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MM02 - The Big Picture
What is Systems Thinking?
Systems theory is the interdisciplinary study of systems. The field studies systems from the perspective of the whole system, its various subsystems and the recurring patterns in the relationships between the subsystems. The application of this theory is called systems analysis, and systems thinking is a tool to implement system analysis.
Systems thinking is a way of helping a person to view systems from a broad perspective that includes seeing overall structures, patterns and cycles in systems, rather than seeing only specific events in the system. This comprehensive view can help you to quickly identify the real causes of issues in organisations and know just where to work to address them. By focusing on the entire system, one can attempt to identify solutions that address as many problems as possible in the system. The positive effect of those solutions leverages improvement throughout the system. Thus, they are called “leverage points” in the system. Reminds me of Archimedes principle, “Give me a lever long enough and a fulcrum on which to place it, and I shall move the world”.
Rather than breaking the system into smaller components, we synthesise various parts to deduce the behaviour of the overall system. The first Principle thinking deals with the analysis of the ecosystem, contrasting to that, the systems thinking deals with Holism. It’s proven and experienced that the sum of parts of the components can create a behaviour that may not exist in isolation.
Why use Systems Thinking?
To find the goal of the system, we need to look outside of it. Ironic, The goal is defined by what the system interacts with. The purpose of a passenger aeroplane is not to fly, but to move people from point A to point B. The engineering department is there to make the business successful; writing code is a mean, not the end in itself.
Systems thinking expands the range of choices available for solving a problem by broadening our thinking and helping us articulate issues in new and different ways. At the same time, the principles of systems thinking make us aware that there are no perfect solutions; the choices we make will have an impact on other parts of the system.
Specific scenarios are so complex that it cannot be solved by reductionism, i.e. solving via the first principle.
E.g. Physicists defines their theories at two different levels, i.e. at micro vs macro-level or atomic vs cosmic level or particle vs wave level.
It would seem intuitive to think that the rules of physics that apply at the atomic scale would be transferable to the macroscopic world. However, attempts to prove this have not been easy. When the size of a quantum system increases, it interacts more and more with its surrounding environment, which rapidly destroys its quantum properties. This phenomenon, known as quantum decoherence, is one of the limitations on the capability of macroscopic systems to retain their quantum properties. This is also evident in wave-particle duality.
In business terms, there are various departments and teams in an organisation, and they are performing focused functions, the leadership and management need to evaluate and optimise the organisation as a whole by keeping minimum or mandatory stock with each section and increasing flow between them. The managers need to ensure that the metric to measure time delay is in place with an appropriate feedback loop to support the growth. The growth of an organisation can only be achieved by visualising it as a whole system; else it can cause the blinding effect of getting lost in details.
One of the great tragedies of analytical thinking is favouring local optimisations. People everywhere are encouraged (through KPIs, bonuses and other incentives) to optimise their local parts, rather than the broader whole, this should be replaced by systems thinking.
How to use Systems Thinking?
Use the Theory of Constraints to find bottlenecks. There is a related body of thinking called Theory of Constraints, developed by an Israeli writer named Eli Goldman (and described in his excellent book “The Goal“). This theory says that any system has a constraint, or bottleneck, on its throughput. Instead of performing local optimisations at various parts of the system, the system should be optimised overall by focusing on that particular constraint.
Once that constraint has been optimised and overcome and is no longer the constraint, another part of the system will become the next constraint. So, efforts should then focus on removing that constraint on throughput, and so on.
The Theory of Constraints has some similarities and essential lessons for systems thinking and should be applied in combination.
Be careful when fixing problems.
Often, people apply quick fixes and bandaid solutions in an organisation. These can end up causing broader and more severe problems in other parts of the system, due to the interrelatedness of the elements. The cure can often turn out to be worse than the disease!
Below are the six most essential tools to implement systems thinking, but if you are a beginner start with Causal Loop Diagrams (CLD) and then start adding below methodologies to your CLD’s.
1) Disconnect vs Interconnected - This requires a mindset shift to identify the input and output of the system. Rather than defining the detail of system or functions, we define the dependencies and dependents of a system. This allows us to minimise the system waste by optimising the inputs and restricting the outcomes to mandatory outputs only. Indirectly impacting system operations.
2) Linear vs Circular - Since everything is interconnected, there are constant feedback loops and flows between elements of a system.
The two main types of feedback loops are reinforcing and balancing. The machine learning principle of RNN is an example of a practical implementation of systems thinking feedback tool. What can be confusing is a reinforcing feedback loop is not usually a good thing. In reinforcing loops, an abundance of one element can continually refine itself, which often leads to it taking over. A balancing feedback loop, however, is where elements within the system balance things out.
E.g. the operation cat drops were conducted by the UK government as a response for balancing feedback.
3) Silos vs Emergent - From a systems perspective, we know that more important things emerge from smaller parts: emergence is the natural outcome of things coming together.
A simple example of emergence is a snowflake. It forms out of environmental factors and biological elements. When the temperature is right, freezing water particles form in beautiful fractal patterns around a single molecule of matter, such as a speck of pollution, a spore, or even dead skin cells.
There is nothing in a caterpillar that tells you it will be a butterfly — R. Buckminster Fuller
4) Parts vs Whole - Cause and effect are pretty standard concepts in many professions and life in general. Causality as a concept in systems thinking is really about being able to decipher the way things influence each other in a system. Understanding causality leads to a more in-depth perspective on an agency, feedback loops, connections and relationships, which are all fundamental parts of systems mapping.
5) Analysis vs Synthesis - Synthesis refers to the combining of two or more things to create something new. When it comes to systems thinking, the goal is synthesis, as opposed to analysis, which is the dissection of complexity into manageable components. Essentially, synthesis is the ability to see interconnectedness. Thus, try a bottom-up approach or zoom out view.
6) Isolation vs Relationships - Systems mapping is one of the critical tools of the systems thinker. There are many ways to map, from analog cluster mapping to complex digital feedback analysis. However, the fundamental principles and practices of systems mapping are universal. Identify and map the elements of ‘things’ within a system to understand how they interconnect, relate and act in a complex system, and from here, unique insights and discoveries can be used to develop interventions, shifts, or policy decisions that will dramatically change the system most effectively.
When to use Systems Thinking ?
Systems thinking in practice encourages us to explore inter-relationships (context and connections), perspectives (each actor has their unique perception of the situation) and boundaries (agreeing on scope, scale and what might constitute an improvement). Systems thinking is particularly useful in addressing complex or wicked problem situations. These problems cannot be solved by any one actor, any more than a complex system can be fully understood from only one perspective. Moreover, because complex adaptive systems are continually evolving, systems thinking is oriented towards organisational and social learning – and adaptive management.
If you can identify Purpose, Elements and Interconnects of systems, then it is an ideal candidate to use system thinking as this can help in following scenarios:
Rapid Learning: Understand the Big Picture
Rapid Impact: Solve Real Problems
Rapid Adaptation: Identify Patterns
Rapid Innovation: Eliminate Bloat
Where to use Systems Thinking?
The similar approach can be extended to System Engineering, Human Evolution, Natural ecology, Behaviour Physiology and last but not the least; Business Process definition.
Problems that are ideal for systems thinking intervention have the following characteristics:
The issue is important.
The problem is chronic, not a one-time event.
The problem is familiar and has a known history.
People have unsuccessfully tried to solve the problem before.
Who should use Systems Thinking?
Anyone responsible for the bigger picture and want to bring change beyond the single discipline needs to adopt system thinking. There are several TED talk that delivers message to bring positive change in the world using systems thinking.
Example of Systems Thinking
Food for thought
The human body can operate as a system in holistic form, each part have a specific purpose but cannot operate in isolation.