Sense and Respond in Real Time
Supply chain management has always been analytics and data intensive. But recent AI, automation, and data management breakthroughs help all types of supply chains sense demand, operations, and volatile conditions and respond to what's happening.
Eliminate Data Silos
Eliminate data silos by allowing teams to turn dozens of isolated data sources into one virtual data layer. Virtualization removes bottlenecks and enables consistency and reuse, providing access to supply chain data on demand in a single logical layer that is governed and secure. It creates a unified interface to customer information as if it was a single system.
Proactively Identify Risks
Supply chains are often one of the largest sources of risk for the enterprise. Proactively identifying risk factors and addressing them is key to supply chain resiliency. Accessing data from all your suppliers and identifying deviations from normal levels and lead times is necessary to sense risks in real time.
Respond to Markets with Agility
As market conditions change, use advanced data science tools to integrate market intelligence into product-specific demand-forecasting models and generate a realistic prediction. Based on its time horizon, risk-informed decisions can be infused back into sales and operations planning.
Streaming Business Intelligence
Streaming Data Science