Abstract:
Process mining is becoming a popular big data analytics and artificial intelligence
tool in business today as a result of technological advancements being accelerated
by digitalization. Fast process adaptation to keep up with the pace of the quickly
evolving business environment, however, is a significant challenge for the majority
of organisations. Process mining has the potential to make big data-driven insights
accessible, transforming data mining into a process mining capability therefore
raising the value of process mining. Additionally, process mining insights give
businesses the ability to improve and optimise processes to gain a competitive
advantage. However, the value of process mining in organisational strategic
decision-making is underexplored; this study aimed to fill this research gap.
A qualitative research design was adopted to explore new insights and answer three
research questions. This study put forward the exploratory design using the
philosophy of interpretivism and the inductive approach to developing new theory.
Semi-structured interviews with eleven participants who have implemented process
mining were conducted to gain further insights into this phenomenon.
With respect to the value of process mining this research found benefits that include
better decision making, cost savings, business process transparency and
enhancement of business processes through automation. However, organisations
still need to rely on human intelligence and expert intelligence to get value from
process mining. On the context of how organisations get value from process mining
four main stages of process mining implementation were found in this study. The
steps identified include: planning, data extraction and processing, mining and
analysis, and process improvement. With respect to the value of process mining in
strategic decision-making, this study found process mining to be applicable in this
context while providing some examples. Generally, the findings of this study
contribute to the extant literature related to process mining.
