Autonomous Operations Meets Anticipatory Fulfilment
Keywords:
Intelligent service experience; data center operations; autonomous operation; predictive fulfilment; predictive service analysis; intelligent fabric; supply chain; online services; customer fulfilment.Abstract
This paper presents the Intelligent Service Experience Fabric, a conceptual framework for autonomous internal and external service delivery in data center environments, with a focus on predictive customer fulfilment. Digital twins continuously feed the observed service experience back into operations, creating a closed loop for orchestrating and controlling service experience operations. This loop also supplies evidence-based inputs for the ongoing calibration of algorithms and AI systems. Governance services adapt their controls as conditions change and as risks emerge in the physical world. Within this Fabric-as-a-Service (FaaS) layer, human resources and the institution's human-centred services are also exposed as consumable FaaS services.
Infrastructure Service Experience Operations support intelligent consumption, advisement, prediction, and fulfilment of services through five components: Data Ingestion and Integration; Data Management and Governance; Data Quality and Semantics; Data Enrichment and the Semantic Layer; and Analytical and Predictive Modelling. A small set of autonomous control loops governs machine-learning-driven consumer models. These loops enable autonomous data center operations, continuous demand forecasting, digital twin reflection of the service experience, and autonomous fulfilment, advisement, and experience adjustment.
Predictive Customer Fulfilment builds on this foundation to let a consumer service construct a supply-side model of how a product or service is being, or will be, delivered. The model draws on three inputs: consumer preferences derived by machine learning, a product or service recipe derived by machine learning, and service delivery support requests handled by machine-learning and agent-driven processes.
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