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Anthony transitioned to a Corporate Economist & Consultant, advising CXO leaders and Fortune 500 companies on economic analysis, industry trends, and internal strategy. He led analysis around M&A, pricing sensitivity, competitive intelligence, and annual sales forecast for the executive team. pageviews a month and over 1.5B
Analytics for Risk Management This isn't your grandmother's dataanalysis; we're talking about sophisticated pattern recognition that makes your shipping operation smoother than a freshly waxed surfboard. And how do you pick the right carrier if you are now receiving new data of damaged packages?
These sensors capture precise data on factors like location, speed, fuel usage, and driver behavior, transforming fleet management from reactive to data-driven decision-making. The IoT data allows managers to detect inefficiencies, predict maintenance needs, and even assess driver performance.
From a financial standpoint, transportation cost analysis remains focused on determining the value of the resources used to execute a given shipment and goes well beyond benchmarking. Moreover, this kind of analysis does not focus on who ends up paying which expenses in the end. The challenges of limited transportation cost analysis.
Quality and Detail of Data and its Analysis In some of our earlier posts, weve stressed the importance of simplicity in distribution network design , and we will return to that topic later in this article. It would be folly not to take advantage of data availability and accessibility.
So, going into 2025, I would like to focus on current congestion data, global trends and what U.S. So, planning in advance, choosing the right partners that present options, doing an actual cost analysis, and keeping customers educated will be the key to overcome the challenges faced in 2025.
The usual themes were still very present as solution providers and retailers alike were more than happy to talk about omni-channel, mobility, robotics, and machine learning, to name a few. This year, a recurring theme that I saw was about using supply chain data to improve the customer experience across the entire value chain.
Author’s note: Last month, I participated in a webinar hosted by Trimble titled, “Data: Don’t Drown In It, Deliver with It!” The following is an excerpt of my presentation. What is data? According to the dictionary, data is “facts and statistics collected together for reference or analysis.”
Chemical manufacturers collect and use a lot of data in their supply chain. They deal with data on their products, customers, transportation, storage, operations and more. Acquiring that data is not hard but managing and utilizing that information to be able to analyze your business is the challenge. Lane Analysis Reports.
Have you conducted a cost-to-serve (CTS) analysis for your enterprise? And that is the sole purpose of cost-to-serve analysis. If you were going to say, “What is a cost-to-serve analysis?” Only a complete cost-to-serve analysis will expose these underlying issues unless they happen to be discovered incidentally.
Despite all these issues, cargo handled has rose a whopping 22% in the period of December 2021/January 2022/February 2022 compared to the December 2020/January 2021/February 2021 period according to data from the Port of Houston. So no matter how farfetched it may seem, the solution might be that farfetched option that you are presented with.
Bring your business- and tax-related questions to this live webcast presentation and discussion with ATBS President Todd Amen, breaking down results from ATBS' analysis of owner-op revenue, income and cost data throughout the year thus far.
Modern supply chains are evolving beyond anyone’s expectations due to increased use of cloud-computing technologies, wearables and advanced dataanalysis. DataAnalysis Grew Exponentially, Providing More End-to-End Visibility and Continuous Improvement. Dataanalysis is the companion of cloud-computing technologies.
Internet of Things (IoT) sensor-generated data is another key piece of improving railway efficiency and operations. Accordingly, the number of IoT transport units is expected to increase , according to Statista data, from 2.6 Optimizing Railway Operations with Data. Making Data One’s Own. million in 2017 to 3.7
ERP systems essentially integrate all the disparate functions within your business and overcome the so-called ‘silo mentality’ by creating a single, centralized data architecture. The ERP software collects, stores and manages data relating to business activities. What’s Your Business IQ?
superior technology, faster delivery times, eco-friendly vehicles) By presenting a clear description of your business, potential investors or partners can better understand how your company fits into the larger market. Market Analysis Understanding your market is crucial for any business. through 2027. Be specific.
In the grand scheme of things, dataanalysis falls into the categories of descriptive, predictive, and prescriptive. While descriptive datapresents existing figures, predictive data allows you to draw insights from trends in your descriptive data in order to make an educated guess about what might happen next.
For example, in the future, staff scheduling need not be handled by employees, but rather can be carried out by intelligent software tools via data processing. Keywords like full data transparency, self-learning and self-recovery are hallmarks of TGW’s Future Fulfillment Center.
How do you present your case to achieve the results you need? For added ammunition, your argument should be supported by measurable data points. Through precisely curated documentation, management can see clearly defined data that identifies the strengths and weakness of the company’s environmental, health and safety programming.
Much has been made in recent weeks about supply chain data providers changing historical metrics. Well, maybe you should, since it’s the title of the blog…DATA INTEGRITY MATTERS! SONAR isn’t yet the longest-running or most-used data source in the trucking world (but we’re getting there!). Today, SONAR is made up of more than $1.7
Freight and trucking data makes for an excellent resource for shippers and logistic service providers (LSPs) alike. The data obtained from historical and contract load tender information creates a valuable tool – a trucking rate predictor. And it’s important to know why tendered, non-paid data can add so much weight.
It’s easy for shippers, brokers, and third-party logistics providers (3PLs) to get lost in the freight data conversation. The opportunities, to understand market conditions and increase profitability through analytics , are more apparent through the impact and analysis of data. However, spot freight is ever-present.
The answer is not simple and involves research and analysis across a number of factors. Robinson’s own technology and data from the largest network in the freight industry, help our customers stay on top of the trends that influence their supply chains. Analysis of employment data. for Q2 2021, relative to Q2 2018.
This enables you to transform both historical and real-time data into proactive strategies. 360 visibility provides fleet managers with a comprehensive overview of their operations, encompassing past, present, and future data.
The solutions to supply chain problems boil down to the right combination of three factors—technology, data and processes. Fundamentally, the solutions to supply chain woes boil down to the right combination of three factors—technology, data and processes. Data is a critical business asset. Trouble finding skilled labor”.
The systems integrator will be presenting the full spectrum of its digital services at the LogiMAT intralogistics trade fair (31 May to 2 June) in Stuttgart. An integration project’s lifecycle takes place digitally, from the first dataanalysis all the way to final acceptance.
ORTEC uses data-driven analytics to create supply chain visibility and help solve everyday challenges for staying on target, improving the customer experience, and meeting business goals. Performance analysis compares planned versus actual results to support continuous improvement and to reduce cost to serve.
A fleet management system is used to plan a business’s logistics based on an assessment of historical delivery data and to monitor the performance of each vehicle based on tracking technologies such as GPS and telemetry sensors. The focus is on reducing subjectivity in decision-making and making the business smarter.
Lack of Proprietary Data: Machine learning models require vast amounts of data to train and effectively tackle the problem at hand. Data, often being the biggest determining factor in custom model effectiveness. Due to this increase, the overall price third parties charge for inference on data increases dramatically.
In this article, Eytan Buchman, Freightos’ CMO, discusses the importance of data and context in global freight and logistics. The future of global freight data lies in real-time information, contextual insights, and aggregated data that can help companies make better decisions and adapt to a rapidly changing industry.
Since its introduction in 2018, FreightWaves SONAR has provided subscribers with the most current freight market data, analysis and insights. SONAR is the only freight forecasting platform that combines contract tender data with spot rate data and creates predictive freight rates.
As data becomes a critical resource in modern organizations, business users are clamoring for tools to ease access to data for reporting and dashboards. EA plugs data in the form of reports, dashboards and data visualizations into applications, putting the information where it will get used.
Meanwhile, shippers face the challenge of managing their day-to-day transportation networks during a period of unprecedented supply chain disruption. Either one would be a challenge, but performing both at the same time presents additional challenges in a carriers’ market. FILL OUT THE FORM BELOW TO DOWNLOAD THE FREE WHITE PAPER.
Now more than ever, organizations must prepare their supply chain for the present and the unknown challenges and opportunities in the future. Doing so helps organizations detect market shifts and makes supply chain decisions more forward-looking than an analysis of the past, present, and at best, a tactical view of the future.
In recent years, the amount of data available to most companies has exploded. Common issues include: Lack of data-source integration. The ability to gather and compare data from multiple sources is vital to making real-time decisions. Data warehousing costs rise. Scarce manpower. Human error.
The Role of Data Analytics in Supply Chain Management | Image source: Pixabay This article describes the transformation that dataanalysis and the supply chain are fostering and how it will impact business intelligence. Intelligence-driven businesses are interested in supply chain management and dataanalysis.
In today’s digitalized world, manufacturers must keep pace with the rapidly evolving technology landscape to remain competitive, agile, and to protect their electronic assets such as data. To shed light on the importance of upgrading ERP systems, we present five compelling benefits and advantages of doing it sooner rather than later.
Predictive Analysis in Logistics and Supply Chain: How to Apply | Image source: Pexels In logistics, predictive analysis is simply the process of identifying and forecasting patterns, trends, and behaviors in both human and machine learning approaches, data, and algorithms.
One of the biggest obstacles to setting and implementing strategies for responsible sourcing is accessing reliable and current data and analysis, according to The Dragonfly Initiative CEO, Assheton Carter.
It has become a term applied to applications that can perform tasks a human could do, like analyzing data or replying to customers online. Machine Learning is just that – a machine or program that can learn from data. In the 2000s, big data came into play, giving AI access to massive amounts of data from various sources.
Logistics is a complex and swift-changing industry, and decision makers need to be armed with accurate data – and actionable insights – when navigating the evolving landscape. Shippers understand the importance of data. This is especially true in the face of the current freight recession.
the role of Generative AI, a subset of artificial intelligence that can generate data like what it’s trained on, is becoming significant. Alex had seen the wonders of electronic data interchange, warehouse management systems, and transportation management systems. Customer interactions presented another challenge.
To actually realize the promise of end-to-end visibility and control over our incredibly complex supply chain networks, we need really big picture thinking — particularly when it comes to the supply chain data networks that serve as the foundation for true digital transformation. Numbers matter when it comes to supply chain data networks.
Too much leads to resources being monopolised on gathering tons of data and a subsequent risk of “paralysis by analysis” Cost to Serve (CTS) is an approach that helps you avoid both extremes. If profits start to decline afterwards, your CTS data can offer valuable information about what changed and how to get back on track.
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