Each era is shaped by how it perceives the universe and its underlying principles:

- The dominance of the Catholic Church during the Middle Ages prioritized spiritual life and the afterlife, diverting attention from earthly challenges. As people engaged in the Crusades and trade, the encountering of diverse cultures fueled curiosity about different values and habits.

- The Renaissance marked a transformation driven by a questioning of life's purpose amid challenging living conditions. It emphasized the complete understandability of the universe, employing analysis as a dominant method of thought. Cause-and-effect relationships became central, fostering a reductionist view. Isaac Newton saw the universe as a hermetically sealed clock – a closed system without an environment. This perspective, combined with the belief that humans were made in God's image, inspired the Industrial Revolution. Mechanization of work followed the principles derived from the worldview of understanding, analysis, and cause-and-effect relationships. The Machine Age involved breaking down tasks into elementary components for mechanization, resulting in the dehumanization and alienation of work.

- Dilemmas challenging the worldview from the Machine Age included the concept of free will and Heisenberg's uncertainty principle, questioning the complete understandability of the universe. The 1950s witnessed a breakthrough with the emergence of General System Theory. Systems Thinking involves understanding wholes that cannot be divided into independent parts. Unlike analysis, which breaks down systems, synthesis reveals the role or function of the system within a larger context. The 1960s saw an interest in Eastern religion, particularly Zen Buddhism, responding to the desire for a view of God as the universe and a sense of participation in that wholeness through practices like meditation. Edgar Arthur Singer Jr. challenged the traditional view of causality by introducing producer-product relationships, emphasizing that causes are necessary but not sufficient for their effects. This perspective gained recognition in 1954, providing a complementary way of understanding reality alongside cause-and-effect relationships. The shift from a mechanistic view to a systemic perspective involves recognizing systems as having their purposes. Businesses and organizations are no longer viewed as mere machines but as living organisms with inherent purposes such as survival and growth. Post-World War II also witnessed a change in the workforce, with individuals motivated by factors beyond economic considerations. Societal movements highlighted the need to consider multiple levels of purpose within systems – the purpose of the system itself, the purposes of its parts, and the purposes of the larger system it's part of. 

In systemic thinking, we acknowledge the interconnectedness of all things and the importance of understanding wholes. This shift in thinking has profound implications for how we approach challenges, view organizations, and engage with the complexities of our world.

As safety management professionals, we understand that the issues we encounter are often qualitative, and measurements alone can't tell the whole story. To truly understand complex socio-technical systems, we need to embrace systems thinking. A key premise of systems thinking is that to achieve sustainable large-scale systems change, we must change the entrenched patterns that drive the system, and not just rely on exhortations, threats, and fear. Improving results requires improving the system itself.

Communicating our understanding of complex systems is challenging, but it's essential to get the most out of our collaborating community. To make changes that are coherent and likely to succeed, we must identify and engage with others in the system, build a shared understanding of our system, and recognize the interdependent nature of organizations.

Systems thinking requires us to consider all parts of a system, including the simplifying assumptions made in safety models, while also accounting for randomness to make statistical calculations more accurate. But we must remember that our observations are limited by our own biases and assumptions. To refine our models and understand complex systems, we need to approach them with cross-disciplinary understanding. Generalists who can use specific language to relate to specialists can be helpful in this arena.

Sources:

Ackoff, R. (1993), From Mechanistic to Systemic Thinking, in: Systems Thinking in Action conference, 
Deming Institute (www.deming.org)
Leveson, N.G. (2016), Engineering a Safer World: Systems Thinking Applied to Safety, Cambridge: The MIT Press,
Weinberg, G.M. (2001), An Introduction to General Systems Thinking, New York: Dorset House.