To Fail Fast, you need to know when to Fail

One of the basic principles of XP is to provide value. To achieve this ,you do the stories first that bring the most value. Now if those stories are risky or big, then you want to fail fast and move on. However in software development, most things are possible…it's just a matter of time. So how do you fail?

At Ephox we are extremely good at making the impossible possible, just take a look at EditLive!. The things we did in the early days were not possible with the limitations of the Java APIs, so we found a way around them. As such, it is possible to continue with a feature beyond the current return on investment of the feature.

What we need to do is find a way of identifying when to stop the investment in a given feature, mark it as "failed" and move onto the next most valuable feature. To do this however, you need to know what are the conditions by which you define something as having failed.

We recently moved to a tri-estimate approach1 where all stories include a Best case, Worst case and Most Likely estimate. These estimates not only give us an indication of the risk associated with a feature, but also a basis by which to determine "failure".

My framework for "failing" a story is as follows. Once we hit the Most Likely estimate, we re-evaluate the Worst Case estimate with the knowledge gained so far. Assuming the revised Worst case is an acceptable investment in the feature, the new value is then considered the "line in the sand". Once we hit the Worst Case estimate, we review, asking how much longer to go to completion. If the time to go is acceptable, then this is the "failure" time. Once that time has expired, the story fails.

So, for example, figures of 20 and 40hrs are given for Most Likely and Worst Case estimates respectively. At 20hrs, the team revises the Worst Case to 45hrs. It is accepted that the features value is worth 45hrs, and development continues. At 45hrs, the team says there is an additional 3 hrs to go to completion. This final amount of effort is short enough that development continues for the 3 additional hours. At the end of that time, we "fail" the story if it's not completed.

Now of course, there are exceptions to this, but the aim is to identify when a feature is just going to keep going and stop it.

1 – Doug discussed the idea in his article Estimations – Best, Expected and Worst

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