The account-based profitability analysis in SAP S/4HANA has been redefined and considerably extended in terms of its functions. They renamed what was previously known as the account-based profitability analysis to margin analysis. The new name has confused many customers, as the new term is not yet available in the system – at least not in SAP GUI – until the current release. Here – for example, with the definition of the operating concern – reference is still made to the account-based profitability analysis. Margin analysis is active, however, if an activation indicator is set for “the accounting department” in the operating concern.
Unlike cost-based profitability analysis, which continues to be available in SAP S/4HANA, the margin analysis has been greatly extended in recent releases. New developments in the CO-PA environment will only occur in the margin analysis area from now on. For this reason, we generally recommend the use of this form of financial statement.
The previous considerable advantages of costing-based profitability analysis, such as the calculation of costing-based cost items (for example, freight through statistical SD conditions), the display of variable and fixed cost of goods manufactured from the costing data of the materials, the presentation of production variances according to variance categories, or the presentation of incoming orders, can now also be presented with the margin analysis.
Implementation of various functions in the margin analysis
Breakdown of the cost of sales
You can define the settings for the apportionment of the cost of sales to different accounts using the cost components of the underlying costing sheet. It is possible to apportion the cost of sales for goods movements based on customer orders or additional processes (inter-company-code stock transfers, direct sales, and so on). In the standard system, a released material cost estimate or customer order cost estimate is required for this.
The following steps must be executed to carry out the cost apportionment:
Apportionment of manufacturing deviations
In addition to the cost of sales, it is also possible to break down the price differences according to deviation categories in the manufacturing. The prerequisite is the use of standard prices for the manufacturing of materials. Manufacturing deviations are calculated in the product cost controlling (CO-PC) by the deviation calculation and divided into different deviation categories (such as price variances, quantity variances, lot-size variances, and so on).
The steps for setting the apportionment profile for manufacturing deviations are similar to the steps of the cost of sales apportionment profile.
Attributed profitability segments
With general ledger items without assignment to a profitability segment, it is now possible to define what is known as an attributed profitability segment. The idea behind this is to provide as many characteristics in the item as possible to enable an improved level of reporting.
This is implemented such that the CO-PA-relevant data from the general ledger item are used as a basis and are then derived in several steps according to a best-guess principle. The steps differ according to the account assignment category of the item (for example, cost centre, internal order, WBS element, …) and are carried out automatically.
For general ledger items with an attributed profitability segment, costs and revenues are only displayed in the reporting (not in all reports: see the Reporting section) and are not intended for further processing.
Transfer of statistical conditions from the SD
This relatively new function allows statistical conditions for the sale when invoicing a customer order to be transferred to the profitability analysis (CO-PA). The purpose here is the enhancement and optimisation of the reporting with relevant information.
It is necessary to take into account the fact that only statistical pricing conditions with the status of “active” can be transferred to the profitability analysis. In addition to this, in the control parameters for a costing sheet, the “relevant for account determination” indicator must be deactivated. The statistical pricing condition is then posted as a posting document to an extension ledger of the financial accounting, which must be defined and assigned beforehand.
Any analytical app that uses posting documents can use data from the extension ledger.
This function is based on a similar function in the costing-based profitability analysis (transfer of SD conditions to value fields).
Predictive accounting (incoming customer orders)
Predictive accounting – the mapping of incoming customer orders – also makes use of the extension ledger concept.
When a customer order is created, the predictive accounting simulates the goods issue as well as the invoice. It also takes subsequent processes into account, such as the apportionment of the cost of sales (see above).
The results of the simulation are stored as posting documents in an extension ledger, which is also known as a forecast ledger.
As soon as the goods issue and the invoicing have actually taken place, the simulated postings are cancelled, and the actual documents for the goods issue and invoice are posted.
The objective, for example, is to be able to conveniently predict how operating profits will develop at the end of the current financial period or the current quarter. But as well be able to understand these predictions.
There are two analytical apps for predictive accounting in SAP S/4HANA, which are explained in the Reporting section.
It is necessary to remember that for general ledger items with a real account assignment to a profitability segment, the account assignment type is profitability segment (field ACCASTY = ‘EO’). The “Product Profitability” and “Display Line Items – Margin Analysis” apps focus solely on profitability segments in the case of this true account assignment to the profitability segment.
Other analytical FIORI apps, such as market segments, also take attributed profitability segments into account.
The profitability reports (KE30) with which you are familiar from SAP ECC systems can still be used in the margin analysis. This type of reporting can also be integrated into the FIORI Launchpad.
In this respect, please note that it is only possible to read data from the leading ledger. It is not possible to read from extension ledgers.
With the “Product Profitability” FIORI app, you can analyse contribution margins for individual products in connection with the related product information and available profitability analysis characteristics. Based on the cost component split of your standard cost estimate, it enables you to execute a breakdown for fixed and variable costs. You can also display the invoiced quantity and the contribution per unit.
Display line items – margin analysis
You can use the “Display Line Items – Margin Analysis” app to display posting document line items that are of relevance to the margin analysis. You can filter, sort and group the items according to various criteria.
You can display the line items according to the ledger to which they were posted. You can also select an item and use line item details to display additional information sorted by field group. Navigating to related apps is possible.
With the analytical “Market Segments” FIORI app, you can display and analyse actual and planning data for various market segments, i.e. combinations of several characteristics. In this case, please note that data from attributed profitability segments (see above) is also displayed.
Apps in the predictive accounting
With the “Incoming Sales Orders – Predictive Accounting” FIORI app, you can evaluate revenues, sales deductions, cost of sales, and margins that were simulated based on incoming sales orders, goods issues, and invoices in the extension ledger.
Filter revenues, cost of sales and margins based on time periods and different characteristics such as organisation, customer, product, etc.
You can also navigate directly to posting documents, customer orders or products.
With the “Gross Margin – Presumed/Actual” app, you can also compare the forecast data with planning data or actual data from previous periods.
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