The Challenge
AVA Augsburg is a leading European integrated waste recycler, combining waste management and energy generation in a circular economy model serving over a million residents. Converting a long-running SAP ECC landscape to S/4HANA meant migrating master data and historical data to meet the compliance and audit standards of a highly regulated public utility:
- Customer, vendor and material data carrying years of inconsistency and duplication
- Regulatory requirements for data reconciliation and auditable results
- No existing playbook or tools for cleansing data at this scale without prolonged downtime
Data cleanse and S/4HANA upgrade was the first step in the Client's digital roadmap. Client was keen to accelerate this initial phase and create reliable data and an S/4HANA baseline upon which to innovate.
The Solution
Data cleansing and brownfield conversion to SAP S/4HANA was delivered using Q-nnect's Platform Q!, a SAP-certified, AI-assisted data platform. Q!Platform Data Analyzer provided visibility of cleansed data and readiness for migration, and AI/ML capabilities were embedded into each phase of the project.
- 01 · Discovery: Knowledge graphs and graph analytics map data objects and dependencies; static code analysis and ML heuristics review custom code and CDS objects
- 02 · Cleansing: Intelligent similarity detection (nearest-neighbour search, fuzzy matching, vector embeddings) combined with rule-augmented machine learning to flag dead, redundant, and obsolete data
- 03 · Mapping & Rules: Natural language processing and ontology-based reasoning build migration rules with no/low code
- 04 · Validation & Reconciliation: Agentic test automation and pattern recognition apply risk-based testing against historical transaction patterns
- 05 · Cutover: Zero-copy data loads executed through SAP-authorised BAPIs, with no business data stored outside the source
The Results
The client observed the following outcomes:
- Data cleansing completed in 2 months. S/4HANA migration completed in 4 months
- Business Partner (CVI) conversion executed successfully during the upgrade with no disruption to operations
- Migration documentation met the auditor's requirements throughout the conversion
Published outcomes at comparable SAP S/4HANA brownfield migrations also identify:
- Project Duration: 30–40% faster using Q-nnect AI/ML capabilities
- Testing Effort: up to 80% reduction in defects, from accuracy delivered by automated testing
- Visibility: 90% increase in transparency throughout the program
The client also observed the value of Q-nnect semantic data layer and potential to unify SAP and non-SAP data and enable future AI innovations.
Ready to explore AI for energy & resources?
No obligation, no sales pitch — just a clear conversation.
Contact Us