Book: The New Science of Management Decision

Overview
Herbert A. Simon's The New Science of Management Decision (1960) synthesizes ideas from economics, psychology, computer science, and operations research to reconceptualize managerial decision making. The book argues that decisions in organizations cannot be understood solely through classical rational choice models that assume unbounded computational ability and perfect information. Instead, Simon emphasizes realistic constraints on human cognition, the structure of organizational information flows, and the potential of formal models and computational techniques to improve decision quality under uncertainty.

Bounded Rationality and Satisficing
Central to the argument is the concept of bounded rationality: decision makers have limited information, limited time, and limited computational capacity. Rather than optimizing, managers typically "satisfice", they search for a solution that meets acceptable criteria rather than the theoretically optimal one. Simon explains how satisficing emerges from the interaction between individual cognitive limits and the organizational environments in which choices are made, and he explores how changing goals, routines, and information structures affects the search for alternatives.

Information, Organization, and Decision Processes
Information-processing metaphors run throughout the book. Organizations are portrayed as systems that collect, transmit, and transform information to reduce decision uncertainty. Simon discusses the design of organizational structures and rule systems that channel attention and simplify choice, thereby compensating for individual cognitive limits. He highlights trade-offs between centralized and decentralized decision processes and examines how rules, standard procedures, and hierarchies serve as mechanisms for coordinating complex activity without requiring each actor to solve every problem from first principles.

Formal Models and Computational Methods
A major contribution is the advocacy for formal models and computational simulation as tools for management. Simon outlines how mathematical models, decision trees, utility concepts, and stochastic analysis can clarify problem structure and identify robust policies. He also explores the emerging role of computers for simulation and optimization, arguing that computational methods can extend human analytical reach, test organizational designs, and evaluate policies under alternative scenarios. Rather than replacing managerial judgment, these tools are presented as aids that structure attention and improve the quality of satisficing processes.

Decision Making Under Uncertainty
Simon treats uncertainty as a defining feature of managerial environments and shows how probabilistic thinking and sensitivity analysis can make decisions more resilient. He emphasizes distinguishing between risk that can be probabilistically modeled and uncertainty that resists precise quantification. The book recommends mixed strategies, combining heuristic rules, contingency plans, and analytical models, to navigate unknowns. Attention to the sources and costs of information leads to practical guidance about when to invest in data collection and when to rely on rules of thumb.

Legacy and Practical Implications
The New Science of Management Decision helped reorient management theory toward empirically grounded, interdisciplinary approaches that account for human limitations. Its ideas influenced the development of organizational behavior, behavioral economics, decision support systems, and the early field of artificial intelligence. For practitioners, the book encourages designing organizations and information systems that recognize bounded cognition, using formal models to clarify choices, and adopting computational experiments to test policy alternatives. The result is a pragmatic framework that mixes analytical rigor with an appreciation of real-world constraints.