The method behind the software
How the QSEM methodology works
QSEM, the Qualitative Systems Exploration Model, connects participatory causal mapping with transparent structural analysis. It helps people move from a shared representation of a complex problem to a more disciplined examination of the relationships and trade-offs in that representation.
From a causal map to structural analysis
A QSEM workflow begins with the factors people believe matter and the directed relationships between them. The map preserves the reasoning behind the model: what is in scope, how influences are described, and where different perspectives agree or disagree.
QSEM then provides analytical views of that structure. This creates a bridge between an accessible qualitative model and questions about connectedness, pathways, leverage, and competing goals.
The QSEM workflow
The method is intended to be iterative. Analysis is most useful when it sends people back to the model with better questions rather than ending the conversation.
- Map the system you know, including factors, boundaries, and causal directions
- Explore feedback and connected pathways in the shared structure
- Analyse structural relationships and trade-offs across nominated goals
- Discuss what the results mean, what assumptions need review, and what evidence is still needed
Inside BPE-ICR
QSEM's proprietary BPE-ICR engine—Bounded Pathway Enumeration for Impact-Control Reachability—systematically enumerates bounded causal pathways in a map. Influence is attenuated through intermediaries and accumulated across parallel routes so that the analysis can examine how structure connects factors across the defined boundary.
This is a structural lens on the relationships represented in a particular model. Its findings depend on the map, its definitions, its directionality, and the chosen boundary. They should be interpreted alongside domain knowledge, evidence, and the perspectives of the people doing the modelling.
Why transparency matters
A useful analytical result should be traceable back to the model that generated it. QSEM is designed to keep the map and the analytical reasoning visible so groups can inspect, question, and revise the structure rather than treating the output as a black box.
The method supports better-informed decisions and research conversations. It does not prove causality, predict the future, simulate a quantitative model, or guarantee that an intervention will have a particular real-world effect.
Research and provenance
The theoretical background, methodology, and origins of QSEM are described in a peer-reviewed article in System Dynamics Review. The work is led by Systems Science Lab and Dr Adam Hulme, whose focus spans systems science research, methodology development, and practical application.