Seamless Planning - Beta Program Highlights

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Since announcing the Controlled Release of seamless planning between SAP Datasphere and SAP Analytics Cloud, we’ve seen a high level of interest from our community and stakeholders, with many reaching out to learn more about available capabilities, use cases, and business impact. What better way to address these inquiries than by sharing the valuable insights and feedback we’ve gained from our customers and partners who actively tested seamless planning for the past few months through the seamless planning beta program?

Beta Setup: by using the seamless planning functionality, participants could store the SAP Analytics Cloud model’s data (fact and master data) directly in SAP Datasphere, reducing the data footprint while making it available for additional processing and extensibility scenarios through SAP Datasphere capabilities. This blog covers two of the most tested use cases during the beta program and the identified business benefits.

Use Cases

1. Creating Alignment Between Planning and Transactional Data

Business Outcome: increased agility, reduced time to action.

In many scenarios, planning data needs to be combined with transactional data from other systems, such as actuals, to create a comprehensive view for decision-making. For example, monitoring the comparison between actuals and planned data in close to real-time is essential in industries that see a rapid change in demand and market conditions. Imagine a successful marketing campaign where given products sell much faster than anticipated. In these cases, near-real-time tracking of actuals versus planned data enables businesses to identify trends and accelerate the replanning cycle. This way, operations can respond swiftly to changing market conditions – such as reallocating products across stores and distribution centers.

With seamless planning functionality, planning data can be combined with actual data immediately, allowing variance analysis and close monitoring without moving data across platforms. This real-time insight supports agile decision-making, helping businesses stay competitive while achieving their operational and financial goals. Another benefit of using SAP Datasphere as a data foundation is its ability to ensure that data across systems is ready and accurate for analysis. Combining transactional data with planned data often requires data preparation steps, such as cleaning, enhancing, transforming, and aggregating. SAP Datasphere provides key capabilities to optimize and govern these flows, bringing critical insights to users’ fingertips.

Most beta program participants tested this scenario by combining plan data with transactional data from various SAP or non-SAP sources, or by creating reports on joined data from multiple SAP Analytics Cloud models.

How it works: The SAP Analytics Cloud model data is exposed into SAP Datasphere as a table with the semantic type "fact". Using SAP Datasphere capabilities such as Graphical or SQL Views, SAP Analytics Cloud data can be combined with other data sources using standard union or join types. The final data can be consumed live in SAP Analytics Cloud stories through the SAP Datasphere’s Analytic Model.

2. Extending Calculation Logic using SQL

Business Outcome: increased flexibility in analysis and modeling.

SAP Analytics Cloud models are often enhanced with additional data and dimensions to support complex calculation logic, some of which are essential for reporting. While SAP Analytics Cloud’s advanced formula steps in data actions offer a powerful, governed environment for creating these calculations, certain use cases could benefit from the flexibility of custom code in languages like SQL or Python, allowing for even more tailored and sophisticated logic.

During the beta program, many participants tested this scenario of creating calculation logic in SAP Datasphere using SQL, a widely known and versatile language. Implementing calculations such as KPIs and metrics needed for period-end reporting in SAP Datasphere streamlined their SAC models for planning activities and reduced data integration requirements, as data required for calculations was already available in SAP Datasphere.

How it works: The SAP Analytics Cloud model data is exposed in the SAP Datasphere as a table with the semantic type "fact", allowing it to be consumed as a data source in SAP Datasphere Views. Whenever SAP Analytics Cloud end-users publish new data, the updated records are immediately available in the SAP Datasphere where calculations are performed. Once the calculations are complete, the results are instantly available in SAP Analytics Cloud through the Analytic Model.

Feedback

The positive feedback received at the end of the beta program reaffirmed that the strategic direction of closely integrating SAP Analytics Cloud with SAP Datasphere is the right approach. Key takeaways include:

• Unanimous Value Recognition: all participants agreed that seamless planning could add significant business value to their organization.
• Functionality Readiness: Two-thirds of participants indicated that the functionality tested in the beta program meets already identified business requirements, while the remaining third expressed the need for additional features. We carefully reviewed all feature requests and were pleased to find that many align well with our planned future releases.
• Adoption Interest: Over half of the participants are eager to adopt seamless planning within 12 months of its general availability.

Conclusion

The initial release of seamless planning lays the foundation for a future architecture that will gradually accrue more value for our customers. As we expand and enhance this functionality, customers can expect deeper integration capabilities that will streamline business operations and performance.

 

Last Call to join the seamless planning controlled release!

Are you excited about seamless planning and cannot wait until it gets released with SAP Analytics Cloud QRC1? You still have a chance to participate in the Controlled Release with SAP Analytics Cloud QRC4. 

Register here!