The origins of forward-looking decision making: Cybernetics, operational research, and the foundations of forecasting

Abstract

The massive explosion of literature, theory, and methods on all aspects of decision-analytics, machine learning and artificial intelligence, over the past 20 or so years has brought a rapid specialization in each of the substrata of the fields that are using them. The sharp focus on empirical usage of these methods across applications, and the consequent trivialization from data only-driven improvements and multiple method comparisons, have diverted attention from foundational and epistemological concerns and questions, leading to pure empiricism — due to, but not exclusively, increases and availability of computing power. Tapping into the, equally massive, history and literature of the earliest developments from pioneers in the fields of cybernetics, operations research, and forecasting, we re-establish the links to the past on the origins of business and predictive analytics. Using interdisciplinary-sourced material we bring attention to the significance of these early developments and to the need for a return to these early sources in re-establishing our connection with the fundamental principles and questions that define meaningful, forward-looking, decision-making.