Informatec strengthens its Data & AI expertise with Databricks With the Databricks Lakehouse Platform, Informatec unifies modern data engineering, BI, and AI capabilities to help companies accelerate innovation and create measurable business value.
Success Story SKAN AG With Informatec, SKAN AG stabilized its Power BI environment, modernized its ETL architecture, and established a future-proof, standardized BI organization.
Informatec strengthens its Data & AI expertise with Databricks With the Databricks Lakehouse Platform, Informatec unifies modern data engineering, BI, and AI capabilities to help companies accelerate innovation and create measurable business value.
Success Story SKAN AG With Informatec, SKAN AG stabilized its Power BI environment, modernized its ETL architecture, and established a future-proof, standardized BI organization.
Mastering SAP S/4HANA Migration Strategy, Data, and Governance as the Key to Sustainable Project Success Migrating to SAP S/4HANA is more than a technical upgrade - it is a strategic transformation. Organizations must choose between a Greenfield, Brownfield, or Hybrid approach. Yet regardless of the selected strategy, one factor ultimately determines success or failure: transparency over data, clear scoping decisions, and structured validation before and after go-live. Strategies Migration-Phases Success factors Our offer FAQ From SAP ECC or R/3 to S/4HANA Why Data Determines Success or Failure For many organizations, the migration to SAP S/4HANA represents the most significant transformation project of the past decades. Since the announcement of SAP ECC maintenance deadlines, companies are under increasing pressure to act. However, an S/4HANA migration is far more than a technical conversion - it is a strategic realignment of processes, data architecture, and business models. While many projects focus heavily on infrastructure, conversion tools, and project methodology, experience shows that the decisive success factor lies in the data foundation. Organizations that migrate without thorough analysis carry complexity, legacy burdens, and unnecessary costs into the new system landscape. What Does SAP S/4HANA Migration Really Mean? SAP S/4HANA migration refers to the transformation of existing SAP landscapes - typically from SAP R/3 or ECC - to the new S/4HANA architecture including the HANA database. It is not merely a technical conversion. It includes: Process simplification Reduction of system complexity Standardization of customizations Optimization of the data landscape Organizations therefore face a fundamental strategic decision. Choosing the Right Migration Strategy Greenfield, Brownfield, or Hybrid? Greenfield Approach In a Greenfield scenario, a completely new S/4HANA system is built from scratch. Processes are redesigned, best practices are adopted, and only selected data - typically master data and relevant transactional data - is migrated. This approach is particularly suitable for organizations with heavily customized legacy systems or strong transformation pressure. The advantage lies in a clean, modern system architecture. The drawback is the higher project effort and strong involvement of business departments. Brownfield Approach In a Brownfield scenario, the existing system is technically converted to S/4HANA. Processes, customizations, and most data remain in place. This path is faster and less disruptive but carries the risk of transferring legacy complexity, unnecessary Z-transactions, and redundant data into the new system. Hybrid / Selective Data Transition The Hybrid approach combines elements of both strategies. Processes can be selectively redesigned while relevant data is transferred in a controlled manner. This model is particularly suitable for complex, international system landscapes. Regardless of the chosen model, the core question remains: Which data do we truly need in the new S/4HANA system? The SAP S/4HANA Migration Cockpit Capabilities and Limitations The SAP S/4HANA Migration Cockpit is a native S/4HANA tool that operates on predefined migration objects. It enables data transfer from SAP and non-SAP systems. Advantages include: Integration in SAP FioriNo additional license Suitable for low to medium complexity However, limitations become apparent in cases of:Highly customized system landscapes Heterogeneous source systems Data quality issues Lack of business transparency For more complex scenarios, organizations often complement it with tools such as SAP Data Services (SAP DS) to support transformation and cleansing. Yet even these tools primarily answer the question of how data is migrated - not which data should be migrated at all. Comparison SAP DS, Theobald, iVIEW for SAP Typical Phases of a SAP S/4HANA Migration A structured migration project typically follows these steps: AnalyseTechnical and functional current-state assessment Scoping Definition of target vision, simplification, cost reduction System PreparationCustomizing, cleansing, testing MigrationSystem conversion; productive systems temporarily unavailable ValidationData and process verification HypercareStabilization (DEV → Q/S → PROD) The most critical phases are Scoping and Hypercare. LEARN MORE ABOUT SCOPINGLEARN MORE ABOUT HYPERCARE Cloud Transformation, RISE, and Complexity Reduction Migration to SAP S/4HANA represents, in most cases, a structural move toward the cloud - particularly within a RISE with SAP framework. Even private cloud deployments follow cloud economics and standardized operating models. In subscription-based cloud environments, system complexity has direct financial and operational consequences. The more customized and historically evolved a legacy SAP landscape is, the greater the long-term impact in terms of maintenance effort, operational overhead, upgrade risk, and recurring subscription costs. Reducing unnecessary Z-transactions, eliminating unused data, and minimizing redundant structures directly improves system performance and lowers cloud resource consumption. In a RISE scenario, this translates into measurable benefits: optimized infrastructure sizing, improved maintainability, reduced technical debt, and increased innovation capacity. Cloud migration without complexity reduction simply relocates inefficiency. Sustainable SAP S/4HANA transformation requires both infrastructure modernization and structured data simplification. Learn more about Rise with SAP Success Factors of Modern S/4HANA Migration Successful projects are characterized by: A comprehensive current-state system assessment Delta analysis between source and target systems Transparency over actually used processes Re-documentation of historically grown systems Audit-ready reports for scoping and hypercare Clear business decisions based on validated data Organizations that treat migration as a pure IT conversion inherit complexity. Those who approach it as a data-driven transformation achieve sustainable system simplification. iVIEW for SAP as a Strategic Accelerator iVIEW for SAP enables: Transparency independent of the source system Analysis of which data is actually used Cataloging of Z-transactions Delta comparison before and after migration Audit-trail documentation Accelerated root cause analysis during hypercare Within scoping, structured analysis helps avoid unnecessary data imports and realistically define migration scope. Instead of transferring all historical data by default, organizations can determine which information is business-critical and future-ready. This significantly reduces project and cloud costs, cleanses legacy systems, and sustainably optimizes the S/4HANA data foundation. A leaner system improves performance, maintainability, and operational transparency. During hypercare, iVIEW for SAP supports structured root cause analysis. Documented delta comparisons and transparent data lineage allow rapid identification of whether an issue is data-related or application-related. This targeted elimination approach shortens analysis time, reduces operational risk, and accelerates stabilization after go-live. Instead of reactive troubleshooting, iVIEW for SAP enables controlled and fact-based problem resolution. LEARN MORE ABOUT iVIEW FOR SAP MIGRATION Our offer During the Hypercare phase, iVIEW for SAP provides targeted support for structured root-cause analysis. Through documented delta comparisons and transparent data lineage, it allows quick identification of whether an issue is data-related or application-related. This focused “process of elimination” significantly shortens analysis times, reduces operational risks, and accelerates stabilization after go-live. Instead of searching for errors reactively, iVIEW for SAP enables a controlled, fact-based approach to problem resolution. Request SAP ConsultingContact us for a non-binding consultation regarding your SAP landscape. Our experts will be happy to assist you at any time. You must have JavaScript enabled to use this form. Salutation - Select - Mr. Mrs. First name Last name Company Your Email Phone Gewünschte Dienstleistung SAP Consulting Services Mastering SAP S/4HANA Migration SAP Migration Readiness Check SAP S/4 Migration Scoping SAP S/4 Migration Hypercare SAP Migration/Upgrade Consulting & Projects SAP Migration Roadmap SAP Reporting SAP Test Data Management Message ✔ Privacy Policy I hereby agree to the privacy policy. * Mandatory field to answer your request Three Impact Levels of Modern Migration Technical Automated extraction, system comparison, audit reports. Business Cost reduction, time savings, risk minimization. Strategic AI-ready data foundation, composable enterprise architecture, preparation for agent-based automation. Conclusion SAP S/4HANA migration is not merely an IT project - it is a strategic business decision. Greenfield, Brownfield, or Hybrid - all approaches benefit from: Clear data strategy Structured current-state analysis Robust scoping methodology Clean validation processes Those who migrate systems alone inherit complexity. Those who intelligently transform data create future readiness. FAQ – Frequently Asked Questions About SAP S/4HANA Migration How long does a SAP S/4HANA migration take? Depending on strategy and complexity, between 6 months and several years. Greenfield projects often take longer than Brownfield conversions. Is the SAP Migration Cockpit sufficient? For simple scenarios, yes. For complex landscapes with data quality challenges, additional analysis and governance tools are recommended. What is the biggest migration risk? Lack of data transparency and unclear scoping. Insufficient analysis leads to over-migration and prolonged hypercare phases. Should all historical data be migrated? No. A selective data strategy significantly reduces cost, complexity, and cloud capacity requirements. What role does data quality play? Data quality is critical for process stability, reporting accuracy, and business continuity after go-live.