Socio-Technical Assessment of Complexity

TNO-ESI's socio-technical roadmap identified the need for capabilities that can help researchers and industrial partners recognize, diagnose and address socio-technical complexity in engineering challenges. The roadmap proposed a toolbox consisting of three connected elements: 1) an approach to assess socio-technical complexity, 2) a guide to select suitable methods and interventions, and 3) a monitoring capability to evaluate impact over time. In this report, we will describe the development of the first concrete step – the Socio-Technical Assessment of Complexity (STAC). Existing socio-technical and systems approaches offer rich theoretical foundations and powerful methodologies, but often require substantial effort, expertise and stakeholder engagement before value becomes visible. To reduce this barrier, we developed the STAC scan: a lightweight approach that helps project teams identify where socio-technical complexity may reside before committing to deeper analysis. STAC is not intended to replace more comprehensive methods. Its novelty lies in acting as a low-threshold entry point: it creates awareness, supports structured team discussion, and identifies where deeper sociotechnical analysis is valuable. The assessment combines systems thinking concepts, the Seven Samurai model, insights from complexity science, and selected elements from the INCOSE Complex Systems Tradecraft Guide. The result is a process that starts with team alignment on the different systems the project connects with, an individual survey to identify complexity levels in those different systems; and a collective result visualization through automated heatmaps that shows complexity hotspots, areas of disagreement within the team and potential topics requiring further investigation. The approach was iteratively developed and evaluated through multiple pilots with TNO-ESI project teams. Results show that STAC can create productive discussions in project teams beyond a narrow technical focus towards a more holistic understanding of the systems in which their interventions must ultimately operate, while remaining lightweight enough to be used within ongoing projects. This study represents the first building block of the sociotechnical toolbox and provides the foundation for future work linking diagnosed complexity patterns to appropriate socio-technical intervention methods.