Should we use NVivo or Excel for qualitative data analysis?

Coding is now a pervasive technique in qualitative data analysis, whether descriptive or theoretical, done manually by highlighting or rearranging text, or digitally using word processors or other software. However, coding relies on the researcher’s reflection and does not think for itself. I compare two types of software here: one built for coding qualitative data and another originally developed for numerical calculations. Which offers more scientific freedom, and what biases come with each? NVivo excels at organising and visualising data within a single file, enabling researchers to view coded sections in context. Its flexibility supports various inferences – inductive, abductive, and deductive – and allows for critical research evaluations. It also makes it easy to create samples. In contrast, Excel is lightweight, easily transferable, compatible with other software, and better at maintaining data anonymity. Its lack of data import reduces hardware demands and errors, while filtering enhances triangulation and quantification. Excel’s cell-based data reformulation aids narrative analysis. Lastly, neither tool proved clearly superior for data immersion (‘Coding Fetishism’) or transitioning to writing.