Abstract
The notion of autonomous teams is core to agile software development. However, autonomy in agile teams is challenged by increasingly complex software projects, large-scale agile and perhaps increasingly multidisciplinary teams. At the same time, data science roles are making their way into agile teams as companies seek to reap the potential advantages of using data to develop better and more competitive services and products. The consequences of implementing such roles in traditional agile teams are largely unknown. In this paper, we take an exploratory approach to the topic of data science roles in agile teams by a set of interviews with five data scientists as well as three members of an agile software development team. Based on the interviews we identify a set of challenges associated with incorporating the role in agile autonomous teams. Based on these challenges we discuss preliminary recommendations for companies seeking to integrate data science roles in agile teams.
Highlights
Introduction and BackgroundDuring the past decades, agile practices have spread beyond the traditional software development team to include other roles, parts of the organization, and even the organization as a whole [1]
Zimmermann, DeLine, and Begel [3] discuss the role of data scientists in software development teams, but not agile or team autonomy
To avoid too much bias in our data by only interviewing people directly linked to the data science field, the group interview conducted by the second author was with people from an agile development team without data science experience
Summary
Agile practices have spread beyond the traditional software development team to include other roles, parts of the organization, and even the organization as a whole [1]. This introduces challenges such as adapting agile methods while keeping with the central aspects of team autonomy and balancing crossfunctional teams with an efficient team size [2]. The usage of data science in software development has expanded rapidly [1, 3], possibly introducing new challenges to agile team autonomy. In most agile methods the notion of enabling teams to make decisions of their own is central [4] Such teams are often labelled as self-managing, self-organizing or autonomous. We speculate that including data science roles into agile cross-functional teams will further complicate the landscape
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