Business Process Modelling and Automation (Spring 2024)

Abstract

Most organisations these days rely on business process modelling techniques such as BPMN to document, communicate, and analyse business processes. In recent years, however, advances in technologies have propelled the interest of organisations in automating some of their business processes, using technologies such as Robotic Process Automation, Business Process Management Systems, Adaptive Case Management, Chatbots, and Machine Learning.
This course introduces students both to the traditional craft of business processes modelling using state-of-the-art modelling techniques and to the increasingly important area of business process automation. The students learn to build a technological solution that automates a given business process in a real organisation and to design and analyse implementation strategies for the automation project.

Description

Most organisations these days rely on business process modelling techniques such as BPMN to document, communicate, and analyse business processes. In recent years, however, advances in technologies have propelled the interest of organisations in automating some of their business processes, using technologies such as Robotic Process Automation, Business Process Management Systems, Adaptive Case Management, Chatbots, and Machine Learning. 

This course introduces students both to the traditional craft of business processes modelling using state-of-the-art modelling techniques and to the increasingly important area of business process automation. The students learn to build a technological solution that automates a given business process in a real organisation and to design and analyse implementation strategies for the automation project.

Formal prerequisites

Students should be able to:
- Conduct a project in an organization that involves data collection
- Understand what business processes are and how process automation differs from process improvement*
- Understand and create data models
- Perform a theory-based analysis

*Students can acquire these skills by attending IT-enabled Process Improvement in the same semester

Intended learning outcomes

After the course, the student should be able to:

• Identify and elicit information about business processes.
• Apply business process modelling techniques to create models that are formally correct and meet the purpose of modelling in specific situations.
• Reflect on the implications of specific modelling choices (including the choice of a modelling technique) in relation to a given business process.
• Develop a technical solution that automates a given business process.
• Analyse a given business process automation project using research on automation.
• Design effective implementation strategies for business process automation projects based on research on automation.
• Reflect on the implications of choices, including sustainability-related ones, of specific automation technologies in relation to a given business process.

Learning activities

The course will use lectures, exercises, and project work to prepare and engage students in the following learning activities: 

• Process identification 
• Process elicitation and data collection 
• Process analysis 
• Process automation 

Course literature

The course literature is published in the course page in LearnIT.

Student Activity Budget

Estimated distribution of learning activities for the typical student

• Preparation for lectures and exercises: 25%
• Lectures: 15%
• Exercises: 15%
• Project work, supervision included: 40%
• Exam with preparation: 5%

Ordinary exam

Exam type:
D: Submission of written work with following oral, External (7-point scale)
Exam variation:
D2G: Submission for groups with following oral exam supplemented by the submission. Shared responsibility for the report.

reexam

Exam type:
D: Submission of written work with following oral, External (7-point scale)
Exam variation:
D2G: Submission for groups with following oral exam supplemented by the submission. Shared responsibility for the report.

Time and date

Ordinary Exam - submission Mon, 27 May 2024, 08:00 - 14:00
Ordinary Exam Tue, 18 June 2024, 09:00 - 18:00
Ordinary Exam Wed, 19 June 2024, 09:00 - 18:00
Ordinary Exam Thu, 20 June 2024, 09:00 - 18:00
Reexam - submission Wed, 24 July 2024, 08:00 - 14:00
Reexam Mon, 12 Aug 2024, 09:00 - 18:00