SNP Group Solves Data Migration Challenges of SAP Customers in JAPAC Region

⇨ SNP Group is addressing significant enterprise data management challenges faced by SAP customers, particularly in the JAPAC region, by providing flexible, software-based solutions for data transitions including migrations, upgrades, and divestments.

⇨ The upcoming AI-enhanced software platform Kyano will enhance SNP's data migration capabilities by integrating various sources and targets, while also offering an AI-powered service called the Agility Index to measure and optimize business agility.

⇨ SAP customers in the APAC region must consider unique regulatory requirements and mature IT infrastructures when selecting data management platforms, while leveraging AI to streamline and improve data migration processes.

Most SAP customers are chipping away at a laundry list of enterprise data management challenges, including SAP S/4HANA transformations, mergers and acquisitions, system landscape optimizations, cloud data integrations, and system decommissioning. One of the SAP partners at the recent Mastering SAP Connect event in Gold Coast, Australia, SNP Group is squarely focused on these challenges, providing flexible, software-based solutions for data transitions, including migrations, upgrades, and divestments. Headquartered in Heidelberg, Germany, SNP Group currently has more than 1,500 employees worldwide at 35 locations in 20 countries.

In the JAPAC region, SNP Group is on a decent growth trajectory, beating its own targets and achieving 30-40% year-on-year growth, while publicising to the market that SNP can provide faster, less risky, and more cost-effective solutions.

“We tend to see a slower market pace in the JAPAC region compared to other regions, with the possible exception of Australia and Japan, where we’re seeing more rapid movement,” said Phillip Miltiades, JAPAC Managing Director at SNP Group. “Our Australia business has expanded 10-fold in the last twelve months.”

SNP Group has a mature data management platform called CrystalBridge®, used by 7 out of 10 international system integrators, that targets mostly SAP-to-SAP data migration use cases. With the upcoming launch of the AI-enhanced software platform Kyano, SNP Group has further developed its existing data migration and management capabilities to work with most sources and targets, incorporate data integration tools and integrate solutions from SNP’s partner ecosystem. Kyano also provides an AI-powered, continuous cloud service called the Agility Index that measures, benchmarks, and optimizes business agility based on smart KPIs and trend analyses.

“We need to overcome the perception of SNP’s platform as a highly complex solution for selective data transitions,” added Miltiades. “We’re emphasizing the flexibility and speed of software-based transformations compared to traditional approaches. whether it is a lift-and-shift — a.k.a. brownfield — selective data transition — a.k.a. BLUEFIELD^TM — or starting off on a clean slate –  a.k.a. greenfield.”

In the JAPAC region, the company remains focused on attracting new talent – expanding from 80 to 100 employees in a year – and bringing discipline to the go-to-market and delivery processes. It is also shaping agreements with global partners like Accenture, IBM, EY, KPMG and Deloitte, with potential for further growth in partnerships.

Varied geopolitical and economic environments across the JAPAC region will continue to influence customer decisions around data migration and management. Key upcoming appointments in JAPAC leadership for SNP will be general managers in key regions like Singapore, Japan, and China.

What this means for Mastering SAP insiders

APAC-based SAP customers should fully vet unique requirements with prospective data management platform providers. SAP customers in the APAC region face unique data migration and management requirements driven by diverse regulatory environments, rapid technological adoption, and the varied maturity of IT infrastructures. As such, these companies need data management platforms that support country-specific compliance requirements, including data residency, encryption, and audit trails. Countries such as China, India, Singapore, and Australia have distinct data sovereignty and localization laws. For example, China’s Cybersecurity Law mandates data storage within national borders, while India’s Data Protection Bill emphasizes local storage and consent-driven data processing. Also, many organizations in the region rely on legacy systems, requiring migration platforms to connect and extract data from older, non-standardized environments. Data migration tools must provide compatibility and transformation capabilities for legacy systems to integrate with modern SAP landscapes. What is more, countries like Singapore and Japan have stringent privacy laws (e.g., Singapore’s PDPA and Japan’s APPI) requiring secure handling of customer data during migrations. So data management platforms must include robust encryption, anonymization, and access control features to ensure data security.

Stay on top of how AI is evolving data migration and management best practices. AI automates complex data migration tasks, reducing manual intervention and accelerating project timelines. This leads to faster migrations with fewer errors. AI algorithms can also anticipate potential migration challenges, allowing for proactive issue resolution and minimizing downtime. AI tools assess data quality by identifying inconsistencies, duplicates, and errors, ensuring that only accurate data is migrated, and AI-driven solutions correct data anomalies automatically, maintaining high data integrity throughout the migration process. AI interprets data context to perform accurate mapping between source and target systems, reducing the risk of misalignment, and machine learning models can learn from previous migrations to improve future data transformation accuracy and efficiency.

Look to SNP for help with managing data quality, integrity and complexity. Ensuring the accuracy and consistency of data during migration is critical. Poor data quality can lead to operational disruptions and flawed decision-making. SNP provides comprehensive data profiling and cleansing tools, enabling organizations to assess and enhance data quality before migration. Also, organizations with intricate data environments face difficulties in consolidating and migrating data efficiently. SNP’s expertise in handling complex transformations, including carve-outs and mergers and acquisitions, enables streamlined data consolidation and migration processes.