Procurement and production planned and scheduled service capacity based on demand forecasts without anticipating material and capacity needs, leading to excessive lead times for service provisioning.
Goals and Objectives
Manage capacity within the CSP environment to ensure that provisioning times are optimized, and predictive models are applied to ensure that capacity is available to fulfill demand.
Cloud, industry cloud, IoT, prescriptive trade- off analytics, artificial intelligence, machine learning, blockchain, 3D printing, 3D product virtualization, and customization
Use Case Summary
Address the growing challenge of fulfilling demand for configurable products at lower cost to serve optimized customer service-level targets. Also, enable customer-driven customization of products in digital and physical properties.