Influential factors of aligning Spotify squads in mission-critical and offshore projects – a longitudinal embedded case study

Salameh, A ORCID: and Bass, J ORCID: 2018, Influential factors of aligning Spotify squads in mission-critical and offshore projects – a longitudinal embedded case study , in: 19th International Conference on Product-Focused Software Process Improvement, 28-30 November 2018, Wolfsburg, Germany.

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Changing the development process of an organization is one of the toughest and riskiest decisions. This is particularly true if the known experiences and practices of the new considered ways of working are relative and subject to contextual assumptions. Spotify engineering culture is deemed as a new agile software development method which increasingly attracts large-scale organizations. The method relies on several small cross-functional self-organized teams (i.e., squads). The squad autonomy is a key driver in Spotify method, where a squad decides what to do and how to do it. To enable effective squad autonomy, each squad shall be aligned with a mission, strategy, short-term goals and other squads. Since a little known about Spotify method, there is a need to answer the question of: How can organizations work out and maintain the alignment to enable loosely coupled and tightly aligned squads? In this paper, we identify factors to support the alignment that is actually performed in practice but have never been discussed before in terms of Spotify method. We also present Spotify Tailoring by highlighting the modified and newly introduced processes to the method. Our work is based on a longitudinal embedded case study which was conducted in a real-world large-scale offshore software intensive organization that maintains mission-critical systems. According to the confidentiality agreement by the organization in question, we are not allowed to reveal a detailed description of the features of the explored project.

Item Type: Conference or Workshop Item (Paper)
Schools: Schools > School of Computing, Science and Engineering
Journal or Publication Title: Lecture Notes in Computer Science
Publisher: Springer
Series Name: Lecture Notes in Computer Science
ISBN: 9783030036720 (print); 9783030036737 (eBook)
ISSN: 0302-9743
Related URLs:
Funders: University of Salford
Depositing User: Dr Abdallah Salameh
Date Deposited: 11 Mar 2020 09:39
Last Modified: 16 Feb 2022 04:12

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