Most decisions are made using known models of business conditions and automated using rules and analytics based on historical data.
Goals and Objectives
Decrease reaction time in operational decisions by continuously evaluating new data and, in combination with historical trends, using anomaly detection, prediction of potential next best actions, and constraints-based optimization.
Messaging and other real-time data monitoring, movement, analytics, business rules capable of continuous processing, database deployed as a state machine, AI technologies to convert unstructured data to structured data, machine learning, and optimization to decide or make recommendations
Use Case Summary
Rapid identification and response for well-known and slow-to-change conditions across a variety of processes and industries; used in runtime systems for compliance; and when there is a business benefit in rapidly predicting upcoming problems or immediate opportunities where conditions change continuously and data is highly variable, including IoT use cases, real-time promotions, quality controls, and inventory outage predictions