Understanding Human Systems (I): Attributes of System Actors
“A representation does not simplify reality by removing complexity. It simplifies interpretation by making complexity observable.”
In the previous articles we explored how organizations behave as complex human systems in constant evolution.
Technology changes.
Processes evolve.
Teams reorganize.
Priorities shift.
People learn.
Every one of those changes transforms the situation in which the system operates.
If situations continuously evolve, an obvious engineering question emerges.
How can we represent a person within a situation without reducing a complex human system to a collection of metrics or personal characteristics?
This is the challenge SAMM attempts to solve.
Rather than introducing another management theory, SAMM integrates existing knowledge into a common representation that simplifies the interpretation of complex human systems.
It does not replace psychology.
It does not replace Agile.
It does not replace organizational design.
Instead, it provides a situational observation framework capable of transforming multiple disciplines into a shared language that supports better understanding and better decisions.
Like every engineering model, simplification does not mean ignoring complexity.
It means building a representation that preserves what matters while reducing unnecessary cognitive effort.
The purpose of SAMM is therefore not to reinvent existing knowledge.
It is to integrate it.
Knowledge management.
Psychology.
Learning theory.
Organizational design.
Systems thinking.
Each discipline contributes valuable perspectives for understanding human systems.
SAMM simply brings those perspectives together into a single observational framework capable of representing complex situations in a consistent and practical way.
Representing People Within Situations
Every engineering discipline relies on representations.
Architects use blueprints.
Software engineers use architectural models.
Control systems rely on sensors.
Electrical engineers interpret signals.
The representation is never the real system.
It is a simplified view that makes interpretation possible.
SAMM follows exactly the same philosophy.
However, its representation is neither a representation of the person nor a representation of the situation alone.
A SAMM representation describes a person within a specific situation.
That distinction is fundamental.
The representation does not answer:
Who is this person?
Instead, it answers:
How is this person interacting with this situation right now?
The same individual may have completely different representations when the situation changes.
A different project.
A different team.
A different responsibility.
A different organizational context.
Because the objective has never been to describe people.
The objective is to understand situations through the people who experience them.
Every SAMM representation is therefore:
- Contextual.
- Temporal.
- Dynamic.
It represents a person at a specific moment, within a specific situation, for the purpose of interpreting how that situation is evolving.
This distinction changes the role of the representation completely.
It is not a profile.
It is not an assessment.
It is not a classification.
It is a shared representation that makes a complex situation observable.
Human Indicators as Situational Sensors
Once the objective becomes representation, another question naturally follows.
How is that representation built?
Engineering rarely attempts to understand a complex system by observing it directly.
Instead, it relies on sensors.
Temperature.
Pressure.
Voltage.
Speed.
Each sensor captures one observable aspect of the system.
Individually, they explain very little.
Together, they provide a representation that makes the system understandable.
SAMM follows exactly the same principle.
Its Human Indicators are not personality traits.
They are not classifications.
They are not assessments.
They are situational sensors.
Each indicator contributes one observable dimension that helps represent a person within a specific situation.
Only when interpreted together do they provide enough context to understand how the situation is evolving.
Rather than inventing new concepts, SAMM integrates decades of research from psychology, organizational learning, systems thinking and organizational design into a single representation.
Knowledge Level
Knowledge strongly influences how people interpret situations, recognize patterns and make decisions.
This indicator draws primarily from the Dreyfus Model of Skill Acquisition, the work of Nonaka & Takeuchi on organizational knowledge creation, and Argyris & Schön on organizational learning.
Within SAMM, Knowledge Level does not describe how much a person knows.
It represents the knowledge that is relevant for understanding and responding to the current situation.
Mindset
Two people with similar knowledge can react very differently to exactly the same situation.
Often the difference lies in their willingness to learn, adapt and experiment.
This indicator is inspired by Carol Dweck’s work on Growth Mindset and Fixed Mindset.
Within SAMM, Mindset is not considered a permanent characteristic.
It represents how the current situation influences a person’s openness to learning and change.
Learning Shape
Modern organizations require both specialization and collaboration across disciplines.
The concept of T-Shaped Professionals, introduced by IDEO and popularized by Tim Brown, represents this balance between deep expertise and broad collaboration.
SAMM uses this indicator to observe how a person expands knowledge beyond a primary specialization and contributes across domains when the situation requires it.
Frustration Tolerance
Every complex system generates uncertainty.
Pressure.
Unexpected change.
Continuous adaptation.
Understanding how those conditions affect people’s ability to continue contributing is essential for interpreting the evolution of a situation.
This indicator integrates research on resilience and emotional regulation from Albert Ellis and Richard Lazarus & Susan Folkman.
Within SAMM, it does not attempt to measure emotions.
It represents how the current situation affects the system’s ability to continue operating effectively through the individual.
Current Role
Every observation requires context.
The same situation can be experienced very differently depending on the responsibilities a person has within the system.
SAMM therefore incorporates the current organizational role as contextual information.
Its inspiration comes from organizational design approaches such as Team Topologies, where responsibilities determine both the information available and the ability to influence the system.
Within SAMM, the role does not describe the individual.
It describes the position from which the situation is experienced.
None of these indicators is meaningful in isolation.
Knowledge without context explains very little.
Mindset without responsibility provides an incomplete picture.
Role without learning says almost nothing about the evolution of the situation.
Only when these indicators are interpreted together do they produce the contextual representation that SAMM uses to simplify situational interpretation.
A Common Representation
A representation only becomes valuable when it can be shared.
Much of what organizations know remains implicit.
It exists in conversations.
Experience.
Context.
Intuition.
Every observer builds a different mental model of the same situation.
SAMM transforms those individual observations into a common representation.
Not to classify people.
Not to evaluate individuals.
But to communicate how a specific situation is reflected through the people experiencing it.
Each representation is simply a snapshot.
It represents a person within a particular situation at a particular moment.
The notation is intentionally minimal.
Each visual element represents one situational indicator.
Together they provide a compact representation that can be interpreted consistently across teams.
The notation itself is not the model.
It is simply the language that allows observations to be shared.
The value lies in the interpretation.
Not in the notation.
Observing at Human Scale
Representation also has practical limits.
As organizations grow, complexity increases much faster than our ability to understand it.
This is one of the reasons modern organizational approaches encourage small, autonomous teams.
Frameworks such as Team Topologies, LeSS, Amazon’s Two-Pizza Teams, and even Dunbar’s Number all converge toward the same principle.
Keep the system within a scale that remains observable.
SAMM adopts exactly the same philosophy.
Not because smaller teams eliminate complexity.
They do not.
Complexity is an inherent property of every human system.
Smaller teams simply keep that complexity within human observational limits.
This is also how SAMM scales.
It does not scale by observing more people simultaneously.
It scales by changing the unit of observation.
Individual.
Team.
Department.
Organization.
The object of observation never changes.
Only the observation scale does.
Learning from Representation
A representation is never the final objective.
It is the starting point for learning.
Situations generate observations.
Observations generate representations.
Representations generate hypotheses.
Hypotheses improve decisions.
Better decisions create new situations.
And every new situation produces a new representation.
Over time, patterns begin to emerge.
Not personality patterns.
Situational patterns.
SAMM does not attempt to understand people.
It seeks to understand how situations evolve within human systems in order to continuously improve decision-making.
The Contribution of SAMM
SAMM is not another personality framework.
It is not another leadership model.
It is not another organizational methodology.
SAMM provides a common representation of a person within a specific situation.
That representation integrates established knowledge from multiple disciplines into a shared language that simplifies situational interpretation.
Because understanding a complex human system is not about collecting more information.
It is about building the right representation.
A representation that allows everyone to observe the same situation, discuss it using a common language, and make better decisions together.
In SAMM, that representation never describes the person in isolation.
It always represents a person within a situation.