Customer use case of Embedded SAC on Material Stock Analysis
These use cases show the capacity of the embedded SAC. It also shows how to work out an embedded SAC story based on customers’ business requirements. While standard dashboard could not cover all the customers’ needs.
As we all know, first-class analytics can make enterprise more intelligent. This blog is to introduce the embedded SAP Analytics Cloud that can help customers analyze business-related data in real time, which was seamlessly integrated with S/4HANA Cloud.
The embedded SAP Analytics Cloud is now fully managed by SAP S/4HANA Cloud which exposes the embedded SAP Analytics Cloud functionality through Fiori applications, and customers only need to work with it to design the report they want. And in this blog, a successful customer use case of eSAC will be shared to readers to show its strong analytical functionalities and ease of use.
What’s customer’s request?
Customers expect personalized access to data and ad-hoc analytical capabilities to get as much value out of their enterprise data as possible. They want a pre-defined report to display the inventory of materials for management and analysis of inventory data. Especially the financial department and the related inventory colleagues from the customer need to monitor the up-to-date material stock information based on material but currently no such offering like warehouse material stock analysis.
There is a dashboard in standalone SAC (enterprise) version. However it not cover all the customer needs. It is based on current stock.
As shown in the table below, customers hope that these data can be presented on the report.
|Material Code||Company Code||storage Location||Stock Quantity||Unit Price||Stock Amount|
How to solve the problem?
There are four main steps to implement Embedded SAC: creating Custom CDS View, creating Custom Analytical Query, creating Story and creating an Application. The specific steps will be described in detail below. To protect customer sensitive data, some of the screenshots come from dummy test system.
· Creating a Custom CDS View
Find the app Custom CDS View to create a new custom CDS view.
Fill the name of the new custom CDS view and select Analytical Cube for the scenario.
Add a Primary Data Source and an Associated Data Source. In this case, I_MaterialStock is chosen as main data source and I_InventoryPriceByKeyDate is used as associated data source. Set the inventory price to be calculated according to the current system date and select the association conditions of the two data sources.
Add the basic elements required by the report. Pay attention that the system will automatically add fields with key values, and other fields you want need to be added manually. Then maintain the element properties.
After previewing the data, it is found that each piece of inventory will have a value equivalent record in different currencies, so set the element filter conditions according to customers’ need.
If everything is finished, the CDS view can be published.
· Creating Custom Analytical Query
Navigate to Custom Analytical Queries.
Select the new created custom CDS view (YY1_MATERIALSTOCKACTUAL) as Data Source. Fill the name (YY1_MATERIALSTOCKA) and the label (MaterialStockActual) of the query.
Select the field. Pay attention that it is not recommended to change the field label to Chinese, because when adding the calculation, the Chinese label is not supported. The change can be made later.
If all the configurations have been all set, the query can be published.
· Creating Story
The Create Story page allows customers to define SAP Analytic Cloud story for a selected data source. Customers can create different visualizations to the data source. Multiple data sources can be added to the story and users can design interactive dashboards, create new pages, and add visualization such as charts, tables, and other graphics to visualize the data. The items on the page such as chart are arranged as tiles that can be moved around, resized, and styled to your liking.
Therefore, we have defined an SAP Analytic Cloud story for the new created data source to visualize the data that the customer wants to show on the page.
Firstly, navigate to KPI Design group in the Fiori Launchpad (FLP).
Choose “Stories” tab from the Manage KPIs and Reports app page. To create a custom story, choose “+ ”(Add).
Fill the title, tag and information of the story.
Select the new created query.
Layout the Canvas page according to customers’ needs. As shown below, add lanes as needed:
Maintain the title, insert pictures or shapes as needed to complete the style design of the report.
According to the report requirements, the calculation column is added as the inventory amount, and the unit is changed to CNY.
Maintain Calculation column formula. And the columns can be renamed in Chinese.
Unit maintenance is as follows:
Finally, Input Control can be added to set the entire page level or a single chart level. For example, input controls can be set for company code and material number respectively. In this case, put them all on the left side of the report.
· Creating an Application
To create an application (aka FLP Tile) to launch the story, choose Applications > Add Tile.
Choose a Tile Type format from the various options.
Fill out all the details and click on “Save and Publish”.
After successful save of the tile, it will navigate to “Custom Catalog Extension” app to publish a tile in the desired catalog.
In “Custom Catalog Extension” App, add a catalog to publish the tile. After the tile is successfully published, the tile can be found in the directory of Analytics-KPI design, which is convenient for users to view the report.
In this blog, we show how to create a custom SAP Analytics Cloud Story or Dashboard via S/4HANA Cloud and embed it in S/4HANA Cloud Fiori Launchpad. The customized Material Stock Analysis can provide the prompt of date for user to access the stock of specific date, which fully meets the customer’s business needs. By using the S/4HANA Cloud embedded SAP Analytics Cloud, it becomes efficient to help customers solve problems with its powerful function. In the future, we will continue to share more successful stories of embedded analytics to readers.
For more information on SAP S/4HANA Cloud embedded analytics with SAP Analytics Cloud, check out the following links: