Success factors and measurements of

Examensarbete för masterexamen

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Type: Examensarbete för masterexamen
Master Thesis
Title: Success factors and measurements of
Authors: mattson, olliver
Egenvall, Kim
Abstract: Discovering the success factors of an Agile team can prove important for teams that are not performing as well as they should. Combined with measurements for these factors, organizations can pinpoint where problems exist and fix these problems in order to help their teams perform better. Previous research into the topic of Agile success factors have examined factors in relation to Agile projects. However, what this work has not taken into account are what factors affect specifically the team, and how these could possibly be measured. To find these success factors and measurements, a survey was performed. The results were then combined with factors identified from previous literature. This was followed by a second survey, as well as four interviews where the participants ranked the identified factors. The final result was a list of ranked success factors, where the factors most important to a teams success had the highest ranking. The results also introduced some new success factors not previously discussed in literature. The results indicate that the majority of the most important factors relate to people and team spirit, with some factors related to organizational as well as technical factors. The factor deemed most important was "Good communication and collaboration within the team". Compared to previous research, the findings in this report indicate an importance of team spirit, team environment and team capability as opposed to previous literature which advocates project management process as well as customer involvement. These findings can help when Agile teams are not performing as well as hoped by identifying if these factors are present and if not, helping the team in that area in order for them to be successful.
Keywords: Data- och informationsvetenskap;Computer and Information Science
Issue Date: 2017
Publisher: Chalmers tekniska högskola / Institutionen för data- och informationsteknik (Chalmers)
Chalmers University of Technology / Department of Computer Science and Engineering (Chalmers)
Collection:Examensarbeten för masterexamen // Master Theses

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