The tracking and recording of people’s everyday activities through digital technology has fueled the explosion of data over the past couple of decades. These digital traces of human activity have proved highly profitable for companies equipped to glean meaning from such data. In the academic domain, such digital trace data have fostered a growing genre of research designs involving observational data. Such research designs have been a welcome addition to the repertoire of various scholarly disciplines–my own discipline, information systems, being among them. However, as an ever increasing amount of everyday human activity takes place in digital environments, and more data are generated as a result, a myopic focus on such data creates a significant risk of overlooking or misunderstanding the human experience. People possess beliefs, attitudes, cognitions and feelings that are not necessarily fully reflected in digital traces. As such, our scholarly efforts to understand human behavior in the realm of digital technology, risks being incomplete if we focus solely on these digital traces.

I am proud to have had the opportunity to work with Atreyi Kankanhalli (National University of Singapore), Adela Chen (Colorado State University), Dezhi Yin (University of South Florida), Andrew Burton-Jones (University of Queensland) and Susan Brown (University of Arizona) on an editorial that underscores the importance of quantitative behavioral research methods in an age where so much of the focus is on digital traces. It follows from a masterclass that we delivered to the information systems scholarly community. The editorial, which appears in the March 2025 issue of MIS Quarterly, articulates the strengths of quantitative behavioral research methods when it comes to sense-making about the human experience. I strongly encourage you to give it a read.