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InFocus

‘Systems Thinking’: a 21st century skill?

CHRIS WHIPP
discusses a way of thinking that
cannot be taught or learnt
intellectually, but which has to be
tried and learnt experientially –
and played as a game

ON 6th August 1991, the world was changed forever when the world Wide Web is officially credited with coming into existence and the human race took a huge step towards becoming truly interconnected. After 350 years of developing Newtonian scientific thought and method, science opened for us Pandora’s box and committed the human race to playing, what has come to be known as “The Infinite Game” – a game with fundamentally different rules that we are currently struggling to understand. It didn’t happen overnight. The modern seeds were set in the 1960s with multidisciplinary research that led to the development of the “new” sciences, particularly complexity science. However, “Systems Theory” and “Systems Thinking” are represented widely within nature and have also been researched for more than 2,500 years within the Buddhist philosophical tradition. The advantage that we have as a profession is that rather than having to learn the game from the beginning, we can use the systems thinking we already use daily within our clinical practice and just learn what we need to apply the bits of it that are useful to our businesses and our lives. It’s also not about re-inventing the wheel – our scientific thinking is fine in many situations; it’s just about developing an additional set of skills for those situations where they may be useful (Figure 1). Complex Adaptive Systems (CASs) are just that, they are complex (Figure 2) and made up of agents that are independent, that learn and develop. Science works best with simple, closed systems, hence the reductionist approach and the focus on parts, whereas systems thinking works best with open systems and focuses on the relationships between those parts. One does not replace the other: they complement each other perfectly and a good rule of thumb is to use linear scientific methods if you can and systemic methods when these don’t work.

The infinite game

Systems thinking has certain basic concepts, which we will discuss briefly here, that differ significantly from those that apply within traditional science. It has gained the name of the infinite game partly to reflect the difficulty of defining a system from a reductionist (scientific) perspective and to give voice to the concept that you can’t afford to take it too seriously. Conceptually, one of the biggest problems is defining the boundary of the system, how do you draw a boundary (and control something) where the number of variables is huge, the relationships unfathomable and the system unmanageable. We all like to think we are in control but in a truly interconnected world we aren’t; the massive increase in mental wellness problems within western society in the last 50 years reflects in part our struggle with this loss of control/predictability. That we should approach such a serious situation in the same way as we would approach a game may seem counterintuitive, but by accepting we cannot be in total control, focusing on the process (game), playing it to the best of our abilities, reducing our attachment to outcomes we can’t control anyway and not clinging to elusive concepts of what might be right or wrong (when we can no longer possibly know), we can navigate the choppy waters and perhaps even enjoy it. All businesses are currently struggling with these changes as they move from the relative safety of the past to the challenges of an interconnected world (Figure 3). Vets have a unique advantage here in that we are already familiar with the principles from our work: a cat is as much an open CAS as a cow or a veterinary practice and the following systems concepts will probably be familiar.

Self-organisation

A critical concept of CASs is that the members of the system are self-organised and therefore responsible for their actions. This leads to a significant shift in power as has been seen in the demise of various repressive regimes in the last 20 years or so facilitated by easier communication and the internet.

Homoeostasis

Systems seek to maintain the status quo whether it is the RCVS maintaining the regulatory environment or a dog maintaining its temperature. Whilst humans frequently crave change, we also usually resist change and systemic resistance to change should always be recognised and addressed. Telling somebody to do something and getting it done are two quite different things (Figure 1).

Never change one thing

Science aims to work within small closed systems where cause and effect are linear. This is not how things are in CASs. You never change just one thing, the entire system will be affected and, equally important, it takes time for those effects to be seen (e.g. giving propofol and seeing the effects)

Feedback

We recognise positive and negative feedback loops to be central to life itself and they are central to systems thinking. By paying attention to the relationships within the system and the feedback loops that exist, it is possible to identify leverage points, key points where relatively small actions can have big effects. The recent UK riots demonstrate a number of systems
characteristics, including positive feedback loops, emergence and the law of unintended consequence.

Emergence

One of the key characteristics of CASs is that they demonstrate emergence; emergence is “the arising of novel and coherent structures, patterns and properties during the process of selforganisation in complex systems” or, to put it another way, things arise out of the development of the system.

Law of unintended consequence

Unintended consequences will always occur and when working with CASs it is necessary to reframe the western preoccupation with right/wrong and success/failure. The critical scientific method frequently seeks out failure; this does not work with systems where the complexity and uncertainty quickly exceed our human cognitive capacity and there is a need to embrace core positive approaches.

Simple rules

The key to working with complex systems is to develop sets of simple rules that guide actions irrespective of how complex the situation is. For example, a flock of 10,000 roosting starlings might work to just three rules:

  1. 1. Fly towards the centre of the flock;
  2. 2. Match your speed to those around you;
  3. 3. Don’t fly into anybody (www.youtube.com/watch?v=gdQgoN…l1g).

Systems thinking cannot be taught or learnt intellectually, you have to play the game and learn experientially. If anyone wants to know more, I am quite happy to organise a 1:1 or a webinar. Email Christopherwhipp@aol.com.

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