SAP Analytics Cloud and BPC - a hybrid approach
Both SAP BPC standard and embedded versions have been around for many years and are proven solutions for covering more complex planning requirements. However, planning requirements are nowadays changing. More and more focus are being put on the following characteristics:
- Data availability (any time on any device)
- Data simulation and prediction
- Data exploration / Insight
- Reduce local application support
Let us first recap. The embedded version is a planning solution based around BW’s IP (Integrated Planning) functionality. The guiding principle of this approach is not to copy the data but use the BW objects and features instead. Therefore, instead of brining data over to BPC (as in the BPC standard model) it is leveraging existing data in BW. By nature, the embedded version is more IT driven whereas LoB drives in case of the BPC standard model.
SAP Analytics Cloud (SAC), a cloud solution for business intelligence and enterprise planning, can be used for standalone planning implementations, but it can also be used as an extension for the existing planning process in SAP BPC standard and/or embedded. This hybrid approach is a promising solution to facilitate the transition towards the cloud on the one hand, and still build on the investments made in SAP BPC.
If we look at the differences between SAP BPC standard and SAP BPC embedded in combination with SAC, we can notice a big difference in how SAC would complement SAP BPC. This difference can be attributed to the different connections used to connect to SAP BPC.
- For SAP BPC embedded the connection is made through a “live” connection and SAC is merely an interface. Therefore, some of the SAC planning features will not be available.
- With the import connection type, SAP BPC standard data is stored inside a SAC model. All SAC features will be consequently available for SAP BPC Standard.
SAC can serve different purposes in complementing SAP BPC, mainly depending on the requirements. Below we will draft an overview of these different requirements.
Mapping requirements to hybrid scenarios
Besides the planning aspect, there might be a requirement to centralize all reporting requirements in one single place. SAP BPC could be one of the sources used for reporting, but of course this does not exclude the fact that SAC can be used to report on virtually every data source. For SAP BPC standard as well as embedded this would mean a “live” connection could be made to the BPC system by using Bex queries. With the live connection, we indicate that data in BPC or in BW is reflected immediately, in real time, in SAC.
Planning on SAP BPC embedded
For customers with an existing SAP BPC embedded application, besides reporting, SAC could also be used to complement their planning experience. One thing we should mention, because SAP BPC embedded does not store any data in SAC, the added value here is quite limited as not all the functionalities of SAC are available in this setup.
From a technical point of view, a live connection would be made towards SAP BPC embedded application, which will contain an actual aDSO and a planning aDSO. No transactional data or master data replication towards the cloud is required and the SAC web interface can be used to input the planning data.
The SAP BPC embedded planning engine is used, and SAC supports most of the embedded planning features including executing a BI-IP planning sequence. But as mentioned before it will not be possible to leverage SAC specific planning features such as distribution options and predictive analytics.
Planning on SAP BPC standard
When BPC standard customers want to use SAC to enhance their current planning process, the setup will be much different than in the embedded scenario. When creating a connection with write-back option to a SAP BPC standard model, SAC will automatically create a model with the same dimensions and structure as in BPC and import all data into this model.
Because data is physically stored in SAC, all the planning features such as distributing values and predictive analytics will be available in SAC with one exception. Master data on the fly will not be possible, because all master data will have to be maintained in SAP BPC. Master data cannot be changed or added in SAC itself.
When data is published in SAC, this data will be automatically exported to SAP BPC, and after the default logic has run, the updated values are again imported into SAC.
When setting up SAC for SAP BPC standard we have to consider a few different options regarding the technical setup.
This is the standard method when importing SAP BPC into SAC. This is a good solution, but one drawback is that additional effort is required when fully migrating to the cloud. The reason for this is that you cannot simply remove BPC and continue working in SAC. SAC will not allow you to update master data for a write-back model. A new model will have to be created in that case and all stories need to be adapted so they connect to the new model.
This option is aligned with the standard approach with one major difference. One additional model will be created on which all the stories are build. When data is entered in the story, a “cross model copy” data action is required which will copy data to the write-back model and publish the data. Data will then automatically go into SAP BPC.
In this scenario we cover additional requirements that could be present for other LoB. By using additional SAC models next to the SAP BPC write-back model, we could allow users to input data in more detail such as employee expenses by employee or sales planning by SKU. The aggregated result will be copied into the write-back model and as such flow back into BPC. For the LoB models “master data on the fly” will be available as master data can be updated for these models which is not possible for write-back models.
Different scenarios, different options
As technically the SAC connection to SAP BPC standard and embedded is much different, also the available functionalities will differ between both scenarios.
Below an overview can be found regarding what is possible and what not.
Migration path scenario
Besides the hybrid scenarios, we should not forget that SAP Analytics Cloud is a future proof solution covering a lot of planning and reporting scenarios. So fully migrating your current solution into SAC could also be an option.
When migrating SAP BPC into SAC there are some items to consider:
- YTD storage in SAC is not yet supported (workarounds are possible)
- Default logic / Script logic can be converted into “advanced formulas”. The scripting engine of SAC is very powerful.
- All BPC dimensions can be reused in SAC
- Currently there are no modifications possible to the “date” dimension. So, the creation of “dummy” time members beside the standard members not yet possible, but it’s planned for one of the next releases.
- The member formulas in SAP BPC are quite similar to the “measure calculations” in SAC and can easily be converted.
- Security setup between BPC and SAC is quite similar
- BPC templates will need to be set up as “stories”
- BPF workflow can be set up with calendar functionalities in SAC
- Basic currency conversion possible in SAC
- No consolidation possible in SAC. SAP Group reporting would be a valid alternative here.
SAC provides a modern browser-based interface which can be used for planning and reporting and is a valid solution to innovate while protecting your current SAP BPC investment. The combination of SAC with BPC can be a non-disruptive and phased approach to the Cloud with quick time to value.
SAC can also be used to support the Corporate Plan in BPC for Agile LOB Planning, Reporting, Analytics, and Smart Data Discovery.
Another advantage is that a customer can simply replace MS Excel for all offline planning scenarios and feel confident using an enterprise platform.
Below we have listed a few key functionalities you can benefit from using SAP Analytics Cloud:
- Version Management (private versions)
- Driver Based planning
- Multi model pickup
- Currency translation
- Data Actions
- Spreading & Distribution
- Forecasting Algorithm
- Value Driver Tree
To show you an example we have created a recording showcasing how to use it in your organization.
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