An agile enterprise architecture driven approach to enhance communication in geographically distributed agile development
- Publication Type:
- Thesis
- Issue Date:
- 2016
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Agile development is a highly collaborative environment, which requires active communication among stakeholders. This active communication helps in producing high quality working software systems in short releases and iterations. Due to the ever-increasing competition, there is an increasing interest among practitioners and researchers in contemporary geographically distributed agile development (GDAD). GDAD claims to offer several benefits over co-located agile development such as lower production cost, around the clock development, faster time to market, and the liberty of involving the most talented developers across the globe. However, in the GDAD environment, active communication is difficult to achieve due to many challenges such as differences in geographical locations and time.
Literature has reported that agile enterprise architecture (EA) could help enhancing GDAD communication and performance. However, little empirical evidence is known to support this claim. Furthermore, it is not clear how to effectively achieve and study active communication construct in GDAD in terms of its dimensions, determinants and effects on performance? As a result, there is a lack of understanding about how GDAD organisations can establish and maintain active communication among distributed teams. This dissertation contributes to this research gap, first, by developing a research model based on an extensive systematic literature review on the GDAD communication challenges, techniques and strategies to mitigate these challenges, and the impact of communication on GDAD software performance. This study provides important insights about GDAD communication by identifying and empirically examining the relationships among the two dimensions of active communication (communication efficiency and communication effectiveness), one antecedent that can be controlled (agile enterprise architecture (EA)), and four aspects of GDAD performance (on-time completion, on-budget completion, software functionality, and software quality).
The study then validates the research model using an integrated research approach that combines quantitative and qualitative data analyses. The quantitative data are collected using a survey technique from 160 responses and analysed using Partial Least Squares (PLS) analyses. The qualitative data are collected using interview techniques through 10 post hoc case studies and analysed using content analysis technique.
This study reports that agile EA has positive impacts on communication efficiency and communication effectiveness, and on GDAD performance. It has also been found that communication efficiency and communication effectiveness have significant differential impacts on GDAD performance aspects. While communication efficiency is, generally, related to on-time and on-budget completions, communication effectiveness is, generally, related to functionality and quality aspects.
While the prior GDAD literature offers little guidance for GDAD communication issue, this research contributes to both theory and practice, and offers a number of useful insights and agile EA driven GDAD model. From theory perspective, insights and model are theoretically based on and empirically tested about the value and positive impact of agile EA on active communication dimensions and GDAD performance, and the impact of communication efficiency and communication effectiveness on GDAD performance in the GDAD environment. Moreover, from practice perspective, this study indicates that agile EA, communication efficiency, and communication effectiveness together increase the GDAD performance and thus, facilitate a better GDAD performance than in GDAD that does not employ agile EA.
Despite the above-mentioned contributions, like any other studies, this study has also some limitations such as sample size, time and potential analysis bias of applied qualitative and quantitative research methods. A number of steps were taken to mitigate or minimise the effects of these limitations. Thus, findings of this work should be considered with its limitations when interpreting it in the relevant theoretical and practical context.
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