Minimum Viable Product with Seamless Planning
Introduction
Seamless Planning was launched as a controlled release in Q4 2024. In this blog, we will develop a minimum viable product and share insights into how Seamless Planning could influence your SAP IT architecture.
Distinction SAC Native Planning and Seamless Planning
Many of you have likely worked with SAP Analytics Cloud (SAC), a platform that has been available for several years. One of SAC’s key strengths is its ability to integrate reporting and planning within a single tool. However, SAC Native Planning also comes with certain limitations.
One critical aspect of any planning project or application is the handling of reference data, such as actuals. With the SAC Native Planning approach, using reference data requires importing it into SAC. This process can introduce additional complexity and interface development efforts, as SAC is not designed to manage complex staging requirements, such as aggregating actuals to match the granularity of planning data.
Furthermore, plan data often needs to be made available in primary reporting systems. Many organizations rely on tools like SAP Business Warehouse, Power BI, Qlik, or increasingly, SAP Datasphere. This necessitates the creation of yet another interface to transfer plan data generated in SAC to these target reporting systems and applications.
The controlled release of Seamless Planning directly addresses these limitations. Unlike SAC Native Planning, the persistence of plan data in Seamless Planning is not within SAC but instead in SAP Datasphere.
It’s important to note that the modeling of planning applications with Seamless Planning still occurs in SAC. This means any expertise or experience you have gained with the SAC Native Planning approach remains highly relevant and valuable.
That said, it is still necessary to bring data into SAC if reference data is required for logic processing. This release primarily reduces interface efforts in one direction. However, Seamless Planning is continuously evolving, and in the near future, we anticipate the ability to access reference data directly from SAP Datasphere in real time, eliminating the need for data replication.
The following depiction provides a highly simplified representation.
Figure 1: Seamless Planning and Plan Data Storage
Now let’s have a look at the preconditions to utilize the Seamless Planning Approach.
Prerequisites
- A licensed and configured SAC tenant.
- Knowledge and experience with SAC modeling and planning features.
- A licensed SAP Datasphere instance for data persistence.
- Properly configured connections between SAC and SAP Datasphere, especially the Data Storage for Planning needs to be set up correctly. See screenshot.
- SAC tenant running on HANA Cloud. This will impact many existing customers in case they are not yet on HANA Cloud. There is a migration necessary. We will publish another blog about our migration experience, as we did the migration during the last days and collect many insights on potential issues and how to overcome the issues during the migration process.
- There will be no support for classic design experience! Make sure you implement the optimized design experience.
- There will be no support for input tasks. But SAC Calendar is supported.
Figure 2: Tenant Linking Data Storage for Planning
How to create a Planning Model in SAC
Whenever you create a new model, you will be able to select the data storage location. This can be SAC (which means not using seamless planning and would be the SAC Native Approach) or SAP Datasphere (which means using seamless planning with persistence of plan data in datasphere). If you choose SAP Datasphere, you need to choose a so-called space. Please note that classic account models are not supported for seamless planning. They will also not be supported in future!
Make sure you see the following dialog when creating a new model.
Figure 3: Selection of Data Storage Location
In our example we create a model called ZSPSTEPS in the Space STEPZ.
How to report and join plan data in SAP Datasphere
With the seamless planning approach, SAC models will expose the underlying data foundation as a “Local Table (Fact)”, while the public dimension tables will expose the master data as a “Local Table (Dimension)” associated with a translation table (storing the multi-language descriptions) and, in future, hierarchy tables. SAP Datasphere can use SAC-exposed objects in graphical views, SQL views, analytics models, transformation flows, etc. Let’s have a look at this in our example.
Please note that SAC application interfaces will remain in control of the model structure and all data changes. Direct write access to the planning fact table via SAP Datasphere will not be possible. I would describe it like this: The plan data model is “SAC managed” and the data persistence is SAP datasphere for Seamless Planning.
In the following screenshot you find the object sap.sac.ZSPSTEPS in Datasphere in the space we provided in SAC during model creation. The Prefix sap.sac. tells you, that it is a planning model managed by SAC. ZSPSTEPS is the name we provided during model creation in SAC.
Figure 4: Fact Table in Datasphere
For this blog, that’s it. I will continue in another blog to enhance the plan data inside SAP Datasphere for different purposes and continue the journey.
License and Authorization
You need to own licenses for both SAC and SAP Datasphere. SAC is licensed via user-based model whereas SAP Datasphere is licensed by capacity. In the seamless planning approach, you would license the planning functionality via SAP Analytics Cloud users and license the hardware (storage, memory, compute) required for planning via SAP Datasphere capacity units.
For the planning model, data access control and roles/model data privacy remain the tools to secure data as you already might know from your SAC experience.
Conclusion
From the author’s perspective, Seamless Planning represents a significant transformation. While it introduces exciting opportunities, it also comes with certain risks. For customers, it is crucial to carefully reevaluate their planning architecture and thoroughly discuss the potential impact of these new opportunities to ensure a well-informed and strategic adoption.
Undoubtedly, moving plan data persistence to where reference data is most likely located is a step in the right direction. Personally, I believe this is a positive and strategic move. However, it will be crucial to enhance Seamless Planning with additional features, particularly the ability to access reference data directly without the need for replication.
It can also be said that the basic principle is functioning as intended. I have personally created a small example to test it myself as shown in this blog. As we had to make sure that we meet all preconditions, it took a lot of time of course, but after overcoming those topics, applications can be built with acceptable effort and less interfacing efforts.
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Author: Franz-Josef Katzdobler
Franz-Josef is a highly experienced professional in SAP Analytics Architecture, with a strong focus on planning processes and planning architectures across various industries. His expertise spans multiple SAP planning solutions, including SAC Native, S/4 Native, and BPC Live Connection, as well as future-oriented approaches with SAP Datasphere and Seamless Planning. In addition to his deep technical knowledge, he is also skilled in project management, ensuring the successful implementation of SAP solutions. Furthermore, as a systemic coach, he provides guidance and support in navigating complex business challenges, fostering strategic decision-making and organizational growth.