Effective collaboration across demography through digital dash boards and machine learning
In a large sized project with globally distributed environment, it is challenging to have an information radiator which is common across all the demographic locations. Different time zones make it difficult to collaborate and cater to a customer who demands frequent releases and transparency. This paper demonstrates a unique solution driven by a novel mix of digitization and machine learning to solve this classical problem.
Value stream mapping helped us to identify valueless paths in task assignment and hence the team developed a tool backed with machine learning which saved huge time, helping us to deliver our concepts faster to market. We took help of digital dash board, and came up with custom unconventional dash boards, which helped our customer to understand and collaborate better with the development team located in different time zones.
This paper proposes further extensions to machine learning in project management. Improvements can be brought about in areas task estimation and assignments, velocity or turnaround time prediction.
This paper is targeted to agile practitioners who are interested in improving workflows and building intelligent process systems using new modern technologies in globally distributed environment. This modern approach reduces waste and brings in collaboration irrespective of the demography.
Mon 28 MayDisplayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
14:00 - 15:30 | Communication and Collaboration in Distributed ProjectsICGSE 2018 at E2 room Chair(s): Filippo Lanubile University of Bari | ||
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14:30 15mExperience report | Effective collaboration across demography through digital dash boards and machine learning ICGSE 2018 Prabhulinga Manikreddy Siemens Technology and Services Pvt Ltd, Jaikrishna Iyer Siemens Technology and Services Pvt Ltd | ||
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15:15 15mTalk | Questions and answers ICGSE 2018 |