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Machine learning (ML)a specialized field within artificial intelligence (AI)is revolutionizing demandplanning and supply chain management. According to McKinsey , organizations implementing AI-driven demand forecasting solutions can reduce forecast errors by 30% to 50%.
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.
She wrote, “I have been working in the supply chain for 35 years, and we are still trying to solve the “demand” issue. Solving from a supply side seems to work for many companies I work with. I know that your primary focus is procurement. The distribution models were never tested when implemented.
In follow-up qualitative interviews, one of the largest issues with organizational alignment was metric definition and a clear definition of supply chain excellence. In my post Mea Culpa, I reference my work with the Gartner Supply Chain Hierarchy of Metrics. ” Let’s face it all supply chains have error.
Discover which features will differentiate your application and maximize the ROI of your embedded analytics. Brought to you by Logi Analytics. But today, dashboards and visualizations have become table stakes.
The adoption of AI in supply chain automation is enabling companies to make more accurate decisions, reduce cycle times, and better manage complexity. AI in supply chain automation is gradually reshaping how core functions operate, particularly in procurement, warehousing, and logistics.
However, as carbon taxes and emissions reporting requirements continue increasing, supply chain 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.
In my recent Mea Culpa post, I mentioned my prior work on Sales and Operations Planning (S&OP), and the importance of leadership. Leadership and S&OP? If you have walked in the shoes of the supply chain leader, you are probably laughing by now. Is your plan feasible? Sounds easy, right?
While SAP has had procurementanalytics solutions, last year at Spend Connect Live, SAP announced the Spend Control Tower. Daniel Chapman, the senior director of process transformation for procure to pay at Warner Music, was a keynote speaker. SAP’s Business Network is a supply chain collaboration network.
Why do some embedded analytics projects succeed while others fail? We surveyed 500+ application teams embedding analytics to find out which analytics features actually move the needle. Read the 6th annual State of Embedded AnalyticsReport to discover new best practices. Brought to you by Logi Analytics.
In the fast-paced world of modern supply chains, traditional forecasting methods fall short. Advanced supply chain planning is being transformed by probabilistic forecasting , which revolutionizes demand forecasting, supplyplanning, and inventory optimization.
In the fast-paced world of modern supply chains, traditional forecasting methods fall short. Probabilistic forecasting is revolutionizing demand forecasting, supplyplanning, and inventory optimization by significantly improving forecast accuracy and decision-making across distribution networks.
When you talk to companies that have implemented enterprise or supply chain applications, executives will usually admit that they have under-invested in training and preparing users to use the new technology. Molex implemented a multi-enterprise supply chain network platform from SAP called SAP Business Network.
Fragmented systems, rising cost pressures, and shifting risk profiles are making it harder than ever to manage procurement effectively. But what does it actually take to regain control and build a procurement strategy that’s both resilient and scalable? How do you begin developing a procurement strategy?
Fragmented systems, rising cost pressures, and shifting risk profiles are making it harder than ever to manage procurement effectively. But what does it actually take to regain control and build a procurement strategy that’s both resilient and scalable? How do you begin developing a procurement strategy?
During my current supply chain planning market research, I have received briefings from several SCP companies. Many say that they are using generative AI, a type of AI that can create new content and ideas, as part of their journey toward autonomous planning. Solvoyo has a metric they call the user acceptance rate.
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. Businesses face heightened uncertainty in managing costs and securing stable energy supplies.
Direct and indirect procurement are two fundamental approaches in supply chain management, each serving distinct functions within an organization. Both focus on improving efficiency and reducing costs but differ in their strategic approach and impact on the core business operations. Find Out More What Is Procurement?
Procurement and supply chain management are often used interchangeably—but in practice, the lines between them can blur in ways that create real friction. Misaligned priorities, siloed systems, and unclear ownership can directly impact key performance indicators like cost savings percentage and procurement cycle time.
Sudden and significant changes in demand, especially in consumer markets, stack up more challenges, requiring order revision and reallocation. The fulfillment process is further complicated by ongoing shifts in customer expectations and demands and geo-political and weather disruptions.
Today, in supply chain planning, this could not be further from reality. In May 2025, one in seven home-purchase agreements fell through resulting in the cancellation of 56,000 purchase contracts. Each is attempting to slather AI on today’s offering: this fueling a hype cycle for agentic AI. The reason?
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. What’s the technology behind autonomous procurement agents? You may also have heard of Agentic AI.
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. What’s the technology behind autonomous procurement agents? You may also have heard of Agentic AI.
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.
In this type of environment, traditional procurement software and manual processes are insufficient – and many procurement teams are looking to artificial intelligence (AI) for answers. Key Takeaways Understand the potential impact of AI – including Generative AI & AI Agents – in procurement.
Enterprise procurement teams face growing pressure to deliver strategic value – managing supplier risk, ensuring compliance, and supporting sustainability – all without sacrificing speed or control. This blog explores the most common challenges in digital procurement and the capabilities that matter most.
(Most of the business networks were hollowed out by venture capitalists or purchased by opportunists. ” My problem is that we move through these hype cycles with little accountability for spending and with a major opportunity cost to not redefine work. The opportunity is to rethink planning. This will not help.
This year’s conference brought together industry leaders, tech pioneers, and retail professionals to address challenges and opportunities, to explore technologies and strategies that promise to revolutionize the industry. Here are the key insights we gathered firsthand at this year’s event.
When reviewing strategy decks for supply chain teams, I often see statements like “move from a functional-silo’d focus to a drive a more holistic response.” ” Or “push a shift from a focus on cost to drive value?” Functional Metrics. ” Sound familiar? This gap grew over the last decade.
Traditionally, procurement has been a process weighed down by manual tasks, fragmented systems, and endless paperwork. Today, procurement is undergoing a transformation. While procurement teams have long worked to add strategic value, Artificial Intelligence (AI) amplifies their impact.
My head is wobbling with announcements, late-night Friday press releases, company name changes, and executive turnover in the supply chain planning market. Let’s hope that these new executives see the light of a new day. OMP, like o9 and Kinaxis, benefited from the SAP’s APO migration failure. Kinaxis and o9.
For most CPOs and CFOs, deciding on the right purchasing setup — centralized or decentralized — is no small task. Each model has its perks, and choosing the best fit can feel like walking a tightrope. Keep reading to learn: What is centralized purchasing? What is centralized purchasing?
Five years ago, we all thought the COVID-19 pandemic resulted in the most disrupted supply chain landscape we would ever see. Since then, supply chain disruptions and volatility have only increased. With the global e-commerce market predicted to reach $8.1 We were wrong. billion to $23.07 billion in 2023 to $13.3
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.
Supply chain excellence is easier to say than to explain. Executive teams strive to drive improvement in supply chain results; yet, sadly, only four percent of public companies succeed. The supply chain is a complex non-linear system. Understanding this relationship requires modeling. The reason? A Case Study.
Today, I speak at the North American Manufacturing Association, Manufacturing Leadership Conference, in Nashville on the use of data to improve supply chain resilience. Background The Council of Supply Chain Resilience met for the first time this month. Let’s start the beginning. What is supply chain resilience?
In today’s interconnected global economy, supply chains play a vital role in the success of businesses. It is crucial for organizations to understand the importance of Purchase Order collaboration to effectively manage their direct spend, optimize operations, and mitigate risks.
Supply chain efficiency is the cornerstone of success and involves the effective management of processes, resources, and technologies from procurement to production, transportation to warehousing. In the automotive sector, manufacturers are simultaneously reducing inventory costs and delivery times.
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). Let’s start with a basic definition.
”) So, I sat across from a stranger on a cold winter night, the only thing that we had in common was our experience in supply chain planning. . And won’t the supply chain follow suit?” The supply chain planning industry is fraught with big claims with little substance. The facts are clear.
While consultants know the answers (or believe they do), I believe my goal as a research analyst is to unearth new questions that should be asked (and answered together openly in the supply chain community) to improve value. I see a preponderance of reports and white papers that have lots of pages but say little. Back to John.
Procuring transportation for freight is much different than any other procurement category. Transportation procurement needs to support both customer service and a company’s internal supply chain goals. One master of freight procurement is Kyle Masters. Simmons has highly demanding internal and external customers.
By harnessing the growing power of AI to not only sensedemand at a very fine-grain, real-time level, but also to govern decisions about pricing and inventory. Demandsensing has nothing to do with supply; it’s just about where and when, not whether, it will sell.
” At that time, the sales organization used more point-of-sale data than their competitors, they had an impressive and innovative IT team, and their supply chain processes were what I considered best-in-class. This week, the organization reported that net sales decreased 2 percent to $19.5 What Is Outside-in Planning?
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