Visualising Prescriptive Process Monitoring Output
Name
Lana Botchorishvili
Abstract
The emergence of process mining in business process management has given way to developing algorithms that predict future processes based on historical event logs to improve operational efficiency. Further improvements have followed in the form of real-time prescriptive process monitoring tools, which identify volatile process instances and suggest interventions for upcoming activities to prevent risky execution. One of the main challenges of this practice is communicating interventions to end users in a clear and concise manner. This research was conducted to develop a real-time application that visualises available interventions and their impact on a process instance. The tool helps support process analysts in identifying activities that improve a KPI or circumvent a sub-optimal outcome in a process. A resulting artefact is a form of an operational dashboard - Kairos - that visualises prescriptive process monitoring output.
Graduation Thesis language
English
Graduation Thesis type
Master - Software Engineering
Supervisor(s)
Fredrik Payman Milani, Alexander Udo Nolte, Kateryna Kubrak
Defence year
2023