Towards Routines Mining: Designing and Implementing the Argos Miner, a Design Science Artifact for Studying Routine Dynamics with Process Mining

Digital artifacts increasingly support actors in
carrying out organizational routines. These artifacts
leave digital trace data, that is, time-stamped data
about what actions actors performed. While extant
research on routines largely builds on qualitative
methods, the increasing ubiquitousness and prevalence
of trace data enable novel methodological
opportunities. However, several challenges currently
hinder the adoption of trace data in empirical research
on routines in general and their dynamics in particular.
Promising approaches such as process mining are
neither designed for nor sensitive to the concept of
routines. In this paper, we follow a design science
research approach to develop the first iteration of an
artifact, which we coin Argos Miner. This artifact is
based on process mining algorithms and overcomes
challenges inherent in adopting process mining in
routine dynamics research. It enables scholars to
capture reality in flight by analyzing routine dynamics
using a computational, mixed-methods approach.