The Blocking Analytics view helps you to analyze the most common reasons for blocking the cards by teams. This analytics renders blocking data in a pivot table format where you can slice and dice the constraints in the value-stream by visualizing the aggregated frequency of various blocking reasons against parameters like Queue, Card Type, Size, Property and so on for the selected region of the value-stream within the Temporal Range.
So, you can visualize the blocking data in Table, Bar Chart, Heatmap, Row Heatmap, or Column Heatmap while aggregating data by any of these methods: Count, Sum, Average, Minimum, Maximum, 80% Upper Bound, Sum as Fraction of Total, and so on.
For example, placing Reason as horizontal rows and Queue as a vertical column (as shown in the following image) and summarizing them based on Block Time would display average blocked time based on various Reason codes against different columns of the value-stream.
Configuring the Analytics
You can dissect the data by placing the parameter in row or column and the value as per those parameters will be displayed in the table, Alternatively, you can visualize the numbers by opting for Table Bar chart or Heatmap.
- Select the type of table or chart from the variety of options, such as Table, Bar Chart, Heatmap, Row Heatmap, and Column Heatmap.
- Select the method of summation such as Count, Sum, Average, Minimum, Maximum, 80% Upper Bound, Sum as Fraction of Total, and so on.
- Drag and drop attributes or other parameters like Reason, Queue and others to the Row or Column label and render the table or chart according to your requirement.
- Refine your data further by adjusting the Temporal Range or selecting the particular Filters and Value-Streams in the Filter pane. To know more about it, see this Help Page.