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Business Process Management

Overview

Business Process Management (BPM) is a research discipline that combines business and IT perspectives with the ultimate goal of improving an organisation’s business operations and inter-organisational value chains.

BPM is a significant contributor to an organisation's overall performance and competitiveness, a key enabler of innovation and transformation and sets out to increase the effectiveness and efficiency of an organisation.

High levels of BPM principles, methods, techniques and tools are widely applied in many organisations in different industries around the world.

Courses

Our experts

We host an expert team of researchers and teaching staff, including Head of School and discipline leaders.

Our discipline brings together a diverse team of experts who deliver world-class education and achieve breakthroughs in research.

Meet our experts

Associate Professor Moe Wynn
Position
Associate Professor
Division / Faculty
Business Process Management,
School of Information Systems
Research field
Information Systems
Email
Dr Michael Adams
Position
Senior Lecturer
Division / Faculty
Business Process Management,
School of Information Systems
Research field
Information Systems
Email
Dr Wasana Bandara
Position
Senior Lecturer
Division / Faculty
Business Process Management,
School of Information Systems
Research field
Information Systems
Email
Dr Suriadi Lim
Position
Senior Lecturer Business Process Management
Division / Faculty
Business Process Management,
School of Information Systems
Research fields
Information Systems
Data Format
Email
Dr Chun Ouyang
Position
Senior Lecturer
Division / Faculty
Business Process Management,
School of Information Systems
Research field
Information Systems
Email
Dr Sander Leemans
Position
Lecturer in Business Process Management
Division / Faculty
Business Process Management,
School of Information Systems
Research fields
Applied Mathematics
Numerical and Computational Mathematics
Email
Dr Fahame Emamjome
Position
Associate Lecturer
Division / Faculty
Business Process Management,
School of Information Systems
Research fields
Information Systems
Library and Information Studies
Email
Dr Kanika Goel
Position
Associate Lecturer
Division / Faculty
Business Process Management,
School of Information Systems
Research fields
Information Systems
Business and Management
Email
Dr Robert Andrews
Position
Research Fellow
Division / Faculty
Business Process Management,
School of Information Systems
Research fields
Information Systems
Business and Management
Email
Dr Bayan Bevrani
Position
Research Fellow
Division / Faculty
Business Process Management,
School of Information Systems
Research fields
Information Systems
Business and Management
Email
Dr Erik Poppe
Position
Research Fellow
Division / Faculty
Business Process Management,
School of Information Systems
Research fields
Information Systems
Business and Management
Email
Ms Brigitte Colin
Position
Research Fellow
Division / Faculty
Business Process Management,
School of Information Systems
Research fields
Information Systems
Business and Management
Email

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Research

Our discipline is regarded as one of the leading BPM research groups in the world; specialising in process automation, process data analytics (process mining), and process management. We cover both technical and business aspects of BPM using conceptual-analytical and empirical research.

Process automation

We're known for our involvement in workflow patterns research and the open source workflow environment YAWL, a business process management software system that is currently being used in a personnel management application developed by the European Defence Agency.

Our researchers have also contributed new techniques in areas such as process verification, process simulation, flexible workflows and exception handling.

We are currently investigating the next generation of process automation topics. For example we are enabling automation in the cloud and linking new digital technologies such as robotic process automation and block chain to workflow management in close collaboration with industry partners.

View our student topics

Process data analytics (process mining)

Processes today are complex, and they are supported by digital technologies which keep detailed records of when tasks are completed and who completed them. These records can then be analysed to show how processes really performed in the past.  Concrete evidence from such analysis can guide organisations from different sectors to increase operational efficiencies in terms of time and cost.

Process Mining is a new research discipline that combines data mining, process management and visualisation techniques, to extract valuable insights from event data such as when and how the activities are carried out in a hospital setting or where delays occurred in the processing of loan applications.

Process mining techniques support various forms of analyses, such as: automated process discovery, process conformance and performance comparisons. Our discipline members contribute to new process mining techniques and develop new open-source software artefects. We have also applied process mining techniques to the healthcare, insurance, logistics, and public sector processes in Australia.

View our student topics

Process management

BPM is not all about technology. In order for process improvement Initiatives to be successfully deployed within an organisation, strategic concerns must be addressed and effective change management process is essential.

Our researchers work closely with organisations to study successful process improvement initiatives, design and develop new BPM Maturity Models and recommend how BPM competencies can be built within an organisation.

View our student topics

Projects

Brisbane Airport Corporation: Analytics for Wildlife Hazard Management

Project team
Dates

2018-2019

Project summary

QUT researchers in collaboration with Brisbane Airport Corporation (BAC) are applying advanced process analytics to understand the wildlife risks likelihood better. The outcomes of this research project will assist in designing robust wildlife risk models, and to improved risk management process at BAC.

Motor Accident Insurance Commission, Queensland Ambulance Service: Compulsory Third Party (CTP) Insurance Claims Processing: An Exploration of a ‘Best Practice’ Model using Process Mining

Project team
Dates

2017-2019

Project summary

This project aims to discover a best practice model for the Compulsory Third Party (CTP) Scheme in Queensland using evidence-based insights gained from detailed analysis of process data provided to Motor Accident Insurance Commission (MAIC) by commercial CTP insurers.

Motor Accident Insurance Commission, Queensland Ambulance Service: Pre-Hospital Retrieval and Transport Process Analysis

Project team
Dates

2017-2019

Project summary

This research initiative aims to analyse the effectiveness of complex 'road trauma patient management processes' by applying process mining techniques. The outcomes of this research will deliver cutting-edge end-to-end patient care processes needed for effective and efficient service delivery to satisfy the complex needs of healthcare industry stakeholders.

Improved business decision-making via liquid process model collections

Project leader

Associate Professor Marcello La Rosa

Dates

2015-2017

Project summary

This project aims to develop an innovative approach to create and update as necessary the large collection of business process models that represent a complex organisation, so that this collection captures the actual way in which the organisation performs its business processes.

Deploying theoretical, conceptual and empirical research, this project aims to capitalise on the value hidden in large process data, as recorded in event logs. The approach is intended to be implemented in an open-source technology to facilitate advanced investigations and predictions that can ultimately lead to better strategic decision-making. This technology also has the potential to become a research-enabling tool for the large research community in business process management.

Recently completed research projects

Some of our other funded research projects delivering outcomes for industry are:

  • Cooperative Research Centre on Optimal Resource Extraction (CREore): Data-Driven Models, 2017 - 2018
  • Brisbane Airport Corporation: Analytics for Major Project Risk and Opportunity Management, 2016 - 2017
  • QLD Accelerate Partnership: Exposing Insurance Claims Processing Impediments, 2014 - 2017
  • HSE Data Analytics Project
  • CRA DSITI Innovation for Data and Analytics Workflows.

We have worked with other disciplines and institutions to contribute towards the following projects:

  • Towards engineering behavioural research design systems, 2015-2017

Our current student topics

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