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From Data to Decisions: Revolutionizing Supply Chain Management with Demand Sensing and Forecasting

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From Data To Decisions: Revolutionizing Supply Chain Management With Demand Sensing And Forecasting

For demand sensing and forecasting in the supply chain, the ability to quickly ingest and analyze data, and subsequently make strong business decisions is crucial. While this is true across all aspects of supply chain management, it is especially important when tracking actual demand versus projected demand. This crucial need can be slowed down or impeded by issues such as a lack of end-to-end supply chain visibility, antiquated data management processes, or even inaccurate data.

Significant disruptions along the supply chain from external factors such as geopolitical events, supplier capacity issues, poor network inventory visibility, and constant changes in buyer behavior, make synchronizing demand and supply very difficult. This is further complicated by inaccurate data from dozens of disparate applications and enterprise systems within the organization, its partners, and its suppliers. Traditional forecasting methods struggle to keep up with rapid changes in global supply chains, often failing to predict demand accurately during volatile periods.

Companies have traditionally relied on historical data and internal systems for demand forecasting, but this approach is limited in its ability to respond to sudden market shifts. The ability to sense demand disruptions in real time and improve forecasting in this environment is difficult to achieve, especially if you want a high degree of customer satisfaction, and it also highlights the responsiveness needed to adapt quickly to unexpected changes. Companies that leverage demand sensing can emerge stronger and better positioned after disruptions.

An Introduction to Demand Sensing and Forecasting

Demand sensing and demand forecasting are both crucial aspects of optimizing supply chains, but they do have slightly different functions in their approach and focus. Demand sensing uses real-time data and analytics to identify and respond to immediate demand fluctuations, while demand forecasting uses historical data to predict future demand over a longer period (months or years). Different methods, such as statistical modeling and machine learning, are used to enhance the accuracy and adaptability of these processes. Both areas are crucial for companies when it comes to projecting sales, managing inventory, and coordinating replenishment. In the end, the goal is to accurately predict customer demand by using predictive models to forecast future demand.

From a metrics standpoint, companies need to accurately measure forecast versus actual sales, inventory turnover, stockout rates, inventory obsolescence, order fill rates, and on-time in-full percentage. When forecasting, it is important to predict demand for a particular product to avoid excess inventory and stockouts. Advanced analytics and AI tools provide granular insights into sales activities, inventory levels, and financial metrics, supporting more precise decision-making.

Recognizing the growing complexity of these demands, InterSystems surveyed 450 senior supply chain practitioners and stakeholders to examine key supply chain technology challenges, trends, and decision-making strategies across five key use cases: fulfillment optimization; demand sensing and forecasting; supply chain orchestration; production planning optimization; and environmental, social, and governance (ESG). This blog is Part 2 in our Optimizing Supply Chain Performance with Unified Data series, with a focus on demand sensing and forecasting.In the unified data survey, respondents were asked how they currently integrate and prepare disparate information for decision-making. Not surprisingly, 42% of respondents use manual methods, including spreadsheets, to integrate and prepare disparate information for decision-making. While spreadsheets can be incredibly useful and are clearly used by a lot of companies for planning purposes, they also have limitations.

As the picture above shows, spreadsheets are not a useful tool when it comes to decision intelligence. Decision intelligence is focused on improving decision-making by understanding how decisions are made and using AI and machine learning to optimize outcomes. In supply chain, an AI-enabled decision intelligence platform can optimally manage disruptions when and before they occur so companies can react faster and ensure that products are available when companies need them, while also monitoring engagement to improve sales outcomes.

Current State of Demand Sensing and Forecasting

One of the biggest issues with demand sensing and forecasting is that human intervention is often required. This is because AI often lacks the nuances to fully understand the complexity of demand patterns. So, while human intervention is required to bridge that gap, it can be both time-consuming and error-prone, especially if the data a company is relying on is bad. According to the survey results, when asked how they currently forecast demand, 36% of respondents indicated that they have several solutions that require staff input. Aside from the aforementioned issues with human input, the use of multiple systems often leads to disjointed, disparate data silos. When different systems are unable to communicate, decisions take longer to make and are usually not as accurate, leading to errors in demand sensing and forecasting. To maintain data accuracy and relevance, it is crucial that data is updated and transferred regularly.

The harsh reality is that the use of intelligent data platforms is not widespread. The survey revealed that only 27% of respondents have an intelligent data platform. This is most notable in logistics and transport (18%) and pharmaceuticals (19%) where less than one-fifth of companies are currently using an intelligent data platform. For these platforms to be effective, it is essential that all data is validated before being used in forecasting models to ensure consistency and accuracy.

Demand Sensing and Forecasting Challenges with External Demand Signals

According to the survey, the top demand sensing and forecasting challenges are related to issues with data: its collection, visibility, and analysis. It’s no surprise that all of these issues are directly tied to data inconsistencies. Clean data is essential to ensure accuracy and consistency, especially when integrating external datasets.

When asked to identify their top challenges in demand sensing and forecasting, respondents cited the following: no real-time visibility along the supply chain (41%), current processes are too manual (39%), inaccuracies in data within the organization, partners, and suppliers (37%), and no real-time sensing of demand and supply changes (34%). Understanding demand and supply shifts, and reacting accordingly, is at the heart of demand sensing and forecasting. From the demand side, shifts are the result of changing consumer preferences, brand loyalty, or economic factors. From the supply side, these market shifts are tied to raw material pricing or availability, labor shortages, or new entrants to the market. For those companies that cannot sense shifts in real-time, their forecasting accuracy suffers, thus leading to lost sales and higher cost of goods sold.

Supply chain visibility has been a hot topic over the last few years, but most people think of it only from a shipment standpoint. Point-to-point tracking solutions have seen billions of dollars in venture capital investments, but supply chain visibility goes well beyond these solutions. Supply chain visibility enables companies to track the location and status of products, components, and materials as they move through the supply chain. However, it also encompasses the entire end-to-end supply chain, from the sourcing of raw materials to the final delivery to the end consumer. At the core of supply chain visibility is access to real-time data for inventory optimization, tracking, and potential disruptions. To respond effectively to demand changes, companies must be able to adjust inventory levels quickly in response to market volatility and shifting consumer demand.

The second challenge identified by respondents is reliance on manual processes. More and more often, we hear about the autonomous supply chain. Automated demand sensing processes leverage real-time data and advanced analytics to predict short-term demand fluctuations, while manual methods rely on human interpretation of data, which can be time-consuming and prone to errors.

A third challenge highlighted by respondents is inaccuracies in data from within the organization, partners, and suppliers. As far back as 1957, computer scientists have referred to this as “garbage in, garbage out.” In a syndicated newspaper article about US Army mathematicians and their work with early computers, Army Specialist, William D. Mellin explained that computers cannot think for themselves, and that “sloppily programmed” inputs inevitably lead to incorrect outputs. A lot has changed since then, but the underlying principle is the same. Inaccurate data will lead to errors in demand sensing and forecasting, which will impact inventory management, supply chain operations, and profitability.

Demand Sensing and Forecasting Capabilities to Improve Forecast Accuracy

According to the survey, the capabilities respondents believe would most improve their ability to accurately forecast demand correlate with their biggest challenges. The top capability survey respondents said would improve their ability to forecast demand is the ability to ingest and analyze real-time data from many sources in disparate formats (27%). InterSystems Supply Chain Orchestrator is a data platform that ingests all relevant data from the sources that matter, both internally and externally, including geopolitical events, information on supply chain product integrity issues, supplier fulfillment discrepancies, and much more. Harmonizing and normalizing all this information to provide accurate data in real time, the platform simulates your business processes and then applies embedded AI and ML capabilities. With no “rip-and-replace” needed, companies gain accelerated implementation of powerful new capabilities, while lowering total cost of ownership in a way unmatched in the industry today.

The second capability identified by respondents is integrated inventory management with enterprise resource planning (ERP) and electronic point of sale (EPOS) to automate demand-sensing and forecasting (24%). Supply Chain Orchestrator enables organizations to adjust forecast plans with high levels of accuracy to successfully navigate sudden events, disruptions, or trends that affect demand, transforming fulfillment optimization. By leveraging demand sensing, organizations can increase output by adjusting production schedules in response to predicted demand, ensuring they meet customer needs effectively. Organizations can integrate more advanced sensing and forecasting capabilities with their point-of-sale, ERP systems, or applications, achieving faster time-to-value.

Final Thought on Demand Sensing and Forecasting

To be agile and competitive, organizations must be capable of extracting critical insights in near real-time. This remains a significant challenge when so many businesses lack end-to-end visibility or rely on manual data analysis and ad hoc provisioning and integration of different solutions. For demand sensing and forecasting, a reliance on manual data analysis, especially given the current state of disparate data streams, can be catastrophic. If companies are unable to understand the reasons behind supply shifts, they will be unable to adjust their demand forecasting accurately, which will lead to improper inventory availability, lost sales, and higher cost of goods sold.

Demand sensing and forecasting efficiency requires unified, trusted, and harmonized data. As an intelligent supply chain decision intelligence platform, InterSystems Supply Chain Orchestrator provides a complete view of an organization’s supply chain, harmonizing and normalizing disparate data from applications, suppliers, manufacturers, distributors, retailers, and consumers. It uses AI and ML to uncover what is currently happening, predicts what is likely to happen next, and uses prescriptive insights to outline the best options, ensuring maximum effectiveness and minimum delay.

Read the full report here.

Chris Cunnane is the Supply Chain Product Marketing Manager at InterSystems. In this role, he is responsible for developing and executing marketing strategy and content for the InterSystems supply chain technology suite. Chris has 20+ years of supply chain expertise, leading the supply chain practice at ARC Advisory Group, as well as holding various sales, marketing, and operations roles in the wholesale, retail, and automotive parts markets. He holds a BA in Communications from Stonehill College and an MA in Global Marketing Communications from Emerson College.

The post From Data to Decisions: Revolutionizing Supply Chain Management with Demand Sensing and Forecasting appeared first on Logistics Viewpoints.

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Federal Industrial Partnerships and Supply Chain Realignment Under the Trump Administration: Pharmaceuticals, Semiconductors, Critical Minerals, and Energy

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Federal Industrial Partnerships And Supply Chain Realignment Under The Trump Administration: Pharmaceuticals, Semiconductors, Critical Minerals, And Energy

In the months leading up to the 2026 midterm elections, the Trump administration has launched a broad initiative to negotiate agreements with companies across as many as thirty industries. According to reporting from Reuters and other outlets, these deals involve a range of mechanisms, including tariff relief, equity stakes, revenue guarantees, and regulatory adjustments.

The purpose of the initiative, according to administration officials, is to strengthen U.S. national and economic security by encouraging companies to expand production domestically, reduce reliance on China, and ensure the availability of critical products.

For logistics and supply chain leaders, this represents a significant change in the relationship between government and industry. Federal agencies are no longer simply regulators or supporters of infrastructure. They are becoming active participants in corporate strategy, investment, and supply chain design.

Structure of the Deals

The administration’s approach is not uniform. Each agreement varies depending on the sector and company involved. Examples include:

Pharmaceuticals: Eli Lilly was asked to expand insulin production, Pfizer was pressed to increase output of its cancer and cholesterol drugs, and AstraZeneca was encouraged to establish a new U.S. headquarters. In exchange, companies have been offered tariff relief or regulatory flexibility.
Semiconductors: A portion of grants provided under the CHIPS Act has been converted into equity stakes, including a reported 10 percent stake in Intel.
Critical Minerals: The Department of Defense took a 15 percent stake in MP Materials, secured a floor price for future government purchases, and facilitated a $500 million supply agreement between MP Materials and Apple for rare earth magnets.
Energy: The Department of Energy has asked companies such as Lithium Americas for equity stakes in exchange for federal loans supporting domestic mining and battery production.

The unifying theme is the use of federal leverage, such as tariffs, financing programs, or regulatory approvals, to secure commitments from private companies that align with stated national security objectives.

Agencies as Dealmakers

What distinguishes this initiative is the scale of inter-agency involvement. The White House has described the approach as “whole of government.”

The Department of Health and Human Services is leading negotiations in pharmaceuticals.
The Department of Commerce, under Secretary Howard Lutnick, has overseen transactions in steel, semiconductors, and industrial manufacturing.
The Department of Energy is linking financing programs to equity arrangements in energy and mining.
The Pentagon has led negotiations with defense contractors and suppliers of critical minerals.

Senior officials, including White House Chief of Staff Susie Wiles and supply chain coordinator David Copley, are directly involved in negotiations. The presence of Wall Street dealmakers, such as Michael Grimes (formerly of Morgan Stanley) and David Shapiro (formerly of Wachtell, Lipton, Rosen & Katz), illustrates the administration’s transactional orientation.

Financing Mechanisms

The administration is using multiple sources of capital to finance these arrangements:

International Development Finance Corporation (DFC): Originally designed to support development projects abroad, the DFC has proposed expanding its budget authority from $60 billion to $250 billion. If approved by Congress, it would fund projects in infrastructure, energy, and critical supply chains within the U.S.
Investment Accelerator (Commerce Department): Seeded by $550 billion pledged by Japan as part of a bilateral trade agreement, this entity will direct capital into U.S. strategic sectors, serving as a replacement for an earlier proposal to establish a sovereign wealth fund.
Existing Programs: Agencies are repurposing funds from programs such as the CHIPS Act and Department of Energy loan guarantees, often converting grants into equity holdings.

Together, these mechanisms represent one of the largest coordinated federal interventions in U.S. industrial and supply chain development in recent decades.

Implications for Supply Chains

The administration’s policies carry several direct consequences for logistics and supply chain management.

1. Reshoring of Manufacturing

Many of the deals include explicit requirements for expanded U.S. production. This will increase demand for domestic transportation, warehousing, and distribution capacity. It also implies higher utilization of U.S. ports and intermodal corridors, as inputs shift from finished imports to raw materials and intermediate goods requiring processing inside the United States.

2. Critical Minerals and Energy Security

The focus on rare earths, lithium, and other inputs for advanced manufacturing indicates a restructuring of upstream supply chains. Logistics providers should expect increased flows from domestic mining regions, such as Nevada’s Thacker Pass lithium project, to processing and manufacturing centers. This represents a shift away from reliance on Asian supply hubs, particularly China.

3. Government as Stakeholder

Equity stakes and long-term purchase agreements create a different operating environment. Logistics providers serving these industries may find demand more stable due to government-backed contracts. However, these arrangements may also impose compliance requirements and reduce flexibility in adjusting supply networks.

4. Public-Private Coordination

Federal involvement in freight and industrial infrastructure financing could accelerate long-delayed projects. Rail expansion, port upgrades, and domestic warehouse capacity may benefit from this investment. Companies positioned to partner on these projects may see long-term opportunities.

Risks and Concerns

Several risks accompany this shift:

Policy Reversal: Executives have expressed concern that a future administration could unwind or renegotiate these deals. Supply chains built around government-backed agreements may face uncertainty if political priorities shift.
Equity Demands: Some companies are wary of ceding ownership stakes to the federal government. This creates hesitation in sectors where ownership control and investor confidence are sensitive.
Market Distortions: Critics argue that selecting which companies receive government support could disadvantage firms excluded from the arrangements, altering competitive dynamics within industries.
Implementation Capacity: The scale of proposed financing, particularly the expansion of the DFC, requires congressional approval and capable management. Delays or political opposition could slow execution.

Policy-to-Supply-Chain Impact Table

Policy Mechanism
Industry Example
Government Action
Supply Chain Impact

Tariff Relief
Pharmaceuticals (Pfizer, Eli Lilly)
Tariff exemptions in exchange for expanded U.S. production
Increases demand for domestic warehousing, distribution, and cold-chain logistics for added output

Equity Stakes
Intel (10% stake), MP Materials (15% stake)
Federal ownership through converted grants or Defense Production Act
Creates long-term stability in supply flows, but may add compliance requirements for logistics providers

Purchase Guarantees
MP Materials with Apple
Pentagon set floor prices, Apple committed to $500M supply contract
Locks in demand for rare earth shipments, increasing domestic transport flows from mining to manufacturing

Federal Loans Linked to Equity
Lithium Americas (DOE loan, 5–10% stake requested)
Loan support tied to partial government ownership
Supports new mining and battery projects, creating future logistics demand for raw materials and finished batteries

Investment Accelerator Funding
Commerce Department
$550B in financing, partly funded by Japan, allocated to U.S. manufacturing and freight infrastructure
Potential expansion of ports, intermodal rail, and distribution centers, reducing bottlenecks in supply chains

Expanded DFC Financing
Multiple critical industries
Proposed budget growth from $60B to $250B for U.S. supply chains and infrastructure
Large-scale capital for freight corridors, warehouses, and strategic materials, enabling reshoring of production

Case Examples

MP Materials

The rare earth mining company received federal backing through a 15 percent Pentagon stake, floor pricing commitments, and a supply agreement with Apple. This illustrates the administration’s template: equity participation, purchase guarantees, and private-sector co-investment.

Intel

The conversion of CHIPS Act funding into a 10 percent federal equity stake in Intel highlights the new approach to semiconductor supply chain security. By tying financial support to ownership, the government ensures both accountability and a direct role in strategic sectors.

Lithium Americas

A Department of Energy loan of $2.26 billion, paired with negotiations for a 5 to 10 percent federal equity stake, demonstrates how energy supply chains, particularly those tied to electric vehicles and batteries, are being secured through mixed financing and ownership arrangements.

Long-Term Outlook

The administration’s strategy marks a departure from the traditional U.S. model of private-sector–led industrial development. Instead, it resembles coordinated industrial policies pursued in other economies, though with American characteristics.

For supply chain professionals, this means that:

Government will play a larger role in shaping sourcing, production, and distribution decisions.
Access to federal financing and contracts will become a key factor in strategic planning.
Logistics infrastructure may receive substantial investment, creating new opportunities for providers.
Companies must assess political as well as market risks when designing long-term supply chains.

The Trump administration’s pre-midterm industrial deals reflect a significant realignment of government and industry roles in the United States. By leveraging tariffs, financing programs, and direct equity stakes, the federal government is reshaping supply chains across pharmaceuticals, energy, critical minerals, and freight.

The initiative is intended to secure domestic production, reduce reliance on China, and ensure access to strategic inputs. For logistics leaders, the result will be increased reshoring activity, new demand for domestic infrastructure, and closer integration of supply chains with federal priorities.

At the same time, risks remain. The durability of these arrangements depends on political continuity, effective implementation, and the willingness of companies to partner with government under new terms.

In this evolving environment, logistics and supply chain professionals will need to monitor policy developments as closely as they do market trends. Supply chains are no longer shaped solely by efficiency and cost considerations. They are now integral to the nation’s industrial strategy.

The post Federal Industrial Partnerships and Supply Chain Realignment Under the Trump Administration: Pharmaceuticals, Semiconductors, Critical Minerals, and Energy appeared first on Logistics Viewpoints.

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Supply Chain and Logistics News Sept 29 – Oct 2nd 2025

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Supply Chain And Logistics News Sept 29 – Oct 2nd 2025

This week in supply chain news, major companies are demonstrating a mix of strategic adaptations and responses to global pressures. ExxonMobil and Kinaxis are collaborating to develop a next-generation supply chain management solution specifically for the complex oil and gas industry, aiming to increase resilience and provide comprehensive visibility. In a push for network efficiency, FedEx has launched a new direct cargo flight between Dublin, Ireland, and Indianapolis, Indiana, bypassing congested coastal hubs to reduce transit times. The pharmaceutical sector is also focused on resilience, with Eli Lilly and Amgen announcing significant U.S. manufacturing investments to bring critical drug production back to North America. Conversely, General Mills is restructuring its supply chain by closing three manufacturing plants in Missouri as a cost-saving measure in response to changing consumer spending habits. Finally, the U.S. government is imposing new tariffs on imported wood products and furniture, effective October 14, 2025, in a move to address what it identifies as a threat to the domestic industry and supply chain security.

The News of the Week:

ExxonMobil and Kinaxis are Developing a Next-Generation Supply Chain Management Solution for Oil and Gas

The oil and gas industry supply chain is one of the most complex in the world. It involves myriad complex production assets both onshore and offshore, transporting highly volatile products around the globe through pipelines, tank farms, ports, ships, rail, and truck. The end product could be gasoline, petrochemicals, natural gas, hydrogen, or any of hundreds of products from asphalt to motor oil. Disruptions to the oil and gas supply chain can have serious consequences for end users. The industry needs more comprehensive supply chain solutions that increase resilience, provide complete visibility across all aspects of the supply chain, and enable swift responses to business challenges and opportunities. Kinaxis and Exxon are collaborating to digitalize various sectors of Exxon’s business. They aim to leverage Kinaxis’s Maestro software to enhance planning and decision-making processes. Through this collaboration, the two companies aim to share solutions tailored to the oil and gas industry, which currently lacks supply chain management solutions that cater to their specific needs.

FedEx Expands Global Air Network with New Dublin- Indianapolis Route

In an effort to shorten transit times and strengthen its international network, FedEx has launched a new direct cargo flight between Dublin, Ireland, and Indianapolis, Indiana. The new four-day-a-week service bypasses traditional, more congested coastal gateways, which is expected to reduce shipping times by a full day for goods moving between Ireland and the U.S. Midwest. This strategic expansion is a response to the growing trade between the two regions and demonstrates how major carriers are adapting their networks to create more direct and efficient routes to meet evolving customer demands.

Eli Lily and Amgen Announce Massive U.S. Manufacturing Investments

In a major push for domestic drug production, pharmaceutical giants Eli Lilly and Amgen have announced huge investments in new U.S. manufacturing facilities. Eli Lilly is planning a new $6.5 billion factory in Houston, while Amgen is expanding its Puerto Rico plant with a $650 million investment. These moves are a direct response to the global supply chain vulnerabilities exposed in recent years and represent a significant effort to boost the resilience of the U.S. pharmaceutical supply chain. The investments aim to bring critical drug production back to North America, creating jobs and reducing reliance on overseas manufacturing.

General Mills is Closing Three Manufacturing Plants in Missouri

General Mills is closing three manufacturing plants in Missouri—a pizza crust facility in St. Charles and two pet food locations in Joplin—as part of a multiyear supply chain restructuring effort. The company expects to incur $82 million in restructuring charges, including asset write-offs and severance costs. This action is part of a broader trend among food and beverage companies to implement cost-saving measures in response to consumer spending pullbacks. The closures follow previous organizational actions by General Mills, such as job cuts and the closure of its innovation unit, and are intended to improve the company’s competitiveness.

US to Begin Furniture, Wood Import Tariffs on Oct. 14

New tariffs on imported wood products, including furniture, will take effect on October 14, 2025, following a Section 232 national security investigation. The initial duties will be 10% on softwood lumber and 25% on upholstered furniture, kitchen cabinets, and vanities. On January 1, the tariff rates are scheduled to increase to 30% for upholstered furniture and 50% for kitchen cabinets and vanities. The executive order provides for lower tariff caps for imports from specific trading partners, such as the U.K., Japan, and the European Union. These new tariffs are intended to address what the administration has identified as a threat to domestic industry and supply chain security.

Song of the week:

The post Supply Chain and Logistics News Sept 29 – Oct 2nd 2025 appeared first on Logistics Viewpoints.

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Call for Speakers: Ready to Drive Real Change in Intelligent Operations and Resilient Supply Chains – ARC Industry Forum 2025

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Call For Speakers: Ready To Drive Real Change In Intelligent Operations And Resilient Supply Chains – Arc Industry Forum 2025

Call for Speakers – ARC Industry Forum 2025

The ARC Industry Forum is the premier event where operations, supply chain, and technology leaders gather to shape the future of intelligent and resilient enterprises. In 2025, supply chains face unprecedented disruption, but also unmatched opportunity. We are seeking speakers—executives, practitioners, and innovators—who can share strategies, frameworks, and real-world experiences to inspire and guide their peers.

Sample Session Themes

To help illustrate the types of topics we feature, here are a few recent examples:

The New Frontier of Operations and Supply Chain: AI, Resilience, and Intelligence – Exploring how AI, analytics, automation, and connected intelligence converge to deliver agility and resilience.
Building Resilient Supply Chains in the Age of Shifting Geopolitics – Addressing the regulatory, tariff, and policy challenges facing global supply networks.
Unlocking the Power of Knowledge Transfer in Enterprise Systems – Showcasing best practices to fully leverage enterprise and knowledge management systems.

These examples are only a sample of the many tracks available. Additional sessions will cover digital transformation, sustainability, cybersecurity, workforce strategies, and other timely topics.

Submission Guidelines

We invite proposals that highlight real-world case studies, practical lessons, and strategic frameworks. Presentations should be vendor-neutral, educational, and tailored for an audience of senior executives and practitioners.

If you are interested in speaking, please submit:

A proposed session title and abstract (150–250 words)
Key takeaways for attendees
Speaker bio and organizational role

To submit a proposal, or simply for more information, contact us now

The post Call for Speakers: Ready to Drive Real Change in Intelligent Operations and Resilient Supply Chains – ARC Industry Forum 2025 appeared first on Logistics Viewpoints.

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