- Release notes
- Before you begin
- Getting started
- Integrations
- Working with process apps
- Working with dashboards and charts
- Working with process graphs
- Working with Discover process models and Import BPMN models
- Showing or hiding the menu
- Context information
- Export
- Filters
- Sending automation ideas to UiPath® Automation Hub
- Tags
- Due dates
- Compare
- Conformance checking
- Root cause analysis
- Simulating automation potential
- Triggering an automation from a process app
- Viewing Process data
- Creating apps
- Loading data
- Customizing process apps
- Publishing Dashboards
- App templates
- Additional resources
Root cause analysis
When analyzing a business process, you may want to determine which fields are most associated with a certain outcome. This should help you to act on the root causes associated with the outcome. For example, in the Purchase-to-Pay process, you may want to analyze the influence of purchase orders that have maverick buying tags assigned.
With Root cause analysis, you can compare the influence of case fields on a certain behavior to find significant data influencers for specific process situations. A set of cases is defined based on the period filter. This selection is called Reference cases. Within this set of cases, you can select the behavior that you want to analyze. For example, cases with a certain tag. This selection is called the Selected cases. The influence of a field is based on the number of occurrences in the selected cases.
Use the Root cause analysis dashboard to compare the influence of case properties on a set of selected cases within a reference set of cases.
Follow these steps to perform a root cause analysis.
|
Step |
Action |
|---|---|
|
1 |
Use the Period filter to define the set of Reference cases. |
|
2 |
Select Root cause analysis in the menu on the left of the dashboard. |
|
3 |
Use the Filter panel to create filters that define the set of Selected cases, which are the cases you want to analyze the influence on. |
|
4 |
Select the field you want to use for your analysis from the selector. |
The Node limit slider enables you to reduce the complexity of the Root Cause Analysis tree, which increases the readability of the graph. By default, the detail of the Root Cause Analysis is automatically determined. You can use the Node limit slider to change the number of nodes shown.
Cases, for example, Purchase order items, or Incidents.
The above image shows that Maverick buying for example occurs less in the 2800 - BestRun China company (-2%) than in other companies in the reference data, and that Maverick buying occurs more in the 5000 - BestRun Japan 5000 company (10%) than in other companies in the reference data.
The value (%) in the start node is the global baseline percentage, whereas the value (%) in the other nodes is the Influence (%) which represents the deviation of the node’s selected percentage from the global baseline percentage.
Show significant influencers option
The Show significant influencers option enables you to zoom in by displaying the cases with a statistical significant influence. This should help you identify the cases that have the most impact on the selection. This statistical significance is computed from both the Influence (%) and the amount of cases a certain field has.
If desired, you can add more layers to the Root cause analysis. See the illustration below.
In the above example, the combination of fields results in a set of Selected cases that has not enough (relevant) data to determine influencers. In this case, you can narrow down the set of Reference cases by adding a filter on the dashboard.
The illustration below shows the result.
When hovering over the fields in the tree, the Influence (%), the Reference cases, and the Selected cases are displayed.
Below is a description of the metrics.
|
Metric |
Description |
|---|---|
|
Influence (%) |
The deviation of the Selected cases from the Reference cases. |
|
Selected cases |
The number of cases for the field in the total set of Selected cases. |
|
Reference cases |
The number of cases for the field in the total set of Reference cases. |
Assume a total of 100 cases. A filter is applied to sort out cases that exceed a throughput time of 30 days. The filter results in 20 cases, equating to 20% of the total. This percentage is set as the "Reference %" or essentially, your baseline.
When aggregating, for instance, by Supplier, an influence percentage is displayed.
Consider Supplier X having a cumulative total of 30 cases, of which only five cases exceed a throughput time of more than 30 days. This means that 17% of the cases related to Supplier X have a long throughput time.
The influence percentage is computed based on the difference between the calculated % of cases exceeding the set throughput time (in the given example, 17%) and the Reference % (20%) . In this scenario, the influence percentage equals -3% (17%-20%= -3%).
Next, consider Supplier Y has a total of 5 cases. 3 of these cases have a throughput time that exceeds 30 days (60%). In this scenario, the influence percentage of this would be 40% (60% - 20% = 40%).
