Creating Reliable and Resilient Logistics Organizations for Unpredictable Conditions and Unexpected Future

Purpose: The objective of this paper is to develop a general concept for creating resilient logistics organizations under the deep uncertainty that arises from unpredictable conditions and unexpected future, and to integrate it with a framework for ensuring the reliable operation of these organizations under conditions of predictable change. Design/Methodology/Approach: The research methodology was based on a transdisciplinary approach because logistics organizations have the nature of complex systems with different types of systems such as physical, cybernetic and social ones. The research approach used is based on a critical analysis of the literature and case studies from the authors' own experience. The research is supported by Ackoff's 'idealized design' approach and assumptions from The IRGC Risk Governance Framework. Findings: It was found that complex logistics organizations can be successfully modelled as Engineered System of Systems and managed according to the principles applicable to such systems. Furthermore, it was shown that it is possible to combine two different concepts, namely High Reliability Organization and Resilient Enterprise, into one coherent whole in the form of a Reliable and Resilient Logistics Organization. Practical Implications: For practical use of the developed concept, a framework was designed in the form of an algorithm describing the process of creating Reliable and Resilient Logistics Organization in the form of successive stages of action and decisions. Originality/value: The concept of the Reliable and Resilient Logistics Organization is wholly original and is the result of many years of our research into the behavior of complex socio-technical systems under uncertainty. The added value of the work is the model developed, which in the form of a framework can be used in practice in logistics organizations to ensure their continuous and effective operation under various conditions, both predictable and unpredictable changes in the environment.