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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.” Warehouse management systems rely on RF scans of locations and products. 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.
Three months into 2025, we have seen a barrage of on-again, off-again tariffs that have supply chain and logistics teams reeling, as they must rethink everything from next weeks shipping route to their foundational network models. That may sound impossible, but new technology places this capability within the reach of every organization.
From balancing cost-efficiency with ethical sourcing to enhancing transparency and integrating corporate social responsibility (CSR), businesses face mounting pressure to align their operations with sustainability, technology, and energy practices. The energy sector provides a compelling example of CSR-driven compliance.
Just by embedding analytics, application owners can charge 24% more for their product. How much value could you add? This framework explains how application enhancements can extend your product offerings. Brought to you by Logi Analytics.
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.
Lean models alone are no longer sufficient. 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. AI is helping companies better detect risk, model alternatives, and make faster decisions with more confidence.
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.
Small companies outperform large companies, and the marquee customers of major supply chain planning technology providers underperform. The issue is that when companies optimize functional metrics, they throw the supply chain out of balance and sub-optimize value. This shift improves modeling options and the use of disparate data.
The global supply chain landscape is undergoing significant transformations, influenced by rapid technological advancements, shifting consumer expectations, and the intricacies of international commerce. These platforms enable learners to engage in collaborative projects that mimic real-world supply chain challenges.
Körber is a leading provider of logistics software, material handling, voice, and consulting solutions. Technology Can Aid in Hiring the Disabled. Part of the story of this retailer’s employment of the disabled in their DCs is a story of technology adoption. There is a service level agreement that the system will be up 99.9%
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.
When companies consider implementing enterprise software, standard operating procedure would be to look at a public company’s financials before deciding to implement the solution. If the software company is private, the prospective customer often asks for the right to view their financials. How can they be growing so fast?
Knowledge Graphs are emerging as an important tool for building advanced AI capabilities. Agentic AI involves creating a system of interacting agents, each trained on a specific task or dataset. We needed to model the data in a way that we can do simple searching. Data must be modeled consistently across the organization.
To achieve those results, “we had to massage the platform to accept emissions data from our carriers,” Mr. De Golia explained. The model allowed Microsoft to run many scenarios and supported trading off service reliability, cost, and carbon emissions. A clear goal needs to be combined with good data and metrics.
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.
Senior leaders must think beyond incremental improvements, embracing systemic innovation to achieve significant environmental impact. Smart energy management systems further enhance efficiency by tracking and optimizing energy use in real-time. Reducing carbon emissions is a cornerstone of this effort.
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.
A multi-enterprise supply chain network platform provides network-based order fulfillment applications and/or advanced network-based supply chain risk analytics. E2open is a provider of cloud-based, supply chain software. Their platform combines their network and software applications. Infor Nexus.
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 demand error is high, and their ability to model is low. My focus was simple. I was wrong. The reason?
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.
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.
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.
For organizations layered in functional metrics and driving a cost agenda, this is a tough nut to crack. During the pandemic, companies struggled with planning systems turning off the optimizers, and using the technology as a system of record. Steps to Take Here are three steps to take: Adaptive Modeling.
One of my stark realizations this year is that smaller companies are beating larger and often more established companies on growth metrics, inventory turns, operating margin, and Return on Invested Capital (ROIC). (In The metrics selection resulted from work with Arizona State University in 2013.) Standardization of the IT platform.
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. The world of NoSQL unified data models is inconceivable to most. I constantly ask myself, why? Art of the Possible.
Each model has its perks, and choosing the best fit can feel like walking a tightrope. On top of that, we’ll break down how to approach selecting the right centralized purchasing system for your business needs. Some centralized purchasing software solutions like Precoro offer functionality for the RFP process.
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. Cloud software: Stores and distributes real-time data, producing reports accessible to all team members. Let’s get started! What Is Mobile Inventory Management?
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.
Driving an excellent supply chain depends on how people are recruited and managed, processes, and the technology used. In the annual report where they report on their key performance indicators (KPIs), they don’t just report on core financial metrics and the NPS, they also have people metrics. The company recorded 1.9
In this final blog on agility and why you should consider becoming an agilist to survive the new completion (of the continuous mention) of the application of enterprise decision management systems (EDMS) from Taylor and Raden cited in the first blog, I turn to the metric of agility and a new ROI metric of decision yield.
Note to the reader: we selected these metrics for the balanced scorecard for the analysis after work with Arizona State University to understand which metrics, in combination, most closely correlated with market capitalization. My reply to my friend is that “The supply chain is a complex non-linear system.
The systems–based on shipment and order data–were out of step with the market. With fixed models and hard-wired data feeds, teams could not adjust the planning systems to use consumption data or market indicators. Next Steps: Start to model demand based on market data to align the organization on baseline demand.
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. Why Jump Now?
Connected technology transforms traditional supply chains into dynamic systems capable of real-time decisions and proactive problem-solving. Essential Components of Data-Driven Supply Chains Data-driven supply chains combine multiple technologies to create a comprehensive operational framework.
The key areas to consider when upgrading to the cloud include: The Value of Cloud Technology Cost Competitiveness Performance Expectations Upgrades Responsiveness Support Expertise & Response The Value of Cloud Technology Which business drivers and advantages are motivating companies to shift to the cloud?
The supply chain is a complex non-linear system. At each company, there is a relationship between the metrics of growth, margin, inventory, customer service, and asset strategy. For the purpose of this article, I will use Return on Invested Capital (ROIC) as the proxy metric to discuss asset utilization.)
Companies became less clear on the definition of supply chain excellence and how to implement decision support technologies. The financial teams, and the Information Technology (IT) groups, did not see alignment gaps, but the supply chain teams felt them and viewed them as a critical performance issue. Functional Metrics.
Traditionally, procurement has been a process weighed down by manual tasks, fragmented systems, and endless paperwork. AI in procurement refers to using advanced technologies to make procurement processes faster, more efficient, and data-driven. Today, procurement is undergoing a transformation.
built into their supply chain analytics software. When companies feed their customer and process data into predictive models, they better understand future behavior and make decisions based on hard data, rather than gut feelings. Most people have interacted with a predictive model when applying for a credit card or loan.
What is the Perfect Delivery Metric? Improving on this metric will always involve a focus on people and processes, but often also includes implementing new, more robust, supply chain applications. The wrong metrics drive suboptimal behaviors and metrics can often be manipulated.
Metrics such as lead-times, forecast accuracy, inventory levels, and service are used to measure operational risks. Design and planning software has been utilized for the last several decades to manage these operational risks. It is critical that supply chain design toolsmodel real world complexity to effectively model the risks.
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