The Informatica Guide to SAP Modernization

⇨ Preparation, integration, mastering, and governance are essential steps for an SAP modernization.

⇨ AI technologies have the power to help integration and migration initiatives move more quickly.

⇨ Companies should employ migration strategies that minimize timeline, cost, and risk.

Data management is a vital aspect of the move to SAP S/4HANA. It is important that users take a data-centric approach to this change, as the basic underlying data model is changing. The data experts at Informatica enhance business value by helping organizations to prepare, integrate, master and govern their data.

The move to SAP S/4HANA has revealed to many SAP customers that they need to get their data in order. The 2023 SAPinsider Data Management Strategies report found that just 9% of respondents said their data management strategy completely meets their requirements, when it comes to managing data in SAP landscape. Organizations making the move from SAP ECC to SAP S/4HANA must address these issues to maximize the value of their S/4HANA investment.

“Some customers were simply moving their old data from legacy SAP systems to SAP S/4HANA. They were not even bothered about the quality of the data. They were just dumping all the ECC data from multiple different ECC instances to SAP S/4HANA. If you’re not catering to the data issues right now, you are not going to reap the benefits of the S/4HANA solution. It is going to be really hard for you to query the data or consume the data efficiently, even if you migrate all of your datasets to S/4HANA,” said Divya Prakash, Product Marketing Manager at Informatica.

Four Steps to SAP Modernization

Before setting out on an SAP modernization initiative, leading organizations opt to set up a roadmap that can guide their decision-making. Providing a plan can minimize data fragmentation and accommodate the diverse needs among all data users within the organization.

• Prepare – Get to know your data landscape. What do you need to know ahead of your migration from SAP ECC to SAP S/4HANA? What data do you need to migrate? Some data may need to be archived, while other data may have to be masked. You should also determine where your data lies. Some data might sit on-premises or on different cloud systems that are separate from your SAP landscape systems. Also, be sure to determine whether any of your data sets are dependent on one another. This can help determine whether you need to perform a phased migration.
• Integrate – Many larger multinational corporations struggle to create a complete picture of their data because of the heterogeneous data sources deployed to run different line of business independently. For example, apart from running a legacy SAP ECC system, organizations also leverage applications like Salesforce, Workday and Oracle systems to manage and operate different business units effectively. Those enterprises with disparate systems across multiple countries need pre-built connectors to quickly integrate distributed datasets and get a holistic understanding of the enterprise data needs.
• Master – Mastering data is an essential step in the process to help organizations minimize costs and maintain compliance. After integrating datasets, companies may find themselves with duplicated records. To master this data, companies can utilize master data management solutions to ensure data integrity and remove duplicates so users do not overpay for SAP S/4HANA licenses.
• Govern – Even once data is mastered and moved to SAP S/4HANA, users still need to continuously monitor data quality. Organizations should ensure they install governance policies around accessing the data in S/4HANA. Companies should also be aware of the data coming into both SAP and non-SAP systems.

Data Management in the Cloud

To help companies drive growth and modernize their SAP systems more efficiently, Informatica offers its Intelligent Data Management Cloud (IDMC) solution. The IDMC solution is a cloud-native, AI-powered data management solution which combines many data management capabilities in a single platform.

Informatica uses its CLAIRE AI engine to power its IDMC platform. This allows companies to replace hand-coding and other inefficient manual tasks, saving crucial time and allowing IT teams to spend their time creating trusted data for migration and other key data-driven initiatives.

“We leverage multiple AI technologies to power IDMC. The CLAIRE AI engine has the capabilities to automate most data management tasks for us. Data integration or data migration can take a lot of time, depending upon your data landscape. The CLAIRE engine can mass ingest your data from a specific source, like SAP ECC. It can quickly integrate and transform data across different legacy systems and migrate that data,” said Prakash.

CLAIRE also offers AI co-pilot abilities in a cloud SaaS model to provide multiple solutions for the different data management areas that require unique attention across a company’s technology landscape.

How to Measure a Successful Migration

As companies begin their SAP modernization journey, they may struggle to find the right parameters to guide them. It can be difficult to quantify what is a successful migration, so Informatica has developed a list of three key considerations for how companies can measure whether their migration was successful:

• Timeline – After taking stock of their challenges and requirements, companies should have an idea of how long their SAP modernization should take. Data issues are one of the most common reasons for delays in ERP modernization projects. Handling data quality issues ahead of migration can also save time on the back end, as IT teams will not have to spend time improving data quality within SAP S/4HANA.
• Cost – SAP customers should try to minimize the cost of their license by paring down datasets and removing duplicate data points. Cleaning data ahead of time can reduce the cost of migration and storage. Companies can also reduce costs by providing an API-based connection in their new system, giving it access to heterogeneous data in other systems.
• Risk – Companies can address security, privacy and compliance concerns within their SAP modernization strategy by developing a data governance policy. Role-based access control ensures that users can access what they need while also ensuring security and privacy.

A robust data governance and management strategy underpins these measures. By properly managing their data, companies can save time and money, while minimizing the risk of data breaches or non-compliance.

Data-Centric Migrations

When SAP users think about the move from SAP ECC to SAP S/4HANA, they must not forget the data needs of their SAP landscape, not just business processes within the ERP. Applications like Salesforce and Workday have critical data that sits outside of your SAP systems. Taking this data-centric approach will give you more visibility into the implementation approach that will benefit your organization.

Prakash highlighted three different types of approaches that SAP users can take, based on their specific data needs.

• Greenfield approach – this approach works best for those who have a small amount of data that needs to be migrated or are implementing S/4HANA for the first time.
• Brownfield approach – For those companies with a large amount of data or large customizations that have already been built onto SAP ECC, a brownfield approach will likely be the best option, as they do not want to scrap all of their business processes in SAP S/4HANA.
• Selective data transition – Some organizations may want to prioritize only some of their data sets that need to be moved into SAP S/4HANA and will opt for a selective data transition.

What this Means for SAPinsiders

Adopt a data-centric modernization approach. SAP users need to prepare, integrate, master and govern their data as part of a move from ECC to S/4HANA. Companies should work with an experienced data management solutions provider to ensure that they have a well-thought-out approach that emphasizes data management.

Embrace AI. AI is a powerful tool that can be leveraged at scale to address time-consuming work that used to be done manually. AI, automation and machine learning can also govern and enrich data across SAP systems.

Consolidate and standardize data. All data should fit a common standard so it can be consolidated from across legacy systems into SAP S/4HANA. This standardization will help with the process of integration after it is moved to the new system.

Democratize data access. Once data is moved to the new system, it is essential that teams can access the data they need to work efficiently. Role-based access should provide members across the organization with the data they need without compromising compliance or instituting silos. Automation can also help deal with data requests and lessen the burden on IT teams.

Informatica leverages a four-step framework to deliver a seamless SAP modernization program with its AI-powered IDMC end-to-end data management platform. IDMC offers key capabilities, like data cataloging, data integration, master data management, data quality, data governance and much more, that cater to these four key takeaways. This approach allows users to modernize their SAP data landscape via Informatica’s data-centric approach to S/4HANA migration.