On Mining Work, Workers and Workaround

Recent years have witnessed the emergence of sophisticated techniques for discovering work processes under the ‘process mining’ title. Traditional process mining focused on discovering the order of activities as executed by multiple resources in a single process. However, processes do not exist in isolation and together make up a broader working sphere of resources. New forms of process mining have emerged that provide broader insights into the resource perspective of process mining. Coupled with new data sources, this brings opportunities in terms of (1) capturing previously unrecorded work activities, (2) exposing relations between work processes, and (3) navigating between different levels of data granularity. In this talk, I will discuss such opportunities, touching upon the use of process mining for personal process analytics, discovering workarounds from event data, and provide recommendations for accurately recording the behaviour of workers.

Iris Beerepoot is an Assistant Professor at Utrecht University, where she also completed her PhD. Her research takes place in the field of Process Science and revolves around discovering how people work in organisations. Her specific interest is in the aspects of processes that are typically not included in the event data used for process mining, for example, the use of workarounds. The topic of her PhD thesis was aimed at discovering how these workarounds may serve as valuable indicators for processes that need improving. Generally, she employs a resource-centric perspective on processes, looking beyond single processes and taking contextual factors into account.