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Companies leaning heavily on global sourcing? Theyre feeling the heat most, as sudden trade policy curveballs throw procurement plans into chaos. manufacturer I know saw their import costs jump overnight, forcing a rethink of a decade-old sourcing strategy. What Is Agile Procurement?
Reducing cost was the primary objective, and most operational decisionsfrom sourcing to fulfillmentreflected that mindset. Lean models alone are no longer sufficient. Sudden tariff increases can quickly make a cost-optimizedprocurement strategy untenable, leaving companies scrambling to adjust.
The manufacturing sector is facing unprecedented volatility in global trade, with tariffs becoming the latest in a series of uncertainty drivers that are impacting virtually all industries. Manufacturing plants are deeply entrenched; tied to infrastructure, suppliers, skilled labor, and regulatory requirements.
Each supply chain planning technology at the end of 2024, went through disruption–change in CEO, business model shift, layoffs, re-platforming and acquisitions. To build an outside-in model, and use new forms of analytics, we must start the discussion with the question of, “what drives value?” My advice?
Explore the most common use cases for network design and optimization software. Scenario analysis and optimization defined. Modeling your base case. Optimizing your supply chain based on costs and service levels. Optimizing your supply chain based on costs and service levels. Modeling carbon costs.
A data gateway is essentially a connective tissue across your supply chain, providing unified access to supply chain data from various sources, including enterprise systems, data feeds, data warehouses, data lakes, data marts, and business entities. Achieving these goals requires visibility into the entire supply chain.
Home Introducing Freightos Enterprise: End-to-End Procurement, Benchmarking, and Management Freightos Enterprise unifies market intelligence, tender management, and shipment operations into one solution, enhancing logistics efficiency for large import-export businesses.
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.
The modern supply chain is a complex network of suppliers, manufacturers, distributors, and customers, all interconnected and reliant on a shared ecosystem of trust and accountability. Ethical sourcing entails: Labor Practices: Ensuring fair wages, safe working conditions, and compliance with local and international labor laws.
A data gateway is essentially a connective tissue across your supply chain, providing unified access to supply chain data from various sources, including enterprise systems, data feeds, data warehouses, data lakes, data marts, and business entities. Achieving these goals requires visibility into the entire supply chain.
Strategic sourcing and innovative solutions are often viewed as two distinct procurement tools, but they should not be seen in isolation. Think of them as apples and gearseach essential and effective on its own, yet when combined; they create a formidable mechanism for achieving procurement excellence.
Automotive: Can JIT manufacturing survive legal disruptions to tariff policy? Automakers must model dual-path sourcing strategies and reintroduce buffer inventory—not just for parts, but for regulatory flexibility. This is especially risky for firms betting on partial assembly models.
a leading global supplier of mechanical components for the manufacturing industry headquartered in Japan. The manufacturing and supply chain industries are rapidly evolving and increasingly volatile, fueled by shifts in global tariff and trade policy, geopolitical uncertainty, logistics disruptions, and technology developments.
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.
Datacenter Hardware: The demand for powerful computing to train ever larger and more accurate AI models is insatiable. AWS , Google , and Microsoft are also investing heavily in custom AI chips to reduce their dependence on NVIDIA and optimize performance and cost. This puts pressure on other device manufacturers to follow suit.
A term once prominent in supply discussions optimization isn’t heard quite as often as it used to be. That doesn’t mean optimization isn’t as important now as it has been in the past. Also, validated financial statements are key in the underlying optimizationmodels. Quite the opposite.
They offer software systems and technology for complex integration, rapid application development, and advanced analytics and sell those solutions to companies that need to accelerate optimized business outcomes. Further, each product a manufacturer produces usually has different end-to-end supply chain partners.
Our second webinar delved deeper into the technology aspect, focusing on analytical capabilities and scenario modeling. Specifically, we looked at three use cases for scenario modeling using our cloud-based IBP app. The post IBP Scenario Modeling for Recovery, Restructuring and Resilience appeared first on AIMMS SC Blog.
Recent disruptions have exposed significant vulnerabilities in traditional models, driven by geopolitical instability, fluctuating demand, and operational inefficiencies. Just-in-time (JIT) inventory models, lean supplier networks, and offshore manufacturing reduced expenses but left companies exposed to disruptions.
Home Introducing Freightos Enterprise: End-to-End Procurement, Benchmarking, and Management Freightos Enterprise unifies market intelligence, tender management, and shipment operations into one solution, enhancing logistics efficiency for large import-export businesses.
Transportation, warehousing, and manufacturing collectively contribute significantly to carbon emissions, making these areas critical for meaningful change. Meanwhile, advances in AI-driven route optimization reduce unnecessary mileage, cutting emissions and costs. Ethical sourcing is a fundamental aspect of social sustainability.
But between rising costs, complex logistics, and the constant struggle to optimize space and labor, staying ahead can feel like an uphill battle. That’s where warehouse optimization comes in. Here’s what you can expect: A clear definition of warehouse optimization and its core components. Ready to get started?
How are companies leveraging scenario modeling for network design and optimization ? The good news is many of the survey’s respondents recognize the potential of more advanced optimization solutions. In the context of disruptions like COVID-19, scenario modeling can make considerable difference – Tweet this.
Let’s take a closer look at how four key industries—automotive, consumer packaged goods (CPG), high tech, and industrial manufacturing—are navigating the tariff rollercoaster and adjusting to the shifting landscape. Key takeaway Top challenge: Sourcing volatility driven by EV component shortages and fluctuating global tariffs.
In May 2025, one in seven home-purchase agreements fell through resulting in the cancellation of 56,000 purchase contracts. Supply chain was defined in 1982 as interoperability between source, make and deliver. The concept was that managing trade-offs and optimizing the whole to drive business outcomes would improve value.
The issue is that when companies optimize functional metrics, they throw the supply chain out of balance and sub-optimize value. Traditional approaches built optimization on top of relational databases. This shift improves modeling options and the use of disparate data. Supply chain leaders love bright and shiny objects.
Supply chains, 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.
The high-tech firm is more than a manufacturer of PCs, tablets, smartphones, and servers. The company has more than 2000 suppliers and operates over 30 manufacturing sites. During COVID, this more agile and resilient model allowed the firm to grow their market share. Factories serve local markets. We operate in many countries.
They emphasized being an Industry Cloud Complete Company with industry-specific solutions for over 2000 micro verticals across Process Manufacturing, Distribution, Service Industries, and Discrete Manufacturing. Industry-specific content is available for processes like Source to Settle, Procure to Pay, Order to Cash, and more.
Ibrahim Al Syed, the director of digital manufacturing at Celanese, was surprisingly forthcoming about how Celanese developed these capabilities at ARC Advisory Groups 29th Annual ARC Industry Leadership Forum. The company has 55 manufacturing sites across the world. ARC has been actively studying industrial AI for over two years.
In a previous post , I made a case for how the Chief Supply Chain Officer (CSCO) and Chief Procurement Officer (CPO) are smarter together. Accordingly Supply Chain and Procurement will need continuous collaboration. Such sourcing events can be in the context of direct materials or logistics capacity.
In our pandemic research, we interviewed thirty manufacturers. To gain insights, we interviewed Alexandros Skandalakis, Director of Manufacturing Capacity, reporting to operations/manufacturing globally within Philip Morris. We wanted to find a better way to design our network and optimize future manufacturing outcomes.
Translation of the demand forecast into planned orders to minimize manufacturing constraints. Use of optimization to consume planned orders into manufacturing scheduling and distribution requirements planning (including inventory optimization of safety stock). The focus is on functional optimization.
During the pandemic, companies struggled with planning systems turning off the optimizers, and using the technology as a system of record. In the face of variability, this is two-to-six weeks too long to make allocation or procurement decisions. Steps to Take Here are three steps to take: Adaptive Modeling. Higher variability.
This model simplifies the world of RtM into a series of three steps that any RtM practitioner can execute. Here are the Top 5 Do’s and Don’ts to help you build a high-performing RTM model and distributor network: ✅Top 5 Do’s Do Align RTM Strategy with Consumer Behaviour : Design your RTM based on where, how, and why your consumers shop.
How should a global manufacturer make a decision? In short, the research tells me that the manufacturing industries are stuck. In contrast, for a global manufacturer, the answer is more complex. What is the role of make, source, and deliver? And how can supply chain planning help? What defines a feasible plan?
Optimization and simulation are the two main branches of SCND. Optimization accounts for over 90% of all work that is being done by SCND teams. This article describes how to incorporate simulation techniques into optimization, build a stochastic optimizationmodel, and end up with a more resilient supply chain model.
The basic frame of supply chain planning–functional taxonomies for optimization on a relational database–must be redesigned before supply chain leaders can reap the benefit of deep learning, neural networks, and evolving forms of Artificial Intelligence (AI). Or a unified data model across source, make, and deliver for planning?
Today, the steel manufacturing leader has an ambitious digital transformation agenda and is leveraging AIMMS technology to optimize operations in its home country. I belong to this second division and work mostly on mathematical modeling, simulation and supply chain analytics. . Jamshedpur plant (image source: Tata Steel).
” As I dipped my spoon into some scrumptious chestnut soup at a great restaurant, my companion asked, “With the advancements in optimization and self-learning, aren’t we close to having self-driving supply chains?” The perspective of a manufacturing leader is quite different than that of a business leader in logistics.
Since January, Canadians’ weekly grocery trips have become a real-time indicator for the potential impacts of tariffs as shoppers have responded to threats with a showcase of buying power, prioritizing nationally sourced and manufactured products even before a single tariff was enacted. goods were “ rapidly dropping.”
Procurement and Supply Chain Management are essential functions that can help companies navigate these challenges, but they are often siloed and operate in separate departments. Their metrics are often misaligned as well – supply chain focuses on service and procurement focuses on the cost of acquiring materials and services.
PWC’s Digital Trends in Supply Chain Survey reports that 83% of manufacturers say that supply chain technologies have not delivered the expected results. Let’s zoom to the bottom line: the results are less than optimal for all the monies spent and practices deployed. When he speaks of the supply chain, he means procurement.
It’s the key to transforming your supply chain from a source of frustration into a well-oiled, profit-generating machine. By harnessing the power of data science and analytics, you can gain end-to-end visibility across your entire network, breaking down information silos and optimizing every stage of your operations.
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