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With the 2027 deadline looming, strategic assurance practices offer businesses a roadmap to SAP S/4HANA migration success.
In 2023, a leading retail company incurred losses of more than €78 million due to a poorly executed SAP transformation. With SAP ending support for ECC after 2027, businesses must transition to S/4HANA, but a successful migration requires more than upgrading technology. It also requires a strong assurance strategy — embracing a cultural shift towards quality that aligns with business goals, transforming testing processes well before the migration starts, and rethinking operational models. Such a comprehensive approach ensures that the migration not only meets the technical needs but also propels the company forward, supporting its strategic objectives and enhancing operational efficiency.
The Role of Assurance in Migration
Given how critical assurance is to a successful S/4HANA migration, it should be an integral part of every transition plan. However, many businesses focus heavily on the technical side and functional aspects of the migration, such as the system upgrade and business data migration, leaving less time for non-functional aspects like performance, operational stability, and security. Neglecting these aspects can lead to significant disruptions, including downtime, data loss, or performance issues, which in turn can affect customer satisfaction, revenue, and compliance with regulations.
A mindset shift is therefore essential to keep business objectives in mind throughout the migration. Assurance in SAP S/4HANA migration should support and enhance the company's strategic aims (e.g., mergers and market expansions, operational efficiencies or supply chain optimization), positioning quality assurance as a strategic partner rather than a mere procedural step. This involves a transformation of testing processes before migration, moving away from traditional methods to accommodate S/4HANA's modern technologies. Quality engineering (QE) leaders play a critical role in this transformation, preventing defects from reaching the production environment and ensuring a smooth transition.
For organizations deeply integrated with SAP, migrating to S/4HANA might also require a significant transformation in operational models, particularly in the organization and delivery of quality engineering services. Adopting a Testing Center for Enablement model that is aligned with agile methodologies, for example, ensures the assurance process is adaptable and efficient, meeting the rapid demands of modern business and technology landscapes.
Accelerating the Transition with AI and Other Technologies
Artificial intelligence (AI) and machine learning (ML) are playing a pivotal role in transforming how businesses approach the migration to S/4HANA. These technologies serve as key enablers, streamlining the migration process and introducing efficiencies that were previously unattainable. AI can automate repetitive tasks, predict potential issues before they arise, and provide insights to inform decision-making, ensuring the migration process aligns with company goals.
Machine learning algorithms can analyze historical data from past projects to predict outcomes, which can be used to optimize the assurance strategy. By leveraging data from past migration projects, AI develops effective testing strategies that are tailored to S/4HANA’s modern technologies. This shift from traditional methods is a critical aspect of the mindset change and testing transformation emphasized in the assurance strategy, ensuring a smooth transition that minimizes risks and maintains business continuity.
For example, Wipro worked with a major Australian utility company that sought to elevate its customer experience by transitioning from an outdated system to SAP S/4 HANA. Our teams utilized ML-powered intelligent test automation to ensure the migration was completed efficiently and without major disruptions. This approach not only ensured the project was delivered on time but also resulted in a 30% reduction in test cycle time, directly contributing to improved customer service and operational efficiency.
Similarly, a North American Energy company, dealing with the complexity of multiple ERP systems due to past acquisitions, aimed for better system integration and data consistency by migrating to SAP S/4 HANA. Its collaboration with Wipro introduced a future-ready quality engineering model and an automation-first strategy, leading to a 30% reduction in quality engineering costs and a significant decrease in regression test cycle time. This move streamlined operations and enhanced decision-making processes, showcasing the direct value of a focused migration strategy.
Other valuable use cases for AI/ML in assurance include:
- Reducing Dependency on Experts with Business Process Mining: AI uses business process mining to identify improvements in how companies use S/4HANA, reducing the need for specialized experts. It automates the analysis of processes, decreasing wait times and the likelihood of errors.
- Proactive Monitoring in Production Environments: AI monitors business processes in real time to identify and address IT issues before they impact the business. It uses predictive analysis to prevent potential problems, ensuring a stable operational environment.
- Comparing and Improving Business Processes: AI compares a company's current processes against best practices to identify areas for improvement. It then guides adjustments to processes and testing procedures, facilitating a seamless transition to new systems.
Adopting AI/ML not only reduces the time and resources required for migration but also significantly enhances the accuracy and effectiveness of the migration process. Wipro’s proprietary frameworks and tools, which integrate AI and machine learning, have consistently led to a 98% success rate for client migration projects, underscoring the effectiveness of leveraging advanced technologies. These tools are a direct result of hands-on experience with over 200 successful SAP S/4HANA migrations and are powered by GenAI for tasks such as test case generation, data validation, performance analysis and predictive analytics. Through its client work, Wipro has found that AI-driven DevOps introduces advanced methodologies and tools that enable faster SAP S/4 HANA migrations with reduced time-to-market (TTM). For instance, using automated test scripts, intelligent monitoring of system performance, and predictive analytics for migration risk management.
Navigating Challenges and Embracing Opportunities
Adopting AI and other technologies for migration assurance presents several challenges, including concerns around hallucinations and biases in AI models, data security, and the need for solutions tailored to the specific context of each business. Data security is a critical concern, as the migration process involves handling sensitive and proprietary business information. Businesses must ensure that the technologies they adopt comply with stringent data protection standards to safeguard against breaches and data loss.
Despite these challenges, the strategic use of AI and other technologies in migration assurance offers significant opportunities for businesses. To navigate these challenges successfully, companies must prioritize selecting the right technology partners — those with proven expertise in AI and a deep understanding of the migration process. Early and strategic planning for migration, with a focus on incorporating these technologies from the outset, can also play a crucial role in overcoming potential obstacles.
As the 2027 deadline approaches, businesses must prioritize their migration to S/4HANA, with assurance playing a critical role in this transition. Effective assurance will ensure smooth operations while mitigating risks and preventing costly disruptions. Partnering with experienced firms that excel in SAP assurance and leveraging innovative technologies like AI/ML can turn this challenge into an opportunity for growth, setting the stage for enhanced efficiency and a competitive edge in the market.
