A complex problem is different from a complicated one because complex problems mimic features of complex systems rather than those of engineered systems. We use the terms complex systems and complex problems interchangeably—a complex problem exists inside a complex system.
Complex systems are composed of many self-organizing components that interact with each other. They are intrinsically difficult to model and control because of the dependencies and interactions between the parts of a decentralized system. Complex systems have distinct properties such as emergence, non-linearity, self-organization, adaptation, and feedback loops.
Complex problems are hard problems because they do not yield to our usual problem-solving tools, where problems can be broken down into the constituent parts (which we can understand and model) and the individual reactions between them.
Solutions to complex problems need to be collective or system-wide so we need to understand how relationships between the problem, solutions, and the environment change over time.
Complex problems involve human agency. More and more business problems are now complex problems because customers, communities, regulators, employees, and suppliers can organize and act differently than in the past.
“The principles of complexity science can be a valuable tool for understanding and solving business problems.”
Sonder Studio helped Company X apply the principles of complexity science to their most complex business problems. We helped them understand the concept of emergence, which refers to the emergence of new and unexpected patterns and behaviors from the interactions of individual components. In Company X’s business context, this can be used to understand how small changes in one part of the organization can lead to large-scale changes in overall performance.
Another key principle of complexity science that people gained insight from is the idea of self-organization, which refers to the ability of complex systems to adapt and reorganize themselves without the need for central control or direction. We helped employees apply insights from self-organizing systems in complex systems to their business by training people in decentralized decision-making, taking into account data and intuition in decision-making.
A third principle of complexity science we helped Company X employees to understand is the idea of resilience, which refers to the ability of a system to recover from disturbances and maintain its overall functioning. For Company X employees, this is used to design more robust and adaptable organizational structures and processes, as well as to develop strategies for dealing with uncertainty and change.
The key to applying complexity science to business problems is to understand the underlying principles and apply them in a way that is relevant to the specific context. This may involve using mathematical tools and methods such as agent-based modeling, network analysis, and non-linear dynamics. But it most often involves a simpler construct that is highly human-centered using the power of metaphor.
At Sonder Studio, our design-oriented approach is a natural fit for using metaphor. We applied our process to help Company X employees identify the right metaphors, reason precisely about them in the context of their problem, and translate them into new, shared mental models for complex problem-solving. Metaphors are an incredibly powerful design tool that Company X can now use to power their employees' creativity and problem solving skills.
The principles of complexity science can be a valuable tool for understanding and solving business problems. By learning how to embrace the concepts of emergence, self-organization, and resilience, Company X has become more adaptable, responsive, and effective in today's fast-paced and ever-changing business environment.
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