complex-systems

What Are Complex Systems? Complex Systems In A Nutshell

Complex systems consist of many elements interacting with each other in a disordered way. This disorder makes the behavior of complex systems difficult to predict. To understand complex systems think of them as a system is where the whole is more than the sum of its parts.

Understanding complex systems

Complex systems comprise the very fabric of life itself. They are seen in the way birds organize themselves into flying formations and in the emergent structures of plants, snowflakes, and galaxies. Complex systems also describe the formation of human social networks and the communication patterns and social capital that form as a result.

Despite the prevalence of complex systems, researchers cannot agree on a concise definition and there has been relatively little scientific study into the topic. Perhaps the most accepted descriptor of a complex system is one with “wholes that are more than the sum of their parts.” Importantly, the behavior of these wholes cannot be predicted or explained without looking at the interaction between multiple, interconnected components.

Properties of complex systems

Complex systems exhibit certain properties that arise from the dependencies and relationships existing between their constituent parts.

Some of these properties include:

  1. Emergence – from the interaction between individual elements arises the behavior of the system as a whole. In complex systems, this higher-order behavior cannot be created by aggregating behavior at the element level. In other words, higher-order behavior arises spontaneously.
  2. Transitions, tipping points, and non-linearity – complex systems also display non-linear dynamics, which means they may suddenly behave differently or exhibit a new regime. Similarly, complex systems may display a high degree of stability in one moment and become chaotic in the next. Examples of complex systems with these traits include revolutions, pandemics, and financial crises. 
  3. Unpredictability – since interactions are dynamic and non-linear, the behavior of a complex system cannot be predicted by inspecting its individual components. Unpredictability is related to emergence and so-called Black Swan events, which occur when small changes to a system become large effects over time.
  4. Evolutionary dynamics – complex systems are never at rest and do not move toward a knowable endpoint or equilibrium. The mechanism for evolution begins with variation in a few elements that flourish by multiplying in the system. These elements may change the external environment of the system. Conversely, the external environment is also able to change the system by introducing new variations.
  5. Adaptation – some complex systems are adaptive in that they can change and learn from experience. That is, they can organize or reorganize their internal structure in the absence of an external agent. Examples of these systems include the stock market, social insect colonies, the immune system, and the biosphere.

Implications of complex systems for organizations

Now that we have defined the characteristics of complex systems, let’s take a look at the implications of complexity itself in an organizational context. 

South African philosopher and complexity researcher Paul Cilliers defined seven.

1 – Relationships are fundamental 

For organizations to succeed, Cilliers suggested it was the nature of interactions between employees that drive innovation and company culture. 

Focusing on how people are proximally located and rethinking the way meetings are conducted should be prioritized over training individuals to be creative in isolation.

2 – Stable states are not desirable 

While many organizations favor stability and certainty, the truth is they become stagnant and uncompetitive without continuous improvement and the embracing of change.

3 – No organization can be understood independently of its context

Cilliers acknowledges that vision and mission are important, but they can inadvertently define the imaginary boundaries of a comfort zone. Successful organizations interact with their broad environment, which includes other organizations.

4 – The history of an organization determines its nature 

Two organizations with similar histories are not the same. The history of each is comprised of countless events and interactions distributed through the system. These interactions alone determine a unique evolutionary trajectory for both companies.

What’s more, decision-makers should never assume that a practice that works well in one context will do the same in another.

5 – Novel characteristics, desirable or undesirable, may emerge 

An undesirable characteristic may describe the plummeting sales in a previously popular product. Though the organization would prefer otherwise, it should not be surprised by emergence when it occurs. 

By the same token, more desirable characteristics should not be suppressed or ignored simply because they were unexpected. 

6 – Outcome magnitude is determined by the size of the cause and the context and history of the system 

This means the organization should be prepared for the unexpected and not underestimate the potential impact of an insignificant event. 

In a recent TED talk, entrepreneur and CEO Margaret Heffernan suggested companies transition from “just in time” to “just in case”. That is, the focus should switch from efficiency to resilience to counter the unpredictability of complex system outcomes.

7 – Complex organizations cannot grow with excessive central control 

Lastly, it is suggested organizations distribute control through their systems. Too often, managers tasked with making unpopular decisions are keen to offload the responsibility to others and decentralize control. But when the decision is considered a popular one, control is highly centralized. 

As workplaces become increasingly autonomous, the opportunity for all employees to feel motivated and engaged in meaningful work is critical. To achieve this, they must be given some degree of decision-making power – or what we might call autonomy.

Key takeaways:

  • Complex systems consist of many elements interacting with each other in a disordered way. This disorder makes the behavior of complex systems difficult to predict.
  • Complex systems exhibit certain properties that arise from the dependencies and relationships existing between their constituent parts. Some of the core properties include emergence, non-linearity, unpredictability, evolutionary dynamics, and adaptation.
  • The implications of complex systems for organizations were researched by researcher and philosopher Paul Cilliers. The implications suggest relationships are fundamental and stable states are not desirable. Cilliers also found that desirable and undesirable novel characteristics may emerge at any time and that complex organizations could not thrive with centralized control.

Connected Business Frameworks

systems-thinking
Systems thinking is a holistic means of investigating the factors and interactions that could contribute to a potential outcome. It is about thinking non-linearly, and understanding the second-order consequences of actions and input into the system.
second-order-thinking
Second-order thinking is a means of assessing the implications of our decisions by considering future consequences. Second-order thinking is a mental model that considers all future possibilities. It encourages individuals to think outside of the box so that they can prepare for every and any eventuality. It also discourages the tendency for individuals to default to the most obvious choice.
first-principles-thinking
First-principles thinking – sometimes called reasoning from first principles – is used to reverse-engineer complex problems and encourage creativity. It involves breaking down problems into basic elements and reassembling them from the ground up. Elon Musk is among the strongest proponents of this way of thinking.
ladder-of-inference
The ladder of inference is a conscious or subconscious thinking process where an individual moves from a fact to a decision or action. The ladder of inference was created by academic Chris Argyris to illustrate how people form and then use mental models to make decisions.
six-thinking-hats-model
The Six Thinking Hats model was created by psychologist Edward de Bono in 1986, who noted that personality type was a key driver of how people approached problem-solving. For example, optimists view situations differently from pessimists. Analytical individuals may generate ideas that a more emotional person would not, and vice versa.
second-order-thinking
Second-order thinking is a means of assessing the implications of our decisions by considering future consequences. Second-order thinking is a mental model that considers all future possibilities. It encourages individuals to think outside of the box so that they can prepare for every and eventuality. It also discourages the tendency for individuals to default to the most obvious choice.
lateral-thinking
Lateral thinking is a business strategy that involves approaching a problem from a different direction. The strategy attempts to remove traditionally formulaic and routine approaches to problem-solving by advocating creative thinking, therefore finding unconventional ways to solve a known problem. This sort of non-linear approach to problem-solving, can at times, create a big impact.
moonshot-thinking
Moonshot thinking is an approach to innovation, and it can be applied to business or any other discipline where you target at least 10X goals. That shifts the mindset, and it empowers a team of people to look for unconventional solutions, thus starting from first principles, by leveraging on fast-paced experimentation.
design-thinking
Tim Brown, Executive Chair of IDEO, defined design thinking as “a human-centered approach to innovation that draws from the designer’s toolkit to integrate the needs of people, the possibilities of technology, and the requirements for business success.” Therefore, desirability, feasibility, and viability are balanced to solve critical problems.
catwoe-analysis
The CATWOE analysis is a problem-solving strategy that asks businesses to look at an issue from six different perspectives. The CATWOE analysis is an in-depth and holistic approach to problem-solving because it enables businesses to consider all perspectives. This often forces management out of habitual ways of thinking that would otherwise hinder growth and profitability. Most importantly, the CATWOE analysis allows businesses to combine multiple perspectives into a single, unifying solution.

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Published by

Gennaro Cuofano

Gennaro is the creator of FourWeekMBA which reached over a million business students, executives, and aspiring entrepreneurs in 2020 alone | He is also Head of Business Development for a high-tech startup, which he helped grow at double-digit rate | Gennaro earned an International MBA with emphasis on Corporate Finance and Business Strategy | Visit The FourWeekMBA BizSchool | Or Get The FourWeekMBA Flagship Book "100+ Business Models"