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Old Epics Don't Die. Here's How They Fade Away.

Atlassian, Jira, Agile

By Bob Wen

As teams begin to work in an Agile fashion, dividing up work into smaller batch sizes so that it fits in smaller iterations, many business stakeholders wonder about whether the broader themes that they want can be realized from the development and deployment of all these "stories".  To that end, many businesses take those stories and bind them together into an Epic, a container that represents the feature desired or outlines the business direction or strategy.

But does the realization of that business direction or strategy totally depend on the completion of every Story in that Epic?  Not necessarily.  Let's take a closer look.

Build your Epic as an MVP

In The Lean Startup, Eric Ries outlines the process of learning through quick and timely customer feedback as the Build-Measure-Learn loop.  In this loop, entrepreneurs look to take Minimum Viable Products (MVP) through an initial cycle of learning.  Once feedback is obtained, then comes a necessary decision point: pivot (move to a different MVP) or persevere (add more features to the MVP and run it through the Build-Measure-Learn loop again).

If we want to model our Epics on this approach, it's best to start the Epic with the minimum set of stories that can prove (or disprove) a hypothesis of whether it will reach some business value.  Then it's time to design and deploy the initial set of stories that make up the MVP to get feedback.

Measure your Epic

Once your MVP has its stories released, it's time to evaluate how true is the hypothesis.  Is the MVP getting the theorized business value?  What is the customer reaction?

All information (good or bad) is necessary.  It helps inform our Learn process and whether we pivot or persevere.

Learn from Epic Feedback

It's time to act on the data we acquire.  If the data and feedback validate your hypothesis, it's easy to make the decision to persevere.  Add additional stories to the Epic to add more functionality.  If your hypotheis is invalidated by your data and feedback, the decision to pivot to another Epic is just as easy.

What if the data isn't conclusive?  How do you prioritize?  If your Epic is prioritzed using Cost of Delay metrics such as WSJF, you can look at its WSJF to determine its priority against other Epics. (a subject that we have discussed before). Remember to recalculate and evaluate frequently because as the Epic's Job Size gets smaller, its value gets larger (smaller denominators do that) but other Epics may still have larger values.

TAGS: Atlassian, Jira, Agile

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