Reconciliation Strategy
What is this?
Reconciliation ensures that data in SAP S/4HANA matches the original Oracle system.
It validates:
- Financial balances
- Transactional data
- Master data consistency
Why it exists?
Validation checks: → “Can SAP process this?”
Reconciliation checks: → “Is this still correct business data?”
Reconciliation compares legacy and SAP datasets to detect discrepancies before they impact operations.
Core Principle
Validation ensures correctness within SAP
Reconciliation ensures correctness across systems
Both are required.
What Needs to Be Reconciled
1. Financial Data (CRITICAL)
- Trial balance
- GL balances
- Vendor balances
- Open items
Acceptance: → 100% match
Even small mismatch: → Financial inconsistency
2. Transactional Data
- Purchase Orders
- Goods Receipts
- Invoices
Checks:
- Document count
- Quantity
- Amount
3. Inventory Data
- Stock quantity
- Stock value
- Plant-level inventory
Acceptance: → Exact match (or defined tolerance)
4. Master Data
- Business Partner count
- Material count
- Key attributes consistency
Reconciliation Types
1. Count Reconciliation
Compare:
- Number of records
Example:
- Oracle POs = SAP POs
2. Value Reconciliation
Compare:
- Amounts
- Totals
- Balances
Example:
- Total invoice value
3. Record-Level Reconciliation
Compare:
- Individual records
Example:
- Invoice ID → Amount → Supplier
Reconciliation Process
Step 1: Define Scope
- What objects to reconcile
- What level (count / value / record)
Step 2: Define Rules
Examples:
- Exact match required
- Allowed tolerance (e.g., rounding)
Step 3: Extract Data
From:
- Oracle (source)
- SAP (target)
Step 4: Compare
- Record count
- Field values
- Aggregates
Step 5: Identify Differences
- Missing records
- Value mismatches
- Duplicate records
Step 6: Root Cause Analysis
Find why mismatch occurred:
- Mapping error
- Missing data
- Transformation issue
- Sequence issue
Step 7: Fix and Re-run
Fix source or mapping:
→ Re-run reconciliation
Migration Stages
Pre-Migration
- Define reconciliation rules
- Clean source data
During Migration
- Perform reconciliation on test loads
- Identify gaps early
Cutover (CRITICAL)
- Final reconciliation before go-live
- Business sign-off required
Post-Go-Live
- Continuous reconciliation
- Monitor discrepancies
Dependency Mapping
→ Data_Transformation_Pipeline
→ Master_Data_Load
→ Transactional_Data_Load
Reconciliation validates: → Entire pipeline
Common Failures
1. Only Checking Totals
→ Misses record-level errors
2. Ignoring Master Data
→ Causes downstream issues
3. No Defined Rules
→ Inconsistent validation
4. Late Reconciliation
→ Errors discovered too late
5. No Ownership
→ Nobody accountable
Anti-Patterns
❌ “Close enough” numbers
❌ Skipping record-level checks
❌ Ignoring discrepancies
❌ No audit trail
Critical Rule
If reconciliation fails:
→ DO NOT GO LIVE
Key Takeaway
Reconciliation is NOT:
→ Optional verification
It is:
→ Proof that migration preserved business truth
If this is wrong:
- Financials are wrong
- Reports are wrong
- Audit will fail
And SAP will not save you