CFO Coffee Break EMEA: SAP S/4HANA Migration

Most SAP S/4HANA projects discover their data problems too late – during testing, during reconciliation, or after go-live. Finance teams spend months in parallel run mode, reconciling legacy systems to SAP S/4HANA daily, burning through budgets while IT scrambles to fix data quality issues that should have been caught before migration started. The timeline slips. The costs balloon. Go-live gets delayed. And the reconciliation cycles that were supposed to end with the migration actually just move into SAP S/4HANA where they're even harder to trace. This three-part CFO Coffee Break series tackles that gap directly. Each session is under 20 minutes, hosted by Paul Coughlan, insightsoftware's EMEA Account Manager, and built around practical approaches finance teams are using to get to go-live on time and on budget. No slides, no sales pitch. Current information on what's actually working for CFOs running SAP S/4HANA migrations today. Session 1 of 3 │ Data Readiness Before Migration: Stop Problems at the Point of Entry  Paul opens with a frame on where SAP S/4HANA projects slip: data quality issues discovered during testing that force rework, parallel run reconciliation that eats timeline, and GL balances that don't match reality once you're live. Then walks through how leading finance teams build data quality into their migration approach before testing starts – stopping duplicate vendors, incomplete materials, and GL mapping errors at the point of entry rather than trying to fix them downstream. Session 2 of 3 │ Parallel Run Efficiency: Reconciliation Strategy That Doesn't Delay Go-Live For finance teams currently managing dual close cycles, Paul walks through how to structure parallel run reconciliation so it validates data integrity without becoming a months-long bottleneck. Real reconciliation strategy for the pre-go-live window – identifying what actually needs daily sign-off, what can be spot-checked, and what can be deferred until post-go-live cleanup. Session 3 of 3 │ Post-Go-Live Stabilization: Month-End Close in SAP S/4HANA Without the Manual Overhead The closing session. Paul walks through what happens after cutover – how finance teams approach the first month-end close in SAP S/4HANA when legacy processes don't yet apply, how to stabilize close cycles without rebuilding manual workarounds, and where insightsoftware solutions fit into post-go-live support.

Most SAP S/4HANA migration timelines slip not because of technical issues with SAP S/4HANA itself, but because data quality problems discovered during UAT testing force rework. Duplicate vendors that should have been cleaned in the legacy system become a full remediation project. GL mapping errors that were hidden in legacy accounting surface when you try to validate opening balances. Material master records with incomplete attributes break downstream processes. The testing phase extends. Parallel run cycles multiply. Go-live gets pushed back months. Leading finance teams take a different approach: they build data quality into the migration strategy before testing starts. That means running data validation against legacy systems now – not during UAT – and fixing issues at the point of entry. Duplicate vendors get consolidated before extraction. GL mappings get validated against actual balances. Material master completeness gets verified before data loads to S/4HANA. The testing phase becomes validation of a known-clean dataset rather than discovery of problems. In this opening session, Paul walks through how finance teams approach data readiness as a distinct migration phase – what to validate, when to fix, and how to measure data quality improvement. In this 20-minute walkthrough, you'll see:

• Where data quality problems hide in legacy systems – and what finance teams are discovering when they run validation before migration starts.

• Master data validation strategy: GL chart of accounts, vendor master, material master, customer master – what needs to be clean for SAP S/4HANA to function, and how to identify gaps.

• Duplicate and orphaned record remediation – the mechanics of consolidating vendors, merging GL accounts, and cleaning up historical data without breaking open transactions.

•  Data completeness assessment and remediation – which fields are mandatory in SAP S/4HANA vs optional in legacy, and how to fill gaps at scale.

• Timeline impact: how much does data readiness add to the migration schedule, and what do you save in testing and parallel run when you start clean.

The parallel run window is where many SAP S/4HANA projects get stuck. Finance teams are running the close in both legacy systems and SAP S/4HANA simultaneously – a dual close that's supposed to last a few weeks stretches into months of daily reconciliation, variance investigation, and firefighting. GL balances don't match between systems. Customer subledger totals are off by small amounts in S/4HANA. Intercompany balances reconcile in legacy but not in S/4HANA. Controllers are spending 10+ hours a day investigating variances instead of preparing for go-live. The issue isn't the reconciliation tool – it's the strategy. Teams that get through parallel run quickly make a deliberate choice: not everything needs daily sign-off. Some accounts require validation daily. Some can be validated weekly. Some can be deferred to post-go-live cleanup. By treating parallel run as a phased approach rather than a "reconcile everything perfectly" exercise, finance teams compress the timeline from months to weeks without sacrificing control. In this session, Paul walks through how to structure your parallel run reconciliation strategy – what gets daily attention, what gets weekly spot-checking, and what can wait until post-go-live. In this walkthrough, Paul covers:

• Reconciliation strategy framework: which accounts and subledgers are critical for go-live sign-off vs which can be addressed post-cutover – and how to make that decision.

• Daily reconciliation focus: GL balance validation, intercompany balancing, and customer/vendor subledger account testing – the minimal set that proves data integrity on day one.

• Weekly and milestone validations: full balance sheet reconciliation, open item clearance testing, and control environment validation – done less frequently but more thoroughly.

• Variance investigation workflow: identifying systematic issues (GL mapping problems) vs transactional variances (rounding, timing) vs data quality issues (missing records) – and what each one means for go-live readiness.

• Timeline management: how long should parallel run actually take, what risks are you accepting if you shorten it, and how do you measure readiness for cutover.