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Data Management for a leading US Supermarket chain migrating to S/4

Published on 8 November 2021
Data Management

60 years old super market chain at US decided to implement S/4 and we helped them through this journey and like our client, organisations are moving from their legacy systems to S/4 HANA motivated by benefitting their business through S/4’s advanced capabilities (Read Maximising Business Value though S/4 HANA). As organisations migrate the backbone of their operations, it is actually lot more complex than it sounds. Gartner estimates that 60% of the ERP investments are perceived as having failed as they are believed to have compromised the business in some way.

Why does data pose significant challenges during S/4 migration?

As a business grows, processes get more complex, technologies evolve and eventually updating or replacing the existing system becomes a “need” rather than a “want” to survive in a competitive landscape. While organisations move from SAP ECC or any other Legacy System to S/4 HANA in order to gain a competitive advantage, they often face roadblocks along the way.

Lack of Data Quality & Governance Assessment:

Data held in the legacy system is critical for business operations and decision making. Migrating this entire data to a new system must be efficient and error-free for a seamless transition to S/4. All transactional data needs to be complete and accurate before migration, and inconsistencies must be identified through data integrity checks. Moreover, data governance needs to be set up along with the future data accessibility provision. Hence, data migration needs a strategic approach that factors in different aspects of the current status of the data and defines its future state as well.

Data Management - Key Challenges

Overrunning of Schedule & Budget:

A successful data migration consists of a series of interdependent activities carried out over a period of time. As the volume of data increases, having business-ready data to be migrated becomes one of the key priorities even before laying out a data migration timeline. Assessing source and target systems can also be a challenge, especially when dealing with significant amounts of data spread across multiple systems. Multiple mockloads and validations are also necessary to ensure a seamless transition to post-migration activities. Each organisation needs to customise its data migration specific to their business needs which might lead to ambiguity in the scope of the project, eventually resulting in schedule and budget overrun.

Change Management

If the end-user doesn’t adopt the technology, the initiative ultimately fails. Therefore, it is essential that the end-user understands the post migration scenario in terms of data standards, accessibility of the data and the associated benefits. Organisations must have a comprehensive change management plan in place to support their employees in training, and understanding the new system.

Our early engagement framework helped us create a data migration roadmap for our client. Being a supermarket chain, migrating the huge volume of data was already a challenge. Moreover, the data was scattered across different systems with no unified platform. The business readiness of the data had to be assessed and Data Quality had to be ensured prior to migration. Business users were also not experienced enough to validate the data as well.

Data Management Data

Applexus Methodology for a Successful Data Migration

Our methodology revolves around three key steps:

Impact and Readiness Assessment

Before the data migration, we delve deep into assessing the current status of the data and whether it is business ready i.e having the capability to offer insights about the current business processes. We gather information about known data quality issues, data standards, relevant metadata and review existing source systems & documentation while assessing quality needs. Automated data quality reporting tools are also deployed to elicit any data quality issues. At this stage we also prepare future-state data standards and cleansing requirements. As our client had several data sources, it was essential to assess the business readiness of the data prior to migration.

Mass Customisation with Pre-built Solution

Following the SAP best practices, the data migration approach is defined for migration using BODS (Business Object Data Services). Business Object Data Services (BODS) is a GUI tool which allows you to create and monitor jobs which take data from various types of sources and perform some complex transformation on the data as per the business requirement and then will load the data to a target which again can be of any type (i.e. SAP application, flat file, any database). With our unique pre-built BODS jobs for S/4 migration we were able to achieve a quick cutover. Custom requirement for additional business objects for data migration were incorporated in our pre-built solution. This enabled us to fast-track S/4 migration even with the enormous volume of data that our client had in its legacy system. This unique approach ensured that project doesn’t deviate from schedule.

Iterative Validations

During our multiple mockloads and validations, business users were made aware of the mapping of the master data and transactional data to the new system. This approach ensures that the data which is being migrated is accurate. Moreover, it also minimises any post migration complications and ensures seamless transition.

Data Management Client Benefits

 

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