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Manhattan Associates’ Strategic Vision – Unifying Platforms Integrating AI and Leading the Future
Published
10 mois agoon
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At this year’s keynote, Manhattan Associates outlined its current strategic direction, underscoring platform unification, AI integration, and leadership transition. The presentations provided a clear account of the company’s continued investment in product development and operational capabilities, alongside practical use cases from customer deployments.
Leadership Transition and Strategic Continuity
Eddie Capel, Chairman of the Board
Eddie Capel, Chairman of the Board opened the event by reaffirming Manhattan Associates’ ongoing focus on innovation, partnership, and adaptability. His comments reflected a long-term orientation: technology and strategy are expected to evolve in parallel with shifts in the global supply chain environment. Capel’s remarks highlighted the need for organizations to remain operationally synchronized—across systems, partners, and functions.
He emphasized that tools must speak the same language to support efficient, intelligent operations. Capel also referenced the increasing importance of modular, interoperable systems and the company’s work to reduce friction across supply chain processes. His introduction of Eric Clark as the incoming President and CEO framed the leadership change as an extension of Manhattan’s current trajectory rather than a pivot.
Eric Clark: Emphasis on People, Platform, and Market Responsiveness
Eric Clark, President & CEO
Eric Clark, President & CEO opened by acknowledging the legacy of the organization and thanking Eddie Capel and the broader team for their support. He explained that his decision to join Manhattan was shaped by three main factors: the quality and depth of the team, the pace of platform innovation, and the resilience of the customer community. In his view, these components form the foundation for long-term operational and commercial success.
Clark cited the Manhattan Active Platform as a differentiated asset in the enterprise technology market. Built as a unified suite rather than integrated point solutions, the platform includes end-to-end functionality across supply chain execution, commerce, and planning. He stressed the strategic advantage of managing all functions on a single codebase, which allows for faster updates, stronger data integration, and reduced implementation complexity.
Recent examples included the rollout of a new inventory planning application and the introduction of a hybrid AI-powered demand forecasting engine. Clark noted that these developments were designed to meet emerging customer needs, particularly in markets experiencing unpredictable demand and inventory constraints.
He also introduced the company’s new agentic AI strategy—referring to intelligent software agents that can make autonomous decisions and manage specific operational tasks. According to Clark, these agents are being deployed to reduce manual intervention and enable more adaptive, responsive systems in real-time environments.
Brian Kinsella: Practical Application of Platform Unification
Brian Kinsella, Senior Vice President, Product Management
Brian Kinsella, Senior Vice President, Product Management, focused on the measurable outcomes associated with unified applications. He reported that over 25 customers are currently moving toward unified supply chain execution—leveraging consistent data models, processes, and system behaviors across distribution, transportation, and fulfillment functions.
Kinsella detailed recent functionality developed to support these goals. Examples included dynamic trailer door assignments, shipment planning enhancements, drag-and-drop yard visualization tools, and integrated labor planning modules. Each feature was tied to a larger goal: removing operational silos and enabling system-wide coordination.
He introduced a new solution called Enterprise Promise and Fulfill, built to address enterprise-wide inventory visibility and order fulfillment orchestration. Unlike traditional order management systems, this application incorporates live data from across the network and supports multi-node order allocation and dynamic lead time calculation.
Kinsella also stressed that unification is not only a design goal but a practical enabler of speed, accuracy, and efficiency for customers seeking to simplify multi-system architectures.
Sanjeev Siotia: AI Agents and System Architecture
Sanjeev Siotia, Executive Vice President & CTO
Sanjeev Siotia, Executive Vice President & CTO, provided a technical update on the Manhattan Active Platform. He explained how the company’s API-first, microservices-based architecture serves as the basis for current and future enhancements. Each service operates independently while integrating seamlessly, allowing for more resilient deployments and easier scaling.
Siotia introduced the concept of agentic AI in greater detail. These agents are software entities powered by large language models, capable of coordinating tasks, making decisions, and adapting in real time based on context. This capability marks a shift from traditional rule-based systems to more flexible, learning-based automation.
He offered specific examples, including a labor optimization agent designed to monitor warehouse workflows and adjust assignments dynamically. These agents are already in production, contributing to operational task management and responding to thousands of user queries.
To support broader adoption, Siotia announced the launch of Agent Foundry—a toolkit for customers to create and deploy their own AI agents. He also noted a strategic collaboration with Google to support interoperability between Manhattan’s AI agents and external platforms, ensuring customers can extend capabilities as needed.
Customer Case Study: Duluth Trading Company
AJ Sutera, Senior Vice President, Chief Technology & Logistics, of Duluth Trading Company, presented a customer case study highlighting the retailer’s digital transformation over the past several years. He outlined the company’s approach to rethinking fulfillment, digital strategy, and channel operations, particularly as part of a major warehouse automation investment.
Sutera described a $60 million project to build an automated fulfillment center in Adairsville, Georgia, launched in September 2023. The initiative was supported by partners including Manhattan Associates, Summit Advisory Services, and others. According to Sutera, the facility has improved operational metrics related to order accuracy, fulfillment speed, and labor efficiency.
His remarks focused on change management as much as technology—emphasizing the need for new skills, clearer roles, and accountability across teams during the transformation process. He credited strong partnerships and coordinated execution as key factors in the project’s success.
Ann Ruckstuhl: Platform Availability and Ecosystem Partnerships
Ann Ruckstuhl, Senior Vice President & CMO
Ann Ruckstuhl, Senior Vice President & CMO, concluded the session by discussing Manhattan’s go-to-market ecosystem. She confirmed that Manhattan Active Solutions are now listed on the Google Cloud Marketplace, increasing availability and simplifying access for enterprise buyers.
Ruckstuhl discussed the company’s partner strategy, including collaboration with Shopify and Google to expand AI-enabled solution delivery. These partnerships are intended to support more flexible deployment options and help customers build integrated commerce experiences.
She encouraged attendees to explore current capabilities through the Unity Pavilion and hands-on demonstrations, which included AI agent use cases, platform configurability, and roundtable discussions on sector-specific applications.
Manhattan Associates used the keynote to communicate its continued investment in unified system design, AI functionality, and customer enablement. The leadership transition from Eddie Capel to Eric Clark was framed as a handoff aligned with the company’s existing direction.
With live deployments of unified applications, practical AI agents in use, and new tools for customer-led development, the company is positioning itself for scalable execution across complex supply chain environments. The focus remains on reducing system fragmentation, simplifying operations, and improving business responsiveness in a dynamic global market.
The post Manhattan Associates’ Strategic Vision – Unifying Platforms Integrating AI and Leading the Future 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.
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
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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