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Open Sky Group, a global leader in supply chain execution solutions, has announced a strategic partnership with Easy Metrics , a premier provider of labor management and warehouse performance management solutions.
Frederic Laluyaux, the CEO of Aera Technology, agrees with this assessment. Masson of ARC points out, “Each AI use case requires specific datasets and may necessitate different tools and techniques.” Short-term forecasting relies on POS and other forms of downstream data. trillion rows of data into the platform. “So
Similarly, UPS uses its ORION system, which integrates real-time and historical data to optimize delivery routes, saving fuel and enhancing delivery reliability. Enhanced Efficiency Through Real-Time Data Connected vehicle technology drives efficiency improvements across route planning, driver safety, maintenance, and fuel management.
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.
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. Error is error, but is it the most important metric? My answer is no.
Solvoyo has a metric they call the user acceptance rate. This metric measures the percentage of time the planners accept replenishment, transportation, or inventory plans as they are without any change in the timing of the delivery or the quantity to be delivered. We are a platform. Forecasting is not an actionable item.”
Demand forecasting is a critical strategy for supply chain management that can dramatically improve business decision-making and financial performance. However, securing leadership buy-in for demand forecastingtechnology requires a strategic approach that clearly demonstrates value.
Retrofitting existing infrastructure with energy-efficient technologies further enhances sustainability efforts. Critical practices include: Circular Supply Chains: Designing systems that minimize waste and emphasize recycling and reuse. Advanced route optimization tools further support these goals.
This complexity has introduced gaps in visibility and responsiveness that traditional systems werent designed to handle. It is not a technology on its own, but rather a process that combines planning, execution, and monitoring through integrated tools and workflows.
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.
This requires a thorough readiness assessment, selection of appropriate technology, and careful integration with existing business processes. This assessment helps identify whether existing systems can support DPP integration and what upgrades or changes are necessary.
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. He leads a team of market experts who study every facet of the logistics industry to bring the best available insight to customers.
Thats why modern BI systems are quickly becoming the go-to solution for data-driven enterprises. They integrate, align, and activate data across the business to drive better, faster decisions unlike legacy reporting tools that can’t. But lets be clear: not all BI platforms are created equal. Why does that matter?
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. Agent AI is emerging as a game-changing tool for understanding and responding to customer behavior in real-time.
If there’s a bright spot anywhere it’s the fact that, as logistics challenges have grown, so has the availability of advanced technologies to manage these challenges. For logistics teams, digital control towers add maximum value when they’re integrated with the transportation management system (TMS). Warehouse Task Automation.
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 example, AI-enabled systems can monitor global trade activity, policy changes, and even weather patterns to flag emerging risks before they impact operations.
Yet, despite significant investments in tools and talent, many organizations still struggle to connect strategic vision with real-world operations. Most S&OP efforts break down due to disconnected systems, siloed data, and a lack of cross-functional engagement. The result? Underwhelming S&OP outcomes and lost opportunities.
Samuel Parker and Joe Lynch discuss DAT iQ: the metrics that matter. Samuel is an experienced market strategy and product leader with over 10 years of experience in supply chain logistics and innovation, specializing in helping technology companies build high-performing Go-to-Market teams. Samuel has his B.A.
Despite the evolution of technology, none of the 28 industry segments I follow can drive improvement at the intersection of operating margin and inventory turns. Investment in Legacy Technologies. The industry continues to invest in technology architectures that are inside-out and limited. A failed blogger.” The reason?
If “the forecast is always wrong,” is improving forecast accuracy even the solution to our demand planning woes? Artificial intelligence and machine learning ( AI/ML ) can improve forecast accuracy, but a bigger problem is the failure to set accurate expectations around forecasting models, not the accuracy of the models themselves.
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.
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?
One of the industry’s biggest concerns is how to digitise and transform quickly, without starting from scratch and having to throw away your enormous investment in traditional systems. The good news is that you don’t have to—even if you have hundreds of legacy systems and ERP instances across your company.
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!
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. Technology integration: Leveraging digital tools to enhance visibility and decision-making.
To keep customers like my dad satisfied, RGD and Quick-commerce companies need to invest in new technologies to optimize the supply chain and logistics operations. These technologies are often invisible to the end-user but make a big difference in keeping the promises about product availability, freshness, and speed of delivery.
By combining leadership and technology, I believed that we had the opportunity to create a better supply chain. The gap is the result of the stewpot of corporate politics, misguided consultants, and over-hyped technologies. The SAS forecastingsystem implemented in 2019 was not tested for model accuracy. I was wrong.
Each saw the need to change and not dwell on the loss of the position as they knew it, but to embrace the potential of new opportunities stemming from the technology inflection. Today’s technology shifts are similar. Companies have invested in using transactional data, due to limitations in prior technologies. The reason?
End-to-end supply chain visibility, planning, and execution support software are critical in agile supply chain performance. CPG companies that utilize an autonomous supply chain technology see a reduction in their inventory and cost and an increase in revenue. each with discrete plans generated typically in sequential batch runs.
Financial crises, global tensions, supply shortages, technological innovations, and regulatory changes are inevitable we just cant predict when theyll strike. Modern businesses must approach stock optimization as a dynamic, responsive system rather than a static holding pattern.
A proof of concept (POC) is an increasingly common method to select the best supply chain software vendor for your company, yet many supply chain practitioners still lean on the traditional RFI (request for information) tool. Software selection is risky. 6 Focus on the wrong metric. Seven Ways RFIs Fall Short.
It’s like having a magic wand that optimizes inventory levels, prevents shortages, and sharpens your demand forecasting—all from your smartphone. Mobile inventory management is a digital solution that combines a mobile inventory app with cloud-based software to track, manage, and optimize inventory in real-time.
Definition As I follow the evolution of supply chain technology, I am struck by what I see as a stream of paradox and anomaly, and the tendency of supply chain leaders to cling to convention. technologies. My observation is that softwaretechnology leaders are attempting to make historic practices faster versus redefining capabilities.
Connected technology transforms traditional supply chains into dynamic systems capable of real-time decisions and proactive problem-solving. Demand Forecasting: Analyze past data to predict future needs. Route Optimization: Calculate the most efficient delivery routes based on several factors.
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. Let’s take a closer look at each one. Accuracy and transparency. Greed for more data.
New forms of technology are an enabler. ” The problem is that each of the outside-in processes encountered problems with traditional technologies, and as a result, got stuck and had limited adoption. .” CPFR: Collaborative Planning, Forecasting and Replenishment garnered great fanfare late in the 1990s.
It is just not enough to do a software upgrade or slowly push continuous improvement projects. He did this first by implementing demand sensing from Terra Technology (now E2Open) eight years ago. Completed in 2012, the ERP project forced the company to standardize organizational design, roles, and metrics. Nick does this well.
Good forecasting leads to good demand planning —and good demand planning means better profitability. That’s why it’s essential to be sure you’re equipping your organization with the right demand planning software. Here are our answers to some of the most common questions about demand planning software.
It could write poetry, generate code, or answer inquiries about next months forecast. In supply chain terms, this translates into going beyond monitoring key performance improvements (KPIs) to enable systems to heal themselves and the processes and operations they run when disruptions occur. At least, not yet.
As an entrepreneur I’ve been reflecting on this a lot: The current milestone in logistics and fulfillment is using emerging technologies to capture and leverage exponentially growing data sets in warehouses and throughout the entire fulfillment network. The rise of autonomous technologies.
Using balance sheet data from 2011 to 2019, we chart companies’ progress by peer group on rate of improvement and performance in the metrics of growth, operating margin, inventory turns, and Return on Invested Capital (ROIC). Let me share some and see what you think: Does forecast ownership make a difference in outcomes?
The Company was attempting to gain economies of scale by grouping manufacturing technologies within a common infrastructure to reap the benefits of a co-generation facility, a centralized warehouse, and a talented administrative team. Engineers could sign up for hour-long blocks to use the new systems.
Most companies buy decision support technology, but do not redefine work to improve decisions. A shift from functional metrics to a balanced scorecard. I like the use of growth, margin, inventory turns, Return on Invested Capital, customer service and ESG metrics. Improved Forecast Value Added (FVA). Fire the Apes.
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