{"id":31395,"date":"2025-10-15T10:13:53","date_gmt":"2025-10-15T10:13:53","guid":{"rendered":"https:\/\/leadersinsport.com\/performance-institute\/?post_type=article&p=31395"},"modified":"2026-04-02T16:21:07","modified_gmt":"2026-04-02T15:21:07","slug":"what-are-complex-environments-and-what-are-their-implications-for-leaders","status":"publish","type":"article","link":"https:\/\/leadersinsport.com\/performance-institute\/articles\/what-are-complex-environments-and-what-are-their-implications-for-leaders\/","title":{"rendered":"What Are Complex Environments and What Are their Implications for Leaders?"},"content":{"rendered":"\n\n
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\n 15 Oct 2025 <\/p>\n \t\t\t\t\t\t\n\t\t\t\t\t\t\t<\/span>Articles<\/a>\n\n\t\t\t\t\t\t

What Are Complex Environments and What Are their Implications for Leaders?<\/h1>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\n \n\t\t\t<\/div>\n\t\t<\/div>\n\n\t<\/div>\n<\/div>\n
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In the first part of a miniseries exploring complexity in sport, Everton\u2019s Head of Sport Science Jack Nayler explains how a watershed moment transformed his approach to his work.<\/p>\n \n \n \n

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By Jack Nayler<\/h6>\n
I first stumbled across the concept of complexity a little over ten years ago and it was a watershed moment in my career.<\/h6>\n

However, in a truly complex manner, it was the combination of my lived experience to that point, my educational background and the reading I was doing in my own time around the subject that led to my appreciation of complexity and its implications for those concerned with sporting performance.<\/p>\n

Over the course of four articles, I want to explain how I see the world of elite sport, the complex system at its heart, and the most effective way I currently see of managing performance within that context.<\/p>\n

I will delve into the implications for sports and the operations within teams before outlining what this all means for leaders in this space.<\/p>\n

But first, I want define what a complex system actually is and set out its characteristics.<\/p>\n

Learning from failure<\/strong><\/p>\n

My real understanding came, inevitably, in learning from failure.<\/p>\n

The white paper by the late Dr Richard Cook of the University of Chicago entitled How Complex Systems Fail<\/a> was instrumental in helping me to understand the ramifications of complexity on the undertaking of performance in a sports setting.<\/p>\n

Dr Cook was an anaesthetist and simultaneously and internationally respected researcher. His short treatise is regarded as one of the most influential works in the field of patient medical safety. It was this understanding of how systems fail that brought together everything else I had seen and learnt and began to change the way I saw performance management in professional sports.<\/p>\n

Around this time, I was challenged by a friend in the industry to put together my thoughts on building a performance department for a sports team. I found it challenging just to make an org chart and list positions without giving the background and rationale for why and how the department existed in that structure as well as its philosophical construct. This exercise of transferring ideas from my head on to paper forced me to critically confront my assumptions and crystallised my thoughts on how I believe we need to operate in the complex environment of elite professional team sports (specifically football as this has been my professional experience).<\/p>\n

So, what do we mean by complex? <\/strong><\/p>\n

Dave Snowden is a researcher in the field of knowledge management and is the creator of the Cynefin Framework<\/a> that helps us to make sense of the different types of environments in which we operate.<\/p>\n

\u2018Cynefin\u2019, which is pronounced \u2018ku-nev<\/em>-in\u2019, is a Welsh word explaining there are multiple factors in our environment and our experience that influence us in ways we can never understand.<\/p>\n

The model contains five domains, all of which can exist at any given moment, and we move between them:<\/p>\n

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Source: HBR<\/p><\/div>\n

The clear domain has obvious cause and effect and well-established best practice.<\/strong> There are many examples of this in elite sports, for instance, data hygiene when downloading and analysing GPS data or packing medical equipment for an away match.<\/p>\n

In the complicated domain, there are correct answers to problems, but they may take some expertise or understanding to deliver and there are governing constraints within which the answer will lie. <\/strong><\/p>\n

An example from sport would be developing a fuelling strategy for a player in a match. We need learned expertise in nutrition and we need to do some analysis on the demands that player faces in match play, as well as understand how their physiology responds to those demands. There are then governing constraints (carbohydrate is the main fuel source in performance) but within those constraints, the solution will be different depending on the sport and the athlete, but the solution can be determined.<\/p>\n

I find the easiest way to consider the difference between a complicated and a complex environment is by using the analogy of a car.<\/p>\n

A car is an extremely complicated piece of technology. The first practical automobile was invented by Karl Benz in 1885 and had several hundred components. The modern family car by comparison contains over 30,000 parts on average.<\/p>\n

Despite this huge number of component parts, should one of them fail and the car stop working, the defective component can be replaced and the performance of the car restored. The performance of the car in this case is its ability to move with you on board and there is a linear process from depressing your foot on the accelerator to make that car move. A skilled technician should be able to completely take the car apart, rebuild it and restore its performance.<\/p>\n

Take that same car and ask it to transport you across a city such as London and it enters a complex system where the performance of the car (the time it takes to transport you from point A to point B) is no longer determined by the car itself (it would make little difference if you drove a Ferrari or a Fiat), but in the interaction of the inter-connected parts that make up the complex system. These include the status of the driver (in how much of a hurry they are and their relative stress level), the other cars and their respective drivers, traffic signals, roadworks, cyclists, pedestrians, emergency services, major events going on that day, the time of day and the weather etc. There are many other potential components to the system, not all of which are obvious when sat in the car itself.<\/p>\n

The performance of the car (how quickly it reaches its destination) will emerge from the interaction of all these components and each one is concurrently performing at the centre of their own complex system.<\/p>\n

So, the first thing to know is that in a complex environment, performance emerges from between the components an in inter-dependent manner, and not from the summation of the performance of each component in isolation.<\/strong><\/p>\n

The next part to understand about complexity is that it is fractal. Fractals are geometric shapes that contain the same detailed structure at ever smaller scales. This means that complex systems exist at smaller and larger scales and nest within one another. They simultaneously are affected by the scale below and affect the scale above.<\/p>\n

Below the scale of our car, the driver is their own complex system, and their performance is determined by (amongst other things) their genetics, upbringing, education, wellbeing, as well as how well they have slept last night, what they had for breakfast and whether they are running late or not.<\/p>\n

At a larger scale, the performance of the traffic system designed by city planners is affected by the performance of all the cars on the roads.<\/p>\n

The person closest to the action in the complex system has the greatest chance to affect it at any given moment, in this example it is the driver of the car. Each decision they make will create a new reality and alter the course of the complex system (for reference see the film Sliding Doors). The decision to put your foot down to get through an amber light rather than braking in anticipation of a red light will affect the course of the complex system and other components within it.<\/p>\n

This person closest to the action may have the greatest chance to influence the performance of the system, but they also have the narrowest focus and least ability to see the big picture. This is where external information can help inform their decision (SatNav, Waze or radio traffic reports). Ultimately though, it remains their decision.<\/p>\n

Because performance emerges in real time as we navigate through the city and react to what we encounter in front of us, we cannot with complete accuracy predict what will happen in the future as we set out on the journey, or how good our performance (the journey time) will be.<\/p>\n

All decisions taken by the driver therefore contain an element of risk and are (hopefully educated) gambles. These decisions are being made on a moment-by-moment basis are determined in part by what has already happened and will influence what is to come.<\/p>\n

As all the components in the system are simultaneously operating in their own individual complex system, agreement between them isn\u2019t perfect. Thus, complex systems are never perfect, they operate in a sub-optimal mode. No route across London provides a perfect path where you will be able to drive without braking or even coming to a stop. The challenge is that we cannot know exactly where the imperfections will lie.<\/p>\n

Once we have finished our journey and the performance is determined, the impact of all our decisions is laid bare. With hindsight our choices take on a sequential profile and we can fall victim to a narrative fallacy, where each decision makes sense in context of what came after it. What we need to remember is that at the time we made each decision, we were blind to the future and couldn\u2019t know exactly the outcome. That left turn that led to roadworks suddenly becomes a disaster that caused all our problems, whilst the decision to cut through the backstreets, a moment of genius. However, we will never know the alternate realities of the other options we could have selected.<\/p>\n

The last part of complex systems I wish to convey is that the more we try to control the system, the more we leave ourselves open to system errors adversely affecting our progress in the long-term. <\/strong><\/p>\n

By control I mean to attempt to force or determine an outcome. The decision to jump a red light or speed along a section of road can lead to being pulled over by the police, which will cause a delay that greatly outweighs the seconds saved through our actions. The right way to operate in the system will emerge by experimentation, trying different routes, times of day or even modes of transport to complete the journey.<\/p>\n

To bring us out of an over-extended analogy and back into the real world I want to emphasise that we should not be fatalistic about complexity. I don\u2019t want to come across like the system will determine the outcome, regardless of what we do to affect it. I believe we are an integral component in any system with the chance to affect its direction and outcomes (just remember they might not be perfect).<\/p>\n

If we are also able to step back and appreciate the interaction between systems at larger and smaller scales than that in which we are currently operating, we can be very powerful.<\/p>\n

Chaos and Confusion<\/strong><\/p>\n

The final two domains in the Cynefin framework are Chaos and Confusion. Chaos is where there are no clear rules or cause and effect at all, even with hindsight, and it is better to act now and think later, shooting more from the hip.<\/p>\n

Confusion is the dark centre of the framework, when you aren\u2019t sure which of the other four domains you are currently in.<\/p>\n

Most of the time in elite sports I believe we deal with complexity and thus I think it is the most important to try and understand. In the next two parts I will go on to discuss the implications of operating in this domain for sporting organisations, and what that means for leaders in this space.<\/p>\n

Summary<\/strong><\/p>\n