Facts about the course

ECTS Credits:
Responsible department:
Faculty of Logistics
Course Leader:
Bjørn Jæger
Lecture Semester:
1 week

LOG904-171 Robotic Process Automation (Autumn 2021)

About the course

Typical supply chain challenges are related to the exchange of information among business applications. For example, across applications in procurement, sales operations, billing, customer operations, and finance and accounting. These business areas are supported and automated by several IT applications. In general, operations in one application might require data from other applications. Often, this is handled by tedious manual interaction for copying and pasting data. For example: a user logs on one application (A), then discover a need for information found in another application (B). The user logs on application B to read the information and type it into application A. This takes time, is error prone and makes it hard to digitize end-to-end processes. Integrating IT applications by updating the software of each application is an option, but in practice companies often find it hard to justify the IT investments required. Robotic Process Automation (RPA) is a software tool that works on top of other applications. RPA enable fetching and storing data across existing applications without changing the applications. This makes RPA a powerful tool for organizations to automate repetitive, tedious tasks giving organizations more time to focus on other issues.

Topics covered:

Introduction to RPA, RPA in supply change management, hands-on case study on applying RPA in an accounting firm.

The course is connected to the following study programs

Recommended requirements

Basic programming skills, for example in macro programming or in a programming language.

The student's learning outcomes after completing the course

How to apply RPA to practical business applications.

Forms of teaching and learning

Lecturers, hand-on assignments and group discussions.


Form of assessment: Home assessment with presentation

  • Duration: -

  • Grouping: Group

  • Grading scale: Letter (A - F)


  • Barabási, Albert-László, and Réka Albert. 1999. "Emergence of Scaling in Random Networks." Science 286 (5439):509-512. doi: 10.1126/science.286.5439.509.

  • Barthélemy, Marc. 2011. "Spatial networks." Physics Reports 499 (1):1-101. doi: https://doi.org/10.1016/j.physrep.2010.11.002.

  • Boccaletti, S., V. Latora, Y. Moreno, M. Chavez, and D. U. Hwang. 2006. "Complex networks: Structure and dynamics." Physics Reports 424 (4):175-308. doi: https://doi.org/10.1016/j.physrep.2005.10.009.

  • da F. Costa, Luciano, Francisco Rodrigues, Gonzalo Travieso, and Paulino Villas Boas. 2007. "Characterization of Complex Networks: A Survey of measurements." Advances in Physics 56:167-242. doi: 10.1080/00018730601170527.

  • Erdös, P. , and A. Rényi. 1960. "On the Evolution of Random Graphs." Publication of the Mathematical Institute of the Hungarian Academy of Sciences 5.

  • Fortunato, Santo. 2010. "Community detection in graphs." Physics Reports 486 (3):75-174. doi: https://doi.org/10.1016/j.physrep.2009.11.002.

Last updated from FS (Common Student System) Oct. 24, 2021 7:20:20 AM