Identifying Innovations in SAP S/4HANA Sales

A few examples of the aforementioned changes and innovations in SAP S/4HANA Sales are now briefly highlighted:

• The user experience: SAP Fiori
• Simplification and changes to the data model in Sales in SAP S/4HANA
• Analytics (see the last unit of this course for more details):
  • SAP S/4HANA embedded analytics to enable smart business processes (like the sales order fulfillment cockpit)
  • Management support by providing relevant sales KPIs out of the box with additional flexibility to create dedicated KPIs

One of the cornerstones of SAP S/4HANA is the user experience (UX) based on SAP Fiori. In the next unit, a more detailed overview of available and enhanced business roles for SAP S/4HANA Sales is given. The existing and updated SAP Fiori apps are also discussed.

SAP Fiori itself is a technology that offers a state-of-the-art web user interface (UI). It is based on HTML5 and SAPUI5. It also enables a user to personalize their screens. From a technical point of view, many front-end devices are supported (smart phones, tablets, laptops, desktops, etc.) providing state-of-the-art screens.

SAP Fiori enables developers to design and adapt a screen to the needs of the end user for a particular role, putting the user in the center of the business process. Following this principle, SAP tries to ensure that the SAP software is not simply targeting a generic individual who just needs to enter information in screens, but that the software is aware of the business context, the tasks, and the specific situation that every specific user is working in. Every user needs to be provided, with all relevant information that this specific user needs to perform their tasks.

The entire SAP ERP 6.0 data model was examined and underwent extensive restructuring when SAP S/4HANA was first introduced. Redundancies were eliminated, many smaller tables were combined into fewer bigger ones, and so on.

From a more general and technical point of view, the simplifications in the data model refer to the following:

• Only main tables remain. There are no redundancies stored anymore, like aggregates or totals (i.e. information that can be calculated/combined in real time when needed).
• There is a clear separation of master data and transactional data.
• Unused tables/columns got removed from the database.
• No cluster/pooled tables are used anymore: table pools and table clusters are no longer supported. Only transparent tables are used now.

Simplification also means simplification of the structure itself: the structure of the SAP S/4HANA database follows the Principle of One. Data is stored only once and all duplicate functionality in the system (and the corresponding tables) is removed.

An example of this is material valuation. In SAP S/4HANA, only one valuation method for materials is supported: valuation using the material ledger. In SAP ERP there were two: material valuation in Inventory Management (IM) tables related to the material master record and also valuation using the material ledger. In SAP S/4HANA this has been simplified: only valuation using the material ledger remains.

The available options in SAP S/4HANA for performance management and embedded analytics provide significant business benefits in many areas. Also in the areas of Sales (including its billing functionality).

Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP) are combined in SAP S/4HANA to create modern applications that combine transactions with analytics. Analytical reporting on transactional data is often referred to as embedded analytics in SAP S/4HANA. A wide variety of analytical options are available such as simulations, predictive analytics, and so on.

To summarize:

With the seamless integration of analytics features in S/4HANA, you can benefit from a variety of analysis options. Many analytical apps are available to support these analysis options.

More examples include:

Analytical apps Based on the Analysis Path Framework (APF): APF-based apps are interactive drill-down apps that you can use to explore KPIs and their influencing factors by drilling down into multidimensional representations of data, such as charts or tables. Various types of visualizations are available such as charts or tables.