Systems thinking

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. Derek Cabrera's self-published 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. For example, the Waters Foundation presents systems thinking as 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. Other models characterize systems thinking differently. Recent scholars, however, are focused on the "patterns that connect" this diversity or pluralism of methods and approaches.

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

a system is other than the sum of its 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)

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 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 that seek equilibrium but can exhibit patterns, cycling, oscillation, randomness, or chaos (see chaos theory), or exponential behavior (see Exponential Function).

A holistic system is any set (group) of interdependent or temporally interacting parts. Parts are generally systems themselves and 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 account for unquantifiable variables such as opinions, culture, or politics, etc., and may treat people as passive elements, rather than as beings with 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.

The systems approach

The systems thinking approach incorporates several tenets:

Interdependence of objects and their attributes – independent elements can never constitute a system

Holism – emergent properties not possible to detect by analysis should be possible to define by a holistic approach

Goal seeking – systemic interaction must result in some goal or final state

Inputs and outputs – in a closed system inputs are determined once and constant; in an open system additional inputs are admitted from the environment

Transformation of inputs into outputs – the process by which the goals are obtained

Entropy – the amount of disorder or randomness present in any system

Regulation – a method of feedback is necessary for the system to operate predictably

Hierarchy – complex wholes are made up of smaller subsystems

Differentiation – specialized units perform specialized functions

Equifinality – alternative ways of attaining the same objectives (convergence)

Multifinality – attaining alternative objectives from the same inputs (divergence)

A treatise on systems thinking ought to address many issues including:

Encapsulation of a system in space and/or in time

Active and passive systems (or structures)

Transformation by an activity system of inputs into outputs

Persistent and transient systems

Evolution, the effects of time passing, the life histories of systems and their parts.

Design and designers.

Using the tenet of "multifinality", a supermarket could be considered a:

"Profit making system" from the perspective of management and owners

"Distribution system" from the perspective of the suppliers

"Employment system" from the perspective of employees

"Materials supply system" from the perspective of customers

"Entertainment system" from the perspective of loiterers

"Social system" from the perspective of local residents

"Dating system" from the perspective of single customers

As a result of such thinking, new insights may be gained into how the supermarket works, why it has problems, how it can be improved or how changes made to one component of the system affects other components.

Applications

Systems thinking is increasingly being used to tackle a wide variety of subjects in fields such as business analysis, business management, computing, engineering, epidemiology, information science, health, manufacture, sustainable development, and the environment.

Some examples:

Hierarchical frameworks

A number of hierarchical frameworks have been developed, but such hierarchical frameworks have also been criticized in an article in the journal Philosophy of Science, which noted that they are plagued with conceptual deficiencies; the authors concluded that "the concept of discrete ontological levels does not succeed and has been used to motivate several problematic claims about the natural world".

Kenneth Boulding's hierarchy of systems

The following table shows Kenneth E. Boulding's 1956 hierarchy of systems.

Level Characteristic unit Summary description (1) framework static systems (2) clockwork simple dynamic systems (3) thermostat control mechanisms and cybernetic systems (4) cell open systems, or self-maintaining structures (5) plant genetic/societal systems (6) animal mobile, teleological systems with self-awareness (7) human individual animal systems with self-consciousness (8) human society social systems with self-consciousness (9) transcendental idea ultimate, absolutes, and inescapeable knowledges

Stephen Haines' seven levels of living systems

Stephen G. Haines' seven levels of living systems, published in 1998, are in hierarchical relationships with each other, systems within systems. They begin with Earth as the largest living system and extend all the way down to cells, the smallest living system.

Level System (1) Cell (2) Organ (3) Individual organism (4) Group, team or department (5) Organization (6) Society or community (7) Earth

Stafford Beer's classification of systems

The following table shows Stafford Beer's 1959 classification of systems based on degrees of complexity and uncertainty.

----------------------------------------------------------------------- SYSTEMS Simple Complex Exceedingly complex ----------------------------------------------------------------------- Deterministic Window catch Electronic digital EMPTY computer -------------------------------------- Billiards Planetary system -------------------------------------- Machine-shop Automation lay-out ----------------------------------------------------------------------- Probabilistic Penny tossing Stockholding The economy --------------------------------------------------------- Jellyfish Conditioned The brain movement reflexed --------------------------------------------------------- Statistical Industrial THE COMPANY quality control profitability

Katz & Kahn's open system model

In The Social Psychology of Organizations (1966), psychologists Daniel Katz and Robert L. Kahn developed their open system theory for the interpretation of organizational actions in terms of input, throughput, output, environment, and other characteristics. Their open system model built upon Bertalanffy's general systems theory, and has been adapted into various business process models, such as the "five phases of systems thinking" framework.