Process analytics mainly comprises of data-driven analysis of business processes using the massive amount of event log data captured by information systems in the organisations. Various analytical techniques have been developed to help extract insights about the actual business processes with the ultimate goal of process improvement.
However, in the ‘big data’ era, we often face the problem that there is too much data to analyse. Without a clear objective for analysis, the tasks such as extracting the relevant data, analysing data and interpreting the results can be not only time consuming but unfruitful.
Hence, we've introduced a new concept called ‘guided process analytics’ to refer to data-driven process analysis initiatives that are motivated by and aim for recommendations of specific process improvement actions.
The research activities led by this research initiative are of an explorative nature and can be scoped to cater for different types of research student projects.
They will start from a literature review covering state-of-the-art process analytics approaches and techniques and how they are used to inform process improvement recommendations.
As a result of this project, we expect to have the following outcomes:
- new methods and techniques for querying process event logs to retrieve, aggregate, and/or infer relevant and reliable data for process analysis
- a ‘tool box’ of data-driven process analysis capabilities
- a systematic approach for generating log requirements to guide data curation for continuous (and automated) process analytics.
Skills and experience
To be considered for this project, we will be looking for:
- familiarity with the fields of data mining, process analytics, and process improvement/redesign
- reasonable writing skills
- problem-solving and logical thinking capabilities
- computer programming skills.
You may be able to apply for a research scholarship in our annual scholarship round.
Contact the supervisor for more information.