Process Analytics -- Data-driven Business Process Management

TL;DR

This paper broadens the understanding of data-driven business process analysis by integrating organizational and human factors, emphasizing a socio-technical perspective beyond technical process mining methods.

Contribution

It introduces the concept of process analytics, combining technical analysis with organizational and stakeholder considerations, supported by a real-world case study.

Findings

Highlights the importance of socio-technical factors in process analysis

Contrasts traditional process mining with a broader process analytics perspective

Provides insights from a large company's implementation of data-driven process analysis

Abstract

Data-driven analysis of business processes has a long tradition in research. However, recently the term of process mining is mostly used when referring to data-driven process analysis. As a consequence, awareness for the many facets of process analysis is decreasing. In particular, while an increasing focus is put onto technical aspects of the analysis, human and organisational concerns remain under the radar. Following the socio-technical perspective of information systems research, we propose a new perspective onto data-driven process analysis that combines the process of analysis with the organisation and its stakeholders. This paper conceptualises the term process analytics and its various dimensions by following both an inductive and deductive approach. The results are discussed by contrasting them to a real-life case study from a large company implementing data-driven process analysis and automation.