In the first part of the post series, we addressed fundamental inquiries crucial to a successful SAP S/4HANA implementation, covering pivotal questions around the different SAP S/4HANA impact layers, such as SAP infrastructure, data migration, integration, and application.
Furthermore, we examined the implementation of new functionalities, simplification items, and the assessment of innovations within S/4HANA, aiming to optimize processes and potentially replace or integrate third-party solutions.
With reference to the S/4HANA Impact Analysis Model, let's proceed with exploring the potential benefits of transitioning from ECC to S/4HANA, emphasizing that this journey is not merely about complying with mandatory technological changes due to the expiration of ECC maintenance.
The generic added-value changes
From an infrastructure perspective
S/4HANA's in-memory computing boosts data processing speed and analytics for real-time insights, vital for agile decisions, leading to improved efficiency and productivity, fostering business growth.
S/4HANA's architecture supports scalability, aiding organizations to adapt to evolving needs and future growth without major infrastructure changes.
S/4HANA's cloud options offer flexibility and scalability, aligning infrastructure costs with usage, optimizing resource allocation and expenditure. Despite higher initial infrastructure investment, benefits in performance, scalability, and flexibility can outweigh costs over time, yielding a strong return on investment for S/4HANA adopters.
From a data layer perspective
Real-time data analysis can enable proactive decision-making by identifying trends, anomalies, or opportunities as they occur. This agility can be particularly valuable in dynamic environments where quick responses to changing market conditions or operational challenges are necessary.
The developed capabilities by using real-time data enhance process efficiency by identifying bottlenecks or inefficiencies in real-time, allowing for immediate remediation actions.
Having access to real-time data analysis capabilities can support initiatives such as predictive maintenance, fraud detection, or supply chain optimization, which can drive significant cost savings and operational improvements.
From a frontend perspective
While SAP Fiori can be used in both SAP ECC and SAP S/4HANA, there are specific added values and benefits that SAP S/4HANA offers in the context of Fiori usage compared to ECC:
Deep Integration with S/4HANA Functionality: Fiori apps in SAP S/4HANA seamlessly integrate with the platform's functionality, providing users with immediate access to real-time data, analytics, and insights. This integration empowers informed decision-making within business processes.
Enhanced Performance and Scalability: SAP S/4HANA's in-memory computing architecture ensures superior performance and scalability compared to ECC. Users experience faster response times and improved system performance, even with large data volumes and complex transactions.
Advanced Analytical Capabilities: SAP S/4HANA embeds powerful analytics, including predictive analytics and machine learning, directly into Fiori apps. Users can gain deeper insights, anticipate trends, and make proactive decisions, driving better business outcomes.
Support for Fiori Elements: SAP S/4HANA introduces Fiori Elements, streamlining app development with pre-defined templates and annotations. This accelerates time-to-market for new applications, reducing development effort and cost.
Mobile-First Approach: SAP S/4HANA prioritizes mobile accessibility, ensuring Fiori apps are responsive across devices. With access to critical functions and data anytime, anywhere, users enjoy enhanced flexibility and productivity.
From an integration perspective
Transitioning from an existing middleware solution to SAP Business Technology Platform (BTP) Integration Suite can offer several advantages as well:
Seamless Integration: SAP BTP Integration Suite seamlessly integrates with SAP's ecosystem, enabling smoother data exchange, streamlined processes, and enhanced interoperability.
Pre-built Connectors: SAP BTP Integration Suite offers pre-built connectors, accelerating integration projects, reducing development effort, and saving time and resources.
Hybrid and Multi-cloud Capabilities: SAP BTP Integration Suite orchestrates integrations across diverse cloud and on-premises environments, ensuring flexibility, scalability, and resilience.
Unified Platform: SAP BTP Integration Suite provides a unified platform for managing integration activities, simplifying the landscape, reducing complexity, and improving visibility and control.
Built-in Monitoring: SAP BTP Integration Suite offers built-in monitoring and analytics for real-time visibility into integration flows, enabling proactive optimization of processes.
Event-driven Integration: SAP BTP Integration Suite supports event-driven architectures, facilitating faster and more responsive business processes, and better adaption to changing business conditions.
Discover whatever added value for yourself, then urgently concretize it within a rough-cut business case and weigh it against complexity (risk).
This approach has proven its worth on the way to the actual development of the transformation strategy in order to prevent excessive risks being taken in the transformation on the one hand and opportunities being carelessly missed on the other.
To anyone regarding SAP transformation solely as a technical hurdle: This perspective has received backing from SAP itself for numerous years, as evidenced by its development of the Vision-to-Value framework.
The objective is to utilize the analysis results in crafting a preliminary roadmap for the company. This roadmap will delineate the individual realization phases and, in the case of a tender, distinctly outline the phases within the scope of services.
Generate benefits by utilizing the generic added-value changes
When it comes to the necessary discussion during the decision-making process as to what added value the S/4HANA transformation will bring, generic added value is no longer sufficient. Instead, it is now important to apply the generic added value from a business perspective in the respective processes on a case-specific basis.
In the given example, an engineering company had unique demands and challenges when exploring the transition to becoming data-driven organizations. In the final decision paper the following added-value scenarios were outlined:
Optimizing Product Development: Our company faces complex product development processes involving extensive research, design, and testing phases. Being data-driven will help optimize these processes by leveraging insights from historical data to improve our product design, identify potential issues early, and streamline development timelines.
Predictive Maintenance: Our company deals with maintaining large and expensive assets such as machinery, equipment, or infrastructure. Adopting data-driven approaches, such as predictive maintenance, will help anticipate possible equipment failures, schedule maintenance proactively, and minimize downtime, ultimately reducing costs and improving operational efficiency.
Quality Control and Assurance: Ensuring product quality is paramount for our company. Data-driven approaches enable us to implement robust quality control measures by analyzing data from manufacturing processes, identifying patterns or defects, and implementing corrective actions in real-time to maintain high-quality standards.
Supply Chain Optimization: Our company has complex supply chains involving multiple suppliers, partners, and stakeholders. By leveraging data analytics, we can optimize their supply chain operations by forecasting demand, improving inventory management, reducing lead times, and mitigating risks, thereby enhancing overall efficiency and reducing costs.
Performance Monitoring and Optimization: Monitoring the performance of our projects, processes, and assets is critical for identifying areas of improvement and optimizing resource allocation. Data-driven analytics enable us to track key performance indicators (KPIs), analyze performance trends, and identify opportunities for optimization across various aspects of our operations.
Innovation and R&D: Our company thrives on innovation and continuous improvement. Data-driven decision-making can fuel innovation by providing insights into market trends, customer preferences, and emerging technologies, guiding our research and development efforts, and supporting the identification of new business opportunities.
In order to present these scenarios credibly in a business case, the individual scenarios must be specified and made measurable. We will address this task in the next post.
To be continued....
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