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At ToolsGroup, we’ve long championed probabilistic demand forecasting (also known as stochastic forecasting) as the cornerstone of effective supply chain management software. Like betting that a champion racehorse will win a specific race, this “single-number” forecast assumes one definitive result.
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. Probabilistic Demand Forecasting represents a paradigm shift in supply chain planning. On average, our customers achieve: 99.9%
Volatile markets, global disruptions, and the need for real-time insights are pushing traditional systems to their limits. Understanding AI Agents At its core, an AI Agent is a reasoning engine capable of understanding context, planning workflows, connecting to external tools and data, and executing actions to achieve a defined goal.
Access to Unique Process and Asset Capabilities: Some suppliers offer unique skills, technologies, or processes that are not available in-house or through other sources. Long term forecast collaboration becomes a critical requirement for manufacturers and their direct suppliers to focus on to de-risk their supply chains.
Enterprise procurement leaders are under more pressure than ever—juggling cost control, compliance, supplier risk, and internal complexity, all while trying to modernize outdated systems. AI, automation, and generative tools are redefining efficiency, allowing procurement teams to move from reactive to proactive decision-making.
Jack Fiedler : We’re unique in the technology industry. We’ve taken the same hybrid approach from a supply chain technology perspective. I’m responsible for the overall digital transformation, including technology. But then it very quickly evolved into a full intelligence platform.
AI is not a new technology in the supply chain realm; it has been used in some cases for decades. Demand planning engines have natural feedback loops that allow the forecast engine to learn. The forecast can be compared to what actually shipped or sold. More recently, many other cases have emerged.
Proactively adopting cleaner energy sources ensures alignment with these evolving regulations. The industry’s dependency on traditional energy sources necessitates an urgent shift toward cleaner alternatives. Retrofitting existing infrastructure with energy-efficient technologies further enhances sustainability efforts.
I laugh when business leaders tell me that they are going to replace their current supply chain planning technologies with “AI.” Each supply chain planning technology at the end of 2024, went through disruption–change in CEO, business model shift, layoffs, re-platforming and acquisitions. You are right.
When one thinks of supply chain software vendors, the name InterSystems may not spring to mind. They offer softwaresystems and technology for complex integration, rapid application development, and advanced analytics and sell those solutions to companies that need to accelerate optimized business outcomes.
Industry-specific content is available for processes like Source to Settle, Procure to Pay, Order to Cash, and more. Automate: utilizes technologies such as RPA, IDP, and IPaaS. Automate: utilizes technologies such as RPA, IDP, and IPaaS. iPaaS provides a comprehensive set of tools for connecting applications.
From sourcing and bid evaluation to warehouse slotting and dynamic routing, AI tools support faster and more consistent outcomes by processing large volumes of operational data and identifying patterns that human decision-makers may overlook. These capabilities are now being integrated into mainstream TMS, WMS, and ERP platforms.
SAP is embedding its generative Joule across the SAP Ariba source-to-pay solution portfolio to make it easier for their customers to manage routine inquiries, such as status updates, summarization, and frequently asked questions. It is a brilliant tool.” Those types of disagreements disappear in a SCCN platform.
They integrate AI into demand forecasting, inventory optimization, and logistics operations to improve efficiency, reduce costs, and mitigate risks. Organizations examine past sales trends, apply seasonal adjustments, and make forecasts based on historical models. Amazon is a leader in AI-driven supply chain management.
Adding to this already uphill battle, we don’t have trustworthy new product forecasting methods because forecasting new products with no sales data is very hit-and-miss. Machine learning (ML) provides an effective weapon for your new product forecasting arsenal. Why is new product forecasting important?
A data-driven, technology-enabled approach is required to build resilience and efficiency. The COVID-19 pandemic and ongoing geopolitical shifts demonstrated the risks of relying on single-source suppliers and minimal inventory buffers. AI and Automation in Supply Chain Management Technology is redefining supply chain operations.
Business leaders see the open sharing of feedback on software as too risky. How can I improve the process of software selection? How can I improve the process of software selection? Buying supply chain planning software is hard. Many technologies (I count six) are missing, and most of the ratings are just wrong.
The global supply chain landscape is undergoing significant transformations, influenced by rapid technological advancements, shifting consumer expectations, and the intricacies of international commerce. Preparing the next generation to excel in this dynamic field requires more than traditional education methods.
Unfortunately, outdated tools and fragmented processes make it difficult to maintain visibility across the supply chain and adapt at the pace of business. Digital procurement streamlines workflows and unifies data, enabling faster sourcing, better collaboration, and improved accuracy.
Demand forecasting has evolved dramatically in recent years. Traditional forecasting methods often fail under high variability, leading to excess costs, stockouts, and obsolescence. What is Demand Forecasting in Supply Chain Management? What is Demand Forecasting in Supply Chain Management? Image source: Stefan de Kok 2.
When my fiance heard about the price, he advised that I find a local hairdresser and set up a frequent-shopper account with them for a few months until the tool is back in stock. And pretty much everyone realized that the old technologies used in planning are not going to cut it anymore when there are so many moving parts in the game.
AI is reshaping the way organizations source, manage suppliers, and drive value today. As supply chains become more interconnected and risks more dynamic, traditional procurement tools fall short. AI agents offer a smarter, faster way to manage sourcing, risk, and spend across the entire procurement lifecycle.
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 supply chain management. Traditional approaches often divide departments like sales, marketing, and production.
The pace of technological evolution is pushing organizations to the brink. The groundbreaking technology is transforming how companies manage sales and operations planning (S&OP). This eliminates the need for lengthy back-and-forth communications and manual data entry by delivering a single source of truth.
Companies leaning heavily on global sourcing? manufacturer I know saw their import costs jump overnight, forcing a rethink of a decade-old sourcing strategy. Consequently, when shortages emerged, they had already secured alternative sources, thereby averting a significant disruption to production. For example, U.S.-based
During his tenure in the industry, he built innovative pricing and forecasting models, leveraging internal and external data sources to improve internal decision-making and increase profitability. Prior to joining DAT, Adamo led the pricing and decision science teams at FedEx.
In this article, we break down the differences between procurement and purchasing, explain why the distinction matters, and explore how technology can align both functions to drive efficiency, compliance, and long-term value. Technology unifies procurement and purchasing, improving visibility, compliance, and workflow automation.
Many large organizations have multiple systems for order, warehouse, or transportation management that are barely integrated frequently not at all. Optimizing fulfillment requires a series of steps to get a shipment from its source to the end customer.
Reducing cost was the primary objective, and most operational decisionsfrom sourcing to fulfillmentreflected that mindset. All of this points to a larger issue: systems that perform well under stable conditions but lack the flexibility to respond when those conditions change. For years, supply chains were engineered to be lean.
Proprietary warehouse, transportation , and labor management systems bolted onto legacy ERP systems, all “enriched” with off-the-shelf and bespoke software solutions, are a recipe for disaster. Yet, the money was spent, and the technology is now in place. Every system in your network collects it and stores it somewhere.
They need visibility across multiple internal systemslike ERP, CRM, and financial platformsand even external sources shared with suppliers, partners, and customers. Thats why modern BI systems are quickly becoming the go-to solution for data-driven enterprises. But lets be clear: not all BI platforms are created equal.
Despite their best efforts, current events and market dynamics caught up with them, leading to issues managing their suppliers and sourcing the materials needed for their products. If nothing else, the last few years highlighted the importance of sourcing strategically. Upcoming Recession? Price Volatility.
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. AI-powered demand forecastingsoftware can significantly improve predictive accuracy, making it a crucial component of modern supply chain planning software.
Companies that previously prioritized cost-cutting and centralized sourcing quickly found themselves exposed to serious production and distribution risks. In response, many organizations have shifted toward decentralized and regionalized supply chain models, distributing production and sourcing across multiple regions.
With multi-echelon networks, supplier uncertainty, multiyear product lifecycles, and reverse logistics channels , aftermarket supply chains exceed the capabilities of traditional planning tools. Traditional supply chain planning tools fall short for several key reasons: Inability to handle intermittent demand patterns.
Manufacturing ERP (Enterprise Resource Planning) software integrates all your core business processes into one powerful platform. Think of it as the central nervous system of your operation, connecting everything from production planning and inventory control to supply chain management and financial reporting.
With the E2E exception-base autonomous planning, the system automates decisions from demand forecasts, production plans, and order fulfillment strategies to delivery with minimal need for manual intervention. End-to-End Supply Chain Planning Platform The end-to-end process begins with data.
We need planning platforms to keep up with all the changes. This means we need more agile, flexible, and scalable planning platforms to process and consolidate new data sources, drive insights using advanced analytics such as AI/ML to drive autonomous decisions, and expand collaboration within and outside our organizations.
When it comes to running a company, when things break down executives have traditionally said “we need to improve our forecasting!” Would better forecasting accuracy be a good thing? Unfortunately, most companies cannot, and will never be able to, consistently rely on highly accurate forecasts. Absolutely!
ToolsGroup identifies five key drivers shaping the future of supply chains: changing customer expectations, heightened competition, rising operational complexity, technological advancements, and geopolitical tensions. Technological Advancements Real-time inventory tracking and predictive analytics give leading firms a competitive edge.
How 3PLs Can Gain Visibility and a Competitive Advantage Offering Automated Billing and a Self-Service Interactive Customer Portal It’s hard to imagine a third-party logistics (3PL) business today operating without some form of a warehouse management system ( WMS ) connecting the digital dots. But can technology do more?
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