Systemic Thematic Analysis: Data Structuring with Soft Systems Methodology


  • Maya Vachkova Centre for Systems Studies, University of Hull


The rise of civil society begs for a more participatory form of governance, and evaluations of State-led interventions in social life. We live in an age of globalisation, and information can be easily transmitted, but this capacity is not always leveraged for civil society voices to be effectively heard. One such case was a face-veiling ban, passed in Bulgaria in 2016 without the participation of Muslim citizens. Because of this lack of participation, I sought to interview Muslims and understand their perspectives on the face-veiling legislation. To engage different perspectives is key during the planning of an intervention, as well as throughout its evaluation. Data were collected via semi-structured discussions with participants from all the main Muslim minorities in Bulgaria and respondents were asked about their attitudes to the face-veil as well as their attitudes to its restriction.

This paper discusses a methodological innovation for data analysis: a systemic method for organising qualitative data based on the relational identification of stakeholders and their perceptions of social transformations – in this case banning the face-veil. The data analysis used a blend of two approaches - soft systems methodology (SSM), an established approach for systemic enquiry, and thematic analysis, which helps researchers analyse and interpret patterns in qualitative data. The innovation here is the use of SSM for theory-informed coding.

While my project structured the data using SSM, there is a more general methodological principle at play here: any systems approach can be used for theory-informed coding in thematic analysis. Thematic analysis is a qualitative technique free from theoretical commitments, which makes it uniquely compatible with systems approaches.