Survey work, and more broadly, employee research, has historically been informed almost exclusively by quantitative data. Across work within organizations, applied research, and theoretical research, the use of quantitative methods overwhelm that of qualitative methods. Said another way, we love our surveys and rating scales. This is evident not just in the way that practitioners gather and analyze data in organizations, but also the journal articles produced by academics, and the training graduate students receive.
Quantitative data and methods provide rigor and insight that are crucial to driving change within organizations at scale, but are not enough. As organizations become more complex, the questions we ask and the data we use to address those questions also become more complex. We might easily gather if employees feel positive or negative on a particular topic, or if those opinions have improved or declined, but often we are missing the all important ‘why.’ Qualitative data, such as text comments, blog posts, passive data across social media, etc. provide deep description of nuance needed to understand the complexity of the answers to the questions we ask. If tools and resources are rated negatively on a survey, open text comments can tell us what tools are lacking, or what additional resources people need, ultimately making the results more insightful and actionable.