In this excerpt from the podcast “SAP S/4HANA Data Migration and Master Data Management best practices”, Terry Penner, Bill Todd and Randy Connelly discuss best practices and practical approaches for migrating data and master data management with SAP S/4HANA and SAP Business Technology Platform.
Topics discussed
Part 1: Data Migration
- Key challenges
- Best practices for system conversion
- Best practices for selective data transition
- Best practices for new implementations
- Data migration tool options
Part 2: Master Data Management
- Challenges and priorities
- Efficiently working with master data
Part 3: Clean Core
- Data management and clean core
- Getting started with data migration to S/4HANA
About the speakers
Terry Penner is part of the SAP BTP Marketing and Solutions team, focused on BTP for SAP S/4HANA. He has more than 20 years experience in the SAP platform and analytics, including working directly on hundreds of customer implementations.
Bill: is a principal solution advisor from SAP. For the past 20 years, his focus has been on data management solutions. He is passionate about data, and has deep experience in data quality, data integration and master data management.
Randy: is the global data governance practice lead for Syniti, with more than 30 years experience in the SAP space, in data migration and data quality. The last 12 years have been focused on master data governance.
Part 1: Data Migration
Terry: Welcome to our expert panel discussion on best practices for migrating data and managing master data for S/4HANA cloud customers, particularly those in the early stages of their RISE with SAP journey.
Let's start off talking about data migration. First, why is data migration and master data management important to an S/4HANA customer starting their RISE journey.
Bill: Accurate and trusted master data is crucial for any business initiative, particularly for transitioning to S/4HANA and embarking on your RISE journey. Without a solid foundation of reliable data, you risk building on unstable ground due to potential inaccuracies. To draw an analogy, think of constructing a building - everything begins with a strong foundation. Similarly, master data forms the fundamental base for S/4HANA.
Randy: Migration is a critical component of your digital transformation into S/4 HANA. This process involves setting up key business standards, policies, and rules to meet your operational needs. On top of that, these standards are leveraged in the master data governance area. This is to ensure that you maintain data integrity by consistently applying the standards, policies, and rules set during migration.
As long as organizations utilize these standards, they can improve their operations and efficiencies. This will also pave the way for future innovations.
Key data migration challenges
Terry: Based on your experience with customers, what are some of the key data challenges that S/4HANA customers are facing as they migrate to S/4HANA Cloud Private Edition, whether it's from ERP or S/4HANA on-premises?
Randy: One thing I often notice is the crucial role of data cleansing, harmonization, and aligning business interests. By alignment, I mean getting everyone on board, whether on a regional or global level, with new standards, policies, and rules. Achieving this consensus can be tricky due to differing viewpoints. So, it's essential to focus on change management to ensure solid user acceptance and confidence, paving the way for smooth progress.
Bill: Absolutely, Randy, I totally agree. It all circles back to the quality of data. We really don't want to carry over old data issues into the new system. This is our opportunity to get it right, and data quality is always an issue that needs careful handling.
As for the S/4HANA customers you asked about, I've found that the conversion of business partner data is a significant and often tricky task. In S/4HANA, we see our customers and vendors through the business partner model. It's a broad category that encompasses companies that might be both a customer and a vendor.
The challenge here lies in the transition of data. Currently, most companies treat customers and vendors as separate entities. But with S/4HANA, they need to be viewed as business partners. This is a critical aspect that needs addressing as part of the migration process. Moving forward, we will treat such records as business partners.
Data migration best practices for system conversion
Terry: There’s three main data migration approaches to consider: system conversion, selective data transition, and a new implementation. Let’s talk about the benefits and drawbacks of each of those options and best practises.
The first approach of system conversion, or 'lift and shift', is a popular method when moving to S/4HANA. It's basically a technical upgrade where you're doing the bare minimum. You're not really taking advantage of the new S/4HANA innovations, and there's usually little customization involved. You're not changing the data, just moving it.
What needs to be considered with system conversion?
Bill: In my experience, the approach we're discussing is ideal for companies with strong data management practices and high-quality data. It's particularly useful if you're in a rush to transition to S/4HANA and are considering a simple "lift and shift" strategy. However, ensure your existing data is of high quality to maximize the benefits of this approach. Otherwise, you're just transferring all your old data and its associated issues. If you plan on addressing data issues later, it's akin to moving all your old stuff into a new house and then deciding to declutter. It doesn't make sense, right? Why would you want to move boxes of unwanted items from your old house to your new one?
Randy: Sure, you made some excellent points there. Many organizations, especially when transitioning to S/4HANA, really start to consider implementing formal governance. Even if they're just doing a straightforward system conversion, they need to think about this in a wider context. As they begin to formalize their governance, there's likely to be changes in their standards, policies, and procedures that need to be consistently applied. This might also be a part of the 'house cleaning' process where they need to adjust their master data to align with the new processes and the data they want to use moving forward. So, the house cleaning aspect is critical in this context.
Data migration best practices for selective data transition
Terry: Let's talk about the second approach to migration, selective data transition.
This can involve multiple SAP ERP systems or ERP systems. Typically, there's data harmonization and cleansing required, and definitely data migration necessary. What best practices do we need to know?
Randy: One of the key things to remember is that SAP provides applications such as ADMM [ SAP Advanced Data Migration and Management Tool ] and SKP [ Syniti Knowledge Platform ] via Syniti. These are essential for conducting important activities. An integral part of this process is the use of an application that can standardize tasks and create a process that can be repeated and reused.
Many organizations approach this on a case-by-case basis, focusing on a single ERP system, division, or business unit at a time. This repeatable and reusable process is crucial for efficiency. It allows for data to be gathered into a common repository and transformed.
Just as important is validation, which ensures alignment with the new S/4 environment. This leads to the creation of loads for the new S/4 environment, guaranteeing high quality data.
This process pairs well with formalized governance from an MDG perspective. It allows the creation of load programs that can be used for both S/4 and MDG, whether in a hub model or co-deploy back into S/4.
Bill: When Randy mentioned the importance of a repeatable and reusable approach, he was really emphasizing the need to tackle tasks one at a time. This could mean focusing on one business unit today and another tomorrow. Or, if you often merge with or acquire companies, you'll eventually have to integrate their ERP systems.
Having a standard methodology - complete with tools, processes, rules, and data conversion routines - is crucial. This way, we can hope for a rinse-and-repeat scenario where we can apply this approach again and again. This approach allows for an effective phased implementation.
As Randy noted, this methodology often dictates how you'll actively manage and govern your data as you create it. For instance, as you generate new master data for your HANA system, you'll likely reuse many of these rules. If a rule helps keep data clean from the get-go, it's likely a good rule to keep for future data creation. Therefore, having a repeatable and reusable system is key.
Data migration best practices for new implementations
Terry: Yes, that will certainly help with the total cost of ownership.
And then for the third approach of starting with a new implementation, what are your thoughts on some best practices for this approach?
Randy: Similar to what we just discussed; a key part of the process often involves a "Big Bang" implementation. This means that instead of a phased approach where each ERP system or business unit is handled individually, everything is implemented all at once.
In such a case, it's crucial to have a standardized process that can be used across all areas - be it materials, business partners, financials, or transactional data. All these must be realigned to fit into the new S/4 environment.
An aspect we didn't touch on earlier is that there might be a need for data construction. This involves creating new data that didn't exist in the old systems but is necessary in the new system to meet operational needs.
We need to leverage standardized processes to validate and create load files consistently, as there will be several test cycles. The goal is to ensure that everything is working and improving, so that by the time you reach the production implementation, you have clean data with an accuracy rate of 99% to 100%.
The drawback is the time and effort up front, but the outcome can make it well worth the effort.
Bill: The “Big Bang” approach is no small task. You're diving into a large project from the start, but the payoff is in the final product. Yes, it requires quite a bit of effort, but the result? You've tackled all the issues and managed all the data. There's hardly anything left to do when you're migrating. Well, unless you're acquiring a company or something like that.
Then, you might lean more towards the second approach we've discussed, the system conversion or selective data transition. And remember, these methods aren't always separate. Sometimes, there's a bit of a hybrid, right? They don't have to be mutually exclusive.
Data migration tool options
Terry: What are recommended tool options for migrating data?
Randy: When you think about transitioning to S/4HANA, the first thing that usually comes to mind is the SAP S/4HANA Migration Cockpit. This tool allows you to extract, map, and load data directly into your S/4HANA system. However, the key thing to consider, as we've often discussed, is the cleanliness of your data. The Migration Cockpit works wonderfully for those who've already cleaned, harmonized, and deduplicated their data.
If your data isn't clean or if you're dealing with a different situation, another option we've discussed is SAP's Advanced Data Migration by Syniti. This tool offers a comprehensive and customizable solution for your unique circumstances, regardless of whether you're migrating from multiple or single ERP systems, or a combination of SAP and non-SAP systems. It provides immense flexibility for data cleansing, harmonization, and validation, which are crucial when introducing new master or transactional data into your S/4 environment.
Part 2: Master data management – challenges and priorities
Terry: Let's pivot to master data management and some of the key challenges and priorities.
Bill: Dealing with data issues is always a significant challenge. It's crucial to identify and correct these problems. Take duplicate data, for instance. Identifying duplicates can be tricky, but many robust matching engines and techniques can help with this.
The bigger challenge I've noticed from my interactions with customers isn't identifying the duplicates but figuring out how to create the best record from these duplicates. They often refer to this process as survivorship or merging. In SAP master data governance, we call it creating a 'best record'.
The goal is to allow data experts or stewards to review the duplicate records and decide how to consolidate them. For instance, if we have five versions of the same company, we need to figure out how to create that one superior, or 'golden' record, moving forward.
A solution like SAP Master Data Governance can be helpful in this scenario because it has specialized processes, tasks, and user interfaces for reviewing duplicate records and creating a 'best' or 'golden' record. So, that's one major challenge. But there are others, of course.
Apart from correcting data issues, another significant challenge that comes to mind is automation. In this era of AI, companies want to automate as much as possible, like auto-creating master data or extending materials to plants and sales organizations. This has been a focus in the last two releases of SAP master data governance with its data derivation capabilities. With the current trend of generative AI, I foresee a lot of progress in the future in this area. So the two critical areas are automation and correcting data issues.
Randy: A key term that's often linked to this discussion is self-enablement. Many organizations are striving for this, to reduce their dependence on IT departments. They're leveraging platforms like MDG to empower the business to maintain data quality, ensuring they have reliable data they can trust.
You gave an example of an international manufacturer of industrial materials. They faced issues during the deduplication process due to variations in units of measure - metric or imperial. This problem affected warranties and spare parts for their products across different regions.
A product purchased in one region may end up in another, but the warranties still apply. However, when spare parts are needed, if there's a discrepancy between metric and imperial measurements, it becomes a significant international challenge.
To overcome this, they reviewed their governance process, looking at how they could standardize units of measure globally. This ensures they can support their products anywhere in the world.
This situation demonstrates the importance of master data. It's not just about the top-level data - the underlying attributes also need to be analyzed. In the context of data governance, it's crucial to understand how these are used and the impact they have on the business.
Efficiently working with master data
Terry: What are key points that I need to know about working with master data efficiently in S/4HANA?
Bill: When discussing master data management and S/4HANA, it's crucial to stress the importance of establishing appropriate governance early on for creating or altering master data for S/4. If not, you run the risk of S/4HANA reverting to past behaviors, potentially operating in a system that didn't uphold governance over master data creation.
That's why companies transitioning to S/4HANA should think about using something like SAP master data governance. I often describe it as a gatekeeper, or even a bouncer, acting like a firewall to ensure we stick to a regulated process. This process actively governs how we create or update master data, ensuring it's accurate, reliable, consistent, and compliant with any regulations. Plus, it provides transparency so we can trace how that master data was created.
Without such governance, you could end up creating master data without any checks, validations, or oversight, and without an audit trail. That's where MDG steps in, providing a governance layer to control how master data is created for S/4HANA.
And don't delay - many times, if you wait until you're live on S/4HANA, it's almost too late. On day one, people will start creating master data, so if you don't have this in place from the start, you're setting yourself up for potential difficulties.
Randy: I agree with you Bill, especially when transitioning to S/4 it's essential to establish formal governance. This isn't just about cleaning up your data, but also maintaining its cleanliness.
There are many organizations currently mapping out their transition strategies and they might not be ready just yet. However, they can utilize governance and SAP MDG as stepping stones towards S/4. A lot of organizations might not realize that they can set up an MDG environment on S/4HANA, which allows them to introduce formal data governance into their legacy ECC or ERP systems.
While preparing to transition to S/4, this approach gives them the data model necessary for the S/4 environment and accommodates new data requirements. This data can then be replicated back to existing ECC and non-SAP systems in their current formats, keeping the data clean.
Once they activate their S/4 environment, they already have all the necessary information prepared and it's compatible with the new S/4 data models. So there are really some excellent options for organizations looking to clean their data and transition to S/4.
Part 3: Data management and clean core
Terry: How does data migration and fit in with a clean core strategy and even more important, what happens after I migrate the data. How do I how do I stay clean?
Bill: It's important to remember that "clean core" can have different meanings for different people, depending on the context. In this case, when we're talking about migrating data to S/4HANA, a clean core refers to the accuracy and usability of that data. Everyone wants a clean core system, and that always begins with clean data.
Randy: Organizations aiming to transition to a clean core will need to strategize on how they'll undertake data cleaning, harmonization, and migration activities. They'll face challenges, but they'll also have to determine how they're going to map eliminated data elements to the new clean core system. This is crucial to ensure business activities continue to run smoothly. They will need to consider the migration issues we discussed earlier as part of their shift to a clean core.
Terry: Yes, we recently did a podcast and blog on a deeper dive on what clean core means, whether it's extensions, processes, data - it's an important concept. How does how does MDM master data management fit into that clean core strategy?
Bill: For the importance of maintaining cleanliness in your systems, we emphasize the need to clean up data, migrate it to S/4, and then continue to keep it clean.
That's precisely where master data management becomes crucial. It's a process that helps you maintain this clean core system. As I've mentioned, active governance and control are key. You need the right people, process, and technology to ensure your core stays clean. This is where master data management, specifically solutions like SAP master data governance, come into play.
Randy: Earlier we emphasized the importance of maintaining cleanliness in our system. The central idea is to first clean up the data, transition smoothly to S/4, and then ensure it stays pristine.
This is where the role of master data management becomes critical. It's a process that's essential for sustaining a clean core system. Like I mentioned before, it's about actively governing and controlling the system. To do this effectively, you need the right combination of people, processes, and technology. That's where a specific solution like SAP Master Data Governance steps in to support this goal.
Getting started with data migration to S/4HANA
Terry: Any final words of advice for customers who are migrating data to S/4HANA, whether they’re doing the “Big Bang” approach or a new implementation.
Randy: I think it's crucial for any organization to carefully consider what path suits them best. Every organization is unique, with its own needs and culture, especially when it comes to handling change management. Whether a company can handle a 'Big Bang' approach or if it needs to take it step by step, maybe rolling out a new ERP system or tackling it division by division to ensure success.
We've gone over many of these points in our conversation, but it really comes down to a case-by-case basis. It's about finding the right fit for each organization, and that includes deciding if a 'clean core' strategy is the right move. The big plus of a clean core is how it simplifies upgrades. It takes away a lot of the hassle and worry because, with a clean core, your upgrades are automatically in sync, whether we're talking about S/4 or your MDG platform. There are a lot of considerations for every organization.
Bill: Clean core is essential for streamlining business processes. The key is to do things differently, to adopt best practices, and to work efficiently, making sure everything aligns with SAP's recommended methods. This includes using SAP Advanced Data Migration and Management, or ADMM, to ensure data is clean, correct, and smoothly transferred to S/4. Then, there's SAP Master Data Governance, or MDG, which is crucial for overseeing how master data is created.
I remember working with a major high-tech company, and they had a clear rule: the only way into S/4 is through SAP MDG. It's how they ensure their master data is properly set up for S/4. They made it clear to everyone in the company that this was the change they had to embrace. By sticking to this process, they could trust that their data foundation would be accurate and reliable for the future.
Terry: Thanks Bill and Randy for joining me in this conversation and discuss this important topic for S/4HANA customers.
Listen to the full podcast at SAP S/4HANA Data Migration and Master Data Management best practices with SAP BTP
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