Optimizing Decision-Making in Engineering

This comprehensive book explores the evolving landscape of decision-making processes for engineering and IT professionals in increasingly heterogeneous technological environments. It addresses critical gaps in current educational materials by examining how technological advancements, situational awareness challenges, human-machine intelligence integration, and virtual uncertainties impact modern decision-making frameworks. The book provides a complete journey map of decision-making that connects theoretical foundations with practical applications, offering readers a structured approach to navigate complex adaptive systems in our data-driven society. Optimizing Decision-Making in Engineering: A Journey Mapping Perspective includes an in-depth exploration of cognitive and emotional engagements in decision-making, analysis of how advanced design functionalities influence cognitive biases and heuristics, and examination of decision-making under virtual conditions where physical touch is absent. It presents analytical tools such as decision trees, Bayesian networks, and multi-criteria decision-making models (AHP, TOPSIS), while incorporating emerging technologies like artificial intelligence, virtual/augmented reality, IoT, and big data analytics. Real-world scenarios, use cases, and strategic frameworks like the Cynefin framework and Roger's model provide practical context for theoretical concepts. Designed for technology professionals, including CTOs, IT Project Managers, Systems Architects, UX Directors, and Engineering Team Leads, this resource equips Product Managers, Business Analysts, Solution Architects, and Digital Transformation Consultants with enhanced decision-making capabilities for complex environments. The comprehensive guide delivers particular value for specialized roles such as AI Ethics Officers, Human Factors Engineers, and Digital Experience Strategists, providing frameworks applicable across autonomous systems, healthcare technology, immersive experiences, retail analytics, and advanced manufacturing operations.