Understanding Informational Bottlenecks in Complex Systems: Strategies for Enhancing Decision Quality in Financial and Non-Financial Markets

Abstract

Informational bottlenecks in complex systems represent a critical challenge, influencing the quality and timeliness of decision-making across financial and non-financial markets. This research investigates the origins and dynamics of informational bottlenecks, exploring their impact on system efficiency, resilience, and decision quality. By examining theoretical models and real-world case studies, the study identifies key mechanisms through which bottlenecks emerge, including data overload, communication inefficiencies, and cognitive biases. Additionally, it evaluates strategies for mitigating these bottlenecks through advanced analytics, machine learning, and organizational design interventions. Special attention is given to the role of technology in enabling effective data flow and enhancing decision-making processes. This interdisciplinary analysis spans financial markets, where rapid information processing is vital, and non-financial systems such as supply chains and healthcare networks, highlighting universal challenges and tailored solutions. The findings contribute to a deeper understanding of how informational bottlenecks disrupt system performance and propose actionable strategies for fostering robust and adaptive decision-making frameworks in complex environments.