Making Team Dynamics Visible: How To Map Collaboration Using Valency Matrix
Most teams are built with structure in mind. Roles are defined, interfaces drawn, and responsibilities put in place. But structure alone does not ensure success. What happens between the boxes and lines is often what defines the outcome. This is the domain of team dynamics: the interactions that shape how work actually flows, where decisions are made, and how problems are solved.
In technical environments, we model systems with care. We define interfaces, track dependencies, and expect consistent behavior according to a set of requirements. The social architecture of a team, however, often remains invisible until it causes friction, misalignment, or slowdowns.
Once I experimented with a simple method to make team dynamics visible. I used the concept of valency, borrowed from chemistry, to measure how strongly team members are connected in their day-to-day collaboration which led to very insightful results.
This article outlines what team dynamics really means, explains how valency measurement works in this context, and shows what we learned by applying this approach.
1. What Are Team Dynamics?
Team dynamics refer to the real patterns of interaction between people working together. They describe who talks to whom, how information moves, where decisions are influenced, and which relationships carry energy, friction, or silence.
An organizational chart shows formal roles, while team dynamics reveal the real flows of interaction. Not all of these are aligned with the structure, as intended.
Good dynamics support shared ownership, rapid feedback, and trust. Poor dynamics introduce friction, uncertainty, and isolation. These patterns evolve over time and are shaped by personalities, history, unspoken norms, and shifting expectations.
Unlike documented processes or job titles, dynamics develop organically. They often remain unmeasured and unspoken, yet they shape the behavior of the team more than any official chart.
In engineering terms, dynamics are like system behavior during runtime. Even with a defined architecture and a bunch of simulations, the operation of a real system often reveals patterns and interactions that could not be predicted.
2. What Is Valency in a Team Context?
In chemistry, valency describes how many bonds an atom can form with others. It defines the structure and behavior of molecules.
In a team, valency can be used as a way to measure the strength of collaboration between individuals.
A strong valency indicates regular, high-quality, mutual collaboration. A weak valency indicates limited, low-impact, or one-sided interaction.
This framing helps us move from vague impressions to measurable observations. Instead of asking, "How is the team doing?" we ask, "Who is working with whom, and how strongly?"
3. The Valency Mapping Method
We applied a structured process to map collaboration inside a eight-person cross-functional team.
Step 1: Define the Scope
We selected a specific team with clear shared goals.
Step 2: Collect Pairwise Ratings
Each team member rated their collaboration with every other member using the question:
"How strongly do you collaborate with [Person X] on a weekly basis?"
Scale:
0 = No interaction
1 = Occasional or transactional
2 = Regular and relevant
3 = Ongoing, high-bandwidth co-creation
These scores were subjective by design, intended to capture perceived collaboration rather than just formal coordination points.
Step 3: Build the Matrix
We created a matrix where each cell captured how one person rated their collaboration with another, resulting in an asymmetric structure that reflected differing views of the same relationship.
Step 4: Visualize the Collaboration
We used two views:
A heat map showing collaboration strength across the matrix.
A network graph showing nodes (people), edge strength (valency), and node centrality (collaboration load).
Code for visualization available on GitHub
4. What We Learned
The visualizations revealed things we had not seen in plannings or retros.
Some people were central connectors, with strong ties across the team. Others were more isolated than expected. Some relationships appeared balanced. Others were asymmetric, with one person feeling strong alignment and the other feeling almost none.
One surprising weak bond was between the architect and the test engineer. This gap had not surfaced in planning meetings, but it showed up clearly in the data.
A newly onboarded engineer had only one strong connection. This created risk, both for that person and for the system around them.
By turning perceptions into a visible structure, we were able to have new kinds of conversations that invited curiosity and openness, without triggering defensiveness or judgment. The visuals provided a shared reference point that helped us reflect together on what collaboration actually looked like.
5. From Insight to Action
The map became a conversation starter that naturally led to a series of concrete changes in how the team collaborated.
We colocated people who had low valency but shared dependencies. In several cases, even a few days of working side by side helped establish trust and context.
We reworked onboarding to encourage broader connection. New joiners were guided to build at least three meaningful bonds in their first month.
We also followed up on asymmetric ratings, which often revealed mismatched expectations. One person believed they were collaborating well because they shared regular status updates, while the other felt excluded from meaningful discussion or decision-making. This awareness helped both sides adjust their approach.
Over time, valency mapping became part of our regular team development process, supporting ongoing reflection and adjustment.
6. Outlook: More Topics about Team leadership
This article is the first in a series exploring how teams actually work, and how we can lead and shape them more effectively. In future posts I will examine methods for improving collaboration, strengthening shared purpose, designing roles that grow with the organization, and handling uncertainty in fast-moving environments.
If you work with people who design and build complex systems, and you want to approach the human side of that work with more clarity and structure, stay tuned.