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

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

The XP customer team: A grounded theory

The initial definition of XP resulted in many people interpreting the on-site customer to be a single person. We have conducted extensive qualitative research studying XP teams, and one of our research questions was “who is the customer”? We found that, rather than a single person, a customer team always exists. In this paper we outline the different roles that were typically on the team, which range from the recognized “Acceptance Tester” role to the less recognized roles of “Political Advisor” and “Super-Secretary”

How Do Real Options Concepts Fit in Agile Requirements Engineering?

Agile requirements engineering is driven by creating business value for the client and heavily involves the client in decision-making under uncertainty. Real option thinking seems to be suitable in supporting the client’s decision making process at inter-iteration time. This paper investigates the fit between real option thinking and agile requirements engineering. We first look into previously published experiences in the agile software engineering literature to identify (i) ‘experience clusters’ suggesting the ways in which real option concepts fit into the agile requirements process and (ii) ‘experience gaps’ and under-researched agile requirements decision-making topics which require further empirical studies. Furthermore, we conducted a cross-case study in eight agile development organizations and interviewed 11 practitioners about their decision-making process. The results suggest that options are almost always identified, reasoned about and acted upon. They are not expressed in quantitative terms, however, they are instead explicitly or implicitly taken\ud into account during the decision-making process at interiteration time

Complementing Measurements and Real Options Concepts to Support Inter-iteration Decision-Making in Agile Projects

Agile software projects are characterized by iterative and incremental development, accommodation of changes and active customer participation. The process is driven by creating business value for the client, assuming that the client (i) is aware of it, and (ii) is capable to estimate the business value, associated with the separate features of the system to be implemented. This paper is focused on the complementary use of measurement techniques and concepts of real-option-analysis to assist clients in assessing and comparing alternative sets of requirements. Our overall objective is to provide systematic support to clients for the decision-making process on what to implement in each iteration. The design of our approach is justified by using empirical data, published earlier by other authors

Coaching culture model as a driver for a successful team management

Current fast-paced environment challenges companies to shift the focus of business away from control, power and micromanagement towards personal and professional progression by learning and upskilling practices, as well as nurturing leadership competencies, in order to stay competitive. Coaching has been considered a practice that enables businesses to facilitate growth, assist learning, thus getting to a safe environment pushing self-confidence, mutual support, creativity, multicultural communication. Yet, there is a lack of clarity on what coaching represents as a phenomenon, as well as how exactly companies can benefit from it and, if they can, which formats are the most efficient in which cases. Moreover, it is not enough to develop and implement a set of separate coaching practices - in order to see the qualitative outcomes, coaching culture model should be developed and applied. Therefore, this study takes a step forward in the understanding of coaching culture framework, develop a coaching culture model and see how it can be useful within the corporate environment. Theoretical base for this research consists of coaching theories by Whitmore, Bachkirova, Cox, Clutterbuck, Jakonen, Vesso, Alas as well as other authors, such as Wolf, Rosha, Lace etc. who studied factors impacting coaching process and its outcomes. Change management models by Lewin and others are used for coaching culture model implementation planning. The empirical analysis was made with qualitative research. The case company participating in the research went through the company-wide questionnaire, while a few team members completed the semi-structured interviews. The activities were made before and after the coaching culture model was implemented in the company. The conclusion of the study is that coaching culture model has a positive effect on the team management process. The final version of the model ensures that by addressing the following aspects: having structured processes towards agile and team metrics’ establishments (Objectives and Key Results, Key Performance Indicators etc.), waterfalling practices from the leadership team as the starting point and towards the rest of the teams, making sure applied practices are customized for each particular team to ensure its full efficiency, encouraging commitment and engagement, thus boosting employees’ potential. These results are discussed by formulating the theoretical and practical implications of the research, limitations and suggestions for further research on the topic

On the Adaptation of an Agile Information Systems Development Method

Little specific research has been conducted to date on the adaptation of agile information systems development (ISD) methods. This article presents the work practice in dealing with the adaptation of such a method in the ISD department of one of the leading financial institutes in Europe. Two forms of method adaptation, static adaptation and dynamic adaptation, are introduced and discussed in detail. We provide some insights plus an instrument that the ISD department studied uses to deal with the dynamic method adaptation. To enhance our understanding of the observed practice, we take into account two complementary perspectives: the engineering perspective and the socio-organizational perspective. Practical and theoretical implications of this study are discussed.Keywords: agile method; information systems development; method adaptation; method engineerin