Process Control Chart | Targetprocess - Enterprise Agility Solution

Process Control Chart

Process control chart shows cycle time distribution for completed entities (user stories, features, bugs, tasks, requests) within a certain timeframe.

In Targetprocess there are several more kinds of reports used to track Processing Time and Cycle Time metrics. More on them: Processing Time and Cycle Time Reports

To access this chart, please navigate main (top) menu -> Reports -> Process Control.

As in the screen below, you can see all the user stories that have been completed in the last 3 months.

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Process control chart has powerful filters. For example, you can create a query to extract all the entities by their tags or by their custom fields from the latest release. Or use other filtering options, there are lots of them (see how to use filters in new reports).

Each small bubble is a standalone user story. On mouseover you can see its name and lead/cycle time. Click the bubble for complete details.

There are 3 lines that break the chart into several areas. The lowest line is a median. It represents how many days does it typically take to complete a user story.

The other two lines are control limits. If you see user stories between the warning limit and the control limit lines, this is suspicious. If a user story goes beyond the control limit line, this is a really bad thing, and you should investigate why it took so many days to complete. These limits are calculated statistically; they depend on the overall distribution of stories in the chart.

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Let’s check some real cases. See the odd user story on top of the picture below? It’s way beyond the control limit line. The other one (34 days) is suspicious.

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So why it’s taken 80 days to complete the first user story? Obviously, there has to be a reason. We can click right on the bubble for details:

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Aha, the story had 15 bugs. OK, then we click the Flow tab for even more details:

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The story stayed for too long in the In Dev state. Most likely, the developers haven’t paid enough attention to it. We don’t know for sure, but now we know at least what we need to find out: why so many bugs, and why it’s taken that long to fix them.

The other story which took 34 days to complete looks suspicious. Click on the bubble for more details:

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Again, too many bugs. What do we see on the Flow tab?

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There were quite a few switches between states and some moderate delays, but it wasn’t as dramatic as in the previous user story. Still, it is interesting where do all those bugs come from in this rather simple user story.

As you can see, Process Control Chart clearly shows which stories demand your attention. Then you can dig into details.

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