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Is Systemic Operation Design Capable of Reducing Significantly Bias in Operational Level Planning Caused by Military Organizational Culture

机译:系统运行设计能否在军事组织文化引发的作战层面规划中显着减少偏差

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摘要

Bias caused by organizational culture is a constant companion of military planning. Cognitive models dominated by Newtonian, mechanistic, and reductionist thinking have all but fixed bias at the operational level of war where environmental orientation to a rival is rarely more than an ideological mirage. The results are brittle campaign plans that are predictable by any thinking competitor. Systemic Operation Design claims to address this problem by re-orienting users to each unique problem they face. It rejects the unconscious application of previous experiences and cognitive templates as a dangerous trap that is more likely to produce incoherent and flawed actions than effective operational art and science. As a holistic approach, it seeks to self-consciously and cognitively orient users to the problem at hand before investigating the logic underlying the form of the system that connects them to a given rival entity. Instead of working in reverse from teleological, mechanistic, rigid, and pre-determined strategic end-states to possible actions likely to deliver them, the approach seeks to frame the logical terms for planning to begin while recognizing that the most likely outcome of a given action is a series of new issues that will alter the dynamic and adaptive system, preferably in the strategic direction desired. It sets as its goal the manipulation of the evolution of systemic changes resulting from actions or threatened actions, which create circumstances that facilitate one's own logic and are self-regulating. This paper examines the continuing problem of bias caused by military organizational culture and an addiction to the rigid application of reductionist epistemologies. It then investigates how Systemic Operation Design seeks to overcome the problems it claims to address, and concludes by outlining the principal future organizational challenges that its application might demand.

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