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Distributed sensemaking in network risk analysis.

Jacob Taarup-Esbensen1,2

  • 1Center for Risk Management and Societal Safety, University of Stavanger, Stavanger, Norway.

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|February 2, 2022
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Summary

This study introduces a network risk analysis model based on distributed sensemaking to improve how organizations understand and manage uncertainty. It highlights four key dimensions for effective risk analysis and decision-making in complex environments.

Keywords:
risk analysisrisk sciencesensemaking

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Area of Science:

  • Risk analysis and management
  • Organizational behavior
  • Decision science

Background:

  • Risk analysis is increasingly vital across global organizations.
  • Understanding risk perception and organizational control has advanced significantly.
  • There's a need for improved conceptual models in risk science.

Purpose of the Study:

  • To introduce a conceptual model for risk analysis based on distributed sensemaking.
  • To identify key dimensions central to organizational sensemaking of uncertainty.
  • To illustrate the practical application of a network risk analysis model.

Main Methods:

  • Development of a conceptual model for risk analysis.
  • Identification of four central dimensions: activities, sensory systems, individual roles, and information coordination.
  • Application of the model using three case studies from the Arctic context.

Main Results:

  • The proposed model reveals critical insights into organizational decision-making processes.
  • It exposes potential weaknesses in current risk analysis and decision-making.
  • The Arctic examples demonstrate the model's utility in identifying vulnerabilities.

Conclusions:

  • Distributed sensemaking is crucial for effective network risk analysis.
  • The model enhances an organization's capacity to perceive, process, and act on contextual changes.
  • This approach supports better risk management and decision-making in complex operational settings.