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Supply chain practitioners seeking the best way to speed decision intelligence, unify supply chain data, and increase operational efficiency can benefit from a supply chain data gateway. Here are 10 ways a supply chain data gateway can improve your performance across the end-to-end supply chain.
Many global multinationals accelerated their investments in digitizing data during the pandemic. According to Colin Masson, a director of research at ARC Advisory Group, the opportunity to mine these vast quantities of data to achieve business value is “NOW.” Mr. Masson leads ARC’s research on industrial AI and data fabrics.
The company aims to change this with the expansion of its data fabric portfolio. A supply chain data fabric can help companies augment their supply chain processes. Now companies are trying to collect data from multiple tiers of a supply chain in near real-time. Decisions need to be digitized.
Our daily lives are inundated with data. Supply chain teams face a similar dilemma – companies are overloaded with vast amounts of data, and the ability to sift through the noise and focus on relevant insights has become a critical capability. Why Context Matters Context transforms data into actionable insights.
This GEP-sponsored Supply Management Insider guide breaks down the data barriers to meeting sustainability goals. CPOs are now being measured on sustainability targets. How can they meet this new challenge?
These are big data platforms that monitor news sources and assorted databases from governments, financial institutions, ESG NGOs, and other sources to detect when an adverse event has occurred or may be about to occur. Most argue that when the UI is trained with the companys own data, the risk of hallucination is small.
Read more The post Reimagining Transportation Procurement: Leveraging Data and Technology for Smarter Freight Decisions appeared first on Talking Logistics with Adrian Gonzalez. Yet, we all know that waste and inefficiencies still.
Poor data quality is the Achilles’ heel of supply chain management (see “The Big (Crappy) Data Problem In Supply Chain Management.”) This is especially true for data received from suppliers, logistics service providers, and other external trading partners.
Forecasting has evolved into a sophisticated science, combining historical data, real-time market signals, and predictive analytics. Advanced Forecasting and AI Evolution With ongoing geopolitical disruptions and supply chain volatility, the need for responsive and sophisticated forecasting capabilities has never been more critical.
This GEP-sponsored report will show you how to leverage data for a collaborative supply chain that delivers results and how to future-proof supply chain management strategies. The C-suite is laser-focused on supply chain performance.
That’s where data analytics comes in. Modern supply chains thrive on real-time data, execution-focused applications, and dynamic decision-making. In this post, we’ll explore how data analytics can revolutionize your supply chain. Demand Forecasting: Analyze past data to predict future needs.
Data is the lifeblood of AI in the supply chain. Without sufficient data, AI models can’t uncover meaningful patterns, make accurate predictions, or provide valuable insights for informed decision-making in complex and dynamic environments. At the same time, feeding your AI models too much data can also be a problem.
In this commentary we focus specifically on the importance of a broader end-to-end data management framework while overcoming the fragmentation of data that is locked in separate, unconnected software applications.
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.
In response to these challenges, a leading heavy equipment manufacturer selected GEP to redesign its source-to-contract processes and implement a convergent data model to help manage procurement data across its multiple locations.
IoT: Powering the Future of Digital Product Passports The Internet of Things (IoT) continues to impact how industries track products and manage data. This network of devices enables seamless, automatic data collection from physical objects in near real-time.
This proliferation has made the need for – and lack of – industry data standards all the more acute. And one of the main objectives of all this digitized data and integration in one source of truth is supply chain visibility , that will not only let logistics experts optimize operations, but also detect and react to disruptions.
Understanding AI Agents At its core, an AI Agent is a reasoning engine capable of understanding context, planning workflows, connecting to external tools and data, and executing actions to achieve a defined goal. Integrate with External Tools and Data: AI Agents can augment their inherent language model capabilities with APIs and tools (e.g.,
Blue Yonder and Agentic AI Blue Yonder announced they were working with Snowflake, a company providing an enterprise data fabric solution, to transform access to disparate data for supply chain management in March of 2022. It turns out data fabrics are the necessary foundation on which to build advanced agentic AI solutions.
From new pricing strategies and material substitutability to alternative suppliers and stockpiling, a new GEP-commissioned Economist Impact report reveals that enterprises are adopting a variety of approaches underpinned by data and technology.
The book goes beyond theoretical concepts and serves as a playbook for crafting data-driven go-to-market strategies. Company specializes in crafting GTM strategies that are grounded in data – backed insights and sophisticated mathematical models. Data-Driven Insights: Gain valuable insights into your marketing efforts.
Shippers, brokers, carriers, news organizations and industry analysts rely on DAT for trends and data insights based on a database of $150 billion in annual market transactions. Real-time Market Insights: DAT provides real-time data on spot market rates, capacity availability, and lane-specific trends, enabling informed decision-making.
The platform collects data and makes sure the master data is internally consistent. If a user makes changes to the plan, they log that data. You have to have a digital platform where you get all your relevant data.” And that data has “to be internally consistent. We are a platform. Bakkalbasi asks rhetorically.
With an open API, integration of our data into your business platforms is easy, coupled with our ruggedized GPS asset tracking devices installed in less than 10 minutes, we can get you up and running quickly. Industry leading data security, low total cost of ownership and rapid ROI, BlackBerry Radar is Engineered for Intelligence.
What’s Inside: How CPOs are driving strategic decision-making and technology adoption The top priorities and challenges for procurement in 2025 Why AI, sustainability, and data analytics are essential for success Read this essential report to chart your path forward and influence procurement tools and processes.
Backup Data & Systems: Use a 3,2,1, strategy to back up data. Have 3 copies of your data, in 2 geographically dispersed locations, and 1 location off of your network. When that does happen, you’ll want to do anything to restore your data. Hackers know this and rely on your intense desperation to save your business.
Unlike the bevy of pay-for-play podcasters and social influencers pelting us with opinions, my focus is on data and research processes. Many followers answered my surveys, and over the past six months, I mined the data to try to answer the question of what we can learn from the past decade to improve planning. I give thanks for this!)
Dynamic Pricing: Real-time data from decentralized oracles (such as Chainlink) can adjust contract terms based on market prices or demand fluctuations. How Smart Contracts Improve Logistics IoT-Enabled Tracking: Sensors on shipping containers continuously log real-time data (e.g., Solution: Layer-2 scaling solutions (e.g.,
For example, if an asset issue was detected, solving that issue could involve multiple applications used by multiple people, seeing different information, entering different data, bouncing emails and texts back and forth, and moving information from one place to another. We needed to model the data in a way that we can do simple searching.
Storytelling is more than just data visualization. Storytelling provides an organized approach for conveying data insights through visuals and narrative. Data-driven storytelling could be used to influence user actions, and ensure they understand what data matters the most.
The combination of SAP agent technologies and Databricks data fabric solution, sets the stage for end-to-end enterprise orchestration. Databricks offers a Data Intelligence Platform. Databricks type of solution is increasingly being called a data fabric or a data platform built on data fabric principles.
Heres an excerpt of what I wrote at the time: To derive business value from visibility, you have to do something with the data and insights collected. I first raised this question in an April 2022 post. Its the doing, the actions taken to improve your transportation.
Companies find it difficult to fully trust the data from suppliers, complicating efforts to ensure product authenticity, safety, and ethical sourcing. The specific origin data reinforces De Beers’ commitment to consumer confidence , transparency and ethical sourcing. ERP & SCM Systems (2000s2015): Centralized ERP suites (e.g.,
Data fabrics, knowledge graphs, a digital thread, and digital twin technologies are critical. John Galt’s Supply Chain Planning Platform John Galt is right to single out data fabrics as an increasingly important technology. This creates a unified view by stitching together data sources in real time.
Organizational data literacy is regularly addressed, but it’s uncommon for product managers to consider users’ data literacy levels when building products. Product managers need to research and recognize their end users' data literacy when building an application with analytic features.
Further, AI-driven demand sensing allows businesses to combine scattered data which is essential for better forecast accuracy. People are used to interacting with data in a complex waynot just for scheduling but to get real, in-depth answers. This reduces error rates and creates actionable insights for short-term decision-making.
Energy management solutions are products that energy utilities use to produce power and data centers use to consume power. By 2014, the company had purchased the Coupa solution, developed an internal modeling team, and created data extraction and cleansing routines. This is when the firm hired Mr. Botham.
Dexory, the robotics and data intelligence company announced it has closed an $80 million Series B funding round. Through unique data sets generated from far-reaching sensor and image data, continuous scanning and the latest AI developments, Dexory unlocks new levels of optimization and seamless efficiency. “We
Backup Data & Systems: Use a 3,2,1, strategy to back up data. Have 3 copies of your data, in 2 geographically dispersed locations, and 1 location off of your network. When that does happen, you’ll want to do anything to restore your data. Hackers know this and rely on your intense desperation to save your business.
Proactive Security Measures:DAT employs a range of proactive measures, including multi-factor authentication, advanced monitoring tools, and regular security testing, to safeguard user accounts and data, and to prevent fraudulent activities like identity theft and double brokering.
We have all the connected planning data we get from blue Yonder, all of the product data we get from the product systems, all of the shipment information that’s coming in from the carriers, as well as risk information from Everstream and other sources. We can now have really good data-driven conversations.
Machine learning improves the vehicle’s performance by analyzing data from past deliveries and refining its operations. Cloud Computing: The data collected by ADVs is processed through cloud platforms, enabling real-time communication, route adjustments, and fleet management.
Infrastructure Upgrades Apples plan to upgrade and expand its infrastructure includes significant investments in data centers and other facilities. Support Data-Driven Decision Making : Advanced data centers will enable better data analytics and insights, driving more informed and strategic decisions.
Sales and marketing leaders have reached a tipping point when it comes to using intent data — and they’re not looking back. More than half of all B2B marketers are already using intent data to increase sales, and Gartner predicts this figure will grow to 70 percent. Intent data can be overwhelming if you don’t know how to use it.
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