Supply Chain

Based on historical business cycles and supply & demand, the fragility of modern, complex supply chains is failing to address emerging problems. Building a resilient supply chain requires connecting all your data wherever it is, unifying it to achieve consistency, and applying AI to develop deep insights for decision-making and automating manual processes.

Benefits

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.

Capabilities

Data Virtualization

Create a virtual data layer with semantic consistency by combining your diverse, distributed data sources, on-premises or in the cloud.

Metadata Management

Discover, harvest, and manage metadata from all applications, databases, data lakes, enterprise data warehouses, APIs, social media, and streaming sources you use.

Streaming Business Intelligence

Streaming BI provides complete point-and-click visual analytics on real-time and historical supply chain data for complete contextual awareness and deeper, faster insights.

Streaming Data Science

As opposed to training machine learning models on historical supply chain data, streaming data science assumes that conditions that impact decisions in real time are dynamically changing.

Streaming Automation

At the core of automated logic are visual tools to express, debug, and simulate supply chain inputs and reactions needed to orchestrate low-level tasks for robotic warehouse optimization, vehicle routing, and alerting.

API Management

API management technology lets you design, deploy, productize, secure, and analyze APIs as products, an essential ingredient for supply chain success.