Estimated time to resolve HR cases

  • Release version: Xanadu
  • Updated August 1, 2024
  • 2 minutes to read
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    Summary of Estimated time to resolve HR cases

    The Estimated Time to Resolve a Case (ETTR) feature in ServiceNow uses machine learning to predict how long it will take to resolve HR cases by analyzing similar closed cases. This capability enhances transparency for employees and helps HR agents prioritize work and manage performance effectively. Managers gain insights useful for SLA management and improving case resolution processes.

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    Key Features

    • Machine Learning-Based Predictions: ETTR uses case attributes such as short description, category, priority, and assignment group to estimate resolution time.
    • Configurable Solution Definition: Customers can use the default ETTR regression model or adjust fields, filters, and training frequency to better fit their needs.
    • Multiple User Views: ETTR predictions are visible in the Employee Portal, Now Mobile app, Agent Workspace, Platform case lists, and case configuration views for admins.
    • Automated Model Training: The predictive model (mlsnsnhrcoreglobalhrcaseresolutiontime) auto-trains when required plugins are installed and system properties are enabled.
    • System Properties and Business Rules: Allows customization of ETTR display settings for employees and agents, as well as confidence level thresholds. The business rule “Predict Estimated Resolution Time” can be configured to fit organizational needs.
    • Resolution Time Metrics: Tracks actual resolution time, minimum and maximum ETTR in days, and point estimates to provide a comprehensive prediction interval.
    • Data Population for Accuracy: On upgrades, a scheduled job populates actual resolution times for existing cases, while business rules automate this for new cases.

    Practical Benefits for ServiceNow Customers

    • Improved Employee Experience: Employees receive clear expectations around when their HR cases will be resolved.
    • Enhanced Agent Productivity: Agents can prioritize their workload based on predicted resolution times and track performance more accurately.
    • Better SLA Management: Managers receive data-driven insights to monitor service levels and optimize HR case handling.
    • Flexible Configuration: Organizations can tailor the predictive model and display settings to align with their HR processes and reporting requirements.

    Determine the Estimated Time to Resolve a Case (ETTR) for a case by analyzing similar closed cases in the past for better visibility and transparency.

    Machine learning predicts the estimated time to resolve a case (ETTR) based on attributes of a case such as its short description, category, priority, assignment group, and so on. For more information about configuring the machine learning regression solution definition for ETTR, see HR PIWB template: Recommend estimated time to resolve

    To make predictions, you can use the existing ETTR solution definition or change some of the default settings such as the fields, a filter, and the training frequency.

    By analyzing the resolution time for similar closed cases in the past, the ETTR capability offers the following benefits:
    • Gives employees better transparency and set expectations on resolution time for their cases.
    • Helps agents in prioritization of work and measure performance.
    • Provides data that can help managers with insights into SLA management and estimated time to resolve for cases.

    ETTR for HR Cases

    On configuring Estimated HR Case Resolution Time (ml_sn_sn_hr_core_global_hr_case_resolution_time) and training the predictive model, you can see the HR Case Resolution Time option. See the Estimated time to resolve value from:
    • Employee portal view and Now Mobile view
    • Agent workspace
    • Platform view with a list of cases
    • Case configuration view for admins
    For more information, see Viewing ETTR predictions

    ETTR predictive model

    The Estimated HR Case Resolution Time (ml_sn_sn_hr_core_global_hr_case_resolution_time) is configured and the predictive model is auto trained when all the following conditions are met:
    • The Human Resources Scoped App: Core (com.sn_hr_core) plugin is installed.
    • The Predictive Intelligence for Contextual Search (com.snc.contextual_search_ml) plugin is installed.
    • The glide.platform_ml.auto_training.enabled system property is set to true.
    Business rules and system properties
    Verify the following system properties and business rules:
    • Use or configure the following system properties and corresponding values to display the ETTR values per your requirement:
      • ml_sn_sn_hr_core.COE_ETTR_display_agent
      • ml_sn_sn_hr_core.COE_ETTR_display_employee
      • ml_sn_sn_hr_core.estimated_resolution_time_confidence_level
    • Use or configure the Predict Estimated Resolution Time business rule per your business needs.

    ETTR model

    Regression solutions such as ETTR enable you to predict a point estimate and prediction interval. This capability informs the agent, employee, and service owners on the estimated resolution time for a case based on the time taken to resolve similar issues historically.
    • Actual resolution time: Stores the actual time of resolution of a particular case. This field stores the resolution time from opening to closing of the case.
      Note:
      When you upgrade, run this Populate Actual Resolution Time schedule job once for populating the actual resolution time for existing HR cases. For all upcoming cases, the business rule Populate Actual Resolution Time automatically generates the resolution time.
    • Max ETTR: Indicates the maximum estimated resolution time in days for case completion. Estimate is based on the time taken for resolving similar HR cases.
    • Min ETTR: Indicates the minimum estimated resolution time in days for case completion. Estimate is based on the time taken for resolving similar HR cases.
    • ETTR in days: Stores the point estimated resolution time in days for case completion.