Analyzing Incoming Sales Orders Using the Extension Ledger

Objective

After completing this lesson, you will be able to Analyze Incoming Sales Orders Using the Extension Ledger.

Analyzing the Sales Order Cycle in a Make-to-Stock Business Scenario

Order capture and order fulfillment are the core responsibilities of an internal sales representative. In today's world, managing increasing order volumes while tightly controlling sales operation costs are key contributors to a company’s margins. Therefore, efficiency and effectiveness are essential to the order and contract management process.

In this chapter, we review the order-to-cash process from the perspective of margin analysis. Starting with the receipt of customer orders, delivery, and invoicing, you see how the individual phases of the process are recorded in accounting and which evaluations are possible in margin analysis.

Analyzing Incoming Sales Orders Using the Extension Ledger

Predictive accounting shows the impact of future sales on accounting, starting right when a sales order is created and before any journal entries are posted to the general ledger. Predictive journal entries are created in a special prediction ledger. This ledger allows you to see the possible impact on your margin of future goods issues and billing, before the actual transactions take place.

SAP S/4HANA uses an extension ledger in accounting to store the values coming from incoming sales orders. Normally, a sales order doesn’t update accounting. The first actual accounting entry is at the time of the goods issue. However, with the incoming sales order functionality, sales orders post entries to the extension ledger.

The image represents a diagram or flowchart depicting the sales order process in a Make-to-Stock (MtS) scenario. The diagram illustrates the flow of information and the impact on various financial and operational aspects, such as revenue, cost of goods sold (COGS), stocks, and bonuses. The process begins with the creation of a sales order (SO), followed by delivery and billing. The diagram also highlights the involvement of different modules or systems, such as FI (Financial Accounting), NEW GL (New General Ledger), SD (Sales and Distribution), and PCA (Profitability Analysis).

The Extension Ledger in Margin Analysis

For margin analysis to store predictive data in SAP S/4HANA, you need an extension ledger. An extension ledger sits on top of a standard ledger, as shown in the following figure.

The image represents a diagram illustrating the relationship between the sales order, goods issue, and invoice processes, and their impact on different ledgers in an accounting system. The diagram shows that data from these processes is recorded in the ACDOCA table, which serves as the basis for the Extension Ledger (0E) and the Leading Ledger (0L). The Extension Ledger is used to capture additional dimensions related to the transactions, while the Leading Ledger represent the primary or controlling ledger for financial reporting purposes. The arrows in the diagram suggest the flow of information from the sales order, goods issue, and invoice stages to the ACDOCA table, and subsequently to the Extension and Leading Ledgers.

The extension ledger is an add-on ledger that uses a delta logic. For example, if you have defined the extension ledger 0E with the leading ledger 0L as the reference ledger:

  • When you post a document to the 0L, it is not posted in 0E. Likewise, when you post a document to the extension ledger EL, it isn’t posted in 0L.
  • When you run a P&L and balance sheet report for 0L, you only see the figures posted to 0L. However, when you run a P&L and balance sheet report for extension ledger 0E, you see both postings from the reference ledger 0L and extension ledger EL.

The extension ledger is always defined with reference to a standard ledger. It inherits the basic settings of the underlying ledger such as the assigned currency types.

Incoming Sales Orders in Margin Analysis

Predictive accounting enables you to look at and analyze data using a forecast of future results based on the most up-to-date data. It enables you to have a better understanding of what your results are at the end of the current period or quarter, and why. 

When a sales order is created, predictive accounting simulates the corresponding goods issue and invoice. The results of the simulation are stored as journal entries in an extension ledger. The postings in the extension ledger, along with the current data from the underlying base ledger, enable you to see a forecast, for example, of the revenue for one product. You can also see a report on all line items of one product. You can display and analyze the data in detail but also at a higher level, for example, in a financial statement.

Note

Classic Report Painter reports can't be selected from the extension ledger. CDS-based reporting is required.

Data in predictive accounting is processed as follows:

  • When a sales order is created, predictive accounting checks if delivery and invoicing is possible.
  • The system simulates follow-on processes and creates the journal entries in financial accounting accordingly.
  • Subsequent financial processes such as revenue recognition and the splitting of costs of goods sold are also triggered. All corresponding documents are displayed in the system as if they were real data. The documents can be identified by a prefix.
  • The simulated data is available in reports, and you can see and analyze it in your financial statements by selecting the extension ledger as the source.

Example

Create a Sales Order

In this example, a sales order is created for the product FG1_CP, which the customer orders. The planned revenue of EUR 120, along with the cost breakdown, is transferred to the prediction ledger.

Sales Order Application in SAP S/4HANA

My Sales Overview Application

There are multiple methods for reporting the predictive accounting entries created by sales orders. As these entries are posted in the extension ledger, any standard report with a ledger selection can be used since the data resides in the universal ledger. Essentially, all financial accounting-related queries and apps display the predictive accounting entries.

The My Sales Overview app provides detailed information about current sales.

This application allows you to view and create sales data through actionable cards, displayed in a dashboard format. Sales data can include:

  • Incoming sales orders.
  • Blocked credit memo requests.
  • Customer returns.
  • Customer information.
My Sales Overview Application in SAP S/4HANA

Key features of the application include:

  • Cards that present sales document information, allowing you to expand them for more details. For instance, the Blocked Credit Memo Requests card shows the status of credit memos and provides further details for a specific credit memo request.
  • The Quick Actions card enables the creation of various sales documents, including sales orders, sales quotations, credit memo requests, and customer returns.
  • A global filter allows results to be filtered by sold-to party, sales organization, distribution channel, division, and more, affecting all cards except the Quick Actions card.
  • Cards displaying graphs and analytics also offer aggregated data and data by status.
  • In your user settings, you can set default sales area filters (Sales Org., Distr. Channel, and Division) and default currency settings (Display Currency) under the Default Values option.

Open Sales Quotations

The app displays a list of incomplete sales quotations. Entries on the card are sorted by the last changed or created date. From within the app, you can directly navigate to the Manage Sales Quotations app. You can also select a specific open quotation to view more details.

The figure illustrates sales quotations that have been posted and remain unprocessed in the system for an extended period.

Open Sales Quotations

You can directly navigate to the quotation to determine the reason for its rejection.

Display Quotation Application with the field Reaso for Rejection highlighted. The selected reason is Rejected by Approver

You can then contact a sales representative to discuss if they should speak to the customer about the reason for the offer's rejection. This step is important in customer relationship management.

Incoming Sales Orders, Open Sales Orders

Another example is the analysis of incoming sales orders. It is crucial that sales orders are followed up on and processed promptly.

Screenshot displaying the card for Incoming Sales Order and a card for Open Sales Order.

The sales volume of EUR 571 pertains to three sales orders with the numbers 29, 30, and 31. You can navigate directly to these sales orders. Starting from Incoming Sales Orders, you can select all created sales orders that meet the selection criteria. When you choose Open Sales Orders, all sales orders with the overall status Open that correspond to the selection criteria are selected.

Image is showing that the card Open Sales Orders is listing the Sales Order with the ID 31. An arrow is pointing to a screen with the Display Sales Order app showing the details for the sales order with the ID 31.

Complete Prerequisites and Sales Order Creation

Business Example

Your company is ready to test the integration of sales and services to Accounting (FI) and Controlling (CO). Topics include the mapping of the Sales and Distribution (SD) condition types to the CO-PA value fields, and the effects on valuation and derivation.

You want to check the following:

  • Transfer of Incoming Sales Orders to the Predictive Accounting Ledger.
  • Transfer of Statistical Conditions in the sales order for Warranty costs that updates the Predictive Accounting Ledger.
  • Review the condition types that are mapped to the value fields in your operating concern so that the corresponding value fields are populated when a sales order is posted.

To test a sales order, you need an inventory. To post the goods receipt, use the Post Goods Receipt without Reference app in the tile group Logistics – Cross Functions. 

Familiarize yourself with the process of posting a goods receipt and creating a sales order by utilizing the interactive simulation.

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