Proactive problem management and Resolution insights overview
The Proactive problem management workspace is a purpose-built console to support problem coordinators in end-to-end activities to identify valuable problem investigations. To access this workspace, click More > Workspaces > Proactive problem management in BMC Helix ITSM.
The following video illustrates how you can use the Proactive problem management workspace in BMC Helix ITSM Insights.
Related links
Proactive problem management dashboard
If your organization has a license of BMC Helix ITSM Insights, as a problem coordinator, you can access the Proactive problem management workspace from BMC Helix ITSM. This workspace enables you to run analytics on incident data and leverage AI clustering technology to identify patterns of recurring incidents.
The Proactive problem management dashboard displays recurrent incidents as clusters in the form of a heat map and a list. You can also view filters, list of jobs available, and a list of presets. You can download the heat map or the list view as a CSV or PDF file. Starting with version 23.3.01, Major Incident is added as a required system field in the data set as a result of which Major Incident is added as a filter in the dashboard.
If you do not see major incident details in List view of the Proactive problem management dashboard, see Troubleshooting.
When you log in for the first time, you must create a one-time or recurrent job in the Proactive problem management settings page to view incident clusters in the dashboard.
Permissions
To be able to access the Proactive problem management dashboard, you must have the Problem Master, Problem User, or Problem Submitter permission.
Visual impact of incident clusters in Heat Map
The Heat Map tab is selected by default and displays clusters based on the job configured. The tiles in the heat map display the following details:
- Cluster name
- Number of incidents in that cluster
- Percentage of incidents within a cluster compared to the number of incidents on which the job is run
- Number of problem investigations related to the incidents in the cluster
Clusters with higher percentage of incidents indicate important clusters that need to be prioritized for problem investigation.
A heat map visualization displays a tile of colored rectangles, with each rectangle representing a cluster. Heat map is a graphical way to allow users to quickly grasp the impact of variables. By observing how cell colors and size change across the heat map, you can observe if there are any patterns in value for one or both variables.
To select the metric that determines the size of each rectangle, click Size by and select one of the following options:
Option | Description | Calculation |
|---|---|---|
Number of incidents | Displays the cluster size based on the number of incidents. | NA |
Total resolution time | Displays the cluster size based on the total resolution time. | Total resolution time = ∑(Last Resolved Date-Submit Date) |
Total effort | Displays the cluster size based on the total effort spent. | Total effort = ∑(Total Time Spent) |
To customize the number of clusters in the heat map, in the Max clusters shown field, specify how many clusters you want to view in the heat map. You can specify any value between 5 and 50. To view the clusters and its pertinent information on the heat map, the maximum number of clusters is limited to 50.
You can configure the default number of clusters in the heat map from the settings menu. To learn more, see Configuring-proactive-problem-management-settings.
To select the variable that determines the color of each rectangle, click Color by and select one of the following options:
Option | Description | Calculation |
|---|---|---|
Average priority | Displays the color of clusters based on their average priority. | Average priority = ∑(numeric value of priority of all incidents) / ∑(Incidents in the cluster) |
Trend | Displays the average daily trend per cluster, that is, the average percentage daily increase or decrease in number of incidents created within a cluster. A positive trend (0 to 100%) is shown in red, and a negative trend is shown in blue. | NA |
Cluster quality | Displays the colors of clusters based on their quality score. High quality clusters are shown in green, and low quality clusters are shown in red. | NA |
The Color by list displays the fields that you select in Group by of one-time and recurrent jobs. Use the Color by list to group clusters and analyze incidents based on your selected fields while performing problem investigation.
You can filter the clusters based on the quality of the clustering job by moving the Cluster quality slider. A higher number in the slider displays clusters that have a high quality score on the heatmap. The default quality range in the slider is 60-100, that is, clusters that have a quality score between 60 - 100 are displayed on the heatmap.
You can configure your preferred minimum range in the slider from the settings menu. To learn more, see Configuring additional stop words, number of jobs, and default number of clusters.
Click on a cluster to get a drill-down view of the cluster or to create a problem investigation.
List view of incident cluster details
The List View displays the incident clusters in a tabular format for a detailed view. The view displays incident clusters, number of incidents, trend, total effort, total resolution time, average priority, level 1 grouping (if level 1 is not machine learning in the job configuration), and level 2 grouping (if selected in job configuration), the number of problem investigations related to the incidents in the cluster, and the cluster quality.
Starting with version 23.3.03, the following columns are added in List view:
Column name | Description | Calculation |
|---|---|---|
% of incidents in job | Displays the percentage of incidents within a cluster compared to the number of incidents on which a job is run. | (Number of incidents in the cluster * 100) / Total number of incidents in the PPM job |
Average resolution time (hours) | Displays the average time it took for the service desk agents to resolve each incident in the Proactive problem management cluster. | Average resolution time (hours) = Total resolution time / ∑(incidents in the cluster) |
Average effort (minutes) | Displays the average effort it took for the service desk agents to resolve each incident in the Proactive problem management cluster. | Average effort (minutes) = Total effort / ∑(incidents in the cluster) |
Starting with version 23.3.01, Major Incident is added as a default column in the List view. The column displays Yes for a cluster that contains at least one major incident, and Candidate for a cluster that contains at least one major incident candidate.
The fields that you select in Group by of one-time and recurrent jobs appear as columns in List view. You can enable the columns by using the Visible columns filter.
To filter clusters that contain major incidents or major incident candidates, in the Major Incident filter, select Candidate and Yes.
Alternatively, you can sort the Major Incident column by using the 
icon in the table header.
You can sort the table based on the ascending or descending order of cluster quality and other metrics by using the icon in the table header.
To refresh the clusters in this view, use the 
icon.
Incident analysis within clusters
When you click on a cluster, the drill-down view for the cluster is displayed. You can view the following metrics:
- Total incidents in the cluster
- Total effort in minutes
- Total resolution time in hours
- Average priority
- Percentage of incidents in the cluster.
You can select an incident cluster, and then create a problem investigation or relate it to an existing problem investigation.
To view the major incidents or the major incident candidates in the cluster, from the Visible columns filter, enable the Major Incident column. After you enable the column, you can sort it by using the icon in the table header.
The Grouped by resolution insights tab displays incident clusters that have a similar resolution. Every resolution insights cluster displays the number of associated incidents and the knowledge articles used for resolving incidents, if available.
The following video illustrates how you can use the resolution insights capability in BMC Helix ITSM Insights.
https://www.youtube.com/embed/DyZn9MavVGQ
If knowledge articles are referred to while resolving incidents, the service desk agent enters the knowledge article ID and other details in the resolution note of incidents. The Knowledge referenced column displays the knowledge articles that are mentioned in the incidents' resolution notes. If you have the Knowledge User permission, you can view the associated knowledge article in BMC Helix ITSM. Click the link in the Knowledge referenced column to view the knowledge article.
The Resolution insights quality column displays the similarity score of a resolution insights cluster in percentage. A higher percentage indicates a good quality cluster. You can enable the column from the Visible column list.
Click to see how Resolution insights quality is calculated.
You can view the incidents related to a resolution insights cluster by clicking the link displayed in the #incidents with this resolution column. The resolution insights cluster is displayed in a new tab that lists the incidents that have a similar resolution.
You can create a problem investigation from incidents in a resolution insights cluster. For more details, see Managing-clusters.