Strategic Data Management: Paving the Way for Successful S/4HANA Migration
Key Takeaways
⇨ Why organizations need a trusted data culture to move to cloud-based SAP.
Recent SAPinsider research confirmed that for 21% of IT professionals, the volumes of unstructured/semi-structured data to analyze and drive business processes are skyrocketing. In other words, enterprises sit on massive oil reserves of data. The smart ones with the right tools will be able to extract that data for migration to new ERP systems; the dinosaurs of business will not.
Effective data management is the catalyst for ERP modernization and increasingly the foundation of organizational growth. On the flipside, it can also undermine progress if it is managed poorly.
It is fair to say that aging, almost “prehistoric” ERP systems cannot keep pace with the challenges of modern business. Lacking both flexibility and scalability, legacy ERP can strangle data and require that organizations persist with time-consuming, outdated manual processes. Data silos and a lack of integration with the latest cloud-based tools stymie progress for any business looking to innovate and increase competitiveness. Migrating to the cloud is an urgent necessity to avoid extinction.
SAP and data migration
The problem is ERP migration can be a tricky business. The sheer complexity of legacy ERP, with multiple ERP systems running multiple customizations, has meant that ERP migration and change projects tend to run over time and budget.
SAP users also face the challenge of migrating to S/4HANA. SAP has been pushing its S/4HANA ERP platform since 2015 and has set an upgrade deadline for existing SAP users of 2027.
According to a UK and Ireland SAP User Group (UKISUG) survey of 116 SAP user organizations, 61% said that data management challenges have slowed or will slow the automation of their business processes. More specifically, 66% claimed that data management is a challenge when moving from SAP ECC 6.0 to SAP S/4HANA.
The aforementioned SAPinsider research into data management strategies meanwhile found almost 30% of IT professionals were concentrating on implementing a centralized master data repository on S/4HANA. 85% required support for both SAP and non-SAP data sources, with 37% deploying modern data integration, data orchestration and data migration tools.
But the fix needed here isn’t a simple question of porting data across to an upgraded ERP system, according to Khoi Hoang, vice president, global technical and solution architects at .
“What happens if you don’t put data into perspective?” as Hoang recently asked SAPinsider. “S/4HANA is a completely different data model. A lot of the ECC systems have been customized. So how do you put customized data from ECC into a more standardized S/4HANA?”
Hoang adds that there is some uncertainty among existing SAP users as to how to treat the data. There has to be an assessment of that data, he says, adding that if organizations don’t stop to assess then there is a risk of moving bad data into S/4HANA. This would slow down or stop the implementation completely, like tree amber coating an unfortunate insect.
There is the additional issue of third-party data, especially if organizations are embarking on data migration as part of a bigger digital transformation. How can organizations build a data model that fits with third-party sources but still manages data from legacy systems into a new S/4HANA system?
If organizations do not start with the data and work out a data management plan before they start implementing new platforms and software, it could lead to expensive and complex data integration work.
Making the case for data management
For most, it is not a question of ‘if’ but ‘when?’ when it comes to digital transformation. Modernization is essential to enable organizations to find opportunities, realize efficiencies, innovate and deliver products/services. Migrating to S/4HANA in the cloud is therefore a strategic imperative to empower organizations – but getting the data management strategy right is key.
First and foremost, it is essential that organizations do not look for shortcuts. Attempts to use existing data to simply try and migrate to S/4HANA will not work. If anything, this would lead to wasted time, money and increased business risk. For any organization looking to modernize their SAP landscape, understanding existing data and managing that data for migration to the SAP cloud is critical.
Any data migration journey requires a range of data management capabilities, including data integration, data governance, data catalog, data quality and master data management (MDM).
“Being able to discover what’s out there, being able to catalog the existing systems, understanding the attributes from each of these and then defining what those attributes mean – all of this metadata intelligence has to be reconciled as part of the journey to S/4HANA,” says Hoang from Informatica. “But imagine having to do this manually. It’s overwhelming.”
Getting the data discovery right at the start is vital – but this should go beyond just identifying sources. It should also include a detailed assessment of data quality and application dependencies. How critical are certain data sets to operations, and will they be low or high risk in terms of governance? Is the data quality consistent to the extent that it would enable better decision making?
A data stewardship and governance plan also plays an important role as it ensures data meets industry standards – but also that it is managed effectively throughout its lifecycle. This means that the organization can be confident in its data use and effectiveness, across multiple applications. A big part of this is consistency, especially for organizations looking to consolidate legacy ERP systems into S/4HANA.
The consistency and reliability of core master data entities is necessary for S/4HANA’s streamlined processes and analytics. Leveraging master data management (MDM) becomes pivotal to harmonize data and reduce redundancy prior to migration.
Through MDM, organizations can ensure data is accurate, complete and consistent across all departments and functions, regardless of where it lives. This centralization of key master data domains reduces the complexity of managing multiple data onboarding points and ultimately this should lead to more informed business decisions through better access to consistent, high-quality datasets.
MDM also enables the creation of a single, trusted view of data by consolidating data from multiple sources. This can drive optimization of operations and departments through a more detailed understanding of all functions, a main facet of any centralized data strategy. Through automated processes such as augmented data management techniques, organizations can ensure this data is kept up-to-date and consistent, especially as they look to “scale the mountains to the clouds” and migrate to S/4HANA.
In addition, it is important to leverage data management tools that can provide data context and enrichment, which will allow them to benefit most from S/4HANA capabilities. This should make the path towards S/4HANA migration easier. The point is that before any migration, the data can be prepared to not just limit potential issues but to really enhance the S/4HANA experience.
How data is managed across multiple systems will determine the viability of IT investments. It will also determine whether or not data is really enhancing decision making and helping to propel businesses forward.
As organizations continue to assess S/4HANA, look for business cases and even undergo pilot projects. It is worth remembering that getting the data element right at the start is critical to any successful implementation. Organizations that plough on ahead regardless be warned – any S/4HANA implementation really will only be as good as the data it’s devouring.