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Polish Information Processing Society
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Annals of Computer Science and Information Systems, Volume 15

Proceedings of the 2018 Federated Conference on Computer Science and Information Systems

Scrum Adoption Challenges Detection Model: SACDM

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DOI: http://dx.doi.org/10.15439/2018F270

Citation: Proceedings of the 2018 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 15, pages 949–957 ()

Full text

Abstract. Scrum has been the most widely adopted Agile methodology over the past decade with Scrum and Scrum variants offering alternatives to the old software development methods. While Scrum plays an important role in the success of Agile development, it does come with its own challenges. In previous research challenges have been analyzed at the organizational and team level, primarily via case studies. However, fundamentally, Scrum needs to be adopted at the individual level. Furthermore, challenges such as inexperience, poor communication, specialization, lack of teamwork, low-quality, organizational culture and Scrum compatibility, have been identified as contributors. This paper therefore discusses the Scrum and Agile adoption challenges faced both globally as well as within the South African borders, from the findings of a narrative review. Secondly, a custom model adapted from the Diffusion of Innovation theoretical model was developed to detect the Scrum adoption challenges experienced within software organizations at the individual level. The custom model referred to as the Scrum Adoption Challenges Detection Model (SACDM) consists of four constructs, namely; individual factors, team factors, organizational factors and technology factors. The constructs are composed of nineteen independent variables that assists in understanding which factors contributes towards an individual either adopting or rejecting Scrum within a software organization. SACDM is therefore used to detect the adoption or rejection of Scrum as the dependent variable based on the independent variables being tested within the four constructs. The model can further be used with a survey questionnaire to provide generalized awareness of Scrum adoption challenges allowing software organizations to make more informed decisions when adopting Scrum. Future research is to allow the model to contribute towards Scrum adoption challenges predictive analysis.

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