Examining decision characteristics & challenges for agile software development
Introduction
Agile software development (ASD) emerged in the late 1990s to address the uncertainty of customer requirements, technology evolution, and changing business environments. Agile approaches rejected the highly-formalised thinking of the time in favour of dynamic, user-centric methods characterised by short development cycle iterations, continuous releases, and rapidly evolving requirements, dynamic underlying data, and reflection (Fowler and Highsmith, 2001, Schwaber and Beedle, 2002).
There are many characteristics of ASD that affect decision making, including its fast-paced iterative and incremental nature, its organic and flexible developer roles, and its emphasis on self-management (Austin and Devin, 2009, Moe and Aurum, 2008, Zannier et al., 2007, Zannier and Maurer, 2006, Zannier and Maurer, 2007). Differentiating features of decision making in ASD merit significant research. No research to date has attempted to identify in a holistic, structured manner, an over-arching set of ASD characteristics that affect decision making. This is concerning given that agility fundamentally affects software development decision making through a number of key characteristics; there is a need to understand the challenges to decision making that these over-arching ASD characteristics present (Henderson-Sellers and Serour, 2005). It is important to contextually research these characteristics and map them to challenges for decisions so that we can provide a framework for both researchers and practitioners to better evaluate decision making in ASD teams. Therefore the objectives of this research are to:
- 1.
Identify contextually specific decision characteristics present in ASD.
- 2.
Describe the challenges such characteristics pose for decision making for ASD teams.
We conducted an in-depth case study to examine these research objectives. This case study included 18 individual interviews, 2 focus groups, and observation of 21 team meetings with supplementary project documentation. We then used these data to create a framework to illustrate the decision challenges for each decision characteristic identified.
In the sections that follow, we present a background to decision making and contextualise it for ASD. To provide a structure for the identification of decision characteristics and related challenges, we first discuss ASD, followed by decision processes, decision intelligence, and decision quality. We then outline our research method to describe our case study. Finally, we present our findings, discussion, and conclusions.
Section snippets
Agile software development
There are 2 dominant perspectives in the agility literature in terms of the enablement and evaluation of agility: (i) a method adherence-based view and (ii) a principle or value-based perspective. Many studies adopt the former, measuring agility by the number of XP or Scrum practices that are used (Dybå and Dingsøyr, 2008). However, there are 2 limitations of this narrow focus. First, agility is a vague and multi-faceted concept given that agile is practised in so many different ways: it is
Method
We conducted an in-depth exploratory case study (Stake, 2000, Yin, 2003) using multiple methods of data collection (Benbasat et al., 1987). This is particularly appropriate in the ASD context where decision making behaviours are complex, dynamic, and highly social.
Results
Seven key characteristics of decision making in ASD emerged in relation to each of the 4 agile values. We also examined the corresponding decision challenges for each decision characteristic (see Table 3). Italicised text in this section delineates the bullets summarised in the table.
Discussion
The central contribution of this research is a framework for a) understanding the decision characteristics that relate to the 4 core agile values, and b) evaluating the challenges these characteristics present for the decision process, decision intelligence, and decision quality. This builds upon prior research indicating the general decision obstacles that ASD teams face: (1) an unwillingness to commit to decisions; (2) conflicting priorities; (3) unstable resource availability; and (4) a lack
Conclusion
There are many ASD characteristics that affect decision making, but there is no holistic, structured manner depicted via an over-arching set of ASD characteristics that affect decision making. This study provides this framework, identifying 7 decision characteristics across the 4 agile values. Corresponding to these characteristics we have also defined the challenges associated with the decision process, decision intelligence, and decision quality, thereby addressing our 2 research objectives.
Acknowledgements
This research is supported by a 2016 Fordham University Faculty Fellowship, Fordham University's Gabelli School of Business Summer 2016 Research Grant and 2016 Gabelli Grant SS16-1094, and a Science Foundation Ireland grant 13/RC/2094. It is also co-funded under the European Regional Development Fund through the Southern & Eastern Regional Operational Programme to Lero - the Irish Software Research Centre (www.lero.ie).
Meghann Drury-Grogan is an Assistant Professor of Communication & Media Management in the Gabelli School of Business at Fordham University. Her research focuses on business communication, project management, and decision making on software development teams. She has taught international academic and practitioner audiences. Her graduate and undergraduate courses focus on business communication, decision making, project management, leadership communication, and global business and communication.
References (63)
- et al.
Diagnosing decision quality
Decis. Support Syst.
(2008) - et al.
The role of user capability and incentives in group and individual decision support systems: an economics perspective
Decis. Support Syst.
(1994) Performance on agile teams: relating iteration objectives and critical decisions to project management success factors
Inf. Software Technol.
(2014)- et al.
Obstacles to decision making in agile software development teams
J. Syst. Software
(2012) - et al.
Empirical studies of agile software development: a systematic review
Inf. Software Technol.
(2008) - et al.
Compensating effects of GSS on group performance
Inf. Manage.
(1999) - et al.
An investigation of effort-accuracy trade-off and the impact of self-efficacy on web searching behaviors
Decis. Support Syst.
(2004) - et al.
Attributes affecting computer-aided decision making: a literature survey
Comput. Human Behav.
(1994) - et al.
On the effectiveness of decisional guidance
Decis. Support Syst.
(1996) The impact of intelligent decision support systems on intellectual task auccess: an empirical investigation
Decis. Support Syst.
(2006)
Task complexity and contingent processing in decision making: an information search and protocol analysis
Org. Behav. Human Perform.
Past, present, and future of decision support technology
Decis. Support Syst.
A model of design decision making based on empirical results of interviews with software designers
Inf. Software Technol.
Agile Project Management Methods for IT Projects, The Story of Managing Projects: A Global, Cross–Disciplinary Collection of Perspectives
Managing Agile Projects
Research commentary-weighing the benefits and costs of flexibility in making software: toward a contingency theory of the determinants of development process design
Inf. Syst. Res.
The case research strategy in studies of information systems
MIS Q.
The best laid plans of mice and men: the role of decision confidence in outcome success
North Am. J. Psychol.
Bounded ideation theory
J. Manage. Inf. Syst.
Knowledge sharing: agile methods vs. tayloristic methods
Agile Project Management: How to Succeed in the Face of Changing Project Requirements
Agile software development: the people factor
IEEE Comput.
Agility from first principles: reconstructing the concept of agility in information systems development
Inf. Syst. Res.
Losing the plot: decision behaviours in agile systems development
Group process losses in agile software development decision making
Int. J. Intell. Inf. Technol., Spec. Issue Inf. Syst. Serv. Based Syst.
An exploration of the relationship between contribution behaviours and the decision making process in agile teams
Understanding fit and appropriation effects in group support systems via meta-analysis
MIS Q.
An investigation of the decision-making process in agile project teams
Int. J. Inf. Technol. Decis. Making
Building theories from case study research
Acad. Manage. Rev.
Customising agile methods to software practices
Eur. J. Inf. Syst.
Cited by (42)
An empirical evaluation of scrum training's suitability for the model-driven development of knowledge-intensive software systems
2023, Data and Knowledge EngineeringMaintenance Cost of Software Ecosystem Updates
2023, Procedia Computer ScienceLogics' shift and depletion of innovation: A multi-level study of agile use in a multinational telco company
2022, Information and OrganizationCitation Excerpt :Some studies found that Agile implementation can foster ambidexterity (e.g., Ramesh et al., 2012) through the routinization of exploration (Vidgen & Wang, 2009). More recent studies, however, problematize the impact of Agile on organizations', teams', and individuals' innovative capabilities (e.g., Annosi, Foss, & Martini, 2020; Drury-Grogan et al., 2017). For example, Hodgson and Briand (2013) found that Agile practices can undermine creative work by providing an ‘illusion of autonomy’ in teams.
Security in agile software development: A practitioner survey
2021, Information and Software TechnologyScrum versus Rational Unified Process in facing the main challenges of product configuration systems development
2020, Journal of Systems and SoftwareCitation Excerpt :Various studies have focused on the two methods’ pros and cons in general software development projects (Cho, 2009; Larman, 2004; Noordeloos et al., 2012; Usman et al., 2014). Other studies have investigated the tailoring/adaptation of agile methods (Campanelli et al., 2018; Campanelli and Parreiras, 2015), and others agile methods’ challenges (Drury-Grogan et al., 2017) in general software development projects. However, the authors cannot guess how applicable the results of these studies are to PCS projects due to the numerous differences between PCS projects and other software development projects.
Team wisdom in software development projects and its impact on project performance
2020, International Journal of Information ManagementCitation Excerpt :Along with these efforts, managers must know that team members with more experience may dominate key decisions during a project. In that case, as Drury-Grogan et al. (2017) noted, junior members or less experienced team members may not become involved enough in the decision- making process, their decision inputs are not explored, and/or more experienced members change their estimates. In this respect, management should instead implement a procedural justice climate for the software development project teams, especially for any in-house software development project teams.
Meghann Drury-Grogan is an Assistant Professor of Communication & Media Management in the Gabelli School of Business at Fordham University. Her research focuses on business communication, project management, and decision making on software development teams. She has taught international academic and practitioner audiences. Her graduate and undergraduate courses focus on business communication, decision making, project management, leadership communication, and global business and communication. Dr. Drury-Grogan has published in leading international journals and conferences and has received numerous awards, including an NCA 2012 Best Paper Award, the 2011 IEEE Software “Best Research Paper” award, and the SIG IT Project Management “Best Paper Award” at ICIS 2011 for her research in business communication and decision making. She was a 2002 Rotary Ambassadorial Scholarship & Stipend recipient. She serves as a reviewer for prestigious journals in the communication and software development fields. She has worked with organizations such as Boston Scientific, Hewlett Packard Enterprise, Information Mosaic, and Mazars Ireland. Prior to Fordham, Dr. Drury-Grogan worked for Deloitte Consulting LLP as an organization and change management consultant developing communication strategies; implementing change and communication plans; and designing governance models, decision making frameworks and organization structures across industries, including Fortune 500 companies and the public sector.
Kieran Conboy is a Professor in the College of Business, Public Policy & Law at NUI Galway. He previously worked for Accenture Consulting and the University of New South Wales in Australia. Kieran teaches graduate and undergraduate courses in information systems innovation, agile and lean project management, portfolio management, and contemporary models, e.g. crowd sourcing and crowd funding. He has recently co-developed a global standard for information systems curriculum content, published in the Communications of the Association of Information Systems. He has advised and published widely in the areas of management and workplace innovation, particularly in agile and lean processes in software organizations. He has worked with organizations such as Microsoft, Cisco Systems, and Fidelity Investments. Kieran has also advised international public sector organizations in the health and education sectors, the E.U. Commission, and national funding bodies in Ireland, U.S.A., and Australia. Kieran was also a 2009 Fulbright award recipient at Carnegie Mellon University working with the Software Engineering Institute on the business value of IT systems.
Tom Acton is interim Head of School and Senior Lecturer in Business Information Systems at the J.E. Cairnes School of Business & Economics, National University of Ireland, Galway, Ireland. His main research interests lie in decision support systems, usability and acceptance, and mobile devices. He holds a PhD degree on Decision Support for Small-Screen Information Systems. He holds other qualifications in mathematics, education, software design, commerce and science. He has a number of journal publications, book chapters and conference papers. Recently he has served as Vice Dean for Teaching & Learning, Associate Head of Teaching & Learning for the School of Business & Economics, and Head of the Business Information Systems discipline. Recently, he has also served as associate editor on a number of journals, including the European Journal of Information Systems (EJIS) and the Journal of Theoretical and Applied E-Commerce Research (JTAER).
- 1
http://business.fordham.edu/faculty/drury/index.asp