Ann is invited to help an Agile Release Train (ART) that has struggled through multiple Innovation and Planning (IP) Iterations. They just finished the second Iteration in the Program Increment (PI) and have nothing to demonstrate at the System Demo.Program stakeholders are really concerned.


What should Ann do?



a. Have every team demonstrate their team increment to the stakeholder separately in the team branch


b. Re-architect the system so that there are no dependencies between the teams, and integration is not needed


c. Stop working on any new functionality and fully integrate and trust the system, adjust scope based on learning


d. Re-plan the current PI. De-Scope to leave enough time to integrate what has been built during the IP iteration

Respuesta :

Answer:

C: Stop working on any new functionality and fully integrate and test the system; adjust scope based on learning.

Explanation:

In this case, it was mentioned that the Agile Release Train has struggled through multiple innovation and planning iteration. An agile release train is simply a release cycle which has been seriously pre-planned into various phases for individual projects and release team have to work in accordance to, so that they can successfully deliver their release. Since they have finished the second iteration in the program, and do not have any system demo to demonstrate, the next option for Ann is to quit any work on any new functionality, but rather work towards full integration and testing of the system, to find out if there might be need to adjust the scope of the project based on learning.

Based on the information given, the correct option will be C. Stop working on any new functionality and fully integrate and trust the system, adjust scope based on learning.

Based on the information given, the Agile Release Train has struggled through multiple Innovation and Planning (IP) Iterations.

Therefore, since the stakeholders are concerned about the scenario, Ann should stop working on any new functionality and fully integrate and trust the system, adjust scope based on learning.

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