HR Predictive Intelligence Workbench implementation

  • Release version: Xanadu
  • Updated August 1, 2024
  • 3 minutes to read
    • Summarize
    Summarized using AI
    This content was generated using new OpenAI-powered functionality. Results are provided on an as is basis and are not guaranteed to be accurate or complete.

    Summary of HR Predictive Intelligence Workbench implementation

    HR Predictive Intelligence Workbench enables ServiceNow customers to leverage machine learning to optimize HR business processes by training and implementing predictive models. These models augment existing workflows for improved case handling, knowledge management, and process automation within HR services.

    Show full answer Show less

    With the snpiwbhrcontent.admin role, users can explore pre-built use case templates, create, train, and tune machine learning models tailored to their HR data, and integrate the best-performing models into production workflows.

    Key Features

    • Use Case Templates: Includes guided and classic templates to simplify setup. Guided templates offer step-by-step configuration, while classic templates provide comprehensive setup details. Some templates come with auto-trained models for faster deployment.
    • Solution Definitions: Templates available when both Predictive Intelligence and HR are active. These solutions cover classification, similarity, regression, and clustering use cases to predict HR services, assignment groups, case categorization, knowledge gaps, case resolution time, and more.
    • Model Lifecycle Management: Supports creating, training, testing (single or batch), tuning, and integrating models. Allows multiple models to be refined to balance coverage and precision before deployment.
    • Prediction Accuracy Maintenance: Enables ongoing monitoring and retraining to manage prediction drift, ensuring models remain accurate as business conditions evolve.

    Practical Use Case Examples

    • Auto-categorize Email Cases: Automatically categorize incoming HR email cases to save time and reduce costs.
    • Predict HR Service or Assignment Group: Determine the correct HR service or assignment group for new cases to streamline case routing.
    • Recommend Knowledge Articles: Suggest relevant articles for HR cases or tasks to accelerate issue resolution and task completion.
    • Identify Knowledge Gaps: Detect clusters of HR cases lacking knowledge base coverage to prioritize content creation.
    • Estimate Case Resolution Time: Predict expected resolution times for HR cases using historical data for better transparency.
    • Profile-Based Recommendations: Provide personalized content and catalog item recommendations based on similar user profiles.

    Implementation Considerations

    Customers should begin by selecting suitable use case templates based on their HR data and business needs. Guided templates simplify initial setup, while classic templates offer more customization. Auto-trained models allow faster evaluation and integration but can be tuned or rebuilt if required.

    After training, customers should thoroughly test model predictions to select the best candidate for integration into HR processes. Continuous monitoring and maintenance are essential to adapt models to evolving HR service patterns and ensure sustained accuracy and value.

    You can use machine learning to optimize your business processes. You can train and implement HR Predictive Intelligence Workbench use cases to augment your existing application workflows.

    Explore common use case templates

    With the sn_piwb_hr_content.admin role, you can explore the use case templates and create predictive machine learning models. To create a machine learning model, you first select a pre-built use case template. You can use one of the following templates for setting up the use cases.
    • Guided templates include a comprehensive setup process to help you through implementation. Templates with available auto-trained models accelerate your setup process, by providing a pre-generated model based on your data.
    • Classic templates include a comprehensive setup information to help you through implementation. Leverage the existing templates to configure, test, and train the models based on your business requirements.

    When a template indicates Auto-trained model available, this means you can go directly to the evaluation phase of the use case setup. If the auto-trained model is acceptable, you can directly integrate the model with your business processes. Otherwise, you can tune this model or create another model. You may change the name and description of the use case later.

    Solution definitions

    These solution definitions are available as templates on instances where both Predictive Intelligence and HR are active. Create your own solution definition records to customize the behavior.

    Table 1. HR Solution Definitions
    Solution Type Solution Definition Description Implementation
    Classification Predict the HR service for incoming cases Predicts the correct HR service for cases. Guided
    Classification Predict the assignment group for incoming cases Predicts the correct assignment group for cases. Guided
    Classification Email Case Categorization Auto-categorizes the HR service for the email cases for improved productivity by saving time and costs. Guided
    Similarity Similar Closed HR Cases Recommends similar cases closed in the past to assist an HR agent for faster and better resolution. Classic
    Similarity User profile based recommendation Recommends top 3 relevant articles and catalog items based on users with a similar profile for content discovery and personalized experience. Classic
    Similarity Similar HR Cases and knowledge Automates the discovery of knowledge gaps in your knowledge bases and recommends insights into improving knowledge that is driven by demand. Classic
    Similarity Similar Knowledge Articles for HR Task Displays related articles to assist employees in completing the HR or Content or Campaign to-dos. Classic
    Similarity Similar Knowledge Articles for HR Case Uses ML to identify the most relevant knowledge articles to assist an HR agent for faster and better resolution. Classic
    Regression HR Case Resolution Time Determines the resolution time expected a case by analyzing similar closed cases in past for better visibility and transparency. Classic
    Clustering Demand Insights: HR Case Clusters Need Knowledge Identifies the case clusters that do not have knowledge and helps with filling the knowledge gaps in your knowledge base. Classic

    Use case creation phases

    Creating a predictive machine learning model involves several phases. After you create and train your model, evaluate and tune, test prediction results, and integrate the model with your business process. Use case model creation phases include:
    • Create and train models: Define parameters to create a model that you train based on your unique data. Create multiple models as you tune and refine your models by defining the right combination of coverage and precision to use.
    • Test your models: Get prediction results from your models to decide which one is best to integrate with your business process. To see if a model returns a correct result, you can use either the single or batch testing process.
    • Integrate the best model: Deploy the best model into your business process. After you determine which model returns the best, correct result, integrate it into production.

    Prediction accuracy maintenance

    You can manage prediction drift by retraining, modifying, or creating new solutions to reflect changes in your business conditions. Test and modify your business rule over time to ensure it works as desired across multiple consumption points and user persona.