Customer

Industry
Digital Automation and Energy Management
Use case
ERP Migration
Users
Business User

Multinational company specializing in digital automation and energy management. The company integrates world-leading processes, energy technologies, and end-point, connecting products, controls, software, and services via the cloud across the entire product lifecycle.

Challenge

The company had a 30+ year homegrown ERP system that was hard to maintain and didn’t meet business demands. To mitigate these issues and improve the process, the customer was set to decommission the legacy system and transition all related business processes to SAP S/4HANA. As part of this, the customer needed to migrate all existing open sales orders from the legacy system to SAP S/4HANA.


The main challenges:

  • Large amount of orders and fulfillment cases
  • Each case required individual migration approach and technical solution
  • Complex data profiling, extraction, and transformation
  • Many dependencies in the upstream and downstream systems that require subsequent corrections
  • Very short downtime window for production load

Solution

The project team created a set of projects using the DataLark platform to accommodate the highly complex migration scenarios. The process didn’t require coding, as DataLark already comes with pre-build plugins and connectors that can be easily utilized for orchestrating the required data extraction, transformation and upload steps. The approach ensured data integrity across the entire environment comprising multiple interconnected systems and applications.

Project Goals

The project's primary goal was to migrate all open sales orders from the legacy sales management system to SAP S/4HANA (in US and Canada) in a phased manner.

Data Validation
To ensure that loaded data was aligned with the data from the original data source.
Security
As sales orders had very sensitive financial information and customer data.
Performance
As all migrations had to be performed during a limited downtime window to reduce the impact on the ongoing business activities.
Project Efforts
The team developed a plan where each migration stage progressively followed the project roadmap. The team included QA Engineers, SAP SD Consultants, SAP MM Consultants, SAP PP Consultants, SAP MDM Consultants, a Project Manager, and a Solution Architect.
Data Profiling and Extraction
The team determined use cases for each sales order, conducted a sanity check of source data, and created a pull of orders that had to be migrated, including system backups.
Data Transformation and Load
The team transformed the source data based on the translation and mapping rules configured in DataLark into the format suitable for SAP. All sales orders are loaded to S/4 using DataLark connectors and standard SAP API.
Validation and Reconciliation
The implemented solution validated migrated orders, evaluated and compared values from three sources: initial data from the legacy system, transformed data, and migrated data in S/4HANA. Such an integrated approach increased system transparency and allowed for the creation of reports that can be used for further analysis and review by auditors.
Additional Remediation Activities
After the first stage of sales orders migration, the team using DataLark repointed existing objects in all other related applications to reference newly created sales orders in SAP S/4HANA instead of old orders from the legacy system.
Results
The client achieved remarkable outcomes
The tool ensured precise data migration, preserving the integrity of critical business information and averting any loss or corruption.
DataLark streamlined the migration process for a fast SAP solution deployment, enabling the organization to swiftly leverage the benefits of SAP functionalities.
The implementation of DataLark led to minimized downtime, allowing uninterrupted business operations during the migration process.
The tool enabled the seamless migration of historical data, ensuring that the organization possessed a comprehensive record of its business operations within the SAP system.