Skill Recommendation components in Workforce Optimization for ITSM
Summarize
Summary of Skill Recommendation components in Workforce Optimization for ITSM
Workforce Optimization for ITSM enhances incident resolution by recommending relevant skills to agents. It leverages roles for access control, tables for storing skill data, configurable properties for tuning behavior, and a scheduled job to automate skill prediction and recommendation. This system uses both supervised and unsupervised machine learning models to identify the most suitable skills needed to resolve incidents efficiently.
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Key Features
- Roles:
- Skill Recommendation User (snsre.user): Allows viewing skill recommendation data.
- Skill Recommendation Admin (snsre.admin): Grants administrative capabilities to configure skill recommendation properties.
- Configurable Properties: Accessible via Skill Recommendation > Configuration, these properties allow administrators to:
- Enable or disable skill recommendations.
- Set the maximum number of skills predicted using supervised and unsupervised learning (default 3 each).
- Define how many similar resolved incidents to analyze for predictions (default 15).
- Specify the threshold for Predictive Intelligence to recommend a skill to an agent (default 20 predictions).
- Choose or replace Predictive Intelligence solution definitions for supervised and unsupervised skill predictions tailored to incident resolution.
- Scheduled Job: A daily job runs at 1 AM to analyze incidents closed the previous day, recommending skills that helped resolve those incidents for similar open cases.
- Data Tables:
- User Predicted Skill [snsreuserpredictedskill]: Tracks how often a skill is predicted for each user; entries not recommended in the last 60 days are automatically purged.
- Task Predicted Skill [snsretaskpredictedskill]: Stores predicted skills associated with incident types; records older than 60 days are automatically deleted.
Key Outcomes
By implementing these skill recommendation components, ServiceNow customers can:
- Improve incident resolution efficiency by assigning the most appropriate skills to agents based on historical data and machine learning models.
- Customize and control the prediction parameters to align with organizational needs and incident types.
- Maintain up-to-date skill recommendations through automated daily updates and data management.
- Empower administrators and users with role-based access to monitor and manage skill recommendation processes securely.
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] |
|