System Thinking

 Solving Problems with System Thinking :

What is a system?

System is a group of interacting or interrelated elements that act together according to a set of rules to form a unified whole,

What is a Complex Adaptive system?

A system that is complex in that it is a dynamic network of interactions, but the behaviour of the ensemble may not be predictable according to the behaviour of the components.

What is System Thinking?

Away of making sense of the complexity of the world by looking at it in terms of wholes and relationships rather than by splitting it down into its parts.

What  System Thinking is important?

Systems thinking, which is more of a mindset than a set of guidelines, helps people understand how they may collaborate in various team settings and, using that knowledge, develop the optimum procedures for completing virtually any task. If we know where to look, systems are everywhere.

Types of problems :

There are 3 main types of problems that can be seen in our day today life.

1. Simple problems

2. Complicated problems

3. Complex problems

 1. Simple problems :

A Simple Problem has a clear cause and effect that is easily identifiable and fixable. 

Example : Following a recipe 

The recipe is essential, Recipe are tested to assure easy replication, No particular expertise required, Produce standarized products, Best recipe always give the best product and optimistic approach to problem possible.

2. Complicated problems : 

Complicated problems originate from causes  that can be individually distinguished, They can be addressed step by step for each input to the system there is a proportionate output the relevant systems can be controlled and the problems they present admit permanent solutions.

Example : Sending a rocket to the moon.

Formulae are critical and necessary, sending one rocket increases assurance the next will be OK, Rockets are similar in critical ways. There is a high degree of certainly of outcomes.

Characteristics of complicated problems :

• Definability
• Reducibility
• Predictability
• Solvability

3. Complex problems :

Complex problems are typically defined as those that include the ability to approach them from multiple, sometimes competing, perspectives and which may have multiple possible solutions.

Example : Raising a child.

Formulae have a limited application, Raising one child provides experience but no assurance of success with the next, Uncertainty of outcome remains, Optimize approach to problem possible.

Characteristics of complex problems :

• Difficult to define
• Cannot be broken into parts
• Cannot  be predicted
• Cannot be solved only can be addressed
• Sovability is influenced by external factors

What are wicked problems:

Wicked problems are those that have numerous interrelated variables that make them seem impossible to resolve. Solving wicked problems demands a thorough understanding of the stakeholders involved and an inventive approach given by design thinking because the factors are frequently incomplete, in flux, and difficult to describe.

By using system thinking we can solve the problems in complex systems. To solve such problems in complex systems there should be a good interaction between all the individuals in the system. Complexity is emergent from interactions among wholes. Individual actions are simple and local and the should learn and adapt to the system.

As an example, when we consider a beehive, it is also a complex system consists with many members such as workers , drone and the queen. So when working together they have to perform several complex tasks such as proper communication, Nest construction, Environmental control, Defence and division of the labour. 

Complex systems and Business :

Due to dependencies, rivalries, relationships, or other types of interactions between their parts or between a specific system and its environment, complex systems have behaviour that is inherently challenging to model.

We can forecast the likelihood of specific events by looking at how the components of a system interact. In order to anticipate the weather, societal problems, the spread of illnesses, financial recessions, and other events, complex systems theory can be used.

Example : U.S. cavalry was called in by park officials in Yellowstone National Park in the late 1800s to hand-feed elk in an effort to increase the game population. Elk numbers increased, the elk began consuming aspen trees, beavers were using aspen trees to construct their dams, and the beaver dams were catching the spring runoff, allowing trout to spawn. Less trout equated to more elk.

Dealing with Complexity :

The largest problem, in my opinion, is that people are frequently overly adept at tying together causes and effects. The majority of cause and effect was very obvious ten thousand years ago. And our minds have developed to handle that.

However, it means that even though cause and effect are incomprehensible in this type of system, your mind will still construct a story to explain what happened when you observe something occurring in a complex adaptive system.

You will obtain really good solutions to issues when knowledge is diversified, information aggregation is healthy, and incentives are healthy. That's what nature does, and that's what we need to improve at doing.