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

Frederick Benaben (1) , Matthieu Lauras (1) , Benoit Montreuil (2) , Louis Faugère (2) , Juanqiong Gou (3) , Wenxin Mu (4)

1 CGI - Centre Génie Industriel
2 Georgia Institute of Technology [Atlanta]
3 SEM - School of Economics and Management [Beijing]
4 BJTU - Beijing Jiaotong University

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.

Mots clés: risk management; risks; force fields; physics; artificial intelligence; knowledge management; opportunity

Domaines: Sciences de l'ingénieur [physics]

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⟩