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The growing availability of digital trace data has generated unprecedented opportunities for analyzing, explaining, and predicting the dynamics of process change. While research on process organization studies theorizes about process and change, and research on process mining rigorously measures and models business processes, there has so far been limited research that measures and theorizes about process dynamics. This gap represents an opportunity for new information systems research. This research note lays the foundation for such an endeavor by demonstrating the use of process mining for diachronic analysis of process dynamics. We detail the definitions, assumptions, and mechanics of an approach that is based on representing processes as weighted, directed graphs. Using this representation, we offer a precise definition of process dynamics that focuses attention on describing and measuring changes in process structure over time. We analyze process structure over two years at four dermatology clinics. Our analysis reveals process changes that were invisible to the medical staff in the clinics. This approach offers empirical insights that are relevant to many theoretical perspectives on process dynamics. 

Using data from the audit trail of an electronic medical record system, we examine the effects of a disruption on the clinical documentation process. We use process mining to construct a network that describes the process and then we use a latent factor selection model to analyze changes to that network. Rather than attempting to discover a particular process model, our goal is to identify theory-based factors that explain change and stability in the overall pattern of actions. We conduct the analysis at two levels of granularity and we compare time periods with and without disruption. The paper contributes to current research on routine dynamics as network dy-namics by demonstrating the use of network science to predict the structure of an organizational routine. 

In research on process organization studies, the concept of multiplicity is widely used, but a fundamental confusion about what process multiplicity means persists. As a result, we miss some of the potential of this concept for understanding process dynamics and process change. In this paper, we define process multiplicity as a duality of ‘one’ and ‘many’, and we conceptualize ‘the many’ as a space of possible paths encompassed by a process. We use the notion of paths to operationalize process multiplicity and make it accessible for empirical research. When we see process as a multiplicity, process change can be understood as expanding, shifting or contracting the space of possible paths. We suggest that this concept of process multiplicity also has implications for a range of other theoretical and practical topics, including standards, standardization and flexibility as well as process replication, management and resilience.