Another interesting metric related to work items is type distribution. Simply counting the number of items of each type over time, or as a snapshot can indicate workflow patterns and areas for investigation or simply provide context for other workflow metrics
If your organization uses many different customized work item types then we recommend theming into broad categories such as “requirements
” and “changes
” before analysis.
Our project data shows that there are often higher number of bugs and changes than requirements, this isn’t necessarily a bad thing. Bugs and Changes are normally smaller in scope and effort than requirements types and so there’ll typically be many bugs per requirement. There’s a difference between Development Bugs and “Escaped Bugs” which we describe in Bug Frequency.
Requirements heavy distributions indicate projects at an early stage of their workflow. Excessive bug heavy distributions indicate poor quality practices. Excessive change heavy distributions indicate unstable requirements and therefore too much up front requirements work.
How these distributions change over time can be particularly informative. For many teams we can identify their release cycles by the changes in their work item distributions when we see a pattern of:
Creation of a mass of detailed requirements types (i.e. Stories)
Followed by a lag of correlating bugs/changes a few weeks later
This is a standard, and healthy, iterative