How to get SAP S/4HANA Migrations Right

If you’re from a company reliant on SAP, then an SAP S/4HANA migration is one of the biggest changes your business is likely to make in the coming years (digitally, anyway). It’s an opportunity to modernise, simplify, and create a platform for long-term digital growth. But it also comes with risks, and one of the biggest isn’t in the system itself. It’s in your data.

If you carry over duplicate records, outdated materials, inaccurate supplier info or inconsistent customer entries, you’re not transforming anything. You’re just putting bad data into a new system and expecting better results. That creates more problems than it solves, especially when it comes to reporting, planning, or automation.

This is why your S/4HANA migration strategy has to start with a conversation about master data- so let’s have it.

Why move to S/4HANA at all?

Many businesses are moving to S/4HANA because ECC support is coming to an end in 2027, so they feel like SAP has tied their hands. But there are good reasons to act sooner. S/4HANA offers real-time reporting, a simplified data model, improved integration with cloud tools, and a more modern, flexible interface. It’s designed for companies that want to run leaner and smarter. Great for industries with rising risks and costs, which frankly, encompasses most of them in this climate.

The challenge is making sure that what you put into the system is clean, trusted and ready to support better decision-making. If your data is full of duplicates, inconsistencies or obsolete entries, those advantages get undermined straight away. It might be cliche, but it really is a classic GIGO situation. Simple to summarise but far from simple to prevent or solve.

When should data preparation begin?

Far earlier than most teams think. Cleaning up your master data isn’t a quick task and this is where your focus should be when kicking off the migration. It involves identifying and merging duplicates, fixing gaps, standardising values, and agreeing on ownership. That can’t be done during the final weeks of the project. Ideally, it begins as soon as the decision to move to S/4HANA is made.

Treating data as a late-stage activity is one of the most common mistakes in SAP transformation projects. If you do that, you’ll either delay the go-live or carry over avoidable issues that will cost far more to fix later.

The risks of migrating bad data

One of the most common pitfalls in any S/4HANA migration is assuming that the new system will automatically resolve the problems created by poor data in the old one. It won’t. If anything, S/4HANA exposes bad data more clearly and makes its consequences more severe.

For example, duplicate customer or vendor records don’t just clutter the system — they create confusion in finance, procurement, and sales. One department may use one version of a supplier, another might use a second, with different payment terms or contact details. Inconsistent material descriptions can result in incorrect inventory reporting or product selections, which in turn affects logistics, planning, and even customer fulfilment.

Over time, these issues add up to real costs. Processes that were supposed to be faster in S/4HANA get delayed because users are unsure which records to trust. Automation is undermined because workflows break when they encounter unexpected data. Reports meant to guide strategic decisions produce conflicting results. At best, users lose faith in the system. At worst, the business starts building manual workarounds — exactly the kind of inefficiency the migration was meant to eliminate.

There are also regulatory risks. In sectors like life sciences, food and beverage, or manufacturing, incorrect product master data can result in compliance breaches. Auditors expect clear traceability, accurate documentation, and controlled master data changes — and S/4HANA, like any system, can only deliver that if the inputs are reliable from day one.

Even beyond the operational impact, bad data simply increases the cost of migration. Poor quality records take longer to map, clean, test, and reconcile. They increase the likelihood of rework and delay. And once live, they lead to more support calls, more change requests, and more time spent correcting rather than improving.

For organisations investing heavily in an ERP transformation, that’s a costly way to start.  The bottom line is that without clean, validated master data, even the best-designed S/4HANA environment won’t deliver on its promise.

Approaches to S/4HANA migration

When planning a move to SAP S/4HANA, one of the first strategic decisions you’ll need to make is how to get there. There’s no one-size-fits-all route — each business must weigh up technical, commercial, and operational factors before deciding on the right approach. But whichever path you choose, the state of your data will play a critical role in determining how smooth — or painful — the journey will be.

Here are the three main approaches:

System Conversion (Brownfield)

This is a technical upgrade of your existing ECC system to S/4HANA. It keeps your business processes and historical data intact, which can be appealing if your current setup works well and you’re looking for minimal disruption.

However, it also brings over your data exactly as it is. That includes duplicates, inconsistencies, legacy records, and any workarounds built up over time. Without a thorough data cleansing and governance effort before conversion, you’re simply lifting and shifting years of accumulated issues into a new system, which can complicate reporting, slow down new processes, and add friction to user adoption.

New Implementation (Greenfield)

A greenfield approach is a fresh start. You build a new S/4HANA system from the ground up, giving you the opportunity to redesign processes, standardise templates, and enforce clean data structures from day one.

This method is ideal for organisations that want to leave behind complexity, or for those undergoing major business transformation. But it requires careful planning around what data to bring across, how to migrate it, and how to avoid introducing poor-quality legacy records into a clean environment. Cleansing and validating master data ahead of the move is essential.

Selective Data Transition (Hybrid)

Somewhere between brownfield and greenfield sits a hybrid model. Selective data transition allows you to move only the data and processes you want — for example, specific company codes, master data domains, or recent transactional data.

This approach offers more flexibility. It’s well-suited to companies with multiple SAP instances or those wanting to consolidate regional systems without losing critical historical information. But it still relies on a strong data strategy: deciding what’s worth keeping, ensuring consistency across sources, and cleansing everything that enters the new system.

In all three scenarios, clean and governed master data is a constant requirement. Even the most advanced migration tools won’t prevent data issues from reappearing in S/4HANA if they’re not addressed at the source. That’s why building data readiness into your migration planning isn’t optional — it’s foundational.

How to prepare your master data for S/4HANA

Preparing for S/4HANA isn’t just about choosing the right migration method or managing technical infrastructure — it’s about ensuring your core business data is in the best possible shape. Without this, even the most advanced system won’t deliver the expected results.

The goal is to build trust in your data before it lands in S/4HANA. That means taking a deliberate, structured approach to master data preparation — and giving it the same attention you’d give to any other part of the project.

Here’s what a well-prepared master data workstream should include:

Start with a full data assessment

Before anything is migrated, you need a clear picture of what exists. Begin by profiling your master data —customers, vendors, materials, assets, etc. — to identify duplicates, outdated records, incomplete fields, inconsistent formats, and usage patterns. This step highlights which records are still relevant and where the biggest quality issues lie. It also gives stakeholders a data-driven view of the scope and effort involved in cleaning things up.

Clean, standardise, and enrich

Once the issues are understood, the hard work begins. Deduplicate records across systems, align naming conventions and formats, and fill in missing attributes where possible. Use pre-built validation rules to ensure data is logically sound — for example, no future birthdates in customer files, or no materials with invalid units of measure. This is also a good time to enrich your data with any additional information that will be required in S/4HANA but isn’t currently captured.

Define ownership and accountability

Clean data doesn’t maintain itself. Assign clear ownership for each master data domain, with defined responsibilities and workflows for approving, updating, and monitoring records. If a product description needs to change, who signs that off? If a new supplier is added, who ensures the data is complete and compliant? These roles need to be established well before go-live, not discovered afterwards.

Rationalise and archive legacy records

There’s no point migrating data that hasn’t been used in years. Apply filters to identify inactive customers, suppliers, or products, and set rules for what gets archived instead of migrated. Focus the effort on records that support current and future operations, not long-closed transactions.

Test with real data scenarios

As your new system is built and tested, make sure you’re validating against real master data — not perfect test cases. This helps you spot where formats don’t align, where logic needs adjusting, or where business processes are still relying on old, unstructured information.

Automate wherever possible

Manual cleansing might work in small volumes, but it doesn’t scale. Tools like Maextro automate key steps in the process, from identifying duplicates to managing workflows and approvals. Because it’s built for SAP environments, it fits naturally into both ECC and S/4HANA landscapes — allowing you to prepare clean, structured master data without reinventing how your teams work.

Best practices for a smooth data migration

Every successful S/4HANA migration has one thing in common: preparation. And when it comes to master data, preparation doesn’t just mean cleaning up spreadsheets. It means putting the right people, processes, and tools in place — early — so your business doesn’t carry the same data issues into a more powerful, but less forgiving, system.

Below are some of the most important data-focused best practices to keep your migration on track:

Involve the business early

Master data lives in the business, not just in IT. Your procurement team knows what makes a supplier record useful. Sales understands how customers are grouped and segmented. Involving these teams early — during data assessments, cleansing, and testing — ensures the system reflects real-world needs and doesn’t rely on assumptions made in isolation.

Prioritise quality over quantity

Migrating every last record is rarely the best approach. Focus on what’s active, accurate, and needed to support future processes. That might mean moving only the top 80% of frequently used materials, or recent customers with open orders. Set clear criteria to define what stays, what’s archived, and what’s cleaned up but not carried forward.

Define governance, not just clean-up tasks

Cleansing is a project — governance is a habit. If you want clean data to stay clean after go-live, you need clear ownership structures, data creation workflows, and approval logic embedded into business processes. Use the migration as an opportunity to formalise and document how master data should be handled going forward.

Use automation to scale your effort

Manual fixes work for short-term cleanups but don’t scale across thousands of records or multiple master data domains. Use tools like Maextro to automate validations, approvals, deduplication, and status tracking. The more automation you apply before go-live, the more sustainable your governance will be post-migration.

Validate in real scenarios, not just technical checks

Don’t just test whether the data loads — test whether it works. Use real business scenarios to validate whether product hierarchies display correctly, whether payment terms are pulling through on vendor master data, and whether users can search and retrieve what they need without confusion or duplication.

Embed data ownership into the new system

Make sure that once S/4HANA is live, there’s no reversion to old habits. Ensure that roles and responsibilities for master data maintenance are built into the system design, with controlled access, clear approval processes, and regular reviews.

Track data quality continuously

Once you’ve gone live, don’t assume the data will take care of itself. Build regular data quality reporting into your analytics layer or master data platform. Set KPIs for completeness, duplication, and usage — and treat these like any other operational metric.

Final thoughts

Moving to SAP S/4HANA is one of the most important steps a business can take toward digital transformation. But it’s not just a systems upgrade — it’s a replatforming of your entire operational landscape. Success hinges not just on technology, but on trust. And trust, in any enterprise system, comes from data you can rely on.

Poor master data is one of the most common, costly, and preventable problems during migration. It slows the process, causes errors post-go-live, and undermines confidence in the new system. The good news is that it’s entirely fixable — but only if addressed early, with the right strategy and tools.

That’s where data cleansing platforms like Ditto make a real difference. Built specifically for SAP environments, it helps organisations assess, cleanse, and govern their master data in a scalable, automated way — before, during, and after migration. Whether you’re cleaning up legacy customer records, validating materials data, or introducing governance around supplier onboarding, Maextro gives you the control you need to move forward with confidence.

A clean, governed data foundation won’t just make your S/4HANA project more successful — it will make your business faster, more efficient, and more resilient in the long term.

If you’re planning your journey to S/4HANA, don’t wait to start the data conversation. The earlier you prepare, the more value you’ll unlock.