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Training to Improve Decision Making System Dynamics Applied to Higher-Level Military Operations

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Journal of Battlefield Technology, Volume 6 Number 1

Bjørn T. Bakken and Martin Gilljam

Abstract. This paper is concerned with how to improve the training of higher-level military officers, given that the conditions for learning in "conventional" exercises (with a high degree of realism and complexity) are sub-optimal. From other applications (e.g., business and public management) we know that a key feature of effective decision training is high exercise frequency. Another requirement is for the decision-maker to see the full range of consequences resulting from his/her decisions. Both aspects require time compression in the training environment. We suggest applying the same principles when training military commanders, in a newly created concept termed Minimalist Decision Training (MDT). MDT is characterized by simplifying the commander’s operating environment, radically compressing time and space. In Minimalist Decision Training, a typical two-day exercise can cover several repetitions of a thirty-day conflict and at the same time provide continuous feedback about the unfolding of the conflict, consequential to decisions made. To this date, we have tested prototypes of system dynamic models ("microworlds") to be used as MDT environment at the Norwegian Defence Staff College as well as operational headquarters. The pilot users (instructors as well as student officers) have reported a high degree of satisfaction with the models as exercise environments. In particular, the operational relevance of a "high-intensity" model has been assessed. In a post-exercise survey participants indicated that eight out of ten suggested manoeuvre principles were believed to have substantial impact on operational outcome. We take these findings as evidence to support the view that the Minimalist Decision Training concept is viable, and deserving further attention within research and development

Related topics:  system dynamicstraining and analysis

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