The term self-organising teams was popularised in the Agile Manifesto for software development in 2001.
I think that although the authors of the Agile Manifesto considered Agile teams as complex adaptive systems, they did not explicitly mention that. As a result people interpreted the term self-organising teams completely out of context, creating confusion. Many organisations translated self-organising teams into organisations that run themselves with no other governance or management. Gradually this became a contentious point and created a lot of resistance against Agile ways of working.
The best architectures, requirements, and designs12 Agile Principles
emerge from self-organizing teams.
In the latest edition of the Scrum Guide (2020), the term self-organising teams was replaced with the term self-managing teams. This put the emphasis on the team deciding the what, when, and how of their day-to-day work.
Nevertheless, the mention of self-organising teams represented a pivotal moment in our thinking about teams. Traditionally, teams were viewed as a fixed monolithic whole with a lead at the top acting as the brain of the team. When the team did well, the lead would be glorified. But when the team failed, the discussion would be on leadership. In a similar fashion, a few star players would be glorified for the performance of the team. However, this could not be further from what is really going on.
Here, I will talk about how teams self-organise and how we can make the most of this process. But first let’s discuss how we model teams.
The illusion of the monolith
When considering a team as a monolith, the only person with real freedom is the lead or coach sitting at the top of the hierarchy. From a monolith point of view the interaction of the players in the team seem untidy.
John H. Holland in his seminal article on Complex Adaptive Systems wrote about the illusion of the monolith. He says that when we encounter a novel situation we don’t see a monolith. Instead, we build a “picture” of the situation from its individual parts. For instance, when we see a face, we treat it as a compilation of several components, such as hair, eyes, nose, mouth. Each component has different set of attributes, such as colours, textures, etc. By understanding and recombining these “building blocks” we can transfer previous experience to new situations. Instead of treating everything as a novelty. In teams, the rules the players use to interact locally are the “building blocks” that they can change and recombine.
Definition of self-organisation
Historically, there has been a lot of confusion on what self-organising teams are and do. Here, I will provide a clear definition.
Self-organisation or spontaneous order is a process where patterns and order arise at a macro level from the correlated interactions of the system’s autonomous agents at a micro level.
In order for this to happen, there needs to be sufficient internal energy available to trigger the self-organisation of the system and overcome its natural tendency toward disorder. There is no external director or plan directing this process, but rather it is a property of the system itself.
However, a precondition is that the system’s agents are fully autonomous locally with no need for external guidance. Agents follow simple rules when interacting with each other and this loose coupling creates a dynamic structure. Nevertheless, self-organisation is facilitated by external influences that “push” the system to explore a variety of emergent states, moving it eventually towards higher complexity.
For instance, in teams, an external influence (problem to solve), may trigger the emergence of hierarchical leadership. Eventually, the team settles in patterns of behaviour that can be either constructive or destructive over time or both.
A key point to stress is that the tendency to self-organise doesn’t automatically translate to something better. There is no qualitative bias in self-organisation but only spontaneous order, which might as well have negative outcomes.
How complementary interconnected opposites create self-organisation
In general, when the agents of a complex system, such as a team, lack correlated interactions, then the team moves towards chaotic behaviour (entropy). On the opposite, when the team members are too tightly coupled, then the system demonstrates rigid behaviour. Neither of these systems can self-organise.
On the other hand, self-organising teams are neither rigid, nor chaotic. In addition, self-organisation doesn’t mean lack of control but a dynamic co-existence of both constraints and freedom. Self-organising teams, like complex adaptive systems, are always at the edge of chaos but never quite there. They demonstrate complex behaviour that fluctuates in the space between order and disorder in a never-ending dance. As such, it is impossible to predict the behaviour of the system at any particular point in time. However, it is possible to predict the long-term, macro-level patterns of behaviour that it settles in, called attractors.
When order meets chaos
Edward Lorenz in his famous study of weather systems in the 60’s found unpredictability and random behaviour coexisting with pattern and order. Many other scientists have observed similar coexistence of order and disorder in deterministic chaotic systems across many different sciences.
Most interestingly, the concept of coexistence was captured by ancient Chinese philosophers long before it was observed by scientists. For instance, in Taoism, the concept of Yin and Yang symbolises the balance between two opposing but interconnected, complementary forces.
Tao engenders One,
One engenders Two,
Two engenders Three,
Three engenders the ten thousand things.
The ten thousand things carry shade
And embrace sunlight.
Shade and sunlight, yin and yang,
Breath blending into harmony.
Yin and YangFrom verse 42 of Tao Te Ching – Translated by Stephen Addiss & Stanley Lombardo
As Dr Schumacher writes in his book “Small is Beautiful” the discussion is not whether we should choose either top down controls or creative freedom. But rather how these opposing tendencies can coexist in a balanced and complementary way in organisations.
As mentioned before, if we regard an organisation as a monolith, then top down control and decision making makes sense. From that point of view, any creative freedom is regarded as a problem. However, when viewed as a complex adaptive system, the focus shifts on how to use control to enable creativity.
How bi-directional dynamics constrain self-organising teams
Before I start I would like to give a clear definition of teams.
With teams I refer to long-lived, multi-project, open-ended working groups that perform complex interconnected work. An example of this are sport teams, or product teams in business. Ideally, the size of a team shouldn’t be more than five people. But quite often we see successful teams of up to nine people. However, the rule of thumb is to err towards the smaller size. This is because smaller teams have less communication overhead with more actively engaged team members.
Here I explained how teams behave as complex adaptive systems that are non-linear, and self-organising. In fact, Goldstein mentions that nonlinearity is a requirement for self-organisation and the development of novel patterns.
Nonlinearity means that there are circular causal relationships between the team as a whole and its members. The result of this is that teams demonstrate self-organising tendencies, which lead to emergent behaviours at a global level. Subsequently, the emergent behaviour of teams cannot be explained by adding up individuals behaviour in a linear fashion.
Instead the focus should be on analysing the bi-directional nonlinear dynamics that are at play and constrain the behavioural patterns of self-organising teams.
There are three levels of nonlinear dynamics.
Contextual Dynamics or Environment
The contextual dynamics affect significantly the self-organising patterns of teams. But what do I mean by contextual dynamics?
Teams do not exist in a vacuum. They are open systems that coevolve with their environment. Let’s take the example of a college basketball team that competes regionally. The team has access to a limited pool of talent, defined by the existing level of opportunities and competition in their area. For instance, other colleges may be competing for talent in the same region, making it hard to find good players.
Similarly in business, the availability of skills, tools, and talent, or the culture and strategy of the organisation, are all variables that constrain the self-organising patterns of teams. Therefore, the environment in which teams operate, constrain the available space of potential emergent patterns.
At a local level, there are simple rules or principles that define the two-way interactions and cooperative behaviour of team members. It is these interactions that enable self-organisation and create emergent patterns at a global team level.
For instance, in basketball, each player interacts with their nearest teammates and opponents by following simple rules. At any given moment they process a number of local variables, such as position, velocity, and overall movement of other players, continuously adapting to each other. The principles of play they follow act both as constraints and coordination mechanisms. At a global level this process of self-organisation looks like an ongoing dance of patterns.
When a group of people comes together for the first time, each member brings their own mental model shaped on their values, knowledge and experience. If the team members are able to find common ground and create a shared mental model, then they will be able to establish trust, communication, common principles, and adapt in an interdependent manner. If not, then team members will struggle to interpret the information they receive from their teammates, will not be able to anticipate their actions, and collectively will move towards disorder. Hence, the job of a coach or team lead is to create this shared understanding and rules of interaction.
At a global level, we see the overall behaviour and performance of the team as a collective.
In sports, usually a coach sets up a framework or game play with specific principles of play, tactics, and goals for sub-phases of play. These variables constrain the behaviour of players. However, this framework and tactics are not prescriptive but rather conditional rules that players learn through practice and provide them options for action. For instance, if your teammate is at the post with no-one guarding him, then pass him the ball.
Nevertheless, during a game, players may still interact locally in an unpredictable way, which was not part of the intended tactics but still within the wider framework of play. The key point here is that any top-down game tactics shouldn’t be executed in a rigid, prescriptive, and predictable way. The goal of the strategic framework at a global level is to constrain the local behaviours while allowing players as much freedom as possible during play.
Constrains enable the self-organisation of teams, while allowing the freedom to team members to interact on how they think is best to complete the tasks. As I mention in a previous article, in order to improvise you need to have a baseline structure on which to improvise on.
Enabling self-organising teams
Joao Ribeiro et al (2019) in their article “Exploiting bi-directional self-organising tendencies in Team Sports” discuss the constant interplay between both global-to-local and local-to-global dynamics in shaping system behaviours. They stress out that traditional coaching methods are too top-down and prescriptive, failing to harness the bi-directional influence that local dynamics have on the game strategy.
Furthermore, they point out how the constraints at several different levels (local, global, contextual) influence the self-organisation of sport teams. Specifically, they claim that the game model is more the result of a bottom-up process rather than top-down, due to the interactions of constraints at different levels. For instance, the ideas of the coach, the players’ capabilities, the tactics, the budget, and other constraints define the game model.
In business, project management methodologies, such as Critical Chain, and agile frameworks, such as Scrum and Kanban, use the theory of constrains as their core philosophy. In Scrum there are timeboxes that limit how much time the team spends on specific events or how much work they commit to. While in Kanban, there are work-in-progress limits that constrain the amount of work at any given stage. In both Scrum and Kanban, constraints improve the workflow through the system, enabling the self-organisation of the teams.
Developing Intelligent Performers
To enable self-organisation, coaches should help players increase their perception of possible actions at any given moment, through manipulation of known constraints. For example, when a coach sets up a principle that the ball needs to move through the left side of the court, the players have the freedom to explore several potential actions that enable this principle. This will possibly lead to successful team outcomes. As such, Joao Ribeiro et al (2019) suggest the establishment of specialised player development programs along with practical frameworks for breaking down team training in focused sub-phases of play. This will positively influence the performance of self-organising teams.
Furthermore, they mention that during a game, new patterns of play may emerge from local interactions as players quickly adapt their behaviours to constantly changing opponent tactics. So, learning through continuous experimentation, both during competition and practice, is key for developing intelligent players.
Intelligence refers to their ability to be both rational and creative when processing information while using their physical, perceptual and emotional skills at the same time. It also means being able to sense and respond to challenges in the moment while reshaping their rules for interaction. This has become a central aim in modern Physical Education across the world.
Ultimately, the goal is to have intelligent performers who seek individualised solutions to challenges through a creative learning process. Coaches and team leaders need to create a learning environment that enables continuous improvement. Through this process, self-organising teams will be attracted in the long-term towards preferred, stable states of collective order (attractors). This means that players will learn to organise themselves in ways that are desirable and bring the expected results. But this is a dynamic process, with teams eventually settling in repeated patterns that work for them.
The difference between flocks of birds and self-organising teams is that humans have the unique ability to see the whole. We have the ability to understand the constraints at play and use them as levers to influence the self-organisation of the group. This is quite different from central planning and trying to play God.
But although we may not be Gods we have the unique ability compared to all other species to use second-order thinking and understand self-organising teams at a deeper level.