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Data for data’s sake lacks value, especially in the view of the supply chain. And across the market, submitted data becomes rapidly outdated. And in some industries, outdated data can have disastrous consequences. For instance, take the value added by more accurate data in the health industry.
Data-driven transportation management , including the checks and reviews that accompany healthy data management practices, are part of the process of getting the most out of the tech stack. Throughout the supply chain, data-driven transportation management’s success is only as good as the data quality and integrity in use.
Therefore, enterprises need to know how to apply transportation data to increase on-time shipping performance. . Aggregate data from beyond the four walls of your business. Yet all benchmarking begins with access to the right supply chain data. Extend replenishment lead-time. The data is present.
This “SONAR highlight reel,” which we plan to publish every other week, is intended to concisely hit data highlights and trends in truckload, intermodal and maritime. The end of the second quarter is typically a strong period for truckload freight and this year is no exception. Request a SONAR Demo. Request a SONAR SCI Demo.
In today’s fast-paced retail world, efficient shelf replenishment is crucial. We’ll look at four strategies to optimize shelf replenishment, reducing stockouts, improving inventory management, cutting waste, and boosting productivity. Let’s dive into these four pathways for efficient shelf replenishment and retail success.
Recognize market volatility trends and their impact on replenishment lead time Another beneficial action to boost efficiency with freight management comes from the recognition of market volatility trends. Market volatility can significantly impact replenishment lead time for restocking warehouses and distribution centers.
And while leveraging a freight rate index or ocean import data to lower detention risk , the sheer size of the supply chain makes management difficult at best. According to a recent Journal of Big Data article , “In typical [supply chain management] problems, it is assumed that capacity, demand, and cost are known parameters.
Youve prioritized TMS capabilities, analyzed vendors, and sat through several system demos. All this will help guide the data requirements that support an AP integration of the TMS software. These could be part of the order-to-cash cycle, the manufacturing cycle, or a replenishment cycle. On the surface it sounds easy.
What is big data? All successful businesses use data to develop strategies and review their outcomes. But as the number of systems being used increases, the amount of data available for consumption and analysis grows exponentially. Unstructured data isn’t as accessible to search or export and is often text-heavy.
An intimate relationship exists between truckload providers and ocean import market data. Fortunately, it’s easier than ever for truckload providers to lower detention and demurrage risk with these uses of ocean import data. Improve replenishment planning with access to ocean import data. That one is the simplest of all.
However, it has no immunity to rising costs and fees, changes in taxes, mobile data expenses, and penalties. The solution: Recognizing market trends as they occur in real-time is easier with access to actionable, insightful data. Get started by requesting a FreightWaves SONAR demo via the button below. . Request a SONAR Demo.
Companies are rapidly adopting and using real-time data to clearly understand challenges to better mitigate unexpected problems when they arise. In fact, logisticians should consider these top five use cases of increased visibility and data within logistics and how they improve throughput. Download the White Paper.
This keeps the data clean and easier to use for forecasting going forward. Look out for such trends in your historical demand data and adjust your forecasts accordingly. Qualitative factors: Add any qualitative forecasting factors into your data, such as sales promotions, competitor activity or external market events.
The COVID-19 crisis unveiled major issues within global supply chains and, as we have seen with SONAR freight data, volatility in the market. For those that make the right applications of freight data, the massive problems created by the pandemic could have been more easily mitigated.
Trucking has a decisive advantage on shorter, irregular runs moving in or out of less populated regions, which are also core reasons to view lane-by-lane market data too. . Request a SONAR Demo. Request a SONAR SCI Demo. Intermodal shipping is dominated by the largest shippers in the U.S. Download the White Paper.
They must manage replenishment, returns, supplier contracts and much more. Tracking and managing transportation by understanding freight data, particularly tender rejections and a cohort of core analytics, is the only path forward. Why actionable and insightful freight data, not more raw data, creates strategic value.
This “SONAR highlight reel,” which we plan to publish every other week, is intended to concisely hit data highlights and trends in truckload, intermodal and maritime. Request a SONAR Demo. Request a SONAR SCI Demo. Those rates are now at their highest level in recent years. and Long Beach promise to keep import volume elevated.
Outfitters expertise, along with these data-driven insights allow customers to find their best-fitting footwear. I would sit through the demos, and I would think, how are these bots going to handle large orders that we routinely send our stores? Now, they are replenishing stores more frequently.
Predictive rate analysis and implementation across the supply chain Utilizing real-time data and automated analysis provides valuable information to the network. Streamlined reporting and data sharing among all parties Access to data and easy options for sharing information is essential. Request a SONAR Demo.
(Graphics created by Emily Ricks) The shipper tech stack is continuously expanding, and according to Transportation Impact , “Key to all these new capabilities is data interoperability. Real-time collaborative alert management system No system reaches maximum potential when operating from old and outdated data.
Many companies are still struggling to replenish inventory from the surge of demand in 2020. But most data points to freight demand cranking close to full throttle for several months. Request a FreightWaves SONAR demo via the button below to get started using the data for those goals today. Request a SONAR Demo.
EazyStock is a cloud-based inventory optimization solution that integrates directly with your existing ERP to automatically feed data back and forth. Optimized Inventory Replenishment. With Acumatica you can manually set your replenishment parameters using the minimum/maximum quantity method (“min/max”).
An effective TMS will provide comprehensive data analysis on the current shipping costs and processes which offers you an opportunity to compare your costs and processes versus what is available in the market. . One needs to do extensive and thorough data analysis of all current costs within the transportation and logistics silos.
Data from the Bureau of Labor Statistics (BLS) shows that the demand for heavy and tractor-trailer truck drivers is expected to grow by 2% from 2021 to 2031, yet the supply is not keeping pace. During economic downturns, driver recruitment slows down, and as the economy recovers, there is often a lag in replenishing the driver pool.
While following OS&D helps, it’s only a fraction of the true value of data-driven supply chain management. Cost of goods sold/average inventory volume = X As the result increases, it indicates growth within the company and higher throughput, including replenishing and executing more loads. Request a SONAR demo online to learn more.
Tasks such as demand prediction, inventory allocation, stock replenishment and even mark-down calculations and assortment and financial plan seeding are easily completed with ML/AI-powered tools. Greater data access: A single chatbot or logistics monitoring robot can generate a wealth of valuable information and data.
Part of that transformation means execution with real-time data and communicating any changes or needs in real-time. By connecting data with the decision-makers, operators can automate more processes from replenishment through restocking after returns. . That’s where Lineage Link and Turvo meet at the crossroads of logistics.
Instead, appropriate replenishment parameters can be calculated based on the unknown demand only, lowering tied-up capital and improving customer service levels. Service level is an important KPI for every stock-carrying company, but some companies don’t have enough data available to measure this properly. Planned events in EazyStock.
High error rate due to outdated information and decisions based on inaccurate data. Poor data processing time leads to delays and backlogs, and scheduling conflicts. Logistics Process Workflow Automation Saves Back-Office Resources and Streamlines Replenishment.
Meaningful, easy-to-understand data concepts and visualization will affect accept-or-reject decisions. Most freight flow comes from the West Coast, and as the replenishment continues, it will actually create more imbalance and result in backhaul expectation deviations. Request a SONAR Demo.
For-hire transporters will see continued pressure to accelerate transit times as inventory replenishment problems persist. To achieve that goal and more, request a FreightWaves SONAR demo by clicking the button below, and see how data-driven fleet management can be a game-changer for your enterprise. Request a SONAR Demo.
SRM software also provides all the data needed to empower procurement managers to negotiate bulk discounts and reduce carriage costs. It stores supplier, customer, and order data, often from their first contact with the business through to sale, and then helps manage any queries or further communications. How EazyStock can help.
If possible, use real-time data and big data insights to delve deep into each area of your supply chain. For example, having more accurate demand forecasting, warehouse automation, diversifying your supplier network or bringing new technologies on board to give you real-time data. Where is it causing you problems? Purchasing.
In this blog post, we will explore the highly effective ABCD Analysis technique for warehouse optimization with its pitfalls and how organizations can leverage their data to implement this strategy successfully based on Log-hubs experience over the last years. Florian Brunner Data Engineer Still curious? Explore Want to try our demo?
In this blog post, we will explore the highly effective ABCD Analysis technique for warehouse optimization with its pitfalls and how organizations can leverage their data to implement this strategy successfully based on Log-hubs experience over the last years. Florian Brunner Data Engineer Still curious? Explore Want to try our demo?
Put simply, demand forecasting uses a variety of data to foresee customer demand and inform major business decisions, from launching new products to finding the perfect 3PL partner. How often does inventory need to be replenished? 1 Market Research – Market research gathers crucial customer data by means of surveying.
Especially if the classification is done based on ‘gut feel’ and not hard data. Contact us today for a demo or to discuss your inventory challenges call: (844) 416-5000. While ABC analysis is a relatively easy way to prioritize the management of your inventory, it also has a number of limitations: Too simplistic.
A basic risk of stockout spreadsheet can be easily set up using the following data: Current stock items, items on order and in transit. Ensuring your Data is Accurate and Up-to-Date. EazyStock takes a feed of your current stock data and uses historical sales to forecast upcoming demand. Demand forecasts. Lead times.
To calculate the optimum reorder point for a particular SKU you’ll first need to know the lead time required to replenish the inventory, the expected demand during this lead-time period, and how much safety stock you have on hand. Improving Data. Demand forecasting and inventory management rely on accurate data.
AI can adapt in near-real-time to changing conditions and develop new knowledge by processing more data and revealing more patterns and trends than humans can. Using regularly gathered data, it notices patterns and suggests the next actions. It uses algorithms, software, or systems to learn and adjust without specific programming.
Cyber attacks on supply chains include anything from holding systems hostage to data breaches that compromise individuals’ information. There have been high-profile data breaches in recent years, such as the Target data breach that affected 41 million consumers and their payment cards. Impacts from Disruptions. Invest in Tech.
Our article explains how to forecast and deal with fluctuating demand , including using appropriate historical data and how to deal with periods of stockouts. Using data will improve forecast accuracy and help you understand what’s around the corner, whether that’s responding to increased lead times or changes in demand.
Our article explains how to forecast and deal with fluctuating demand , including using appropriate historical data and how to deal with periods of stockouts. Using data will improve forecast accuracy and help you understand what’s around the corner, whether that’s responding to increased lead times or changes in demand.
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