Exploring SAP Applications for Predictive Analytics Model Training – Supply Chain (20N)

• Predictive Models (F1837) SAP Fiori App
• Overdue Materials - Stock in Transit (F2139) SAP Fiori App
• Mass Maintenance of Products (DD) (F2825) SAP Fiori App
• Record Defects (F2929) SAP Fiori App

SAP BusinessObjects Predictive Analytics integrator is a framework specific to SAP S/4HANA applications that enables the apps to consume and manage predictive models directly in the business application. This framework enables end users to easily consume the data from predictive scenarios without interacting with code.

Predictive Analytics integrator comes with two Fiori UIs:

• The first allows a developer to create predictive scenarios by specifying a model type and dataset and also to create functional areas to group predictive scenarios.
• The second UI allows the Business Analyst to configure and train models using the filters specified in the predictive scenario or to import more complex models from SAP BusinessObjects Predictive Analytics. It also allows the business analyst to manage the lifecycle of the model by checking its quality and triggering retraining when required.

The Overdue Materials - Stock in Transit app provides an overview of the overdue materials for which a stock transport order has been created. You can identify these materials to complete the stock transfer process or investigate potential problems. In addition, you can use the situation handling framework to bring important issues to users' attention with this app. The situation handling framework enables you to prepare proactively for changing situations and manage their effect on purchase orders with overdue materials.

• Transfer Stock
  • Check all stock transport orders where materials are scheduled to arrive in a plant, by, for example, filtering according to the goods issue date.
  • Select the Stock in Transit Process Type in a selection field.
  • Display a list of stock transport orders where the stock transfer process has not yet been completed, by, for example, filtering according to days since posting date.
  • Check items where the goods receipt process is still open or has already been completed with three predefined tabs with selection variants for stock transport order (STO) items where the following information is displayed:
    • The incomplete or open STO items
    • The complete STO items
    • The complete and incomplete STO items together
• Predict Delivery Date
  • Use a predictive analytics model to predict the delivery date for an order. With this information, you get a forecast based on your company's empirical data if a goods receipt can be successfully completed in time. The shipping duration micro chart illustrates the goods movement process for an item and shows, for example, the forecast delivery date in relation to the actual date.
  • If the predictive analytics model is active, the system uses the predicted delivery date as forecast delivery date.

Note

Depending on your authorization settings, the app might only display zero in all the stock value columns in the results table. This type of financial information is often only available to a specific group of users. If zero displays, you can hide these irrelevant value columns in the table display or get in contact with your administrator to clarify what you are authorized to display.

Stock Transport Order Overdue (MAN_MATLOVERDUESITSITN), which is delivered for the Overdue Materials - Stock in Transit app.

You can use this standard template for the following situation example: Warehouse clerks check the status of goods receipts to ensure the planned goods movements in a plant are on track. With this standard template, you get immediate information about overdue stock transport order items, which enables you to begin follow-up actions to guarantee service level or a high throughput of goods.

Key users can use the Custom Fields and Logic app to make data source extensions for the following business contexts:

• Master Data: Product General
• Master Data: Product Plant
• Master Data: Batch

Note

Master Data: Product Plant can be used for the issuing plant and the receiving plant.

Key users can also use the data source, Consumption View for Stock Overdues, to add fields to the following UI elements with the UI adaptation at runtime:

• Filter Bar
• Table View
• Chart View

With the Mass Maintenance of Products (DD) app, you can display and change product details (master data records) relevant to Demand-Driven Replenishment. After you have classified or re-classified your products, you can view the results of the classifications in this app, and based on the results, select products that are relevant to Demand-Driven Replenishment. You can use the mass change feature to change the master data records for several products simultaneously. This is the second app that you'll use when you start with Demand-Driven Replenishment.

• Select products that are relevant to Demand-Driven Replenishment.
• Mark your selected products as DD-relevant by setting an appropriate MRP type.
• Display and change the results of product classifications.
• Select an averaging interval, based on which the Average Daily Usage (ADU) and the Decoupled Lead Time (DLT) is calculated.
• Select which lot sizing procedure the system uses within materials planning to calculate the quantity to be procured or produced.
  Note

  When you select D1 as the MRP type while creating demand-driven materials, the lot-sizing procedure must be H1.
• Set a minimum lot size to define a minimum procurement quantity.
• Export your filtered results into a spreadsheet and save it to your computer.
• Calculate individual lead time of products using one of the following methods:
  • Using the creation date
  • Using the release date
  • Directly from the product master
  • Using predictive analysis
    Note

    You can use predictive analysis to calculate individual lead time for stock transfer products only
• The app also supports integration with email servers, SAP Jam, and saving as a tile on the launchpad.

Note

When you run this app for the first time, you may see that your products don't have a lead time (EFG) classification. Only DD-relevant products are classified based on their Decoupled Lead Time. After you have identified and marked products that are relevant for Demand-Driven Replenishment, you can use the Schedule Lead Time Classification of Products (DD) app to classify your products.

You can create defects of different defect categories. Depending on the defect category, you can record different data for a defect. You can display your own tiles on the SAP Fiori launchpad for the individual defect categories. Defects of the "generic defect" category are independent of any specific reference object, such as an inspection lot or a material. You record generic defects using the Record Defect app or the Process Defects app.

Create quality notification from a generic defect in the Manage Defects app. Further processing of the defect is then only possible in the quality notification.

• SAP Activate Roadmap Viewer

• SAP Best Practices for SAP S/4HANA Cloud, public edition

• SAP S/4HANA Cloud, public edition

• SAP Fiori Apps Reference Library

Note

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