Künstliche Intelligenz in SAP-Umgebungen


Artificial intelligence (AI) and SAP

Technological breakthroughs have recently given artificial intelligence (AI) a considerable boost and sparked interest among many SAP customers. AI offers enormous potential for automation and process insights, especially in the form of machine learning (ML).

What Benefits Does ML Offer? 

ML offers the possibility to extract correlations and decision patterns from datasets. All ML models need to be created once from a set of initial learning data. In our context, this is often historical company data. A great deal of computational effort is associated with creating an ML model. However, once created, it can then be quickly applied to new data with very little computational effort.

Of the numerous possible uses, the following two examples describe the benefits of ML technology within the SAP environment:    

  • Automation of core processes: for the classification of business transactions, automatic decisions, and data transformation, for example
  • Data analysis: data extrapolation for forecasting purposes, uncovering unexpected correlations  

Which ML Models Exist at SAP? 

SAP defines machine learning scenarios (or intelligent scenarios) as a business use case for ML with clear integration points into core processes and firmly defined learning data/results data. A distinction is made between embedded ML and side-by-side ML.

In the case of embedded ML, machine learning is learned and executed directly on the S/4HANA database, which imposes limitations on model selection and performance. With side-by-side ML, the computationally intensive ML processes are offloaded to external systems, enabling more powerful ML applications. Here, various payable cloud services are available based on the SAP Business Technology Platform (BTP), which forms the common platform for most SAP Cloud products (see here). From a technical perspective, however, the use of a customer's own servers or other cloud providers are also conceivable. For both ML approaches, in addition to a few dozen pre-built ML scenarios, there are also options for tried-and-trusted ML experts to develop separate models.

What Does SAP Intelligent Scenario Lifecycle Manager (ISLM) Offer?

SAP Intelligent Scenario Lifecycle Manager (ISLM), which is included in the standard license as of Version S/4HANA 2020 FPS0, is the common control center for both ML approaches in SAP S/4HANA. SAP ISLM consists of the following two Fiori apps: "Intelligent Scenarios" for creating and integrating your own scenarios and "Intelligent Scenario Management" for controlling the operation and timing of learning new ML models.   

While the ML scenarios provided by SAP are integrated directly into the corresponding standard Fiori apps, ISLM exposes the customer-specific ML models as an automatically generated ABAP class or CDS View for use in custom Fiori Apps, ABAP reports or extension implementations.

Embedded ML or Side-by-Side ML?

Embedded ML scenarios therefore allow the use of ML models learned using the company's own data without SAP BTP and additional products. Since there are rapid changes and many detail differences in the list of SAP ML scenarios, we recommend conducting a customer-specific analysis together with XEPTUM.

Below are some examples from the SAP list. For the most part, their names are self-explanatory:

  • Supplier Delivery Prediction from Purchasing
  • Early Detection of Slow/Non-Moving Stocks from Supply Chain Management
  • Sales Performance Prediction from Sales   

Side-by-side ML scenarios require additional products in SAP BTP, first and foremost:

  • SAP AI Core and SAP Business Service: focus on powerful ML models with complex application scenarios, flexible integration of self-programmed ML models possible
  • SAP Data Intelligence: tool with a focus on data connectivity/merging with somewhat more limited ML capabilities
  • SAP Analytics Cloud: tool with a focus on BI, possibilities for ML in the area of forecasting, extrapolation of key figures, predictive analytics

In practice, for example, a side-by-side ML scenario called "Receivables Line-Item Matching" has proven its worth, enabling ML-supported bank statement processing via the SAP Cash Application as part of SAP Business Services. This can significantly reduce the time-consuming task of manual post-processing (see here).

As already mentioned, customer-specific ML scenarios can be defined using the SAP products in the embedded ML approach, and using BTP add-on products in the side-by-side ML approach. These are tailored exactly to company-specific processes and individually relevant data. Moreover, they can be developed in a joint workshop with XEPTUM, implemented in a suitable tool, and integrated into processes via ISLM with reasonable effort. 

What Are the Alternatives to SAP Cloud Products?

In the case of individual ML models, it is of course worth considering whether to run ML on your own servers or with other cloud providers and thereby accept that you will develop your own interfaces for use with SAP. This can also be a suitable approach for end-to-end processes in larger system landscapes that extend beyond individual SAP systems and have many data sources. But beware: depending on the depth of process integration within ML scenarios, you may incur additional license fees from SAP (keyword "indirect use"). This should be clarified beforehand. 

How Can XEPTUM Support You in ML Projects?

There is huge potential for optimization through the use of intelligent technologies. However, SAP's AI product portfolio remains complex. Rely on our team of experts who will combine their comprehensive technology expertise with in-depth process knowledge! We can help you gain an overview and assist you in implementing ML into your IT landscapes and business processes.

This support ranges from analyzing existing scenarios or defining new scenarios through to implementing the appropriate AI model and SAP interfaces as well as supporting the daily operation of a routine AI model. Irrespective of whether we move within the SAP product portfolio or develop our own cross-system approaches,
we will competently accompany you on your journey towards becoming an intelligent company.