This documentation supports the 25.1 version of BMC Helix ITSM Insights, which is available only to BMC Helix customers (SaaS).To view an earlier version, select the version from the Product version menu.

Best Practices for BMC Helix ITSM Insights


We recommend that you review best practices for the BMC Helix ITSM Insights product prior to implementing the product or a feature.

Best practices for proactive problem management

We recommend the following best practices for proactive problem management:

  • Select incidents for a specific duration to avoid unnecessary incidents getting clustered.
  • As issues for each product or service are different, select an appropriate Group by level 1 field based on your organization structure, service ownership, technical stack ownership, or other defining fields.

    Click to view the group by recommendations for clustering 

    Scenario

    Level 1 Grouping

    Level 2 Grouping


    Machine learning

    Fields

    Inputs for machine learning

    Field names

    Machine learning

    Fields

    Inputs for machine learning

    Field names

    Ticket analytics- global view of problems

    ✅️


    Summary


    NA

    NA



    Ticket analytics- global detailed view

    ✅️


    • Summary
    • Description (Detailed description)






    Ticket analytics- problems per support group


    ✅️


    Assigned Group

    ✅️


    Summary


    Ticket analytics- problems per service, resolution product name or category


    ✅️


    Any of the following fields:

    • Service (ServiceCI)
    • Resolution category 1 (Resolution Category)
    • Product Name
    • Category

    ✅️


    Summary


    Resolution analytics – Global view of resolutions

    ✅️


    Resolution notes


    NA

    NA



    Resolution analytics – Resolutions per support group​


    ✅️


    Assignee - Support group (Assigned Group)

    ✅️


    Resolution notes


    Resolution analytics – Resolutions within each Resolution Type​


    ✅️


    Resolution type

    ✅️


    Resolution notes


    Resolution analytics – Resolutions for each Service or Product name or Category​


    ✅️


    Any of the following fields:

    • Service (ServiceCI)
    • Product Name
    • Category

    ✅️


    Resolution notes


    Resolution analytics – Resolutions types each Service or Product name or Category​


    ✅️


    Any of the following fields:

    • Service (ServiceCI)
    • Product Name
    • Category


    ✅️


    Resolution type

  • For better quality clusters with clear boundaries, we recommend adding Group by fields.

    Important

    The quality of the clusters and clustering job depends on the homogeneity of the input incidents, which means how similar the incidents are with respect to each other. Homogenous (similar) incidents result in high-quality clusters.

    Following are some of the common fields used for grouping:

    • Service
    • Company
    • Region
    • Product name
    • Operational categorization 1, 2 and 3
    • Product categorization 1, 2 and 3
    • Custom fields


  • If you are unable to define cluster boundaries and mixed clusters (across technical stacks, services, or organizations) are acceptable, then you can select only clustering fields. However, this option is not recommended.
  • When selecting the number of clusters, we recommend selecting the Let the system find no. of clusters check box. The system automatically selects an optimal number of clusters. However, when you know the number of clusters from prior execution runs or domain knowledge, you can specify a value. 

    Important

    When a job is run by a user or multiple users having the same permissions, the number of clusters generated may vary with every job run even with the same job parameters. The unsupervised machine learning algorithm used here is non-deterministic, which means it may not generate the same clusters for every job run.

    Click to view the recommended cluster number based on the incident size

    The following table provides an approximate range of incident size and the corresponding cluster number to be selected. It may improve the job execution time depending on the homogeneity (similarity) of the input incidents that the algorithm processes. 

    Approximate incident size range

    Recommended cluster number

    Upto 100

    10

    100 to 250

    15

    250 to 2500

    25

    2500 to 5000

    50

    5000 to 10000

    100

    10000 to 100000

    200

    More than 100000

    500

  • We recommend using stop words for the selected language so that frequently used words in incidents (for example, company name, region) which should not be used for generating cluster names can be ignored.
  • Provide appropriate user permissions to users so that they can create problems and analyze incidents.
  • Define your schedule based on the problem management process in your organization. The schedule for clustering jobs can be weekly or bi-weekly or monthly based on your review cycles for problem identification. Typically, the lookback period for each of these schedules is the previous 1-4 weeks of data. 
  • We recommend configuring the one-time job first before configuring the recurring job. If the desired job quality score is achieved, you can replicate the settings in the recurring job. 
  • After running a job, evaluate the job quality score to determine if the clusters are formed as expected. You can tune the data selection, group by fields, number of clusters, and stop words to achieve the required quality score and the right clusters.
  • Use filters to select the data you are interested in clustering. We recommend you preview the filters in the Selected filters area before applying them.

    Important

    You can preview up to 100 filter rows in the Selected filters area.

  • The BMC Helix ITSM Insights algorithm groups incidents based on the fields that you select. For best results in creating clusters, select fields that contain a short description of the incident, and avoid the fields that contain long, unnecessary details.

Best practices for real-time incident correlation

We recommend the following best practices for real-time incident correlation:

  • Select appropriate Group by fields for incident correlation configuration based on your company structure, organization structure, service ownership (business service), and ownership of technical stack. Adding group-by fields improves the initial grouping of incidents. We recommend grouping by Assignee - Company (Assigned Support Company)Assignee Support group (Assigned Group) and Company to create clusters with all incidents related to your company and assigned group. Availability of all incidents of your assigned group and company helps you manage their relationships effectively. 
  • Select textual fields such as Summary, Description as clustering fields. 
  • To obtain cohesive clusters, we recommend setting the similarity threshold should be in the range of 0.6 to 0.8.
  • Avoid changing the configuration often during a run as it clears the existing clusters. 
  • To improve performance while generating clusters, we recommend excluding the Description (Detailed Description) field from the configuration.
  • The BMC Helix ITSM Insights algorithm groups incidents based on the fields that you select. For best results in creating clusters, select fields that contain a short description of the incident, and avoid the fields that contain long, unnecessary details.

 

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