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Manhattan Associates Momentum 2025: New Horizons
Published
10 mois agoon
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Last week, I attended the Manhattan Associates Flagship US Conference, Momentum 2025. The event, held in sunny Las Vegas, was well attended and featured numerous speakers with innovative ideas. Manhattan Associates shared several announcements, including the appointment of their new president and CEO, Eric Clark. His keynote address highlighted the company’s recent accomplishments, such as the introduction of a new inventory planning solution, substantial investments in research and development, and advancements in artificial intelligence.
During the two-day event, I participated in various sessions covering a range of topics, including Warehouse Management Systems, Labor Management, Agentic AI, and Warehouse Automation. This article outlines my key takeaways from the sessions attended and provides an overall summary of Momentum 2025.
1st Keynote:
Eric Clark, the new president and CEO of Manhattan, emphasized the company’s commitment to innovation, community, and people. He highlighted Manhattan’s unified cloud-native platform, which allows for faster innovation and better customer solutions. Recent achievements include a new inventory planning solution launched in October and significant investments in R&D. The company has also focused on AI integration, with AI agents now available on their platform. Clark discussed the benefits of unification, such as reduced project timelines and improved operational efficiency. “Supply chain unification” was an undertone for many of the sessions during the entire event. He also mentioned the importance of employee engagement and unified distribution planning to enhance productivity and labor balance.
Clark highlighted the depth of talent and tenure within Manhattan, with many employees having over 25 years of experience. He described Manhattan’s platform as cloud-native, API-microservices built on a unified platform, which allows for faster innovation. Clark also discussed the significant forces driving disruption in the industry, including economic nationalism, changes in global trade, and rapid cycles of technological innovation. He explained how Manhattan is committed to providing technology and solutions to help organizations thrive in chaos.
Brian Kinsella, senior vice president, presented updates on supply chain execution unification, highlighting progress and innovation across Manhattan Active Applications. He emphasized the benefits of unification, such as dynamic trailer door assignment and shipment planning optimization. Kinsella shared examples of how unification helps customers respond to real-time changes and improve agility. He also discussed updates in yard management, including a new visual tool for a bird’s eye view of the yard and drag-and-drop functionality for task execution. The presentation underscored Manhattan’s commitment to helping associates do their best and maximize the effectiveness of distribution operations.
The keynote was concise and communicated great confidence despite the current economic uncertainty due to US politics. Chaos is now just a part of the plan, and Manhattan Associates has the tools for its customers to remain steadfast.
The Future of Manhattan Associates Warehouse Management Systems
Warehouse management systems are a core offering of the Manhattan Associates Product Suite. Launched in 2020, it has experienced a hyper-growth trajectory. Currently, Manhattan has 433 live sites and releases quarterly updates every 90 days. The team aims to release 40-45 new features every quarter with a sharp focus on innovation, efficiency, and productivity improvement. Some of the key features released last year include trailer weight balancing, a planning workspace for shipment orchestration, and generative AI for action assistance. Unification was an underlying theme of the entire conference, with benefits such as optimized operations, improved visibility, and enhanced collaboration. The unification of transportation management and warehouse management systems has enhanced appointment scheduling and transportation planning. Their WMS solution now has an “Action Assist” feature, which allows users to ask questions through a chat box. Users can upload their own documents, including standard operating procedures, FAQs, and system diagnostics. Allowing their AI Agent to sit on top and become an expert on all of the materials uploaded and practices learned. This feature allows for associates on the warehouse floor to access information with speed, reducing downtimes in cases of emergency. As updates roll out every quarter, it is fair to assume there will be continuous developments in AI with a focus on reducing travel on the floor and processing time.
Navigating the Future of Warehouse Robotics
Rueben Scriven from Interact Analysis presented his research on warehouse automation, beginning with the impacts of COVID-19 on the warehouse space. Before 2020, warehouse construction was seeing a 50 percent year-over-year growth rate. Post pandemic, the rates declined to 20-21 percent, and in 2022, when the interest rates increased and e-commerce volumes decreased, warehouse construction saw a significant drop. From June 2024, construction rates have increased, but with current economic uncertainty, automation and warehouse construction investments have been hindered. Forecasts show a growth trend with a decline in 2025 and a slow uptick to stronger growth in 2027.
The global market for humanoid robots is estimated to be at $2 trillion, with three scenarios for penetration: optimistic, baseline, and pessimistic. There are a few key areas of barriers to adoption, including regulatory standards, lack of comprehensive insurance, and return on investment. Reubens’ research estimates that by 2032, the baseline scenario anticipates humanoid robots shipped annually, with more than 80 percent deployed in China due to less stringent regulations and national robotic policies.
Warehouse automation software consists of four layers:
Layer
Description
Subordinate Control
Manages the lower-level control of each subsystem to achieve the intended result.
Control
Coordinate automated subsystems’ activities to manage the flow of goods through the warehouse.
Execution Layer
Orchestrates the timing and location of order processing to maximize throughput.
Management Layer
Oversees goods receipts, inventory, and other related tasks.
Automation in warehouses will demand changes in how Warehouse Execution Solutions are constructed and will drive demand for additional WES and WMS products.
Agentic AI Supply Chain
To set the stage, Jeff Beadle, senior director at Manhattan Associates, discussed the evolution of automation evolving into Agentic AI within the context of supply chain management. How did we get from traditional automation to AI automation, and now AI Agents work together in an Agentic AI environment? Not to be a marketing fire hose for AI, but Agentic AI could be a paradigm shifter for how supply chains are managed.
In the session, Jeff laid out the trajectory of traditional automation to AI automation, emphasizing the importance of contextual learning and adaptability. Beadle highlighted the role of agents in decision making, stressing their goal-driven, autonomous nature. He provided examples of agentic AI applications in supply chain tasks, such as shipping label agents and invoice management. Beadle noticed that 50 percent of companies have already deployed agents, and agentic AI is expected to handle variability and disruptions more effectively, enhancing supply chain efficiency. Agentic AI is not just one smart agent, it’s a coordinated network of such intelligent, goal-driven agents that creates a self-managing, self-adapting automation system. Traditional automation differs from AI automation because of the latter’s ability to learn and adapt.
Jeff also spoke about emergent behaviors, which could arise in an AI Agent in isolation, but with Agentic AI, the system adapts over time, learning from outcomes and shifting strategy across agents.
Is this AI Déjà vu? What is different this time?
Intelligence and the ability to make decisions.
How agents reason, control, trust, and govern.
Ensuring agents are transparent, dependable, aligned, and safe.
Integration and interoperability.
What is Next?
In the early days of generative AI, challenges included instability and the lack of reference ability. Since then, Large Language Models have helped develop frameworks, systems, and orchestration to support agentic AI. Technology leaders such as Google, Microsoft, and Amazon must work together in advancing agentic AI. A multi-agent architecture demands comprehensive efforts and investments in improving intelligence and decision-making. Agentic AI will enhance existing systems and processes, enabling faster and more reliable operations. Agentic AI can also help manage the promised chaos that recent years have brought to supply chains and the global economy.
Final Takeaways
Since 2020, disruptions in global supply chain operations have become consistent. Solutions driven by generative AI are increasingly in demand from clients, and AI agents are emerging as the next frontier of development in this field. Manhattan Associates emphasized the advantages of unifying supply chains, highlighting the benefits of cooperation, transparency, and agility. Warehouse management systems are evolving rapidly, with Manhattan releasing new features every quarter. As automation within warehouses increases, software will need to adapt to the anticipated surge in new warehouse construction projected for 2027. Momentum 2025 successfully highlighted an extensive range of innovative advancements occurring within the supply chain and AI sectors.
The post Manhattan Associates Momentum 2025: New Horizons appeared first on Logistics Viewpoints.
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Walmart AI Pricing Patents Signal Shift Toward Real-Time Retail Execution
Published
3 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.
The post Walmart AI Pricing Patents Signal Shift Toward Real-Time Retail Execution appeared first on Logistics Viewpoints.
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Supply Chain and Logistics News March 16th-19th 2026
Published
3 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
4 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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