The hyper turbulence of digital transformation mandates that enterprises continuously adapt and evolve systems, services, and processes; these are increasingly complex, and business needs more unpredictable. A global and systematic approach is needed to enable assets optimization while balancing risks.
Goals and Objectives
Portfolio optimization as a real-time capability with embedded intelligence that allows situation analysis, prediction, recommendations, automation, and performance monitoring
Enterprise hardware, personal devices, cloud, Big Data, predictive/prescriptive analytics, mobile, portfolio management applications (PPM, APM), connectivity services
Use Case Summary
Automated analysis of application, service, process, and other portfolios is used to identify redundancies, gaps, overlaps, poor performing items, costs, and life cycle concerns, as well as ML-based optimization and recommendations.