---
schema_version: "1"
id: bc7c8cc7f11dcd6c66af50aec6bd0190bd872bce4b9c42b3992d99abbbb08ab6
title: Enable the Propensity to Escalate Insight Component
collection: admin
version: current
locale: en-us
portal_url: https://docs.salesforce.com/admin/current/en-us/service/264-0-0/service_intelligence_insights_setup.md
canonical_url: https://help.salesforce.com/s/articleView?id=service.service_intelligence_insights_setup.htm&release=264.0.0&type=5
source_site: help.salesforce.com
content_type: documentation
content_hash: cea1757ccdff7ca723e48be81d74bf445d8ad939b2cf3d9ae071b1d8aa2d7558
description: For the Propensity to Escalate model to work as expected, you must modify the associated batch data transformation to integrate the Einstein predictive model.
products:
  - Service Cloud
release: "264"
---
# Enable the Propensity to Escalate Insight Component

For the Propensity to Escalate model to work as expected, you must modify the associated batch data transformation to integrate the Einstein predictive model.

### Required Editions

<table class="slds-table slds-table_bordered slds-max-medium-table_stacked slds-m-bottom_small edition"><colgroup><col></colgroup><tbody><tr class=""><td class="slds-cell-wrap" style="vertical-align:top;"><a href="https://help.salesforce.com/s/articleView?id=service.service_editions_reference.htm&amp;language=en_US" target="_blank">View supported editions</a>.</td></tr></tbody></table>

1. From the app launcher, go to **Data Cloud** **\>** **Einstein Studio**.
2. Open the **Predicted is\_escalated\_\_c** Einstein studio model, and click **Activate**.
3. Go to **Data Transforms**, and open the **SI Scoring DMO**. Then select **Edit** from the dropdown menu. The mapping for the batch data transform displays.
4. To add the AI model node, you must edit the **SI Scoring DMO** batch data transformation.
    1. Click the **Rename** transform node and navigate to the bottom edit panel.
    2. From the edit panel, scroll down to the last transformation **Dummy isEscalated Prediction**, and delete it.
    3. Next, delete the **Output** transformation. You’ll create a new output node in later steps.
    4. Add a AI model after the **Rename** transformation.
    5. From the model names, select the predictive model you created earlier-- **Predicted is\_escalated\_\_c**, and click **Next**. In the **Map Fields** tab, map the appropriate input fields (#Case Age, Case Type, Channel, #EscalatedCases, Priority, CalculatedQueue). (Optional) In the **Modify Output** tab, add the number of top predictors needed in the model prediction. Click **Apply** .
    6. From the AI model, add an output node. Name the output DMO, and select Case ID as your primary key, and Key Qualifier Case as your FQK.
    7. Scroll down the new DMO fields, and make sure the following prediction-based fields are present: #Predicted Escalated, Predictor 1, Predictor 1 Impact, Predictor 2, Predictor 2 Impact. Click **Apply**.

After you’ve completed these modifications, the batch data transformation integrates the Einstein predictive model to generate predictions.