Abstract
The lack of adaptive capacity is one of the major risks facing large multinational organizations as the rapid change and disruptive impact of technology, Generative AI, regulations, climate considerations, socio-economic trends, geo-political events, and other factors continues to accelerate and outpace their ability to adapt. In this session, we highlight applied research and describe network analysis, and simulation techniques implemented by the author in engineering and financial services that have enabled global Data & Analytics organizations to improve their collective intelligence across cultures and influence strategic business initiatives in a highly volatile and disruptive environment. We review the inner workings of: • Virtual-Mirroring-Based Learning (VMBL) implementation with simulation capabilities that promote awareness and self-reflection about communication patterns. We will also discuss how VMBL can support the development of communication and collaboration strategies across cultures by combining techniques from network analysis, scenario analysis and Agent-Based and System Dynamics simulation. Resilience-based workstyles assessment that can be used as fundamental tools for designing and measuring diversity in teams, functional departments, and organizations. We improve our understanding of networks, resilience, and diversity through four resilience-based workstyles that map to corresponding phases of an adaptive cycle. We also operationalize diversity through resilience-based behaviors that are expressed as brokerage network structures. The applied and theoretical contributions of this research provide a template for practitioners interested in building resilience in networks while advancing the theory and measurement of resilience.
Presenters
Nabil RaadDirector Analytics, Enterprise Data and Information Services, Michigan Medicine, Michigan, United States
Details
Presentation Type
Theme
KEYWORDS
Global organizational transformation, Promoting cultural understanding, Collaborative Innovation Networks, Analytics
