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The modern supplychain is a complex network of suppliers, manufacturers, distributors, and customers, all interconnected and reliant on a shared ecosystem of trust and accountability. As industries evolve and global markets expand, ethical considerations have become central to supplychain compliance.
I laugh when business leaders tell me that they are going to replace their current supplychain planning technologies with “AI.” Each supplychain planning technology at the end of 2024, went through disruption–change in CEO, business model shift, layoffs, re-platforming and acquisitions.
Supplychain practitioners seeking the best way to speed decision intelligence, unify supplychain data, and increase operational efficiency can benefit from a supplychain data gateway. Here are 10 ways a supplychain data gateway can improve your performance across the end-to-end supplychain.
India’s growth story can continue if it streamlines and effectively manages its supplychain like the iconic dairy brand Amul that recently entered the US market. Amul’s model supports small producers by integrating large-scale economics, cutting out intermediaries, and connecting producers directly with consumers.
Explore the most common use cases for network design and optimizationsoftware. This eBook shares how supplychain leaders leverage their supplychain design software to tackle a variety of challenges and questions. Scenario analysis and optimization defined. Modeling your base case.
The logistics and supplychain industry is a critical component of global trade, responsible for moving goods and materials efficiently to meet consumer and business demands. Businesses face heightened uncertainty in managing costs and securing stable energy supplies.
Supplychain disruptions have become a persistent operational risk. Geopolitical instability, extreme weather, labor shortages, and fluctuating consumer demand regularly impact global logistics. Amazon is a leader in AI-driven supplychain management.
It has led supplychain vendors to discuss how they currently use artificial intelligence. Further, virtually every supplier of supplychain solutions is eager to explain the ongoing investments they are making in artificial intelligence. When it came out, ChatGPT seemed like magic.
The adoption of AI in supplychainautomation is enabling companies to make more accurate decisions, reduce cycle times, and better manage complexity. AI in supplychainautomation is gradually reshaping how core functions operate, particularly in procurement, warehousing, and logistics.
Jack Fiedler, the vice president for digital transformation of the global supplychain at Lenovo Lenovo is ranked tenth by one leading analyst firm among a list of global companies with exceptional supplychains. During COVID, this more agile and resilient model allowed the firm to grow their market share.
When one thinks of supplychainsoftware vendors, the name InterSystems may not spring to mind. A supplychain data fabric can help companies augment their supplychain processes. They aim to achieve the same success in supplychain management that they have achieved in the healthcare sector.
For years, supplychains were engineered to be lean. Reducing cost was the primary objective, and most operational decisionsfrom sourcing to fulfillmentreflected that mindset. Lean models alone are no longer sufficient. Why Current SupplyChains Struggle The common failure points are not surprising.
Artificial intelligence (AI) and rapidly developing generative AI tools provide complex, real-time, and in-depth insights specific to supplychain management. Further, AI-driven demand sensing allows businesses to combine scattered data which is essential for better forecast accuracy.
The industrial sectorparticularly supplychain management, is facing unprecedented complexity. While Generative AI (GenAI) has shown promise, its limitations in planning, workflow automation, and dynamic adaptation necessitate a more sophisticated approach. Colin Masson, ARC Advisory Groups expert on Industrial AI.
Why Transformation Is a Boardroom Priority Supplychain management is now a core strategic concern for business leaders. Recent disruptions have exposed significant vulnerabilities in traditional models, driven by geopolitical instability, fluctuating demand, and operational inefficiencies.
Supplychain practitioners seeking the best way to speed decision intelligence, unify supplychain data, and increase operational efficiency can benefit from a supplychain data gateway. Here are 10 ways a supplychain data gateway can improve your performance across the end-to-end supplychain.
In today’s interconnected global economy, sustainability within supplychains and logistics has become a necessity rather than an option. Regulatory demands, rising consumer expectations, and global challenges such as climate change and social inequality have made sustainable practices a strategic priority.
Those that also leverage scenarios in IBP are even better prepared to deal with the supplychain shocks caused by COVID-19. Our first webinar with Oliver Wight discussed common people, process and technology pitfalls that hinder IBP initiatives. Let’s explore them briefly in this blog post.
At ToolsGroup, we’ve long championed probabilistic demand forecasting (also known as stochastic forecasting) as the cornerstone of effective supplychain management software. Like betting that a champion racehorse will win a specific race, this “single-number” forecast assumes one definitive result.
Global supplychains have been tested repeatedly by a series of disruptive events, including the COVID-19 pandemic, U.S.-China Companies that previously prioritized cost-cutting and centralized sourcing quickly found themselves exposed to serious production and distribution risks. China trade disputes, and natural disasters.
All supplychain vendors seek to position themselves as leaders in supplychain AI. The current AI landscape can be viewed as a series of wars,” where companies and organizations are battling for dominance across various technological and market battlefronts. But there is a larger AI ecosystem.
Safety Stock: Navigating SupplyChain Volatility Through Strategic Inventory Planning Demand volatility represents a critical challenge for supplychain executives today, with safety stock emerging as a key strategic tool to mitigate market uncertainties.
Trade policies are constantly evolving, forcing companies to assess how these changes impact customer demand, supply networks, fulfillment strategies, and cost to serve. Supplychains need to be more agile than ever, yet much of the advice circulating in the industry remains high-level or less than ideal.
Historically, supplychain leaders managed supplychains in a world of abundance. There are many factors: war, supply shortages, climate change, labor (knowledge and availability), and shifts in governmental regulation. The waste included: Negative Forecast Value Added (FVA) in demand planning.
Demand forecasting has evolved dramatically in recent years. Businesses have shifted from supply-focused approaches to demand-driven models, yet many still struggle to balance accuracy with agility. What is Demand Forecasting in SupplyChain Management? Image source: Stefan de Kok 2.
The supplychain industry is no stranger to uncertainty. Unexpected challenges like shifts in global markets, economic upheaval, commodity shortages, advancements in technology, or environmental changes can send shockwaves through operations in unexpected ways.
Ted Krantz, CEO of Interos Interos , a company providing supplychain resilience and risk management software, emailed me to say that there was a supplychain risk everyone seemed to be ignoring – AI-related risks. The AI-related risks include data poisoning and model corruption.
For the past few years, the news has been filled with stories about supplychain disruptions, supplychain fragility, and the need for supplychain resilience. A term once prominent in supply discussions optimization isn’t heard quite as often as it used to be.
Technology can change or even improve work. Companies today making a fundamental mistake: they are attempting to automate current processes with AI versus challenging and redefining work. Today, in supplychain planning, this could not be further from reality. What’s missing? This bearish attitude is well-founded.
SupplyChain & Logistics News Round-Up (October 7th – 11th) This past week, I’ve been playing tourist in London, one of my favorite cities in Europe. In the context of supplychains, I found the exhibit fascinating and saw that the obsession with foreign objects has persisted throughout history.
Supplychains, which facilitate the movement of products from manufacturers to consumers, have historically encountered issues such as inefficiency, fraud, and a lack of transparency. Companies find it difficult to fully trust the data from suppliers, complicating efforts to ensure product authenticity, safety, and ethical sourcing.
As a supplychain executive, picture beginning your day with a cup of coffee when a news alert notifies you of newly imposed tariffs affecting your primary suppliers in China. This isnt a hypothetical scenario; its the daily grind for many businesses in 2025, where global trade rules shift faster than you can update your spreadsheets.
Gartner predicts that by 2026, 95% of data-driven decisions will be at least partially automated. In fact, Gartner also found that only 10% of CEOs say their business uses AI strategically, and just 9% of technology leaders report having a clearly defined AI vision statement. Yet, many companies struggle to harness AIs full potential.
I find that most companies’ understanding of supplychain planning is immature, and that next week, at the Gartner SupplyChain Summit in Orlando, that many will don their Mickey ears to discuss what I consider outdated supplychain planning models. Buying supplychain planning software is hard.
Five years ago, we all thought the COVID-19 pandemic resulted in the most disrupted supplychain landscape we would ever see. Since then, supplychain disruptions and volatility have only increased. We were wrong. The Ukraine-Russia conflict is ongoing. Tensions flare in the Middle East without warning. billion to $23.07
The pace of technological evolution is pushing organizations to the brink. This is more evident in supplychain, where time-tested methods are being replaced with new ones. The groundbreaking technology is transforming how companies manage sales and operations planning (S&OP). Enter Generative AI (GenAI).
Machine learning (ML)a specialized field within artificial intelligence (AI)is revolutionizing demand planning and supplychain management. According to McKinsey , organizations implementing AI-driven demand forecasting solutions can reduce forecast errors by 30% to 50%.
From May 19 to 21, 2025, CeMAT Southeast Asia and LogiSYM Asia Pacific were co-located for the second consecutive year at Singapore EXPO, creating a comprehensive platform for the regions logistics and supplychain community. Geek+ was honored as Best Warehouse Robotics Company for its smart warehouse automation solutions.
Unfortunately, Helene was not an exception but instead illustrates the “new normal” situation, where weather events of increasing frequency and severity are no longer isolated incidents, but are instead a consistent threat to supplychains. tallying a staggering $182 billion in damages.
It creates a single source of truth for your rate management, automating RFQs and streamlining the entire procurement process. billion rate data points monthly to provide the most comprehensive view of the market, helping you identify savings opportunities and make data-driven decisions.
Increasing concerns over mass supplychain disruptions. Its a rollercoaster for logistics and supplychain leaders operating in global markets. Businesses are facing greater volatility as tariff changes wreak havoc on supplychains, operational costs, and overall profitability. Extreme tariff volatility.
Robotic Process Automation (RPA) refers to process automation that combines process steps with decision models or business rules with little to no human oversight. It is typically applied to high-volume transactional processes with limited variation and clearly outlined business rules or decision models.
Home No More Black Swans: The Age of SupplyChain Uncertainty Freightos Enterprise unifies market intelligence, tender management, and shipment operations into one solution, enhancing logistics efficiency for large import-export businesses. The Problem with Fragmented Solutions The logistics technology space is undeniably crowded.
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