Improving workflow efficiency in a small organization through digital tools
Sarta, Mare (2026)
2026
All rights reserved. This publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited.
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2026052114802
https://urn.fi/URN:NBN:fi:amk-2026052114802
Tiivistelmä
Small organizations often struggle with inefficient manual processes caused by limited resources. In this thesis, efforts have been made to identify and improve the registration process of a small non-profit organization: Tribe Tampere (Finland). Tribe Tampere is a community-oriented organization that seeks to bridge gaps among startups, talent, and other organizations in the startup ecosystem. The organization employs five part-time staff members and relies upon volunteers to perform many of its functions. Due to these limited human resources, many of the non-profit’s current events are burdensome upon the marketing lead of the organization.
The theoretical foundations of this thesis relate to the topics of business process management, workflow management, digital transformation, and AI-supported organizations. Each of these theories formed the basis for the identification of the inefficiencies within the initial process of Tribe Tampere’s event registration, as well as for the implementation of the solution.
Data were collected through a specialist interview with the marketing and event community lead of Tribe Tampere, as well as through observing the initial process at Tribe Tampere. Results of these procedures reveal that there was no automated sending of communications or calendar invitations for Tribe Tampere’s event participants prior to the implementation of the current solution, leading to a no-show rate for those events of between 20-35%.
An automation solution was developed using Monday.com (initially used by Tribe Tampere) and Make.com (implemented to automate Google Calendar invitations for Tribe Tampere). Furthermore, an artificial intelligence language model was used to create templates for confirming registrations and following up on registration requests. A user guide was also created for the client to ensure the solution could be maintained independently.
The findings suggest that small organizations are capable of automating manual workflow tasks to reduce time spent on repetitive processes, and that this can be achieved at no or minimal cost. Suggestions for future studies and development in this area are made within this thesis.
The theoretical foundations of this thesis relate to the topics of business process management, workflow management, digital transformation, and AI-supported organizations. Each of these theories formed the basis for the identification of the inefficiencies within the initial process of Tribe Tampere’s event registration, as well as for the implementation of the solution.
Data were collected through a specialist interview with the marketing and event community lead of Tribe Tampere, as well as through observing the initial process at Tribe Tampere. Results of these procedures reveal that there was no automated sending of communications or calendar invitations for Tribe Tampere’s event participants prior to the implementation of the current solution, leading to a no-show rate for those events of between 20-35%.
An automation solution was developed using Monday.com (initially used by Tribe Tampere) and Make.com (implemented to automate Google Calendar invitations for Tribe Tampere). Furthermore, an artificial intelligence language model was used to create templates for confirming registrations and following up on registration requests. A user guide was also created for the client to ensure the solution could be maintained independently.
The findings suggest that small organizations are capable of automating manual workflow tasks to reduce time spent on repetitive processes, and that this can be achieved at no or minimal cost. Suggestions for future studies and development in this area are made within this thesis.