Recommendations and similar candidates in ERP Semantic Mining

The record for each candidate in ERP Semantic Mining displays information on suggested next steps and similar candidates to help you in replatforming an ERP (Enterprise Resource Planning) app.

Important:

Starting with the Zurich release, ERP Semantic Mining is being prepared for future deprecation. It will be hidden and no longer activated on new instances but will continue to be supported.

Recommended actions for candidates

When you view a candidate, ERP Semantic Mining displays the number of recommended actions or next steps to take. The candidate details also have a Recommendations tab where you can view the suggested actions, and select them to open the associated app on the ServiceNow AI Platform.

For example, you may have to create a workflow in Workflow Studio for one candidate, update an integration spoke for another, and read an extraction table for a third candidate.

Each recommended action has an estimated effort, which is a numerical score that assesses how well the ServiceNow AI Platform has matching functionality. Green actions require little-to-no effort, while red actions are more difficult.

For more information on recommended actions, see Check candidate recommendations in ERP Semantic Mining.

Similar candidates in candidate details

For each candidate, ERP Semantic Mining displays a Similar candidates tab, which lists each similar candidate, a numerical score to represent how closely the two candidates are related, and a link to other similar candidates.

Similar candidates are helpful when planning how to best replatform a legacy app. When you replatform a custom app from the system of record, you don't have to replicate the old app exactly. Use the replatforming process to design a better app. For example, an app that addresses the needs of multiple similar candidates in a single, new app built using low-code tools on the ServiceNow AI Platform.