Feature Lifecycle Analysis uses a simple four-stage model of the life of a product feature.
Feature Lifecycle Analysis is a technique for agile software teams (developers and product owners) working on products that are expected to live long and prosper. It helps balance priorities and identify systemic issues that may not be evident on the usual sprint planning timescale.
It shows how much effort is allocated to the major stages of the feature lifecycle: from initial release to ultimate retirement.
Feature Lifecycle Analysis doesn't provide direct answers. It is a diagnostic providing a fresh perspective on a project, and the basis for helping a team reflect on symptoms, underlying problems and hopefully solutions.
It can be done on paper, a whiteboard, or a spreadsheet. If you use PivotalTracker, then your project can be analysed automatically here.
If we are using agile software development process such as Scrum, then isn't Feature Lifecycle Analysis redundant?
In an ideal world with a well-balanced and high-performing team, we should be able to find our own optimal balance by trusting the process:
That is of course the ideal. But we operate in the real world, and many things can upset the balance of our projects leading to less-than-ideal outcomes. For example:
Feature Lifecycle Analysis is really just a diagnostic that can present in a picture what may otherwise just be a gut-feeling that something is not quite right.
This is a real project that kicked-off a few months ago with a small new team.
Reflections on the analysis:
This project started in Dec-2010 and went live in Apr-2011. It is still actively maintained. We only started doing 4Rs tagging in 2013.
Reflections on the analysis:
This is a pure Javascript client-side application. It collects story data directly from the Pivotal Tracker API for analysis and charting in the browser.
The analysis uses your API key (get it from your PT Profile page). The API key is used only to communicate securely from your browser to the PivotalTracker API. It is not stored in cookies or sent to any other destination. Since this is an open-source project, you can check this.