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This cluster examines the application of artificial intelligence to automate, optimize, and support decision-making within business processes.
This segment defines the scope of AI components in business processes with a focus on performance. Included are performance metrics, latency and throughput measurements, error rates, monitoring indicators, monitoring pipelines, data interfaces, aggregation intervals and SLO definitions. Excluded are implementation how-tos, training data preparation, model architecture decisions, infrastructure deployment details and organizational policies.
Systematic approach to analyze and improve processes to increase efficiency, quality, and throughput.
An approach for systematically increasing value created and throughput across teams and organizations using process optimization, metrics and continuous improvement.