About this report
The Program Increment Heat Map report displays features and stories, represented as nested rectangles, for a selected PI. Each rectangle has an area proportional to a specified dimension of the data, in this case, level of effort (LOE) points. The larger the rectangle, the more LOE points are tied to it. The tiling algorithm that defines sizing of the rectangles tries to keep an aspect ratio close to one (1), meaning that a story with 2 LOE points will be represented by a rectangle that is twice as large as a story with 1 LOE point; a story with 8 LOE points will be represented by a rectangle that is eight times as large as a story with 1 LOE point.
Hover over any feature or story rectangle to display a count of the LOE points assigned to it. You can also click a feature name anywhere on the map to move it to the top-left corner of the map.
The report is beneficial to product owners and RTEs for assessing the LOE points assigned to features and stories by visually comparing the rectangle sizes.
- Select the Reports icon from the left Navigation menu.
- Start typing the report's name in the Search box.
- Once found, select the report.
Note: You can also use the categories on the left to search for the needed reports.
- PI must exist in the system and be tied to a program.
- Features must be created and tied to a PI.
- Stories must be created and tied to features.
- LOE points must be assigned to stories.
How are report values calculated?
- LOE points are entered for stories via the Story Grid/New Story panel
- Feature LOE points = the sum of story LOE points assigned to the feature
- The tiling algorithm tries to keep the aspect ratio close to one (1)
How to interpret this report
When looking at this report, analyze the size patterns of the rectangles, to see if any features or stories are disproportionately large when compared to others. Do the very large features and stories truly represent high-priority work, or are they impediments that will get in the way of higher priorities? Is the work chunked into manageable loads, or are certain features and stories too large to work with? For example, the feature below is comprised of 2 large stories, which should be examined to decide if further breakdown is needed:
In this next example, all of the stories are approximately the same size, meaning the workload is evenly distributed into manageable chunks: