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Supply Chain Visibility

Sept. 25, 2018
Infor has introduced Control Center, a next-generation supply chain visibility and intelligence solution that enables supply chains to be data-driven, self-learning and consistently reliable.

Infor has introduced Control Center, a next-generation supply chain visibility and intelligence solution that enables supply chains to be data-driven, self-learning and consistently reliable.

Control Center combines data from the Infor GT Nexus Commerce Network—a cloud-based, multi-enterprise commerce network for global trade and supply chain management—with Infor’s Coleman Artificial Intelligence (AI) capabilities, to empower supply chain leaders to break down organizational silos.

The solution delivers end-to-end visibility, with deep data science, to help supply chain leaders filter through everyday noise, bring into context the right information for faster decisions, and execute rapidly using predictive and prescriptive intelligence. Control Center’s end-to-end visibility, together with its machine learning capabilities, can predict future supply chain issues and help companies react earlier.

Control Center enables enterprises to take a big step toward self-orchestration of their supply chains by empowering users, automating mundane tasks and delivering network intelligence.

Control Center continuously monitors the flow of products, materials, orders, demand and capital throughout the supply network and separates opportunities from noise. It applies AI and machine learning to understand the context of each opportunity and prescribe the best resolution.

Infor Control Center is built on the Infor GT Nexus Commerce Network, which leverages the intelligence of 20 years of global supply chain data across industries. The Infor GT Nexus Commerce Network is built to orchestrate multi-enterprise processes and flows. Its applications are network-native, and day-to-day execution happens within the network, providing data that is live, accurate and context-rich.

Control Center senses network flow through a series of live-control points. It runs on dynamic observation. It can sense if things are moving or not moving. It calculates and knows “the state of normal,” and constantly observes flow movement to recognize pattern shifts. Even before a problem appears, the system knows that something isn’t right and determines if action is necessary. If so, Control Center prescribes action and measures results to learn and improve over time.

Infor

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