Risk based thinking – New approach for modern enterprises’ management

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Abstract

The current business environment has been constantly changing, dependable on different conditions and requirements. The dynamics of business changes are the result of globalization, market development and other factors. Positive development and business sustainability requires responding to opportunities, but with limited potential threats, which occur with those changes. A natural feedback to negative impacts reduction (or even increasing opportunities) in enterprise management in this environment is a new approach implementation. Risk-Based Thinking (RBT) appears as a basis platform of all management systems (ISO 9001, ISO 140001, ISO 45001, ISO 27001, etc.). Information security was the first management system, where RBT was implementing as a part of the management system. Industry 4.0 requires a change in human-machine-environment area, resulting from the ability to flexibly response to customer and stakeholder demands. Reliability of information, limitation human mistakes limitation in the process, data protection and knowledge in Smart factory is not possible without the creation of effective preventive tools resulting from risk analysis. Current methods and tools for risks identification and its assessment require the development of new system logic processes based on mutual relations. RBT creates a risk management framework, as a part of the management approaches is one of the basic pillars for managing the Smart factory. The aim of the paper is to introduce the new approach of modern management thinking affected by changes made in new revision of ISO 9001. Through a new “Global Risk-Based Management” (GRBM) we try to suggest on the necessity of managements integration using RBT (Risk Register), and possibility to design an effective Risk Map to manage the external and internal risks in a modern enterprise.

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APA

Pacaiova, H., & Nagyova, A. (2019). Risk based thinking – New approach for modern enterprises’ management. In Advances in Intelligent Systems and Computing (Vol. 783, pp. 524–536). Springer Verlag. https://doi.org/10.1007/978-3-319-94709-9_52

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