The following brief discussion provides a general overview of the relationship between the concepts of complexity, resilience and systems thinking. A more comprehensive discussion will follow.

Resilience is a common property of many complex systems [1] and refers to the ability of a system to absorb disturbances, adapt to changing conditions, and continue to function and evolve. Although the word resilience originated in the 17^th century from the Latin word “resiliere”, meaning leap back or rebound, the concept of resilience emerged in the 1970’s from ecological studies on interacting populations. Introducing resilience to ecology for the first time, Holling (1973, p.17) stated that “Resilience determines the persistence of relationships within a system and is a measure of the ability of these systems to absorb changes of state variables, driving variables, and parameters, and still persist.” [2]

In contrast to the idea of a system “bouncing back” in the context of resilience, the phrase “bouncing forward” is increasingly used to emphasize that transformation and growth in a particular system occurs and not merely recovery. In the context of climate change adaptation and disaster risk reduction, Sukaina Bharwani and Julia Barrott at the Stockholm Environment Institute also applied the term to argue that resilience should not just mean returning to the status quo, but rather transforming systems to be better prepared for future shocks.

When studying complex systems such as ecosystems and economies closely, it becomes evident that they exhibit the following characteristics:

• Non-linearity (small inputs leading to disproportionately large outputs)
• Emergence (appearance of complex patterns or behaviours from simple rules or interactions among components)
• Adaptability (system ability to change or evolve in response to its environment)
• Self-organization (spontaneous formation of order and structure arising without central control)

These characteristics effectively allow the system to be more resilient. Considering the phrase of “bouncing forward” again, in the context of complex systems we intervene in, it is evident that the characteristics of these complex systems need to be understood in order to ensure the enhancement of their resilience. Consider the following examples of how these characteristics enable resilience:

• Non-linearity – Allows for tipping points and sudden shifts; understanding it helps anticipate risks
• Emergence –  Helps to identify how local interactions can lead to global stability or instability
• Adaptability – Enables systems to learn from disturbances and subsequently to evolve
• Self-organization –  Supports decentralized responses and spontaneous recovery

Systems thinking is a powerful approach for understanding the characteristics of complex systems [3] in order to enhance heir resilience. By focusing on the relationships, feedback loops, and interdependencies among system components rather than isolating individual parts, systems thinking reveals how behaviours such as non-linearity, emergence, adaptability, and self-organization arise. This holistic perspective helps identify leverage points where small interventions can lead to significant improvements in system performance. It also enables the anticipation of unintended consequences and cascading effects, which are common in complex systems. Ultimately, systems thinking equips decision-makers with the insight needed to design systems that are not only robust in the face of shocks but also capable of learning, evolving, and thriving under changing conditions.

References

[1] Fraccascia, L., Giannoccaro, I., Albino, V., 2018. Resilience of Complex Systems: State of the Art and Directions for Future Research. Complexity 2018, 3421529. https://doi.org/10.1155/2018/3421529

[2] Holling, C.S., 1973. Resilience and Stability of Ecological Systems. Annual Review of Ecology, Evolution, and Systematics 4, 1–23. https://doi.org/10.1146/annurev.es.04.110173.000245

[3] Merali, Y., Allen, P., 2011. Complexity and systems thinking, in: The SAGE Handbook of Complexity and Management. pp. 31–52. https://doi.org/10.4135/9781446201084.n1