Faster ETO Production with CRM-PLM Integration

The customer has been a global manufacturing and technology company offering a wide range of products and services in the areas of process management, climate technologies, network power, storage solutions, professional tools, appliance solutions, motor technologies, and industrial automation.

Every time a customer wanted to modify a product, they would submit an ETO (Engineer to Order) activity request through the CRM Tool, including the Affected Base Model, ETO Number, ETO Order Contact, Sales Order, Order Value, World Area, BU, and other attributes needed for the release process. Engineer will eventually need to manually update ETO details in the PLM Tool (Enovia 3DExperience Platform) using the CRM tool as part of the release process. Here, a lot of unnecessary effort is utilized, ultimately wasting time to release the ETO component in the PLM Tool.

Additionally, CRM data that is entered in an unstructured format had to be transformed manually into a structured format. Moreover, a manual procedure for updating CR (Change Requests) existed for Engineers to release the ETO part by following the change management process. As a result, there was loss of productive time of expensive engineer’s time, and manual update of ETO details had a high risk of human error.

Working with SLK, the customer was able to establish an integration between CRM and PLM (Enovia 3DExperience Platform), which would aid business end users in completing ETO projects more quickly.

In partnership with the customer, SLK developed an automation solution for handling Change Requests (CR) in the PLM (Enovia 3DExperience Platform) system, originating from CRM. The solution involved a scheduled automation task that ran every 30 minutes, retrieving ETO activity request details from the CRM tool and transferring them to the PLM tool. Additionally, an email notification was sent to the designated Engineer, providing instructions to proceed with the Change Management Process for releasing the ETO Part.

To ensure accuracy and efficiency, unstructured data from CRM was converted into structured data using NLP algorithms. This transformation significantly reduced the likelihood of human errors, as the CR properties were automatically populated with the correct information.