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The first industrial revolution showed us how to do most of the world's heavy work with the energy of machines instead of human muscle. The new industrial revolution is showing us how much of the work of human thinking can be done by and in cooperation with intelligent machines.(1)
Industrial robotics offers increased quality and efficiency by using technology to lever the efforts of production workers in repetitive tasks. Companies have looked to lower-level jobs for these gains, with the result that robotics has been a blue-collar phenomenon. However, similar gains can be achieved at managerial levels of the organization--by using "white-collar robotics" to lever the efforts of managers with managerial decision models.
The quotation above was written by a panel of the National Academy of Sciences that was chaired by Nobel laureate Herbert Simon. While the report of that panel emphasized human-computer interaction, we argue that very simple decision models can be developed for many managerial situations, and used to improve managers' decision making. Some models may need to be computer-based for efficiency purposes, but in many cases paper and pencil will do. Even paper-and-pencil models often will make more accurate decisions than the managers they assist.
This may seem like a strong claim, but support for it comes from research and development in the field of "behavioral decision making".(2) The very existence of the field is a recognition that the "art" of decision making is giving way to the science of decision making. Research efforts in behavioral decision making concern how people make decisions and how well they make them, while development efforts concern ways of improving decision making.
Our focus here is on the latter--practical techniques for making better decisions.(3) We examine techniques that have been applied to repetitive decisions--such as forecasting future revenues, evaluating commercial loan applicants, determining individuals' credit ratings, selecting additions to investment portfolios, evaluating employees for promotion, and choosing players for professional sports teams. Repetitive decision tasks can be contrasted to nonrepetitive ones such as locating manufacturing facilities or nuclear power plants, choosing among alternative military weapons systems, introducing innovative transportation alternatives such as electric-powered cars or convertible pick-up trucks, and evaluating options for space exploration. Repetitive decisions are characterized by a larger experience base, more straightforward identification...