Technology > Data Management (Big Data/IoT/Blockchain) | SupplyChainBrain

Data Management (Big Data/IoT/Blockchain): Page 11

In an Age of Disruption, No Supply Chain Can Modernize Alone
To remain competitive in a fast-evolving and unpredictable market, supply chain leaders must rethink their traditional approaches to innovation.
Photo: iStock / thitivong
Leveling the Food Supply Chain Playing Field with Ingredient-Level Data
The path forward depends on using the right kind of data: granular, actionable, and tailored to a company’s specific role in the supply chain.
Photo: iStock / bluecinema
Five Things to Know: Optimizing Your Warehouse with Adaptive and Intelligent Operations
Warehouses that are best equipped to weather the storms of disruptions are often those that have the technology they need to stay resilient.
Photo: Lucas Systems
Transforming the Complex Supply Chain with a Modern TMS
Uber Freight and Leaf Home together modernized the home improvement company’s logistics operations to cope with skyrocketing growth.
Photo: iStock/artiste9999
Quickcode Deploys AI-Assisted Trade Compliance to Enhance Customs Entry
Determining the right HTS code for a given product used to be done manually. Today, by necessity, it draws on the power of artificial intelligence.
Photo: iStock/Douglas Rissing
Investor Appetite Increases for Supply Chain Software Companies
M&A activity is not roaring back, but it is clearly on the uptick, with buyers allocating capital to acquisitions in a discerning yet deliberate way.
Image: iStock.com/welcomia
Coping With New Sources of Supply Chain Volatility: The More, the Merrier
Supply chains need to integrate and collaborate with end-to-end partners and vendors in a more efficient, orchestrated, always-on model.
Image: iStock/ipopba
How IoT and AI Are Modernizing Rail Efficiency and Asset Tracking
As the rail freight sector accelerates its digital journey, the integration of IoT and AI stands out as a catalyst for modernization.
ATHENS, GEORGIA, U.S.A. - Jan 21, 2019: A railroad employee holding a walkie-talkie leans out from a CSX railroad locomotive, looking ahead up the track.
Balancing Centralized Manufacturing Data and Distributed AI Agents
It’s clear why no manufacturing executive wants to bet everything on a pure data model. Centralized architectures are robust, but can be slow and reactive.
Photo: iStock/LeonidKos
Logistics Leaders Rewire Workflows with Agentic AI
While generative AI recognizes patterns and creates content, agentic AI uses these outputs to reason, plan, and take autonomous actions.
Image: iStock/XH4D
Alphabet to Build $15B Data Hub in India
The facility will be the largest AI hub that Google is going to be investing in anywhere in the world outside of the United States.
Google data center in Eemshaven, The Netherlands. Photo: iStock/DutchScenery
Successful Supply Chain AI Implementation for Manufacturers & Distributors
Success rests on four positive factors — incremental transformation, non-disruptive architecture, deep knowledge-worker involvement, and a core foundation built on manufacturing know-how.
Photo: iStock / sankai
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Case Studies
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Case Studies
How a Leading U.S. Floral Distribution Company Reduced Warehouse Labor Costs by 45% with RFID
Case Studies
Recycled Tagging Fasteners: Small Changes Make a Big Impact
Mobile geolocation service for track delivery, cargo shipment and freight transportation. Logistic Import Export business (Elements of this image furnished by NASA)
Case Studies
Enhancing High-Value Electronics Shipment Security with Tive's Real-Time Tracking
Franchise business e-commerce online e-marketplace or digital marketing branch expansion for growth or use technology to analyze product consumer data website management plan for sale service concept.
Case Studies
Moving Robots Site-to-Site