What IS Social System Mapping?

A Social System Map is an Online, Interactive, Visual Language

It's a tool designed to:

      • Help build critical mass and momentum behind tipping points;
      • Help people within social eco-systems SEE and NAVIGATE COMPLEXITY;
      • Amplify and accelerate the system-change efforts of people who are engaged in movements and transformation networks;
      • Help network members collaborate more effectively across differences; surface and leverage the dynamic creative tensions inherent within multi-perspective networks, and navigate wisely within self-organizing human systems;
      • Increase adaptivity, resilience and (re)generativity in social eco-systems.

It has overlaps and resonances with all of these kinds of maps:

A classic cause and effect, stocks and flows

System Map

A classic

Social Network Analysis (SNA)


Asset Map


Power Analysis Map


Stakeholder Map

In fact, it's a mash-up of all of those.

But it's also





A Social System Map Grows Outward From The People

We start with people (and/or organizations, which are just collectives of people) in a dynamic Social Network Analysis (SNA) - to visualize and understand the connections among the network's ACTUAL ACTORS. People in a specific context, with a specific purpose. And unlike with an SNA, which is a snapshot of a single moment, a Social System Map tracks changes to the network structure over time.


But beyond pure network structure, we're also interested in how the different social dimensions of the network (such as identity, experience, stakeholder perspective, roles, etc. - as defined by the people in the network) are reflected in the network's patterns, to help understand the how those dynamics impact the network. We ask about and visualize whatever social differences in the network make meaningful and useful distinctions related to the network's goals.


On top of that multidimensional SNA, we layer in an Asset Map that visually represents the abundance within the community as well as identifies areas of individual or collective need. This is often called the 'offers and asks' layer. It helps network actors identify areas where our gifts can make the most difference.


From there, we include actions taking place in the network - who is working on what, what goals or challenges are they addressing, what strategies are they using, what motivations are driving their energy.


And on top of that, we connect up the network's actions with the forces in the system that the network is trying to transform.


As a Mash-Up, as a Learning Tool, and as a Collective Process - A Social System Map Behaves Differently Than Any of the Above Maps.

The more collaborative and crowd-sourced the Social System Mapping process is, the more relevant it becomes to the people on the ground, the greater the learning about systems and complexity among network members, and the more energy and agency can be liberated throughout the whole field.


But this 'ground-up' dynamic and the complexity inherent in mashing all these dimensions together means that the expectations we'd normally to bring to each of those types of maps above tend to constrain our thinking when it comes to Social System Mapping.


With Social System Mapping we loosen the boundaries of what we're doing and how we do it. We're looking less for an expert-driven conclusive analysis and more for a collective emergent synthesis. It's not a precise definition of a single moment, but a fuzzy approximation of complex dynamics - meant to increase our our collective capacity to manage within the actual complexity in the real world.


When explaining the difference between a Social System Map and any of the more clearly-defined and narrowly-focused mapping methods above, we're reminded of the Wave-Particle Duality, which tells that the tools we use to measure light determines whether we see it as a particle or a wave. A classic Social Network Analysis resonates with 'particle' in this metaphor, and a Social System Map resonates with 'wave'. We're looking at the same thing, but it's differently-knowable because we're using different tools.