The integration of Data Science into the Project Management practice

Desmond LukeStudent: Luke Desmond
Year: 2016
Affiliation: University of South Australia
Level: Postgraduate
Thesis written in English

As “data natives” such as Alibaba, Google and Uber disrupt economies and become part of our daily lives by implementing elements of Data Science such as Big Data, Business Intelligence and Visualisation, all organisations are questioning how they can use these innovative business applications to realise value in their business. This research sought to understand where and how the Project Management practice is currently integrating Data Science into delivering project outcomes, what challenges it faces and how it might leverage best practices in other industries.

Research methods implemented in this study included semi-structured interviews and case studies. The quantitative interviews were analysed thematically, with the results grouped together into affinity groups with an affinity map used to explore the relationships between each of the affinity groups. The case studies involved investigating two substantially different Project Management engagements within a single organisation and examining connections between the case studies, literature review and the interviews.

The research findings generally identified limited adoption of Data Science solutions in the Project Management practice. Where Data Science has been integrated it was apparent that there are significant challenges to overcome before it becomes more widely implemented. There were isolated examples of integrated Project Management and Data Science solutions that could be considered highly sophisticated and comparable to the solutions used by industry leading Data Science practices. These successful implementations of Data Science present opportunities to grow competence and to expand the integration of Data Science into other Project Management areas.

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