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
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.
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.
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.
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, supply planning, and inventory optimization.
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.
In the fast-paced world of modern supply chains, 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.
Machine learning (ML)a specialized field within artificial intelligence (AI)is revolutionizing demand planning and supply chain management. According to McKinsey , organizations implementing AI-driven demand forecasting solutions can reduce forecast errors by 30% to 50%.
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.
My head is wobbling with announcements, late-night Friday press releases, company name changes, and executive turnover in the supply chain planning market. Logility, a conservative company supply chain planning technology, historically had no debt and cash reserves of more than 80M, is undervalued in this deal. Is it musical chairs?
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.
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.
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. The Ukraine-Russia conflict is ongoing. billion to $23.07
He had a load full of cotton bales, and while idling away hours at a shipyard watching stevedores load other cargo onto ships he dreamed up containers that transformed global supply chains. Containerization eventually reduced shipping and loading costs by at least 75%. The myth of the “perfect plan”.
Nine out of ten supply chains are stuck. The secret to unsticking the supply chain is to redesign processes to be outside-in. The supply chain processes need to be designed from the market back. Most companies have designed supply-centric processes from the inside-out. Step Up and Learn the Language of Demand.
The Covid-19 pandemic tested the global supply chain. Like riding a bumpy road, the supply chain leader is riding the ups and downs of changing market conditions facing greater variability day-to-day. Here, based on interviews with supply chain leaders, I share lessons learned. The Failure of Existing Demand Planning Solutions.
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. By aligning supply chain and procurement, spend can be considered more holistically.
”) 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.
Returns Management and Integration With 35% of online purchases being returned, predominantly to physical stores, retailers are grappling with the ripple effects on inventory management. Early adopters of these integrated platforms report significant improvements in inventory turnover and reduction in stockouts.
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.
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.
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.
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?
When you’re perusing luxury handbags online, or testing which cocktail dress suits you the best, you probably don’t pause to consider all the supply chain complexities and analytics required to ensure the fashion items you’re craving are in-stock. shorter product life cycles, and often protracted supply lead times.
For businesses, DPPs are becoming essential to comply with best practice guidance as well as coming statutory regulations that demand transparency in supply chains. Blockchain can also build trust in the supply chain, as all channel stakeholders can verify the same data.
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?
In today’s dynamic and unpredictable business environment, companies face various challenges such as changing consumer demands, global uncertainty, and the impact of natural and man-made events. This approach results in inefficiencies, higher costs, and missed opportunities.
Given the many aspects of retail operations outside a business’ control—from supply chain disruptions and labor shortages to inflation and interest rates impacting both operational costs and customer behavior—the fulfillment challenge this peak holiday season is acute.
The agribusiness supply chain is highly complex. But supporting the process with advanced analytics goes even further, contributing to higher levels of productivity and profitability. Like many organizations, Tereos recognizes the use of advanced analytics as an imperative. Advanced analytics as enabling technology.
Digital commerce efficiently requires the digitalization of many customer-facing operations and sourcing and procurement. For businesses of all sizes, the digital transformation of supply chain planning became the most important initiative. . Accurate and timely reconciliation of purchase orders with receipts.
According to Bloomberg , the coffee supply chain is struggling with constrained supply and increase in prices is inevitable. Traditional, linear supply chains struggle to adapt. This article explores how adaptive supply chains can help businesses thrive. This collaboration enables faster response times and cost savings.
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. What is supply chain resilience? Think this is possible? The reason?
In part 1 of my blog on Planning the Value Chain and Decision Making in Times of Disruption, the focus was on the ability to react and execute amidst the unpredictability of demand. Part 2 in the series explores the “analyticalscenario exercise” and how decisions based on certain scenarios heavily impact each aspect of the value chain.
Consumers are ever more conscious of value, sensitive to health and environmental issues – especially after the COVID pandemic, each demanding more options for their money. End-to-end supply chain visibility, planning, and execution support software are critical in agile supply chain performance.
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). ” I don’t think so. I term this our data jail.
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.
How the digital twin concept drives benefit By using advanced analytics and machine learning algorithms, digital twins can provide real-time insights and recommendations to optimize operations, reduce costs, and increase productivity. Physical change (i.e., changing the structure of the warehouse, modifying processes, etc.)
Chances are, if you’re in marketing, sales, or one of the more technical aspects of business, you’ve used predictiveanalytics in some part of your job. But your company doesn’t have to be a retail giant to use predictiveanalytics. using predictiveanalytics?built PredictiveAnalytics in a Nutshell.
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.
Machine Learning for demand forecasting has matured to a level of accuracy, transparency and replicability that translates into transformative results, including in these five areas: Accuracy, transparency, thoroughness of analytical options and results. Greed for more data.
Analytics and business intelligence (BI) are no longer optionaltheyre essential. They integrate, align, and activate data across the business to drive better, faster decisions unlike legacy reporting tools that can’t. Flexible Delivery Options Interactive dashboards, scheduled reports, alerts, mobile access, and more.
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.
The consulting team pitches a theme–vision of supply chain best practices, big data analytics, or demand-driven value networks– to the executive team, and a new project is initiated. Question 1: What drives a Successful Implementation of Supply Chain Planning? Supply chain planning is now on its third decade.
The Introduction of Smokeless Tobacco Products Complicated Philip Morris’s Supply Chain. This was done at a stock keeping unit level and for the entire manufacturing supply chain. At the end of 2019 that supply chain covered 38 PMI owned factories, 28 third party manufacturers, and more than 180 markets.
(I never republished the report, because not enough has changed to warrant it.) The report centers on the concept of moving from inside-out to outside-in technologies. Why is there a discontinuous line on the model?” This model reminds me of a snail. Here I write about what I hope that he learns.
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