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

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

Coordinating Knowledge Work in Multi-Team Programs: Findings from a Large-Scale Agile Development Program

Software development projects have undergone remarkable changes with the arrival of agile development methods. While intended for small, self-managing teams, these methods are increasingly used also for large development programs. A major challenge in programs is to coordinate the work of many teams, due to high uncertainty in tasks, a high degree of interdependence between tasks and because of the large number of people involved. This revelatory case study focuses on how knowledge work is coordinated in large-scale agile development programs by providing a rich description of the coordination practices used and how these practices change over time in a four year development program with 12 development teams. The main findings highlight the role of coordination modes based on feedback, the use of a number of mechanisms far beyond what is described in practitioner advice, and finally how coordination practices change over time. The findings are important to improve the outcome of large knowledge-based development programs by tailoring coordination practices to needs and ensuring adjustment over time.Comment: To appear in Project Management Journa

Spotify tailoring for promoting effectiveness in cross-functional autonomous squads

Organisations tend to tailor agile methods to scale employed practices to have cross-functional autonomous teams while promoting sustainable creative and productive development at a constant pace. Thus, it is important to investigate how organisations tailor agile practices to get the balance right between teams' autonomy and alignment. Spotify model is originally introduced to facilitate the development of music streaming services in a very large-scale project with a Business-to-Consumer (B2C) model. However, developing a large-scale mission-critical project with a Business-to-Business (B2B) model is not essentially supported by the Spotify model. Thus, embracing Spotify model for such projects should be concerned about the question of how Spotify practices are adjusted to promote the effectiveness of cross-functional autonomous squads in a mission-critical project with B2B model? In this paper, we conduct a longitudinal embedded case study, which lasted 21 months during which 14 semi-structured interviews were conducted. The Grounded Theory (GT) is adopted to analyse the collected data. As a result, we identify practices and processes that promote effectiveness in cross-functional autonomous squads, which have never been discussed in terms of Spotify model before. We also present Spotify Tailoring by highlighting modified and newly introduced practices by the organisation in which the case study was conducted

Software Reuse in Agile Development Organizations - A Conceptual Management Tool

The reuse of knowledge is considered a major factor for increasing productivity and quality. In the software industry knowledge is embodied in software assets such as code components, functional designs and test cases. This kind of knowledge reuse is also referred to as software reuse. Although the benefits can be substantial, software reuse has never reached its full potential. Organizations are not aware of the different levels of reuse or do not know how to address reuse issues. This paper proposes a conceptual management tool for supporting software reuse. Furthermore the paper presents the findings of the application of the management tool in an agile development organization

Bridging the gap between research and agile practice: an evolutionary model

There is wide acceptance in the software engineering field that industry and research can gain significantly from each other and there have been several initiatives to encourage collaboration between the two. However there are some often-quoted challenges in this kind of collaboration. For example, that the timescales of research and practice are incompatible, that research is not seen as relevant for practice, and that research demands a different kind of rigour than practice supports. These are complex challenges that are not always easy to overcome. Since the beginning of 2013 we have been using an approach designed to address some of these challenges and to bridge the gap between research and practice, specifically in the agile software development arena. So far we have collaborated successfully with three partners and have investigated three practitioner-driven challenges with agile. The model of collaboration that we adopted has evolved with the lessons learned in the first two collaborations and been modified for the third. In this paper we introduce the collaboration model, discuss how it addresses the collaboration challenges between research and practice and how it has evolved, and describe the lessons learned from our experience

A survey of simulation techniques in commerce and defence

Despite the developments in Modelling and Simulation (M&S) tools and techniques over the past years, there has been a gap in the M&S research and practice in healthcare on developing a toolkit to assist the modellers and simulation practitioners with selecting an appropriate set of techniques. This study is a preliminary step towards this goal. This paper presents some results from a systematic literature survey on applications of M&S in the commerce and defence domains that could inspire some improvements in the healthcare. Interim results show that in the commercial sector Discrete-Event Simulation (DES) has been the most widely used technique with System Dynamics (SD) in second place. However in the defence sector, SD has gained relatively more attention. SD has been found quite useful for qualitative and soft factors analysis. From both the surveys it becomes clear that there is a growing trend towards using hybrid M&S approaches

Autonomous agile teams: Challenges and future directions for research

According to the principles articulated in the agile manifesto, motivated and empowered software developers relying on technical excellence and simple designs, create business value by delivering working software to users at regular short intervals. These principles have spawned many practices. At the core of these practices is the idea of autonomous, self-managing, or self-organizing teams whose members work at a pace that sustains their creativity and productivity. This article summarizes the main challenges faced when implementing autonomous teams and the topics and research questions that future research should address