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3 Use Cases: Real-Time Reporting with S/4HANA Embedded Analytics

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Introduction and Fundamentals

Embedded Analytics in SAP S/4HANA refers to the direct integration of analytical capabilities within the operational ERP system. Unlike traditional BI architectures, analyses are performed on live data without data replication or a separate data warehouse such as SAP Business Warehouse.

The technical foundation is the Virtual Data Model (VDM), which is based on Core Data Services (CDS) and their corresponding views. These CDS views structure data across multiple layers and define both semantic logic and analytical properties. Through annotations, functions such as key figures, filters, or aggregations are defined directly within the data model. This creates a consistent and reusable data foundation.

Fig. 1: VDM in SAP S/4HANA

Access to Embedded Analytics functionalities is primarily provided via the FIORI Launchpad within SAP S/4HANA. Users are presented with role-based applications such as KPI tiles, analytical lists, or multidimensional reports. In addition, external tools such as SAP Analytics Cloud can be integrated, accessing the same data through live connectivity.

Why is SAP Embedded Analytics worthwhile?

Embedded Analytics is particularly valuable because analytical insights are immediately available on operational data without system discontinuities. Since all evaluations are executed directly on the SAP HANA database, time-consuming and costly data replication into “traditional” downstream BI systems is no longer required. Decisions can therefore be made on the basis of current and consistent data rather than delayed extracts. At the same time, organisations can avoid the costs of additional BI solutions where these are not necessary.

If required, however, traditional BI tools can still access CDS views directly, depending on compatibility and licensing models, in order to create even more complex data models. For example, CDS view data can be enriched with information that does not originate from the source system SAP S/4HANA.

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What do typical Use Cases for SAP S/4HANA Embedded Analytics look like?

Real-Time Logistics Management

In logistics management, Embedded Analytics enables end-to-end real-time control of inventory levels and material flows directly within the operational system. All relevant movement and inventory data is continuously processed on the in-memory platform SAP HANA and is immediately available for analysis without delay.

A typical scenario is monitoring the inventory coverage of a material within a plant. A planner identifies an early critical decline in coverage in a dashboard, which could potentially lead to production interruptions or supply shortages. The visualisation is embedded within FIORI analytical apps, meaning that operational and analytical perspectives are fully integrated.

Using drill-down functions, the end user can immediately analyse the root cause of the deviation. This provides transparency as to whether the inventory reduction has been caused by increased production consumption, delayed supplier deliveries, or incorrect or outdated planning values. This root cause analysis is performed directly on the same data without any media discontinuity.

Based on these insights, the MRP Controler can immediately initiate operational measures. These may include stock transfers between plants, adjustments to procurement quantities, or the prioritisation of existing delivery orders. The key advantage is that these actions do not need to be carried out in a separate system but can be triggered directly from the analysis itself.

The navigation from the dashboard into the corresponding transactional FIORI apps is fully integrated and context-sensitive. This closes the entire cycle of detection, analysis, and action within a single system, significantly reducing response times in logistics management and improving supply reliability.

Fig. 2: Overview Inventory Management

Promotional Campaign Monitoring

In sales controlling, Embedded Analytics enables the immediate evaluation of marketing and promotional campaigns based on operational real-time data. Revenue, volume, and margin information is analysed directly from the underlying transactional data on SAP HANA and made available within the system without any delay.

A typical scenario is the ongoing monitoring of a discount campaign. A sales controller identifies in a dashboard that, although the campaign is generating a significant increase in sales volumes, the margin is falling below the defined target values. This provides early transparency regarding the economic impact of the measure.

Using integrated drill-down functions, the analysis can be refined step by step. This makes it possible to identify whether the deviation is attributable to specific products, regions, sales channels, or customer segments. Such granular analysis enables a differentiated assessment of the effectiveness of individual campaign components.

Based on these insights, the controller can immediately take corrective action. Possible measures include adjusting discount levels, focusing on more profitable product segments, or selectively restricting the campaign in certain regions or customer groups. Dynamic optimisation during an ongoing campaign is also possible.

The key advantage lies in the direct connection between analysis and operational decision-making. Changes do not first need to be initiated through external reporting cycles or separate BI systems but can instead be implemented immediately within the operational application context. This significantly increases responsiveness in sales and marketing controlling.

Real-Time Financial Analysis in the General Ledger

Another use case for Embedded Analytics in SAP S/4HANA is the direct analysis of financial data within the general ledger without time delays or external reporting processes. All posting data is processed immediately and is therefore instantly available for reporting and analysis.

In day-to-day operations, this means that finance teams always have an up-to-date overview of key management indicators. These include open items in accounts receivable and accounts payable, liquidity developments, and period results. This information is not only updated through nightly batch runs or ETL processes but is continuously reflected within the system.

A typical scenario is the monitoring of cash flow during an ongoing accounting period. Controllers identify discrepancies between expected and actual incoming payments at an early stage via dashboards. Through drill-down functions, they can trace these deviations directly back to individual postings, customers, or accounting documents. As a result, the root cause of a change becomes visible during the period itself rather than only at month-end closing.

Compared to traditional BI solutions, there is no need for a separate data warehouse. This reduces data latency, avoids inconsistencies between operational and analytical data, and significantly shortens the analysis cycle.

At the same time, integration into the FIORI environment enables immediate follow-up actions based on analytical insights. End users can move directly from an analysis into relevant financial processes, such as dunning procedures or posting corrections.

Fig. 3: Overview General Ledger

Conclusion

Embedded Analytics in SAP S/4HANA offers companies, particularly those without an existing reporting landscape, a direct and structured entry point into analytical reporting. Since analytical capabilities are already an integral part of the system, there is no need to initially build a separate BI architecture, eliminating concerns around data consistency. Based on the in-memory technology of SAP HANA, operational data can be analysed in real time without replication or additional persistence layers.

The delivered content and the VDM enable the rapid provision of consistent KPIs and reports, which can be extended specifically through enhancements to CDS views. As end users access these capabilities directly via FIORI apps or integrated analytical functions, there is also no need to install additional software, allowing users to work without switching systems.

Another advantage lies in the close proximity to operational data. Since no data replication is required, users always work with a consistent and up-to-date data foundation. This not only reduces reconciliation efforts between departments but also improves the quality of decision-making. Particularly for business users without deep BI expertise, this creates a low-threshold entry point into analytics and significantly strengthens self-service reporting capabilities.

Despite these advantages, actual adoption often remains below its full potential. Reasons include a lack of awareness, established tool landscapes, or the assumption that “real” analytics requires additional systems. Yet this is precisely where substantial efficiency potential exists, which can often be realised without additional licensing costs.

Overall, Embedded Analytics proves to be not merely a technical add-on within SAP S/4HANA, but a strategic tool for faster, data-driven decision-making in operational business processes.

As an SAP consultancy, PIKON supports companies holistically in the field of Business Intelligence, from initial concept design through technical implementation to ongoing operations and support services. Our focus lies on SAP BI tools. We help our customers establish a sustainable reporting and planning architecture that covers both operational and strategic requirements.

In doing so, we consistently follow a 3-Point-Consulting approach that combines Information Technology, business management and people. The business perspective ensures a strong functional process view from the business departments and guarantees that reporting requirements are derived meaningfully from actual business needs. The technological perspective provides the stable and scalable system and data foundation required to operate modern analytics solutions efficiently. People, as the third dimension, are placed at the centre of the transformation: end users must not only be enabled but actively guided through the change process and empowered to work effectively with data and new tools.

This creates a BI landscape that not only functions technically but is also sustainably adopted and delivers genuine added value in day-to-day business operations.

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Martina Ksinsik
Martina Ksinsik
Customer Success Manager

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About the author
Frank Schwab
Frank Schwab
I am Senior Consultant Business Intelligence at PIKON Deutschland AG. My work focuses on the architecture and development of reusable, scalable data models for future reporting in SAP BI.

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