Training Days to Staff Predictor (beta) Models

The Days to Staff Predictor (beta) model enables you to minimize the Days to Staff field from the Days to Staff dataset. Days to staff is the number of days it takes to staff resource requests on projects based on historical data in your org. The Days to Staff Predictor (beta) model analyzes the different data related to this metric in your Days to Staff dataset and highlights the factors that influence it.

Tip:

We recommend you complete the Salesforce Gain Insight with Einstein Discovery trail before setting up the Einstein Discovery models in your org. For more information, see the Salesforce Trailhead website.

Dependencies and Limitations

For information on the dependencies and limitations of the Days to Staff Predictor (beta) model, see PS Cloud AI Analytics Overview.

Training the Model

You can retrain a model if you want to:

  • Improve your model's accuracy. Go to Performance Model Evaluation to view your model's accuracy metrics.
  • Change the variables that contribute to the prediction. Go to Settings to change the variables.

To retrain the existing model:

  1. Open the model from the Model tab.
  2. Click Settings.
  3. Select the variables that you think will generate the most accurate predictions for your projects.
  4. Click Train Model.

Deploying the Model

To deploy the model:

  1. Open the model from the Model Manager tab.
  2. Click , then select View Model Details.
  3. On the Model Settings tab, click the first Edit under Object Connection.
  4. Select Connect to a Salesforce Object, then select Resource Request from the object list and click Next.
  5. Map object fields to model variables as follows:
    Resource Request field mappings for the Days to Staff Predictor (beta) Model

    Model Variable

    Object Field

    Account Typepse__Resource_Request__c > pse__Project__r > pse__Account__r > Account Type
    Allow Candidates to Self-Nominatepse__Resource_Request__c > Allow Candidates To Self-Nominate
    Project Group Name Chain

    pse__Resource_Request__c > pse__Proj__r > pse__Group__r > Group Name Chain

    Project Manager Namepse__Resource_Request__c > pse__Project__r > pse__Project_Manager__r > Full Name
    Project Practice Name Chainpse__Resource_Request__c > pse__Proj__r > pse__Practice__r > Practice Name Chain
    Project Region Name Chainpse__Resource_Request__c > pse__Proj__r > pse__Region__r > Region Name Chain
    Project Stagepse__Resource_Request__c > pse__Project__r > Stage
    Resource Created Datepse__Resource_Request__c > Created Date
    Resource Practice Name Chainpse__Resource_Request__c > pse__Practice__r > Practice Name Chain
    Resource Request Group Namepse__Resource_Request__c > pse__Group__r > Group Name Chain
    Resource Request Primary Skillpse__Resource_Request__c > Primary Skill Minimum Rating
    Resource Request Region Namepse__Resource_Request__c > pse__Region__r > Region Name Chain
    Resource Request Suggested Resource Namepse__Resource_Request__c > pse__Resource__r > Resource Name
    Value Assignment Cost Ratepse__Resource_Request__c > Average Cost Rate Number
    Value Assignment Planned Bill Ratepse__Resource_Request__c > pse__Assignment__c > pse__Planned_Bill_Rate__c

Once you have deployed the model, add the Einstein Predictions component to the Resource Request Lightning page layout to view days to staff predictions on the Resource Request object. For more information on adding components to Lightning page layouts, see the Salesforce Help.