IDEAS home Printed from https://ideas.repec.org/a/vrs/ijcoma/v60y2024i1p280-289n1019.html
   My bibliography  Save this article

Optimization of License Management for Business Process Automation with Robotic Process Automation

Author

Listed:
  • Janik Dawid

    (Jagiellonian University, Doctoral School of Social Sciences, Cracow, Poland)

Abstract

Purpose Nowadays automation of business processes is increasing in popularity among organizations. The undeniable benefits, like freeing up the potential and time of well-educated employees so they can focus on more valued activities, are well known. With the growing number of automated processes, optimization of bot usage has become a significant factor in reducing costs. This paper presents an analysis supporting the proper management of business process automation in the context of bots’ license usage. Design The goal of this research is to build a tool that allows for the analysis of license demand and supports automated management of process runs. Findings For the described case, the research estimated the minimum number of bot licenses to ensure that the automated processes would run in a stable manner, and identified the time periods of different license utilization levels. Practical implication The described analysis is a tool for cost optimization of current bot infrastructure. It supports the continuous improvement processes for automated processes run management with balanced levels of license utilization. Value The analysis can be easily adopted for different setups of bot infrastructure to bring about benefits of cost optimization.

Suggested Citation

  • Janik Dawid, 2024. "Optimization of License Management for Business Process Automation with Robotic Process Automation," International Journal of Contemporary Management, Sciendo, vol. 60(1), pages 280-289.
  • Handle: RePEc:vrs:ijcoma:v:60:y:2024:i:1:p:280-289:n:1019
    DOI: 10.2478/ijcm-2024-0017
    as

    Download full text from publisher

    File URL: https://doi.org/10.2478/ijcm-2024-0017
    Download Restriction: no

    File URL: https://libkey.io/10.2478/ijcm-2024-0017?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:vrs:ijcoma:v:60:y:2024:i:1:p:280-289:n:1019. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.sciendo.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.