SAP S/4HANA embedded analytics
Author: Thomas Fleckenstein, Chief Product Expert for SAP S/4HANA Analytics.
The world’s leading ERP suite, (SAP S/4HANA, just in case you had doubts) is designed to optimally support business processes, making enterprise more efficient, more agile and more intelligent.
Delivering this value was made possible through a number of groundbreaking technologies, qualities and design-principles applied in the development of the SAP S/4HANA. To repeat just a few of them:
- Integration of transactional and OLAP operations on one database
- Reporting and analytics on real-time data
- Consistent look&feel on the UI
- Unmatched extensibility and flexibility to adapt to industries, geographies, business models
In this blog post, and several more that are going to follow, we will shed some light especially on the embedded analytics offering of SAP S/4HANA, which is summarized in the following picture:
And here are the most important messages of the picture above:
- On the presentation layer, embedded analytics is exclusively based SAP Fiori and SAP Analytics UIs
- It comes with a lot (really!) of predefined analytical apps based on Fiori and on SAP Analytics Cloud for the Business User (a user type you will read more about in future blog posts)
- For creating own KPIs, reports, dashboards etc., SAP S/4HANA provides tools for the role of the “Analytics Specialist” (which will also receive further coverage in future blog posts)
- The analytical models (queries, data sources,…) are implemented in the SAP S/4HANA Virtual Data Model, which provides real-time access to the transactional data and which therefore needs no data replication at all.
- Embedded Analytics works (only) on the data that is currently in the S/4HANA system.
- To cover use cases where data from multiple systems needs to be consolidated or long-term analysis requires to look at data that is not available in the transactional system, there is a close integration to the offerings of SAP Analytics, and here especially to SAP Analytics Cloud, SAP Data Warehouse Cloud and SAP BW/4HANA.
Talking about the SAP Analytics offering, it is important to mention that the “enterprise analytics” of the SAP Analytics solutions are not competing with the “embedded analytics” of SAP S/4HANA, but that both offerings address very different use cases and complement each other extremely well.
This becomes obvious when looking at what are typical examples for working with embedded analytics and for working with enterprise analytics.
Examples of embedded analytics:
- A material planner who is responsible for the stock availability analysis for just-in-time (JIT) calls of components and therefore needs to view the mapping of requested components to JIT calls. The necessary alignment with shipping specialists, transport planners, and production planners, requires access to real-time information for accurate decisions is needed.
The respective analytical app in SAP S/4HANA Cloud is the “Stock Availability Analysis for Just-In-Time Calls,” Fiori ID: F3923
- A collection supervisor who wants to assign new collection cases to the colleagues in the collections team needs information on the values of open cases and the remaining capacity of the team before making an informed decision.
This job is supported by the SAP Fiori app “Supervise Collections Worklist,” Fiori ID: F2375
- A salesclerk responsible for resolving blocked orders needs criteria such as the order value, the expected profit, or a prediction of the customer’s payment behavior to decide which orders to focus on. Based on this information, the salesclerk decides to increase a customer’s credit limit to unblock the order. The SAP Fiori app “Sales Order Fulfillment Issues,” Fiori ID: F0029A, supports the salesclerk in this case.
Examples of enterprise analytics:
- A head of purchasing who needs a global view of the activities with suppliers, combined with 3rd party data on e.g. the financial situation of the supplier (revenue, share price, …). A great case for SAP Data Warehouse Cloud where the data can be consolidated, and 3rd party data can easily get added.
- A board of directors assessing the financial situation of the enterprise in the Corona crisis on regular basis. They ideally do this in the Digital Boardroom of SAP Analytics Cloud.
- A sales manager planning the revenue on customer and product level for his/her territory. The best way to do this reliably and based on freely modellable data structures is to use SAP Analytics Cloud planning models and stories.
With that, we have only scratched the surface of embedded analytics and enterprise analytics. But it is important to keep in mind that both have their individual value, strengths and typical use cases. Going forward, however, my focus will be on embedded analytics of SAP S/4HANA.