Modern Enterprise Resource Planning (ERP) systems are challenged by mixed workloads, including OLTP-style and OLAP-style queries, for example:
- OLTP-style: Create sales order, invoice, accounting documents, display customer master data, or sales order
- OLAP-style: Dunning, available-to-promise, cross selling, operational reporting (list open sales orders)
Today's data management systems are optimized either for daily transactional or analytical workloads, which store their data along rows or columns.
This separation leads to the following drawbacks:
- The OLAP system does not have the latest data.
- The OLAP system only has a predefined subset of the data.
- A cost-intensive ETL process must synchronize both systems.
- Data redundancy is introduced.
- Different data schemes introduce complexity for applications that combine sources.
Business applications started out decades ago as a means of capturing systems of record, sales orders, trouble tickets, journal entries, and other records of business operations. Line-of-business personnel needed access to this information to decide, for example, how to price, plan, and set priorities. IT then built separate analytic decision support systems on completely different platforms. In theory, having separate systems for the various workloads offered on different platforms sounds logical. For many years, having separate platforms was the accepted approach to ensure good performance for transactions and analytics, given the different requirements for capturing data versus analyzing data. In practice, however, the requirement to transfer data between the two platforms underlying the two types of systems causes information delays and reduces the ability to connect insight to action because of a disconnect from analytics to source data. This leaves the enterprise at risk when decision makers are forced to rely on stale or insufficient data, or when they cannot connect analytic insights to source data.
SAP S/4HANA Cloud can couple transactions with analysis in real-time, within a single blended environment to determine the best way to get live insight about a fast-breaking situation. Rather than using separate transactional and analytical applications built on separate platforms, a single data management environment for both systems of record and systems of decision (assuming good performance can be achieved for both) can yield the following benefits:
- Users can access and analyze the latest data as soon as it is captured rather than waiting for data transfer, which eliminates a major source of information delay. By reducing the overhead of multiple platforms, IT data management tasks and business data governance functions can be simplified.
- With instant access to data, business personnel can make business decisions faster, based on the latest information. Business processes can also be accelerated. As an example, during an interaction, contact center employees have the latest customer data available. A cross-sell recommendation can be made on the most recent customer orders, or even on an order that is in process.
SAP S/4HANA Cloud blends transactions and analytics allowing operational reporting on live transactional data. With SAP S/4HANA Cloud, this concept is supported using SAP Core Data Services (CDS) for real-time operational reporting. The content is represented as a Virtual Data Model (VDM), which is based on the transactional and master data tables of SAP S/4HANA Cloud. CDS views are developed, maintained, and extended in the ABAP layer of the SAP S/4HANA Cloud system. The system generates SQL-Runtime-Views in SAP HANA to execute the data read and transformation inside the SAP HANA database layer.
The advantages of this approach include full ABAP integration, allowing for instances to re-use existing reporting authorizations, and so on. Also, SAP can make use of the analytical engine (embedded BW functionality) to support an elaborate hierarchy display. These advantages allow for the creation of many more use cases for the VDM. SAP S/4HANA Cloud analytics support not only generic operational OLAP reporting, but also scenarios of embedded analytics for hybrid transactional and analytical applications (such as embedded SAP BI or SAP Smart Business Cockpits) based on the same models. Read access for search/fact sheets is also supported.
Multidimensional reporting includes all explorative analysis tasks that focus on unexpected business questions. Ad-hoc filtering, pivoting, sorting, and rearranging of data in tabular or graphical UIs is supported. A Web Dynpro grid is used in this context.
Key process steps
- Analytical and transactional display of the sales order processes such as sales quotations, sales order fulfilments, customer returns, back orders, demand fulfillment and delivery performance.
- Filter the KPIs according to the different business attributes, such as sales organization, sales document type and sold-to-party.
- Navigate from the KPI insights to the corresponding smart apps for detailed analysis.
- Share high-level process KPIs and high-level process information with persons responsible for process execution in a sales organization.
For sales and distribution scenarios, this scope item provides key information needed for a sales manager or internal sales representative about the different stages of a sales order. The analytical apps provided here highlight the back orders, demand fulfilment, sales order fulfilment and delivery performance in the sales process. A SAP Fiori Overview page is also available that provides the different insight to actions about objects such as sales quotations, customer returns, and sales order fulfilment.
The following are the main elements in the Process Diagram:
My Sales Overview
- Sales Management Overview
- Sales Quotations - Flexible Analysis
- Quotation Conversion Rates
- Sales Contract Fulfillment Rates
- Incoming Sales Orders
- Analyze Confirmations of Sales Orders
- Delivery Performance
- Customer Returns - Flexible Analysis
- Customer Return Rate
- Sales Volume - Flexible Analysis
- Sales Volume - Detailed Analysis
- Sales Volume - Check Open Sales
- Sales Volume - Credit Memos
Sales Volume - Profit Margin
- Sales Scheduling Agreements - Product Demand
- Customer Returns Overview
- Order to Cash Dashboard
- Perform daily activities smoothly using a dashboard of information for the internal sales representative or sales manager from the SAP Fiori Overview Pages
- View delivery performance and sales order fulfillment as a mix of the table and chart visuals on the sales order process in the Analytical List Pages
- Understand key numbers with high-level insights for the sales manager to drill down to action
- Provide status of the sales orders, sales quotations, back orders and unconfirmed orders
- View strategic and operational overviews for the end-to-end sales order processes
Main apps used
|Main Elements||Role Name||Fiori App Name|
|My Sales Overview||Sales Manager / ISR / Returns Clerk||My Sales Overview|
|Sales Volume - Profit Margin||Sales Manager||Sales Volume - Profit Margin|
|Sales Volume - Credit Memos||Sales Manager||Sales Volume - Credit Memos|
|Sales Volume - Check Open Sales||Sales Manager / ISR||Sales Volume - Check Open Sales|
|Analyze Confirmations of Sales Orders||Sales Manager|
Sales Order Items - Confirmed
Sales Order Items - Backorders
Sales Orders - Demand Fulfilment
|Sales Overview||Sales Manager||Sales Overview|
|Delivery Performance||Sales Manager||Delivery Performance|
|Sales Contract Fulfilment Rates||Sales Manager||Sales Contract Fulfillment Rates|
|Quotation Conversion Rates||Sales Manager||Quotation Conversion Rates|
|Incoming Sales Orders||Sales Manager||Incoming Sales Orders|
|Sales Volume - Flexible Analysis||Sales Manager||Sales Volume - Flexible Analysis|
|Sales Volume - Detailed Analysis||Sales Manager||Sales Volume - Detailed Analysis|