Systems Thinking

Systems Thinking involves the use of various techniques to study systems of many kinds. In nature, examples of the objects of systems thinking include ecosystems – in which various elements (such as air, water, movement, plants, and animals) interact. In organizations, systems consist of people, structures, and processes that operate together to make an organization “healthy” or “unhealthy”.

History and overview

Systems thinking has roots in a diverse range of sources from Jan Smuts’ holism in the 1920s, to the general systems theory that was advanced by Ludwig von Bertalanffy in the 1940s and cybernetics advanced by Ross Ashby in the 1950s. The field was further developed by Jay Forrester and members of the Society for Organizational Learning at MIT, which culminated in the popular book The Fifth Discipline by Peter Senge, which defined Systems thinking as the capstone for true organizational learning. Systems scientist Derek Cabrera’s book Systems Thinking Made Simple claimed that systems thinking itself is the emergent property of complex adaptive system behavior that results from four simple rules of thought.

Systems thinking has been defined as an approach to problem solving that attempts to balance holistic thinking and reductionistic thinking. By taking the overall system as well as its parts into account systems thinking is designed to avoid potentially contributing to further development of unintended consequences. There are many methods and approaches to systems thinking (what systems thinking researchers call a “pluralism”). For example, the Waters Foundation presents that systems thinking is not one thing but a set of habits or practices within a framework that is based on the belief that the component parts of a system can best be understood in the context of relationships with each other and with other systems, rather than in isolation; and that systems thinking focuses on cyclical rather than linear cause and effect. Whereas, other models characterize systems thinking quite differently. Recent scholars, however, are focused on the “patterns that connect” this pluralism of methods, this search for universal patterns that cut across the pluralism of individual methods of systems thinking is called “universality.”

In systems science, it is argued that the only way to fully understand why a problem or element occurs and persists is to understand the parts in relation to the whole. Standing in contrast to Descartes’s scientific reductionism, it proposes to view systems in a holistic manner. Consistent with systems philosophy, systems thinking concerns an understanding of a system by examining the linkages and interactions between the elements that compose the entire system.

Systems science thinking attempts to illustrate how small catalytic events that are separated by distance and time can be the cause of significant changes in complex systems.

Acknowledging that an improvement in one area of a system can adversely affect another area of the system, it promotes organizational communication at all levels to avoid the silo effect. Systems thinking techniques may be used to study any kind of system – physical, biological, social, scientific, engineered, human, or conceptual.

The concept of a system

Several ways to think of and define a system include:

  • a system is composed of parts
  • all the parts of a system must be related (directly or indirectly), else there are really two or more distinct systems
  • a system is encapsulated (has a boundary)
  • the boundary of a system is a decision made by an observer, or a group of observers
  • a system can be nested inside another system
  • a system can overlap with another system
  • a system is bounded in time, but may be intermittently operational
  • a system is bounded in space, though the parts are not necessarily co-located
  • a system receives input from, and sends output into, the wider environment
  • a system consists of processes that transform inputs into outputs
  • a system is autonomous in fulfilling its purpose (a car is not a system. A car with a driver is a system)

Systems science thinkers consider that:

  • a system is a dynamic and complex whole, interacting as a structured functional unit circuit
  • energy, material and information flow among the different elements that compose a system (see open system)
  • a system is a community situated within an environment
  • energy, material and information flow from and to the surrounding environment via semi-permeable membranes or boundaries that may include negotiable limits
  • systems are often composed of entities seeking equilibrium but can exhibit patterns, cycling, oscillation, randomness or chaos (see chaos theory), or exponential behavior

A holistic system is any set (group) of interdependent or temporally interacting parts. Parts are generally systems themselves and are composed of other parts, just as systems are generally parts or holons of other systems.

Systems science and the application of systems science thinking has been grouped into the following three categories based on the techniques or methodologies used to design, analyze, modify, or manage a system:

Hard systems – involving simulations, hard systems approaches to system thinking often use computers and the techniques of operations research/management science. Hard systems approaches are useful for problems that can be justifiably quantified. However, hard systems cannot easily take into account unquantifiable variables such as opinions, culture, or politics, etc., and may treat people as being passive, rather than as having complex motivations.

Soft systems (or soft systems methodology) – is a methodology for systems that cannot easily be quantified, especially systems that involve people holding multiple and conflicting frames of reference. Soft systems methods are useful for understanding motivations, viewpoints, and interactions, and for addressing qualitative as well as quantitative dimensions of problem situations. Soft systems approaches to system thinking may use foundation methodological work developed by Peter Checkland, Brian Wilson, and their colleagues at Lancaster University. This approach may include morphological analysis, which is a complementary method for structuring and analyzing non-quantifiable problem complexes.

Evolutionary systems – Béla H. Bánáthy developed a methodology that is applicable to the design of complex social systems. This technique integrates critical systems inquiry with soft systems methodologies. Evolutionary systems, similar to dynamic systems are understood as open, complex systems, but with the capacity to evolve over time. Bánáthy uniquely integrated the interdisciplinary perspectives of systems research (including chaos, complexity, cybernetics), cultural anthropology, evolutionary theory, and others.

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