Architecting a Blueprint for SAP Migration Success with Master Data Management

As support for SAP ECC is phased out, you may be looking for an efficient way to navigate the migration journey to S/4HANA. While you may also be seeking business flexibility or supporting a broader enterprise initiative, your main goal likely remains the same: to execute a seamless migration to S/4HANA while reducing the cost, time and risks associated with your modernization. To be successful, you need to understand the core components that make up the blueprint for an SAP migration to S/4HANA and how master data management (MDM) plays a central role.

The complexity of your SAP modernization program will depend mainly on your data landscape. Because your organization may generate a large amount of business data in different data formats and storage methods, you likely deploy multiple enterprise resource planning (ERP) systems to manage your transactional and analytical data. Given this, when you start modernizing ERP systems, it becomes critical to adopt a data-centric approach to consolidate and migrate data to S/4HANA.

Let’s look at some of the key elements of an SAP migration blueprint and why you need a robust data strategy to support it.

SAP modernization programs can take anywhere from 18 to 24 months or even longer, depending on the complexity of your data landscape. As such, it cannot be overemphasized how critical it is for you to reduce the risks associated with your SAP modernization.

The quality of master data in S/4HANA matters because it informs the business decisions your various stakeholders need to make on a regular basis. Without ensuring master data quality, you risk:

• providing inaccurate insights.
• getting inconsistent outcomes from machine learning (ML) models.
• instilling a lack of confidence in decision-making abilities if your stakeholders do not trust your enterprise data in S/4HANA.

An enterprise-level MDM tool can help you maintain the quality of your master data throughout the SAP migration process, which helps reduce your risk of modernization program failure. Validating the quality of master data being moved to S/4HANA also prevents you from needing to deploy costly and time-consuming data quality tools to bring your data up to the standard you need after it has been successfully migrated to S/4HANA.

Investments in S/4HANA will start paying off once you can deliver quick business value by accelerating the data migration process. Focus on building an extensive list of AI-powered MDM connectors, which can automatically identify and integrate your data across multiple legacy ERP applications and push it to MDM tools.

The amount of data being migrated has a major impact on your total cost of ownership for running and maintaining S/4HANA. Because S/4HANA is built on the in-memory database HANA, moving unnecessary and duplicate records to S/4HANA will only increase your memory usage, contributing to an increased operating cost. Thus, you should leverage SaaS-based intelligent MDM solutions that can quickly apply match and merge algorithms to remove duplicates and potentially save you millions of dollars in licensing costs.

It’s clear that transitioning from SAP ECC to S/4HANA can be difficult and time consuming due to the fact that you need to change your underlying data model. S/4HANA uses a simplified business / partner data model rather than the customer / vendor data model in place in ECC. In the case of a brownfield and selective data transition approach, this is further complicated by the need to perform dual maintenance on the legacy ERP systems and the new S/4HANA environment.

Mapping and conversion to this new data model requires some downtown to eliminate the potential risk of data inconsistency. Additionally, you will need downtime for database migration. Let’s look at how you can optimize this downtime with MDM solutions.

S/4HANA requires a very high standard of data quality for incoming data. The data conversion process can create data inconsistencies. Eliminating these data inconsistencies to keep your data quality in check needs to happen before migrating your data to S/4HANA. Leverage MDM tools and their data enrichment capabilities to adhere to the master data policies prescribed for S/4HANA.

To reduce costly downtime, you might maintain both legacy and S/4HANA environments. In this case, the automated real-time data synchronization capability of your MDM solutions will help maintain the timeliness of your data. Automated data replication will also keep your new S/4HANA systems in sync with the changes made to your legacy systems while the migration and conversion are happening.

First, let’s define what a composable ERP landscape looks like. In a composable ERP landscape, various functions and features are provided as small and independent microservices. These can then be integrated to work together as and when required.

In the context of S/4HANA, a composable ERP landscape would contain its core modules to manage your business functions — such as finance, human resource, supply chain management, etc. — and composable modules — such as analytics and reporting tools, CRM tools, industry-specific solutions, data management tools and APIs — for seamless communication between your ERP modules and other applications.

Adopting composable ERP strategies fuels the growth, flexibility and profitability of your business by enhancing your ERP capabilities. However, to reap the benefits of composable ERP strategies, managing your master data across your component applications is crucial. Start by leveraging MDM tools that can identify and master data across S/4HANA and other cloud-based applications. 

Multiple legacy SAP systems may contain master data related to different lines of business. You need to discover and evaluate the complexity of this master data across on-premises or cloud sources to identify the best migration strategy.

An MDM solution can help you automate master data discovery to determine your master data assets and their domain type. You can also automatically mark personal and sensitive data that needs to be masked prior to migration. Examining hierarchies and relationships of your master data can help identify key data dependencies and suggest if any of your datasets need to be migrated together. For that reason, these master data insights are crucial in identifying the right migration strategy for you.

Let’s assume you’ve identified selective data transition as the right migration approach, which is suitable when you plan to move only priority workloads to S/4HANA. Here, MDM solutions can provide you with prebuilt, extensible and customizable data models for your specified data sets and master them before you migrate them to S/4HANA. Once your data models, hierarchies and relationships are defined, you can quickly onboard your master data by connecting to different legacy source systems.

The key performance indicators (KPIs) to evaluate the success of your SAP modernization program may differ depending on your business priorities, operations territory or leadership guidance. However, you can generally expect greater success if you generate quick time-to-value and mitigate the risks of such a large-scale transformational project.