Physics of Organization Dynamics: An AI Framework for opportunity and risk management - Archive ouverte HAL Access content directly
Conference Papers Year : 2019

Physics of Organization Dynamics: An AI Framework for opportunity and risk management

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Frederick Benaben
Matthieu Lauras
Benoit Montreuil
  • Function : Author
  • PersonId : 1003417
Juanqiong Gou
  • Function : Author
  • PersonId : 1051201
Wenxin Mu
  • Function : Author
  • PersonId : 998572

Abstract

The identification of risks and opportunities is generally massively depending on the ability of managers and decision makers to analyze multi-dimensional situations, to mobilize their experience and to infer risks and opportunities. However, in the Big Data era, early warning systems have shown that data science could be an efficient way to automatize risk detection. In this article, a new and original vision of risks and opportunities management is introduced and discussed in the context of a simple example. The main expected benefit is to enable decision makers to manage the trajectory of a considered system with regards to its performance towards its associated objectives, and to also support the definition of these performance objectives. The system could be an enterprise in an economic context but mainly any social system trying to avoid or manage instability, disruptions or crises.
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Dates and versions

hal-02415464 , version 1 (05-02-2020)

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Frederick Benaben, Matthieu Lauras, Benoit Montreuil, Louis Faugère, Juanqiong Gou, et al.. Physics of Organization Dynamics: An AI Framework for opportunity and risk management. IESM 19 - 8th International Conference on Industrial Engineering and Systems Management, Sep 2019, Shangai, China. p.396-401, ⟨10.1109/IESM45758.2019.8948167⟩. ⟨hal-02415464⟩
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