During a recent project, it became evident once again how significantly an unsuitable migration approach can negatively impact both the project itself and the validation activities around it. One of the most critical issues is the incorrect sequencing of migrations and test activities across the system landscape, from Sandbox to Development, Quality and ultimately Production. 

Too often, migrations executed in DEV or Q systems are treated as “test runs” and simultaneously interpreted as evidence that the later production migration will succeed in the same way. This is a fundamental mistake. Non-productive environments differfrom productive landscapes for many reasons, even though in regulated GxP environments this theoretically should not be the case. Some differences are intentional and necessary, others are historical, technical or operational. 

This creates a false sense of security. A technically successful migration in Q does not automatically mean that the production migration will deliver the same result. Productive systems introduce additional factors such as: 

• significantly larger data volumes
• productive interfaces and real-time communication
• more complex authorization and operational processes
• actual batch processing and background workload
• tighter cutover windows
• higher requirements for data integrity and availability

Especially in regulated GxP environments, such an approach rapidly increases project, compliance and operational risks. The final cutover can quickly become “compliance by visibility” instead of a planned, risk-based and validated system migration. 

A robust migration strategy considers these differences from the beginning and consistently aligns testing and migration activities with production-like conditions, realistic workload scenarios and a validation-ready evidence strategy. 

Our whitepaper explains how SAP RISE migrations and similar datacenter moves can be executed in a compliant, risk-based manner with significantly lower project uncertainty.

Request it at hello@csvlab.com.