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Author's profile photo Joey Li

Customer use case of Embedded SAC on Inventory Aging Report (Enhanced)

This is a PoC in customer system for embedded analytics, especially embedded SAC. S/4HANA Cloud Embedded SAP Analytics Cloud can enhance the analysis function of the current system and can better help customers analyze business related data.

In the previous blog, we have introduced how to create an Inventory Aging Report by using embedded SAC (Customer use case of Embedded SAC on Inventory Aging Report: click here.). Now the report has been enhanced and in this blog the enhancements will be shared to readers. The key steps to implement it are shown in detail below.

What’s the enhancements?

Based on the original report, the information of Storage Location will be added in the report and the logic of stock value and Inventory Aging will be adjusted. Here is the final output for the enhanced inventory aging report. The Value is based on PUP.

Plant Material Material Group Material Desc. Supplier Batch Storage Location 0-30 DAY
               

 

31-60 DAY 61-90 DAY 91-120 DAY 121-180 DAY 181-360 DAY 361-730 DAY
           

 

Over 730 DAY Stock Quantity Stock Value
     

 

How to implement the enhancements?

1. Creating custom CDS View

Same as the original report, the Material Stock (I_MaterialStock) and the Product (I_Product) are still needed to create the new report. Then the Stock Value (I_InventoryPriceByKeyDate) are also needed to provide the valid inventory price of a material on a specified date instead of the Current Stock Quantity and Value (I_StockQuantityCurrentValue) used in the original report.

When creating YY1_Inventory_Quantity, we need to add I_InventoryPriceByKeyDate as the associated data source and edit Cardinality to be [0…1].

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Maintain the input parameter as PostingDate.

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Add Inventory Price.

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The add I_Product as the associated data source and edit Join Condition.

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The other configuration is the same as the original report.

2. Creating custom query

In “Custom Analytical Queries” APP, create a query and select data source YY1_Inventory_Quantity.

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Select necessary fields and add the Calculated Column ZInventoryPrice.

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Check the option of Exception Aggregation, then choose the Function of Last and Dimensions of Posting Date.

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Add the Calculated Column ZTOTALAMT.

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Assign Row and Column.

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Add Input parameters, for example:

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The other configuration is the same as the original report. Then save and publish the query.

3. Creating story

In “Manage KPIs and Reports” APP, we need to create Current Date Input Control based on the original report.

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Select time range for the first period: past 0-30 days.

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The rest of measures are the same, but the only difference is the offset in time range setting. E.g. how to acquire the past 31-60 days:

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Past 61-90 days:

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Then adjust the Calculated Measures for inventory aging. E.g. 0-30 DAY

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Over 730 DAY:

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If all the configurations are done, save and publish the story.

4. Creating an application

The steps to create an application are the same as the original report and readers can refer to the previous blog.

Conclusion

In this blog, we show how we enhance the Inventory Aging Report to better meet the customer’s business needs. By using the S/4HANA Cloud embedded SAP Analytics Cloud, it becomes efficient to help customers to create their custom reports and can enhance easily them. 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:

· Customer use case of Embedded SAC: how to create custom SAC story and the dashboard in S/4HANA Cloud: click here

· A Customer Use Case of Embedded Analytics in S/4HANA Cloud – Extend the Possibility:click here

· Customer use case of Embedded SAC on Material Stock Analysis: click here

· Customer use case of Embedded SAC on Inventory Aging Report: click here

· Customer use case of Embedded SAC on Manufacturing Cost: click here

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      2 Comments
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      Author's profile photo Saumitra Deshmukh
      Saumitra Deshmukh

      Thanks for sharing

      Author's profile photo Marissa Ren
      Marissa Ren

      Learnt more on S/4HANA Cloud embedded SAP Analytics Cloud. Thank you.