by Christine Thompson
The Jira burn-down chart tracks the total work remaining in the sprint and projects the likelihood of achieving the sprint goal. By tracking the remaining work throughout the iteration, a team can manage its progress and respond accordingly. Having spent some time getting to grips with the intricacies of the burn-down chart, I thought that I would share my understanding.
The green line is the burn-up line which indicates the time spent ie. the sum of all the hours logged against the tasks in the sprint. The red line is the burn-down which indicates the time remaining ie. the total estimated time in the sprint minus all the hours that have been logged. You may well expect that as the sprint progresses, the time burnt-down on the red line will equal the time burnt up on the green line but it seems that this is often not the case.
Here’s a snippet from a recent burn-down chart for one of my teams, mid-sprint:
You can see that the time indicated on the axis for the burn-down is 84 hours but the time indicated on the axis for the burn-up is 60 hours. So we have logged less time than we estimated we would need. For example:
If this consistently happens, it tells us something about us overestimating the time we need on our tasks. However, perhaps of more concern would be the converse of this. For example:
Here, we have burnt-up more work than we burnt-down. This is because you can log more hours than you have estimated, for example:
However, you cannot have a negative time remaining. If you log more than you estimated, the remaining stays at zero. This means that the total represented by the time spent (green) line can exceed the total represented by the time remaining (red) line and indicates that work is taking longer than we estimated.
What happens if we increase our estimate because we find out, part way through, that a task will take longer than originally thought? This is where we see the upward spikes in the time remaining (red) line, as indicated above. The start point of the ideal work (grey) line and the start point of the burn-down line do not adjust on the axis to reflect that the additional work has been added, so this exacerbates the difference between the apparent burn-down progress and the amount of work completed on the burn-up.
If your estimates were exactly correct, then adding the time for the scope increases to the apparent burn-down value should then equal the amount of work logged in the burn-up. This isn’t the case in the example above (ie. 35h + 20h + 4h still does not equal 70h) because we are also suffering from under-estimating the time that the tasks will take.
Given this understanding of what the lines on the graph reflect, it appears that there is useful information to be had here about the accuracy of estimating, especially where we are taking longer on tasks than expected, which may need some further investigation. However, I would only be concerned if this were a regular trend and was matched by a similar discrepancy in the story points estimated and completed within the sprint.
One final thought is that we do, of course, want the burn-down to reflect reality and not just match the ideal progress line. So being honest about the progress of the work in a sprint is far more important and useful to the team than artificially logging work to achieve a perfect burn down.