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Blue Yonder’s ICON 2025 Demonstrates Why Supply Chains Must Transform
Published
10 mois agoon
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There is nothing like harnessing the energy of a user conference to outline a bold vision for a transforming world. In that vein, Blue Yonder’s ICON 2025 didn’t disappoint. Hosted at the Gaylord in Nashville the week harnessed the theme of machine speed and precision across connected supply chain processes. As you would expect, major emphasis was placed on the role of AI to deliver accurate, timely, and improved decisions at all points of supply chain processes using a combination of human-to-AI agent and agent-to agent collaboration. Given the company’s position in the market, the company is capable of executing the business strategy that delivers their vision to customers.
Duncon Angrove, Chief Executive Officer, Blue Yonder
What became quite clear over the course of the week was more evidence that the elephant is definitely still in the room, and ICON demonstrated that the rationale for supply chain modernization isn’t about a solution provider just trying to sell wares. Supply chain modernization must occur in today’s digital-centric world. We have been seeing the need for significant modernization (i.e., transformation) dating back years now. Supply chains need systemic change that must occur via communication, data sharing, and process modernization delivered through the use of orchestrated, interoperable AI agents and data fabrics across multiple enterprises. Whether it’s the shock of a pandemic, geopolitics, or global trade wars, the pace and complexity of volatility in today’s world is beyond the means of traditional supply chain business practices. The past approach of limited, incremental improvements is not sufficient for today’s supply chain needs. We are a quarter of the way into the 21st century and many supply chain practices are still behind the times. As people in such a consumer-heavy country (topic for another time) as the US, we experience it daily.
First, the News
Across the week, Blue Yonder leadership consistently mentioned their commitment to an artificial intelligence (AI) “innovation shockwave” and “avalanche.” As Blue Yonder Chief Executive Officer Duncan Angove mentioned in his keynote, the shockwave was the culmination of $2 billion investment the company began making about three years ago. He also noted that the company had rewritten 28 different planning applications onto one platform. At ICON, Blue Yonder unveiled a number of new products and services, as well as announcing a major acquisition. The products and services were focused around the idea of cognitive solutions delivered by the Blue Yonder Platform that is built on Snowflake’s AI data cloud. As defined by Blue Yonder, the company’s cognitive solutions have the following characteristics:
Cloud-native architecture: All cognitive applications are cloud-native, ensuring they are modern and “always current,” providing a continuous stream of business value without “forklift upgrades”.
Platform delivered: They are built on and sit in the company’s platform and Snowflake’s AI data cloud.
Interoperable and end-to-end: The applications are designed to work together as one system, supporting end-to-end supply chain processes.
Multi-enterprise: The One Network acquisition, announced in 2024, extends capabilities across multiple companies and tiers in the supply chain.
Unified data model: Applications are built on a common data model within the Snowflake AI Data Cloud, enabling concurrent demand and supply planning, unified allocation and replenishment, unified returns management, and unified execution decisions.
Intelligent and agentic: The company indicated that its cognitive solutions are inherently intelligent and agentic, leveraging Blue Yonder’s history as an early adopter of machine learning and other forms of AI.
Refined user experience: Integrating collaborative UX as a core tenet of solution development, emphasizing role-based interfaces, mobile-centric design and access, and the addition of multi-modal interaction.
Specifically, the company announced the release of five, new generative AI agents:
Inventory Ops Agent: This agent helps planners match supply with demand by guiding attention to mismatches, exceptions, and systemic issues. It includes root cause diagnosis and alternative action recommendation. It also highlights plan adjustments and communicates changes based on real-time conditions.
Logistics Ops Agent: The solution helps logistics teams monitor conditions and recommend route changes to prevent delivery disruptions, as well as automate appointment scheduling changes. It also identifies ways to optimize transport costs, on-time deliveries, and emissions.
Warehouse Ops Agent: The agent coordinates and manages highly interdependent tasks, including labor reallocation, supply/demand-based predictive warehouse layouts, outbound risk identification, trailer docking and unloading optimization, and risk mitigation associated with on time in full (OTIF) compliance.
Network Ops Agent: This enables supply chain monitoring across a multi-enterprise network. The agent automates order confirmations, stockout resolutions, carrier assignments, predictive ETA updates, container prioritizations, appointment re-scheduling and performance analysis. Users can have multi-modal interactions with the agent to gain real-time insights and collaboratively orchestrate problem resolutions.
Shelf Ops Agent: Thie solution enables planners to perform at-scale planogram edits using natural-language interactions. Actions such as swapping a product with another in many planograms, updating planograms in a project, analyzing performance, and creating custom reports can be performed quickly.
In a nod to helping customers more quickly and effectively adopt and scale this advanced, composable technology, Blue Yonder also announced a layer of planning and implementation services and solutions. The company’s Agent Advisory Activation Service is designed to get customers successfully running agents in 6-12 weeks. Blue Yonder, Snowflake and RelationalAI also co-announced the development of a supply chain knowledge graph that can use unstructured data to record the structure of business relationships and processes in human-readable form. Finally, Microsoft also joined the keynote to announce that Blue Yonder is using Azure AI Foundry as the core development platform across its entire product suite to design, customize, and manage apps and agents at scale.
Blue Yonder’s Chief Sustainability Officer Saskia van Gendt
In addition to cognitive solutions, another main theme was a continued commitment to sustainability. Blue Yonder’s Chief Sustainability Officer Saskia van Gendt joined CEO Angove on stage to announce that the company announced had acquired UK-based Pledge Earth Technologies. The company provides supply chain teams and logistics service providers (LSPs) with accredited emissions measurement and reporting capabilities. In a nod to its end-to-end supply chain strategy, Blue Yonder will now be able to help its customers automate the collection and exchange of shipment data from logistics suppliers to facilitate accredited and traceable emissions calculations across all transport modes, including air, inland (e.g., truck, rail, barges), and sea. Blue Yonder customers can extend their applicable Blue Yonder solutions to include this new capability, allowing them to receive emissions reporting that is in conformance with the Global Logistics Emission Council (GLEC) framework, developed by the Smart Freight Center (SFC), and aligned with International Organization for Standardization (ISO) 14083: Greenhouse gases.
Doubling Down on Integrating AI into Market Strengths
End-to-end, interoperable technology strategies aren’t new, per se, but few companies are positioned to actually carry them out. While the supply chain market is fiercely competitive, market perception is that if it can be done, it requires solutions built upon both breadth and depth of expertise. Blue Yonder is an acknowledged leader across a broad set of supply chain processes as well as within them. And while most every company out there is investing in AI, Blue Yonder is noted for its history with forms of it such as machine learning, going back to JDA’s 2018 acquisition and 2020 rebranding based on that capability.
The change in how software is built and can be consumed also plays in Blue Yonder’s favor. As the use of monolithic systems diminishes, rip-and-replace upgrades, a non-starter for many, aren’t necessary. That doesn’t diminish the widespread challenge of technical debt. However, composable architecture, the basis for most modern software, enables a much more measured approach to adding and connecting functionality. It can be done using managed steps that aren’t limited to being incremental, as they have been in the past. As companies undertake a journey on supply chain modernization, Blue Yonder assists the transformation using the SADA loop concept (See, Analyze, Decide, Act). The SADA loop was adapted from the military’s OODA loop (observe, orient, decide, act), developed by an officer in the US Air Force to improve aerial combat outcomes. Both concepts are bult upon the idea that speed for the sake of speed doesn’t always dictate winning, and that it must be delivered with timing and context to be effective. These concepts underpin how composable software can be applied.
To understand what the SADA loop concept looks like in execution, supply chain teams can take a look at the results from Blue Yonder’s Composable Journey, launched at the beginning of 2024. The Composable Journey is an implementation and transformation methodology for customers to undertake tailored digital modernization. It is designed to digitally modernize supply chains via incremental steps, taken at the pace of the customer, by leveraging composable microservices and their interoperability. Blue Yonder reported that since the release of the program, the company has already completed more than 200 instances with a 12x average jump in business ROI.
Navigating Potential Risks
Holistic interoperability does present challenges, both for the provider and users of those solutions. Blue Yonder will have to navigate those waters as it helps its customers modernize. Even as the company focuses on helping customers address market uncertainty, that same volatility impacts the ability of providers to plan for long-term investment. Determining what functionality to create, as well as what existing capabilities to deprecate, will need to be executed with precise timing and excellence, as competitors are also actively pushing the market to modernize. In volatile markets, mistakes have a compounded negative impact on market share.
For their customers, Blue Yonder will need to be on point as to how it helps them modernize. What they are suggesting is step change to generally risk-averse markets. Moving from entrenched fragmentation to multi-enterprise, intelligent interoperability is necessary, yes, but it’s neither simple nor inexpensive. The technology is there, frankly, but like with most digital transformation concepts, the ability of users to organize people and data correctly is the critical component, as software is the enabler. The sheer volume of expected change could be seen as overwhelming. The pace of the expected return on Blue Yonder’s investment will also need to account for how quickly the market can move to adopt change.
At the same time, Blue Yonder must deal with an array of competitors that range from those using process-specific best-of-breed to holistic solutions approaches. Additionally, Blue Yonder will need to determine how to best integrate its partners in the customer journey. Some of those partners have developed core, vertical expertise across decades and will need to better understand how they, too, benefit from the Composable Journey. Unfortunately, the partner piece of the event was held the day I travelled home, so I don’t have the specifics of the Blue Yonder strategy on this front. However, that’s something I briefly touched on with Angove and will be sure to follow up on. He’s very aware of this issue, certainly, and understands the need to get it right.
The executive team at Blue Yonder provided ample evidence that they are all pulling in the same direction. It seems there has been ample evidence of the benefit of success. Overall, the event demonstrated that Blue Yonder is positioning itself with a bold, transformative strategy built on a modern, unified, AI-driven platform, aiming to deliver step-change value in a volatile world, despite the inherent challenges of large-scale customer transitions.
Michael’s expertise is in market analysis and strategy development for companies facing transformational market drivers. At ARC, he leads a team that researches the impact of energy transition and sustainability on industrial organizations. Mike is also an acknowledge thought leader in industrial digital transformation. He spends considerable time working with clients on the human side of sustainability and digital transformation and their impact on workforce skills development, knowledge transfer, and change management. Michael is also a co-founder and steering committee member of the Digital Transformation Council.
Michael has held multiple senior management positions in business and market strategy. Just prior to joining ARC, he was a key contributor on Oracle’s global industry strategy team for utilities. During that time, he spearheaded many strategic planning and go-to-market initiatives covering topics such as business model evolution, advanced distribution management, operational analytics, distributed energy, mobility, asset management, workforce modernization, and knowledge management.
The post Blue Yonder’s ICON 2025 Demonstrates Why Supply Chains Must Transform appeared first on Logistics Viewpoints.
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Walmart AI Pricing Patents Signal Shift Toward Real-Time Retail Execution
Published
2 jours agoon
20 mars 2026By
Walmart’s new patents and digital shelf rollout point to a more tightly integrated model linking demand forecasting, pricing, and store-level execution.
Walmart has secured two patents related to automated pricing and demand forecasting, drawing attention to how large retailers are evolving their pricing and execution capabilities.
One patent, System and Method for Dynamically Updating Prices on an E-Commerce Platform, covers a system that can dynamically update online prices based on changing market conditions. A second, Walmart Pricing and Demand Forecasting Patent Classification, relates to demand forecasting technology designed to estimate what customers will buy and recommend pricing accordingly. At the same time, Walmart is expanding digital shelf labels across its U.S. stores, replacing paper labels with centrally managed electronic displays.
Individually, none of these elements are new. Retailers have long used forecasting models, pricing tools, and store execution processes. What is notable is the combination.
Walmart now has three capabilities aligned:
Demand forecasting tied to predictive models
Price recommendation based on that demand
Store-level infrastructure capable of rapid execution
That combination reduces the operational friction historically associated with pricing in physical retail.
Pricing Moves Closer to Execution
Traditional store pricing changes required coordination across multiple steps: analysis, approval, printing, distribution, and manual shelf updates. That process introduced delay and inconsistency.
Digital shelf labels materially change that constraint. Prices can be updated centrally and executed across stores with significantly less manual intervention.
This does not change the underlying logic of pricing decisions. Retailers have always adjusted prices based on demand, competition, and margin targets. What changes is the speed and consistency of execution.
As a result, pricing moves closer to real-time operational control.
Implications for Supply Chain Operations
Pricing is not an isolated commercial function. It directly influences demand patterns, inventory flow, replenishment timing, and markdown activity.
When pricing becomes faster and more responsive, those linkages tighten.
Three implications are clear:
1. Increased Execution Speed
Retailers can align pricing decisions more quickly with current demand conditions, reducing lag between signal and action.
2. Stronger Dependence on Forecast Accuracy
When pricing recommendations are driven by predictive models, the quality of demand sensing becomes more consequential. Forecast errors can propagate more quickly into sales and inventory outcomes.
3. Closer Coupling of Merchandising and Supply Chain
Pricing decisions influence demand. Demand impacts inventory, replenishment, and store execution. Faster pricing cycles compress the distance between these functions.
Centralization and Control
Walmart has positioned its digital shelf label rollout as an efficiency and accuracy initiative. Centralized price management improves consistency between systems and store execution while reducing labor tied to manual updates.
That positioning aligns with the operational realities of large-scale retail. At Walmart’s footprint, even small improvements in execution efficiency translate into material cost and accuracy gains.
At the same time, the shift toward algorithm-supported pricing introduces standard enterprise control requirements. Organizations need clear governance around how pricing recommendations are generated, reviewed, and executed, particularly as systems become more automated.
A Broader Technology Pattern
Walmart’s patents are best understood as part of a broader shift in supply chain and retail technology.
AI and advanced analytics are moving closer to operational decision points. Forecasting models are no longer confined to planning environments; they are increasingly connected to systems that can act.
In this case, that connection spans:
Demand sensing
Price recommendation
Store-level execution
The result is a more tightly integrated operating model in which commercial decisions and supply chain execution are linked through software.
What This Signals
The significance of Walmart’s move is not tied to public debate over surge pricing scenarios. The underlying development is structural.
Retailers now have the ability to connect demand forecasting, pricing logic, and execution infrastructure into a faster decision loop.
For supply chain leaders, that represents a clear direction:
Execution is becoming more digital, more centralized, and more tightly coupled to predictive models.
The companies that benefit will be those that can align forecasting, pricing, and operational execution within a controlled, coordinated system.
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Supply Chain and Logistics News March 16th-19th 2026
Published
2 jours agoon
20 mars 2026By
This week’s installment of Supply Chain and Logistics news includes stories about record increases in oil prices, Rivian’s autonomous taxis, and much more. Firstly, the Trump administration has issued a 60-day waiver of the Jones Act, a century-old regulation that requires goods moved between US ports to be transported by US-built vessels, etc. Additionally, this week Uber & Rivian announced a partnership for Rivian to build 50,000 autonomous robotaxis by 2031 with over a billion dollars in investment from Uber. Schneider Electric and EcoVadis announced a partnership to target emissions in the health care sector. Lastly, DHL announces 10 warehousing sites to be used for data center manufacturing capacity, and Mind Robotics raises 100 million in series A funding.
Your Biggest Stories in Supply Chain and Logistics here:
Trump Administration Issues Pause on Century-old Maritime Law to Ease Oil Prices
The Trump administration has issued a 60-day waiver of the Jones Act. This century-old regulation typically requires goods moved between US ports to be carried on vessels that are US-built, US-owned, and US-crewed. However, with oil prices surging toward $100 a barrel due to escalating conflict in the Middle East, the suspension aims to ease logistics for vital commodities like oil, natural gas, and fertilizer. While the move is intended to lower costs at the pump and support farmers during the spring planting season, it has sparked a debate between those seeking immediate economic relief and domestic maritime unions concerned about the long-term impact on American shipping and labor.
Uber and Rivian Partner to Deploy up to 50,000 Fully Autonomous Robotaxis
Uber and Rivian have announced a massive strategic partnership that signals a major shift in the future of autonomous logistics and urban mobility. Under the terms of the deal, Uber is set to invest up to $1.25 billion in Rivian through 2031, a move specifically tied to the achievement of key autonomous performance milestones. The primary focus of this collaboration is the deployment of a specialized fleet of fully autonomous R2 robotaxis, with an initial order of 10,000 vehicles and an option to scale up to 50,000 units. From a supply chain perspective, this represents a significant commitment to vertical integration; Rivian is managing the end-to-end production of the vehicle, the compute stack, and the sensor suite, including its in-house RAP1 AI chips, while Uber provides the scaled platform for deployment. Commercial operations are slated to begin in San Francisco and Miami in 2028, eventually expanding to 25 cities globally by 2031.
Schneider Electric and EcoVadis Announce Partnership to Decarbonize Global Healthcare Supply Chains
Schneider Electric, a major player in the digital transformation of energy management and automation, and EcoVadis, a provider of business sustainability ratings, have announced a strategic partnership aimed at accelerating decarbonization within the healthcare industry. “Energize” is a collective initiative to engage pharmaceutical industry suppliers in climate action. The collaboration focuses on addressing Scope 3 emissions, those generated within a company’s value chain, which often represent the largest portion of a healthcare organization’s carbon footprint. By combining Schneider Electric’s expertise in energy procurement and sustainability consulting with EcoVadis’s supplier monitoring and rating platform, the partnership provides a structured pathway for pharmaceutical and medical device companies to transition their global suppliers toward renewable energy.
Mind Robotics, a Rivian spin-off, raises $500 million in Series A Funding
RJ Scaringe, CEO of Rivian, is positioning his new $2 billion spin-off, Mind Robotics, as a technological solution to the chronic shortage of manufacturing labor in the Western world. By developing a “foundation model” that acts as an industrial brain alongside specialized mechatronic bodies, the company aims to move beyond the rigid, fixed-motion plans of traditional robotics toward systems capable of human-like reasoning and adaptation. Scaringe emphasizes that while these machines must perform with human-level dexterity, they don’t necessarily need to be humanoid in form; instead, the focus is on creating a data-driven “flywheel” within Rivian’s own facilities to lower production costs and help domestic manufacturing remain globally competitive.
DHL is significantly scaling its data center logistics (DCL) footprint in North America, announcing the addition of 10 dedicated sites totaling over seven million square feet of warehousing capacity. This expansion is a direct response to the explosive demand for AI-driven infrastructure and the specific needs of hyperscale and colocation data center operators. By offering specialized services like rack pre-configuration, white-glove handling of sensitive IT hardware, and warehouse-to-site transportation, DHL is positioning itself as an end-to-end partner in a sector where 85% of operators express a preference for a single logistics provider. This move not only addresses the logistical complexities of moving high-value components like GPUs and cooling systems across global borders but also underscores the critical role of integrated supply chains in maintaining the build speed of the digital backbone.
Song of the Week:
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How to Capitalize Quickly to Address Hyperconnected Industrial Demand
Published
3 jours agoon
19 mars 2026By
This first in a blog series offers a review of discussion that occurred during ARC Advisory Group’s 2026 Industry Leadership Forum. Specifically, it details a keynote conversation held with senior executives from Rolls-Royce, BTX Precision, and MxD.
The New Fabric of Demand: Modernizing Collaboration and Transparency for Real-Time Production
Industrial leaders have been talking about tearing down workflow and data silos for decades. Yet here we are again. For most, the reality is that most operations and supply chains today typically don’t indicate much progress. A few leaders have figured out how to use digital tools to scale and build pathways forward, a whopping 12.9% according to our latest data (yes, that’s sarcasm). However, even as they struggle to coordinate, orchestrate, and innovate across their operations and enterprise, much less tightly collaborate outside their four walls. In a digital world, this continued capability gap, the inability to closely link market signals to responsive production and external supply chains, is very quickly becoming a liability.
Recently, at the 30th Annual ARC Industry Leadership Forum in Orlando, I had the privilege of leading a keynote discussion entitled The New Fabric of Demand: Modernizing Collaboration and Transparency for Real-Time Production. As part of that, I moderated an excellent conversation that included Global Commodity Executive Greg Davidson of Rolls-Royce, CEO Berardino Baratta of MxD, and CRO Jamie Goettler of BTX Precision.
In this four-part series, we will explore that conversation fully, digging into how the “fabric of market demand” has fundamentally changed, and why structural modernization, both human and technological, is no longer just an option. It is an industrial imperative that will increasingly determine who wins in disrupted markets.
Why Legacy Workflow Will Actually Get Modernized
If we examine the present through the lens of the past, the fundamental laws of supply and demand haven’t really changed. What has changed is the hyperconnectivity of the world and our compressed time to both reward and volatility.
The hard truth is that legacy linear workflows simply do not work in hyperconnected, digitally-driven environments, which are non-linear by nature. As our industrial environments become more digital, they naturally open up countless new ways for how things can get done and how risk can enter the organization. As a result, disruption has shifted from a rare event to a fairly continuous and pervasive reality. In this new reality, responsiveness differentiates you from the competition, and lag time kills.
To survive and thrive in non-linear environments, tighter, integrated ecosystems are required, where silos are actively torn down or redesigned so that barriers to value can be continuously identified and quickly eliminated. At the core, this concept is unfolding around data access, contextualization, and sharing. It provides the urgency behind the need for building industrial data fabrics.
This rewiring certainly extends beyond operations and enterprise processes, enabling the entirety of the supply chain to be judged on its collective responsiveness to the market, all the way down to the individual company level. In this scenario, data can quickly point out laggards who limit value. As the orchestrators of these supply chains identify these limitations on value, they quickly break off and discard the connection and move on without these weak links.
Pillars of the New Fabric of Demand
To achieve necessary level of operational and supply chain responsiveness, the roles of every entity within an ecosystem must be rethought. In the subsequent three blogs of this series, we will take a deep dive into the three distinct pillars that make up this modern architecture, but I’ll begin by laying them out here:
The Market Signal is the catalyst of the entire ecosystem. It dictates the “what” and the “when,” defining what value, success and risk look like in real-time. In blog 2, I’ll explore how to move from reactive assumptions to proactively capturing the market signals that actually matter.
The Demand Architect is moving beyond traditional order-taking. The Demand Architect designs and orchestrates the ecosystem, aligning external partners as true extensions of the enterprise. In blog 3, I’ll discuss the structural agility required to lead this response, rather than just manage a process.
The Agile Partner is the engine of execution. The Agile Partner links supply chain dynamics directly to the shop floor, differentiating themselves through their responsiveness to the market signal. In the final blog in the series, I’ll tackle how data transparency and trust become technical requirements, not just buzzwords, without exposing mission-critical IP.
Building the Modern Industrial Enterprise
Legacy workflows cannot survive in a non-linear world. Industrial organizations must re-architect operations and ecosystems for real-time responsiveness and secure, transparent collaboration. To do so, they will need to:
Improve the measurement of responsiveness: Efficiency and margin-squeezing are important, but they aren’t game-changers. Your competitive edge now relies on how quickly you can adapt to market signals.
Embrace transparency over secrecy: Modern collaboration requires providing a contextualized “lens” into production status without compromising proprietary IP or cybersecurity. Industrial data fabrics are key.
As always, view technology as a tool, not an outcome: Industrial data fabrics are needed to break silos and AI to manage complexity and improve accuracy and speed of decisions. However, the age-old adage remains true. Just because you can apply AI to something doesn’t mean you should. It must be grounded in measurable Value on Investment (VOI), not just return.
The New Fabric of Demand Blog Series
This is the first in a series of four on The New Fabric of Demand: Modernizing Collaboration and Transparency for Real-Time Production. Over the coming days, I’ll publish a perspective from each of the three pillars of the new fabric of demand:
Pillar 1: The Market Signal
Pillar 2: The Demand Architect
Pillar 3: The Agile Partner
By Mike Guilfoyle, Vice President.
For more than two decades, Michael has assisted organizations, including numerous Fortune 500 companies, in identifying and capitalizing on growth opportunities and market disruption presented by the effects of digital economies, energy transition, and industrial sustainability on the energy, manufacturing, and technology industries.
The post How to Capitalize Quickly to Address Hyperconnected Industrial Demand appeared first on Logistics Viewpoints.
Walmart AI Pricing Patents Signal Shift Toward Real-Time Retail Execution
Supply Chain and Logistics News March 16th-19th 2026
How to Capitalize Quickly to Address Hyperconnected Industrial Demand
Walmart and the New Supply Chain Reality: AI, Automation, and Resilience
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