AI can support higher-value decisions involving risk, reliability, performance, safety, and resilience.

That is why lifecycle intelligence is becoming an important industrial software concept. It reflects the need to move from systems that record activity to systems that help organizations understand and act on operational complexity.

ARC Advisory Group Perspective

Octave has a credible opportunity to participate in this market transition. The company has meaningful software assets across multiple industrial domains, and its Design, Build, Operate, and Protect framework provides a practical way to organize the portfolio.

The central question is execution. Octave will need to demonstrate that its portfolio can become more than a set of adjacent capabilities. Customers will expect integration clarity, practical AI use cases, ecosystem openness, and a roadmap that connects near-term value to a longer-term lifecycle intelligence strategy.

For buyers, the Austin event should be used to evaluate roadmap direction and strategic fit. For partners, it should clarify Octave’s intended role in the industrial software ecosystem. For the broader market, it is another indication that industrial software is moving toward connected intelligence at scale.

The companies that define this next phase will not simply digitize industrial work. They will connect context across the asset lifecycle and convert that context into better decisions.

The post Why Octave’s Austin Event Matters: From Asset Lifecycle Software to Intelligence at Scale appeared first on Logistics Viewpoints.

Continue Reading

Trending