Heterogeneous tailoring approach using the Spotify model

Salameh, A ORCID: https://orcid.org/0000-0002-3012-9353 and Bass, J ORCID: https://orcid.org/0000-0002-0570-7086 2020, Heterogeneous tailoring approach using the Spotify model , in: Evaluation and Assessment in Software Engineering (EASE 2020), 15-17 April 2020 (Postponed due to COVID-19), Trondheim, Norway.

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Organisations tailor agile methods to fit their specific needs. There are two recognised approaches to agile method tailoring: Contingency Factors and Method Engineering. Spotify has developed its own agile culture, which has become influential among agile proponents. The Spotify model has formed the basis of agile methods used in numerous other organisations. We have identified a lack of research into the tailoring approach used in the Spotify model. In order to explore How practitioners do achieve agile tailoring using the Spotify model, a longitudinal embedded case study over 21 months was conducted. A very large-scale FinTech organisation using the Spotify model was selected for the study. We conducted 14 semi-structured interviews and direct observations of agile practices. A grounded theory method was adopted to analyse the data. We discovered a novel approach to agile method tailoring, which we call “Heterogeneous Tailoring". This approach is characterised by two key features. Firstly, each autonomous cross-functional squad is empowered to select and tailor its own development method. This key feature is the main focus of this paper. Secondly, each squad is aligned to common product development goals. The practitioners in our study report benefits of this approach such as improved creativity and productivity, whilst risks of divergence from shared development objectives are mitigated through alignment practices. We contribute in this study by introducing a new third approach to agile tailoring (i.e., “Heterogeneous Tailoring"). This, in turn, complements the tailoring approaches by including Contingency Factors, Method Engineering, and Heterogeneous Tailoring.

Item Type: Conference or Workshop Item (Paper)
Schools: Schools > School of Computing, Science and Engineering
Journal or Publication Title: EASE '20: Proceedings of the Evaluation and Assessment in Software Engineering
Publisher: Association for Computing Machinery (ACM)
ISBN: 9781450377317
Related URLs:
Depositing User: Mr Abdallah Salameh
Date Deposited: 11 Mar 2020 08:57
Last Modified: 01 Sep 2020 11:15
URI: http://usir.salford.ac.uk/id/eprint/56620

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