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In the fast-paced world of modern supplychains, traditional forecasting methods fall short. Advanced supplychain planning is being transformed by probabilistic forecasting , which revolutionizes demand forecasting, supply planning, and inventory optimization.
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.
In the fast-paced world of modern supplychains, traditional forecasting methods fall short. Probabilistic forecasting is revolutionizing demand forecasting, supply planning, and inventory optimization by significantly improving forecast accuracy and decision-making across distribution networks.
Improving demand forecast accuracy is crucial for supplychain success. Traditional demand forecasting methods often fall short, resulting in inefficiencies, excess inventory, and lost revenue. Unlike static demand prediction models, AI-driven forecasting adapts over time, leading to improved demand forecast accuracy.
From demand forecasting to inventory optimization, risk mitigation to sustainability — AI is set to transform everything. It’s a must-read for forward-thinking procurement and supplychain leaders looking to harness the power of AI to achieve transformative results. AI isn’t the future. It’s here, now.
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. Traditional forecasting methods often fail under high variability, leading to excess costs, stockouts, and obsolescence.
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. Traditional forecasting methods often fail under high variability, leading to excess costs, stockouts, and obsolescence.
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%.
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. The forecast can be compared to what actually shipped or sold.
Speaker: Brian Dooley, Director SC Navigator, AIMMS
Is your demand forecasting process evolving with the times? Are you satisfied with your level of forecast accuracy? This webinar shares research findings from a recent survey among supplychain planning professionals and delves into the following: Who is typically responsible for forecasting?
But many supplychain practitioners dont realize that the most common approach to supplychain planningusing a demand-driven forecast as the primary input to future planningis just as outdated. Forecast Accuracy vs. Uncertainty Uncertainty-driven demand forecasting assumes that accuracy is an ongoing challenge.
Demand forecasting is a critical strategy for supplychain management that can dramatically improve business decision-making and financial performance. However, securing leadership buy-in for demand forecasting technology requires a strategic approach that clearly demonstrates value.
Supplychain disruptions have become a persistent operational risk. Traditional supplychain planning, which relies on historical data and reactive adjustments, is no longer adequate for managing these challenges. Amazon is a leader in AI-driven supplychain management.
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. The reason?
As unavoidable variability adds more complexity to your supplychain, this guide shares the effects of uncertainty on businesses and explores ways to alleviate uncertainty & increase manageability through greater forecast accuracy.
The supplychain industry is no stranger to uncertainty. While businesses cant predict every challenge, they can take proactive steps to anticipate disruptions and strengthen their supplychain management systems with advanced demand planning tools.
Based on this, a multiple-month financial, supplychain, and capital expenditure plan is produced. A supplychain planning application is the core technology that enables robust planning. Historically, the supplychain plan that resulted from the IBP process was too static. More than 5.6
Balancing forecast accuracy with inventory management gets more challenging every day. Artificial intelligence (AI) and rapidly developing generative AI tools provide complex, real-time, and in-depth insights specific to supplychain management. This makes it hard to reach agreement. Fortunately, this is starting to change.
In the rapidly evolving world of global supplychains, interoperability—the ability of systems, devices, and organizations to work together seamlessly—has become a critical factor for operational efficiency. Here’s how each layer translates to the supplychain context: 1.
Speaker: Olivia Montgomery, Associate Principal Supply Chain Analyst
The supplychain management techniques that dominated the last 30 years are no longer supporting consumer behavior or logistics and manufacturing capabilities. You'll learn more about: Trending supplychain tech investments to consider. Forecasting techniques to manage inventory. So what’s working now?
CONA Services Provides a Common Platform for SupplyChain Collaboration CONA Services LLC is an IT services company owned and governed by the 11 largest Coca-Cola bottlers in North America. Its main applications include SAP for backend transactions, Blue Yonder for supplychain management , and Salesforce for sales.
In most industries, supplychains have become increasingly complex. As a result, many organizations are moving toward supplychain orchestration as a structured method for improving coordination. Collaborative Workflows Supplychains involve many teams and companies working toward the same outcome.
However, as carbon taxes and emissions reporting requirements continue increasing, supplychain professionals face mounting pressures from inside and outside their organizations to measure and improve performance against new, nebulous sustainability metrics. Sustainability is high on the list of favorite corporate buzzwords.
The adoption of AI in supplychain automation is enabling companies to make more accurate decisions, reduce cycle times, and better manage complexity. AI in supplychain automation is gradually reshaping how core functions operate, particularly in procurement, warehousing, and logistics.
The industrial sectorparticularly supplychain management, is facing unprecedented complexity. Lets delve into the core concepts of AI Agents and multi-agent workflows, their relevance to what ARC Advisory Group calls Industrial AI , and their potential to revolutionize supplychain management.
Neil’s post in response to my post of Driving Value From Outside-in Planning : In her post, ‘Driving Value from SupplyChain Planning’, Lora Cecere provides great supplychain analysis and benchmarking for her supplychains to admire. Supplychain leaders love shiny objects.
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. We run one of the few truly hybrid supplychain networks. That has worked out well for us.
The forecast calls for snow and ice for most of the. Read more The post Above the Fold: SupplyChain Logistics News (January 10, 2025) appeared first on Talking Logistics with Adrian Gonzalez. As you read this, Ill be making my way to my sons graduation from Officer Candidate School (OCS) at Fort Moore, Georgia.
Difficulty forecasting demand due to constant supplychain disruptions. Supplychain analytics creates new insights that help improve supplychain decision making from the improvement of front-line operations to strategic choices, such as the selection of the right supplychain operating models.” – McKinsey & Company.
Imagine a world where supplychains run with complete transparency, efficiency, and automationwhere every transaction, shipment, and payment are executed seamlessly without intermediaries slowing things down. For decades, supplychain management has encountered bureaucratic bottlenecks, inefficiencies, and trust issues.
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. Incorporating Sustainability in SupplyChains Sustainability in supplychains extends beyond energy use, addressing broader environmental and social impacts.
For years, supplychains were engineered to be lean. Recent years have brought a series of disruptions that exposed vulnerabilities in how supplychains are designed. Recent years have brought a series of disruptions that exposed vulnerabilities in how supplychains are designed.
Why Transformation Is a Boardroom Priority Supplychain management is now a core strategic concern for business leaders. Companies that fail to modernize face supply shortages, revenue loss, and regulatory risks. The Shift from Cost-Cutting to Resilience For years, supplychains prioritized cost reduction over resilience.
Speaker: Irina Rosca, Director of Supply Chain Operations, Helix
As we plan for the world of eCommerce and the customer expectation of quick, free shipping, our ability to forecast is turned on its head. Join Irina Rosca, Director of SupplyChain Operations at Helix and an experienced global supplychain strategist, as she walks through the key questions to a successful and efficient distribution network.
When one thinks of supplychain software 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.
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.
During my current supplychain planning market research, I have received briefings from several SCP companies. The people who work with us are those who really, truly believe in what we believed in from the start, that is, autonomous supplychains are possible. Forecasting is not an actionable item.”
Harvard Business Review recently published an article, “ To Build Resilience, CEOs Need to Become Supply-Chain Experts ”. In this article, we wanted to discuss one aspect of supplychain that is often not given enough attention – building strategic relationships and shared value with direct spend suppliers.
Agility and accuracy don’t necessarily need to be at logger heads. In-fact, anticipatory agility enabled by AI and Machine Learning can move the accuracy frontier forward in terms of validity and consistency driving significant business value.
As artificial intelligence (AI) becomes more integrated into supplychains, companies are focusing on how it can support human workers. Human-in-the-Loop Systems: AI as a Support Layer In supplychain operations, AI is rarely deployed to act independently. Walmart has implemented AI to enhance inventory forecasting.
Predictive analytics offers the added benefit of forecasting maintenance needs and planning routes based on historical data, allowing for proactive resource allocation. This will result in a more resilient supplychain, equipped to handle disruptions with minimal impact on delivery schedules. The post Fleet Management 2.0:
In the supplychain arena, the need to make course corrections is exploding. For instance, advanced factory scheduling solutions use predictive maintenance inputs, which rely on sensor data to forecast equipment failures. Short-term forecasting relies on POS and other forms of downstream data.
This disconnect between AIs potential and real-world adoption presents a significant opportunity for companies to gain a competitive edge, especially in supplychain management where uncertainty is the norm. However, its important to recognize that AI and machine learning are not magic fixes for supplychain challenges.
Speaker: Eva Dawkins - Senior Consultant, Supply Chain
The last three years have been a rollercoaster ride for most supplychains, filled with volatile unpredictability and frequent disruptions. We know technology improvements can improve supplychain operations and add significant value for companies even in turbulent times.
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