Skill Recommendation components in Workforce Optimization for ITSM
Summarize
Summary of Skill Recommendation components in Workforce Optimization for ITSM
Workforce Optimization for ITSM leverages skill recommendation to enhance incident resolution by predicting relevant skills for agents. This is achieved through roles, configurable properties, scheduled jobs, and dedicated tables that store skill prediction data. The system uses both supervised and unsupervised machine learning methods to recommend skills that match incident requirements, enabling faster and more accurate incident handling.
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Key Features
- Roles:
- Skill Recommendation User (snsre.user): Allows viewing of skill recommendation data.
- Skill Recommendation Admin (snsre.admin): Grants rights to configure skill recommendation properties.
- Configurable Properties: Accessible via Skill Recommendation > Configuration, these properties control the behavior of skill recommendations, including:
- Enabling or disabling skill recommendations.
- Setting maximum numbers of skills predicted by supervised and unsupervised learning methods.
- Defining the number of similar resolved incidents used for predictions.
- Threshold for how many times a skill must be predicted before recommending it to an agent.
- Specifying Predictive Intelligence solution definitions for supervised and unsupervised skill predictions, allowing customization with user-created models.
- Scheduled Job: The system runs a daily job at 1 AM that processes incidents closed the previous day, recommending skills used in those resolutions to assist with similar open incidents.
- Tables:
- User Predicted Skill [snsreuserpredictedskill]: Tracks how often skills are predicted for each user. Entries not recommended within 60 days are purged automatically.
- Task Predicted Skill [snsretaskpredictedskill]: Stores skills predicted to resolve specific incident types, with records older than 60 days being automatically deleted.
Practical Benefits for ServiceNow Customers
By using these components, ServiceNow customers can automate and optimize the assignment of skills to agents, ensuring incidents are resolved by appropriately skilled personnel. The configurable properties allow tailoring recommendations to organizational needs, while the scheduled job maintains up-to-date skill data based on recent incident resolutions. This results in improved incident resolution efficiency and better workforce utilization.
Workforce Optimization for ITSM uses roles to administer skill recommendation, tables to store skill data, and properties to modify default behavior, and scheduled job to recommend skills in configurable Workforce Optimization for ITSM.
Roles
| Role title [name] | Description | Contains roles |
|---|---|---|
| Skill Recommendation User [sn_sre.user] | Grants rights to view skill recommendation tables. | wfo.user |
| Skill Recommendation Admin [sn_sre.admin] | Grants administrative rights to edit the properties for skill recommendation. |
|
Properties
Navigate to to configure these properties.
| Property | Description |
|---|---|
Enable skill recommendation. sn_sre.enable_skill_recommendation |
Enable this property to start recommending skills for agents.
|
Maximum number of skills to predict based on supervised learning. sn_sre.max_supervised_skills |
Using supervised learning, the maximum number of skills to predict for each
incident ordered by confidence of prediction.
|
Maximum number of skills to predict based on supervised learning. sn_sre.max_unsupervised_skills |
Using unsupervised learning, the maximum number of skills to predict for each
incident ordered by confidence of prediction.
|
Number of resolved similar tasks to use for predicting skills. sn_sre.number_of_similar_incidents |
The number of resolved similar incidents to use to predict skills using
supervised learning, ordered by confidence of prediction, to resolve similar types
of incidents.
|
Number of times Predictive Intelligence must predict the same skill for an agent before recommending it for the agent. sn_sre.user_predicted_skill_threshold |
The number of times Predictive Intelligence must predict the same skill for
an agent before recommending the skill for the agent.
|
Similarity solution definition to recommend skills from similar incidents. sn_sre.unsupervised_solution_definition_for_incidents |
Name of the Predictive Intelligence solution definition used for predicting
skills to resolve incidents using unsupervised learning. If you have created your
own solution definition, you can replace the default one with the one you have
created.
|
Similarity solution definition to recommend skills for incidents. sn_sre.supervised_solution_definition_for_incidents |
Name of the Predictive Intelligence solution definition used for predicting
skills to resolve incidents using supervised learning. If you have created your
own solution definition, you can replace the default one with the one you have
created.
|
Scheduled job
| Scheduled job | Description |
|---|---|
| Start skill prediction | Runs the job every day at 1 AM on all incidents that were closed the previous day. Recommends the skills used to close the incidents to resolve similar open incidents. |
Tables
| Table | Description |
|---|---|
| User Predicted Skill [sn_sre_user_predicted_skill] |
|
| Task Predicted Skill [sn_sre_task_predicted_skill] |
|