This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
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. Since ML began being used in demand forecasting in the early 2000s, ML has helped greatly increase the breadth and depth of forecasting.
By applying the ISO OSI (Open Systems Interconnection) seven layer model, traditionally used in networking, to logistics, businesses can achieve a structured framework that enhances communication, reduces friction, and improves collaboration throughout the supply chain. Here’s how each layer translates to the supply chain context: 1.
The forecast calls for snow and ice for most of the. Read more The post Above the Fold: Supply Chain Logistics News (January 10, 2025) appeared first on Talking Logistics with Adrian Gonzalez. After 10 weeks of basic training and 12 weeks at OCS, hell be a newly commissioned officer in the United States Army.
The logistics and supply chain industry is a critical component of global trade, responsible for moving goods and materials efficiently to meet consumer and business demands. Addressing Energy Challenges in Logistics The logistics sector is a significant contributor to greenhouse gas emissions.
Speaker: Olivia Montgomery, Associate Principal Supply Chain Analyst
The supply chain management techniques that dominated the last 30 years are no longer supporting consumer behavior or logistics and manufacturing capabilities. Forecasting techniques to manage inventory. Curious to know how your peers are navigating ongoing disruption? So what’s working now? What should your plans for 2023 include?
AI in supply chain automation is gradually reshaping how core functions operate, particularly in procurement, warehousing, and logistics. Key Insight: The use of AI in supply chain automation is producing tangible benefits across procurement, warehousing, and logistics.
He leads a team of market experts who study every facet of the logistics industry to bring the best available insight to customers. 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.
Geopolitical instability, extreme weather, labor shortages, and fluctuating consumer demand regularly impact global logistics. They integrate AI into demand forecasting, inventory optimization, and logistics operations to improve efficiency, reduce costs, and mitigate risks.
That capability is accurate, dynamic, real-time forecasting. Thanks to artificial intelligence (AI), machine learning (ML), data science, analytics, and advanced algorithms, today’s forecasting solutions are smarter and more precise than ever.
Further, the journey to autonomous planning does not rely on a highly accurate forecast. “I I have not cared for 20 years”, Mr. Bakkalbasi states with force, what level of forecast accuracy is achieved. Forecasting is not an actionable item.” You don’t act on a forecast; you act on what you purchase.
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. Don’t recalculate the forecast. Warehouse management systems rely on RF scans of locations and products.
Market Growth Outlook Includes a comprehensive five-year forecast with: Global and regional market breakdowns Vertical-specific trends Historical data for benchmarking Executive dashboards and TAM modeling 2. Download the Executive Summary Your roadmap to smarter logistics starts here.
Long term forecast collaboration becomes a critical requirement for manufacturers and their direct suppliers to focus on to de-risk their supply chains. Ensuring that collaborative forecasts, VMI and OTIF data is captured through execution platforms and utilized as part of S&OP and S&OE is critical.
Production plans might be locked for as long as a month, regardless of how accurate the forecast was. Where in the extended network of suppliers, customers, and logistics partners has the problem that limits the plan arisen? Historically, the supply chain plan that resulted from the IBP process was too static.
With freight transport accounting for a significant share of global emissions, efforts to improve logistics now extend beyond operational metrics to include resilience, regulatory compliance, and climate performance. CEVA Logistics, a CMA CGM subsidiary, uses Googles AI tools for warehouse management and demand forecasting.
However, logistics managers cannot deliver against todays goals with yesterdays TMS systems. For example, reduced emissions could result from streamlined routing or fewer trips due to improved demand forecasting. With rapidly increasing freight demand worldwide, it is expected to become the highest-emitting sector by 2050.1
The transportation, logistics, and energy storage sectors are undergoing profound transformation, driven by rapid technological advancements, evolving consumer expectations, and the global pursuit of sustainability. In transportation and logistics, this has manifested as a significant focus on electrification and renewable energy integration.
Companies are restructuring supplier networks, adopting just-in-case (JIC) inventory models, and implementing AI-driven forecasting to anticipate and mitigate disruptions. AI-driven analytics, machine learning, and robotics are improving procurement, inventory management, logistics, and supplier negotiations.
The system can detect a deviation from a forecast, for example, and yet understand if the deviation is in an allowable range and that an alert does not have to be generated. Should it be used to forecast a group of materials? The post CONA Services Embraces Supply Chain AI appeared first on Logistics Viewpoints.
With multi-echelon networks, supplier uncertainty, multiyear product lifecycles, and reverse logistics channels , aftermarket supply chains exceed the capabilities of traditional planning tools. The evidence is compelling: Aftermarket supply chains have evolved beyond the capabilities of conventional forecasting methodologies.
CTSI-Global operates at the intersection of logistics and technology, focusing on solutions that address the challenges of transportation management. At the heart of CTSI-Globals portfolio is its TMS, which supports essential logistics tasks such as load planning, routing, parcel management, and freight auditing.
(NYSE: ETWO), the connected supply chain SaaS platform with the largest multi-enterprise network, announced today at its annual Connect customer conference the release of its highly anticipated 2024 Forecasting and Inventory Benchmark Study.
When a new tariff is proposed, companies using AI-based forecasting tools are often able to adjust their sourcing or logistics strategies well before the policy takes effect. Rather than planning based on a single forecast, supply chain teams can evaluate multiple options in parallel: What happens if tariffs increase by 15%?
In an increasingly competitive logistics landscape, these capabilities allow companies to remain agile and cost-effective. Predictive analytics offers the added benefit of forecasting maintenance needs and planning routes based on historical data, allowing for proactive resource allocation.
With multi-echelon networks, supplier uncertainty, multiyear product lifecycles, and reverse logistics channels , aftermarket supply chains exceed the capabilities of traditional planning tools. The evidence is compelling: Aftermarket supply chains have evolved beyond the capabilities of conventional forecasting methodologies.
Together, the companies will provide businesses with powerful labor insights for workflow analysis, benchmarking, and forecasting across their networks. Read more at Unlocking Powerful Labor Insights with Easy Metrics Partnership The post Open Sky Partners with Easy Metrics for Labor Efficiency appeared first on Logistics Viewpoints.
Unlike some of the other trends articles we have covered at Logistics Viewpoints, which take a deeper dive into technology and application specific trends, this article looked at the top trends executives need to be paying attention to before their strategic planning meetings commence. billion globally, and I forecast it to grow to $9.9
Moreover, maintaining optimal service levels while balancing inventory costs is a delicate act that requires sophisticated forecasting and inventory management techniques, underlining the importance of advanced spare parts management solutions.
For example, Amazon uses AI to optimize delivery logistics. Walmart has implemented AI to enhance inventory forecasting. Many repetitive tasks, such as manual data entry and static forecasting, can be handled by software. The post People + AI: Augmenting the Supply Chain Workforce appeared first on Logistics Viewpoints.
Logistics & Shipment Tracking Tracking shipments across multiple jurisdictions is difficult. Today, logistics firms rely on RFID tags, barcode scanning, and centralized tracking systems, which are vulnerable to tampering and inefficiencies. Suppliers of blockchain logistics solutions: VeChain, IOTA, Helium, IBM TradeLens 3.
Earlier this morning I was thinking about something different, yet interesting to discuss in the intro paragraph of this week in logistics news. And now on to this week’s logistics news. Garvis designed from the ground up an AI-first forecasting solution now called DemandAI+. So I will. Walmart has spent $3.5
Here are some specific use cases: Demand Forecasting AI Agents can analyze historical sales data, market trends, and real-time demand signals to predict future demand accurately. Logistics Optimization AI Agents can analyze transportation networks, weather patterns, and other variables to optimize routes and reduce costs.
Its a rollercoaster for logistics and supply chain leaders operating in global markets. The post Navigating Global Trade Challenges in 2025 (Its Not Just About Tariffs) appeared first on Logistics Viewpoints. Intensifying geopolitical unrest. Increasing concerns over mass supply chain disruptions. Extreme tariff volatility.
The most common trading partner collaborative processes covered in SCCN suites are purchase order/procurement collaboration, demand forecast collaboration, and the transportation shipper tender/carrier accept process. The post Key Takeaways from SAP Spend Connect Live appeared first on Logistics Viewpoints.
The system also contributes to better forecasting accuracy. The post End-to-End Supply Chain Orchestration: Achieving Visibility and Operational Control appeared first on Logistics Viewpoints. The factory uses this information to make scheduling and inventory decisions more efficiently.
This means going beyond high-level forecasts to embrace tools and practiceslike Demand Collaboration, Scenario Planning, and detailed modelingthat make Sales & Operations Planning actionable, dynamic, and performance-driven. As Gartner highlights, companies tend to prioritize improving forecast accuracy to strengthen S&OP results.
Cost Forecasting : The 10% tariff baseline increases landed costs and may affect margin forecasts across multiple sectors. The post US-UK Trade Deal – Key Provisions and Supply Chain Implications appeared first on Logistics Viewpoints. Further negotiations are expected.
Predictive and prescriptive AI addresses use cases like inventory optimization, asset health predictions, yield optimization, and financial forecasting. Predictive Intelligence is being developed to use AI/ML to forecast completion dates for critical activities like Manufacture Complete, Carrier Pick Up, and Final Delivery.
Production plans might be locked for as long as a month, regardless of how accurate the forecast was. Those can include suppliers, contract manufacturers, logistics service providers, customs brokers, governmental agencies, and other participants. Historically, the supply chain plan that resulted from the IBP process was too static.
Inefficient inventory management often leads to last-minute rush orders that inflate logistics costs. Enhanced Demand Forecasting: Are you leveraging AI and advanced analytics to boost your forecasting accuracy? According to McKinsey , businesses that utilize these technologies can enhance their forecasting precision by 50%.
The essence of the question is resilience and the ability to forecast in a variable market reliably. This gets us to the question of what is the role of the forecast?` For most, forecasting is a conundrum full of potholes, politics, and bias. I attempted and failed to: Use Point of Sale Data in Supply Chain Forecasting.
Tom Raftery and Joe Lynch discuss triple bottom line logistics. Tom advises logistics and supply chain companies on technology, sustainability, and communications Summary: Triple Bottom Line Logistics Tom Raftery , a sustainability expert, discusses the importance of triple bottom line logistics in the supply chain industry.
That’s what the weather forecasters were saying Monday morning. Read more The post Above the Fold: Supply Chain Logistics News (February 16, 2024) appeared first on Talking Logistics with Adrian Gonzalez. By that evening, they had dialed back their prediction to 5-6 inches. A reminder that even with all the.
These decentralized networks aim to boost flexibility, reduce risk, and improve responsiveness, aided by technologies such as blockchain, AI-driven logistics, and expanded visibility into supply chains. Demand Planning and Forecasting Cisco has integrated AI-driven forecasting and predictive analytics into its demand planning processes.
We organize all of the trending information in your field so you don't have to. Join 102,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content