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Automated Jira Data Analysis for Optimised Project Supervision and Delay Detection

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Automated Jira Data Analysis for Optimised Project Supervision and Delay Detection

CAS Software AG is a mid-sized Software company in Karlsruhe, Germany. They use Atlassian’s Jira Project Management Tool to organise and monitor customer projects.

During a 5-month internship at CAS Software, I was able to analyse the management and developer side of a software development project using Jira.

Currently, Project Managers need to analyse data manually to successfully reallocate resources, optimise cost-profit-ratio or organise developer teams within a project. Investigating the delayed issues requires downloading of Jira Tempo reports and manual data entry in Excel tables. Therefore, this task is often neglected for its extensive effort.

The objective of this thesis project was to provide a solution to support Project Managers at CAS in supervising projects with the support of a Jira-ticket monitoring tool.

Interviews and surveys were chosen as methods to evaluate the underlying problem for ticket delays and current procedures. The so-called “TimeTrackingTool” is an already existing CAS-internal application that supports project controlling procedures by providing accumulative reports of Jira worklogs.

In the scope of the thesis project the TimeTrackingTool was extended by the “Delay Detection Mode”. This mode analyses different metrics and provides the Project Manager with calculated estimates and delay predictions for individual Jira issues.

The Delay Detection Mode computes key performance indicators for Jira issues such as estimated time, aggregated time and time progress. With the support of the new mode, a Project Manager can prevent delays by reallocating developer resources, changing priorities or further actions.

The resulting software solution is used for a range of similar projects within CAS Software to avoid unnoticed delays for individual tickets and improve project performance overall. Previous calculation of delays and estimates were done in around 45 minutes. The Delay Detection Mode is providing results on average in less than 60 seconds.

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