The importance of the context
One of the most practical learnings of systems theory is that structures influence behaviour. We can consider structures as being whatever influences our decisions. We can refer to the procedures, rules, manuals of operation, the database with one type of inputs and formats and not others, instructions about how to make reports and the kind of information they contain, and so on. Also, the infrastructure, the hardware, the working space or the logistics. Even all those informal or unwritten rules, what we call the company culture, the history, the experience. All are conditioning people to do things one way and not another.
In our day-to-day lives, structures influence our choices. Working in a hierarchical or bureaucratic company will limit our opinions and ideas, or being paid with a substantial individual bonus will discourage our collaborative decisions. In contrast, a flat organisation or a balance between individual and team rewards will stimulate us to act differently.
If we want to change the behaviour in an organisation, we must avoid simplistic solutions focused on direct impact and control. Establishing policies focused directly and exclusively on the goal or, even worse, impositions through direct coercion or external motivation, usually economic, does not work.
We must identify the causes that motivate certain behaviours and seek to change them. A catalyst can stimulate proactivity. Overcoming the limits and constraints can liberate people’s energy. Creating space can let others lead.
Undoubtedly, a change in the rules will change behaviour immediately and more effectively than if we try to influence it directly.
The Game
An instructive game shows this subject very visually, and it’s worth knowing about; it is the "Icosystem Game".
Icosystem uses The Game to illustrate, among others, the following points:
- Simple rules of individual behaviour can lead to surprisingly consistent system-level results.
- Small changes in rules or in the way they are applied can have a significant impact on the aggregate results.
What is swarm intelligence?
Swarm Intelligence (SI) ‘is the property of a system whereby the collective behaviours of (unsophisticated) agents interacting locally with their environment cause coherent functional global patterns to emerge.’
The abilities of such systems appear to transcend the capabilities of the constituent individuals. It responds to the following characteristics:
- Flexible: responding to internal perturbations and external challenges.
- Robust: completing tasks even if some individuals fail.
- Decentralised: with no central control or controller.
- Self-organised: paths to solutions are emergent rather than predefined.
Conclusion
The performance of an organisation can be dramatically increased by collective intelligence. Especially in volatile, uncertain, complex and ambiguous (VUCA) environments, being agile and adaptive is a must. To attain distributed functioning, designing structures that foster collaborative behaviours will be necessary. Nevertheless, self-coordination will first require individuals to know what to do. Then, they have to be aligned with organisational strategy. Finally, they need to be empowered to participate and contribute.
Therefore, the Road Map for self-coordination will include:
1. BEING AUTONOMOUS
The first level of collective intelligence features autonomy. Individuals have to reduce the level of uncertainty through acquiring, understanding and interchanging knowledge.
2. BEING COMMITTED
The second level is the emergence of cohesion. Individuals congregate and become teams through social interactions through processes of integration.
3. BEING DISTRIBUTED
The third level is distributed functioning. Teams are finally ready for self-coordination when they have space to perform. They attain a level of awareness of themselves as a new entity.
References
- Bonabeau, E., Dorigo, M., & Theraulaz, G. (1999). Swarm Intelligence: From Natural to Artificial Systems. New York: Oxford University Press. (Amazon)
- Zamora Enciso, R. (2018). Cooplexity: A model of collaboration in complexity for management in times of uncertainty and change (Third edit). Barcelona: Lulu.com. (Amazon)
The importance of the context
One of the most practical learnings of systems theory is that structures influence behaviour. We can consider structures as being whatever influences our decisions. We can refer to the procedures, rules, manuals of operation, the database with one type of inputs and formats and not others, instructions about how to make reports and the kind of information they contain, and so on. Also, the infrastructure, the hardware, the working space or the logistics. Even all those informal or unwritten rules, what we call the company culture, the history, the experience. All are conditioning people to do things one way and not another.
In our day-to-day lives, structures influence our choices. Working in a hierarchical or bureaucratic company will limit our opinions and ideas, or being paid with a substantial individual bonus will discourage our collaborative decisions. In contrast, a flat organisation or a balance between individual and team rewards will stimulate us to act differently.
If we want to change the behaviour in an organisation, we must avoid simplistic solutions focused on direct impact and control. Establishing policies focused directly and exclusively on the goal or, even worse, impositions through direct coercion or external motivation, usually economic, does not work.
We must identify the causes that motivate certain behaviours and seek to change them. A catalyst can stimulate proactivity. Overcoming the limits and constraints can liberate people’s energy. Creating space can let others lead.
Undoubtedly, a change in the rules will change behaviour immediately and more effectively than if we try to influence it directly.
The Game
An instructive game shows this subject very visually, and it’s worth knowing about; it is the “Icosystem Game“.
Icosystem uses The Game to illustrate, among others, the following points:
- Simple rules of individual behaviour can lead to surprisingly consistent system-level results.
- Small changes in rules or in the way they are applied can have a significant impact on the aggregate results.
What is swarm intelligence?
Swarm Intelligence (SI) ‘is the property of a system whereby the collective behaviours of (unsophisticated) agents interacting locally with their environment cause coherent functional global patterns to emerge.’
The abilities of such systems appear to transcend the capabilities of the constituent individuals. It responds to the following characteristics:
- Flexible: responding to internal perturbations and external challenges.
- Robust: completing tasks even if some individuals fail.
- Decentralised: with no central control or controller.
- Self-organised: paths to solutions are emergent rather than predefined.
Conclusion
The performance of an organisation can be dramatically increased by collective intelligence. Especially in volatile, uncertain, complex and ambiguous (VUCA) environments, being agile and adaptive is a must. To attain distributed functioning, designing structures that foster collaborative behaviours will be necessary. Nevertheless, self-coordination will first require individuals to know what to do. Then, they have to be aligned with organisational strategy. Finally, they need to be empowered to participate and contribute.
Therefore, the Road Map for self-coordination will include:
1. BEING AUTONOMOUS
The first level of collective intelligence features autonomy. Individuals have to reduce the level of uncertainty through acquiring, understanding and interchanging knowledge.
2. BEING COMMITTED
The second level is the emergence of cohesion. Individuals congregate and become teams through social interactions through processes of integration.
3. BEING DISTRIBUTED
The third level is distributed functioning. Teams are finally ready for self-coordination when they have space to perform. They attain a level of awareness of themselves as a new entity.
References
- Bonabeau, E., Dorigo, M., & Theraulaz, G. (1999). Swarm Intelligence: From Natural to Artificial Systems. New York: Oxford University Press. (Amazon)
- Zamora Enciso, R. (2018). Cooplexity: A model of collaboration in complexity for management in times of uncertainty and change (Third edit). Barcelona: Lulu.com. (Amazon)
