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

Large-Scale Agile Transformation: A Case Study of Transforming Business, Development and Operations

Today, product development organizations are adopting agile methods in units outside the software development unit, such as in sales, market, legal, operations working with the customer. This broader adoption of agile methods has been labeled large-scale agile transformation and is considered a particular type of organizational change, originating in the software development units. So far, there is little research-based advice on conducting such transformations. Aiming to contribute towards providing relevant research advice on large-scale agile transformation, we apply a research-based framework for evaluating organizational agility on a product development program in a maritime service provider organization. We found that doing a large-scale agile transformation involves many significant challenges, such as having a shared understanding of the problem, getting access to users, and getting commitment to change that needs to be done. In order to overcome such challenges, we discuss the need for a holistic and integrated approach to agile transformation involving all the units linked to software development.publishedVersio

Exploring Norms in Agile Software Teams

The majority of software developers work in teams and are thus influenced by team norms. Norms are shared expectations of how to behave and regulate the interaction between team members. Our aim of this study is to gain more knowledge about team norms in software teams and to increase the understanding of how norms influence teamwork in agile software development projects. We conducted a study of norms in four agile teams located in Norway and Malaysia. The analysis of 22 interviews revealed that we could extract a varied set of both injunctive and descriptive norms. Our results suggest that team norms have an important role in enabling team performance.acceptedVersio

Agile at scale : a summary of the 8th International Workshop on Large-Scale Agile Development

The Large-Scale Agile Development workshop explored the main research challenges in large-scale software development. We considered multi-site organisations with large-scale projects that include a large number of teams adopting agile methods. Such topics include inter-team coordination, knowledge sharing, large project organisation, agile transformation, agile teamwork quality, project models that facilitate several self-organising teams, and practices for scaling agile methods. We accepted five full research papers, which are included in this volume. The accepted papers report empirical research studies using surveys, observations and case studies. Also, an interactive online discussion session was conducted to compare the two approaches, SAFe and Spotify. The workshop participants, which were around a hundred people, joined this discussion to compare the two approaches and suggest some future research questions about the hybridisation of SAFe and Spotify. This workshop summary contributes as a current snapshot of research along with some results from an interactive discussion about SAFe and Spotify

The Unfulfilled Potential of Data-Driven Decision Making in Agile Software Development

With the general trend towards data-driven decision making (DDDM), organizations are looking for ways to use DDDM to improve their decisions. However, few studies have looked into the practitioners view of DDDM, in particular for agile organizations. In this paper we investigated the experiences of using DDDM, and how data can improve decision making. An emailed questionnaire was sent out to 124 industry practitioners in agile software developing companies, of which 84 answered. The results show that few practitioners indicated a widespread use of DDDM in their current decision making practices. The practitioners were more positive to its future use for higher-level and more general decision making, fairly positive to its use for requirements elicitation and prioritization decisions, while being less positive to its future use at the team level. The practitioners do see a lot of potential for DDDM in an agile context; however, currently unfulfilled

Exploring Self-organisation in Crowd Teams

Online crowds have the potential to do more complex work in teams, rather than as individuals. Team formation algorithms typically maximize some notion of global utility of team output by allocating people to teams or tasks. However, decisions made by these algorithms do not consider the decisions or preferences of the people themselves. This paper explores a complementary strategy, which relies on the crowd itself to self-organize into effective teams. Our preliminary results show that users perceive the ability to choose their teammate extremely useful in a crowdsourcing setting. We also find that self-organisation makes users feel more productive, creative and responsible for their work product

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

The unfulfilled potential of data-driven decision making in agile software development

With the general trend towards data-driven decision making (DDDM), organizations are looking for ways to use DDDM to improve their decisions. However, few studies have looked into the practitioners view of DDDM, in particular for agile organizations. In this paper we investigated the experiences of using DDDM, and how data can improve decision making. An emailed questionnaire was sent out to 124 industry practitioners in agile software developing companies, of which 84 answered. The results show that few practitioners indicated a wide-spread use of DDDM in their current decision making practices. The practitioners were more positive to its future use for higher-level and more general decision making, fairly positive to its use for requirements elicitation and prioritization decisions, while being less positive to its future use at the team level. The practitioners do see a lot of potential for DDDM in an agile context; however, currently unfulfilled

Onboarding: How Newcomers Integrate into an Agile Project Team

Although a stable team is deemed optimal for agile project success, new team members need to join ongoing agile projects. New- comers must rapidly assimilate into the organisational and project envi- ronment while learning how to contribute effectively to the project and integrate into the team without seriously interrupting project progress. This paper addresses how newcomers integrate into an established agile project team and the challenges newcomers and the team face during this process. This paper is a single case study of a co-located agile project team in a large IT department who regularly onboard inexperienced new- comers. We found a mixture of traditional onboarding practices and spe- cific agile practices contribute to the onboarding process. Onboarding challenges include empowerment and mindset change, accommodating part-timers, conveying agile principles, and adjusting to changes in team composition

Understanding Work Practices of Autonomous Agile Teams: A Social-psychological Review

The purpose of this paper is to suggest additional aspects of social psychology that could help when making sense of autonomous agile teams. To make use of well-tested theories in social psychology and instead see how they replicated and differ in the autonomous agile team context would avoid reinventing the wheel. This was done, as an initial step, through looking at some very common agile practices and relate them to existing findings in social-psychological research. The two theories found that I argue could be more applied to the software engineering context are social identity theory and group socialization theory. The results show that literature provides social-psychological reasons for the popularity of some agile practices, but that scientific studies are needed to gather empirical evidence on these under-researched topics. Understanding deeper psychological theories could provide a better understanding of the psychological processes when building autonomous agile team, which could then lead to better predictability and intervention in relation to human factors