Result object

A result object is an extension of the concept of cost units to the sales-related revenues. A result object thus represents a cost and revenue unit .

This extends cost unit time accounting to a multi-dimensional profitability analysis in the sense of a detailed contribution margin calculation in which the contribution margins can be shown for each product, organizational unit and customer segment.

definition

A result object is a cost and revenue support with pronounced characteristic values with respect to all relevant characteristic dimensions.

Computational application

In an operational profitability analysis, a data record is created for profitability analysis for every transaction that affects sales (e.g. as a result of invoicing ) . The data record contains the characteristic account assignments (product, organizational unit, customer segment) and the revenue key figures (gross revenue, net revenue, sales deductions, etc.). At the same time or as part of periodic post-processing (e.g. end-of-month processing), the corresponding sales-relevant costs are added to each revenue transaction. Various methods can be used individually or in combination:

• Overhead surcharge
• Levy
• Service allocation
• Process cost accounting

By bringing together the correct revenues and costs on the respective result object, the corresponding contribution margins per sales unit, per customer and per sales point can be determined.

Accordingly (z. B. product, organizational unit, customer segment and customer) the feature dimensions corresponding to a result object of a specific combination of characteristic values (Ex .: Product = Pneu-4712, OU = Hamburg-Nord, customer segment = truck, Customer = Müller-Transporte) . If there are several data records for a result object, e.g. B. due to several incoming orders, or because the aggregation takes place over several months, these can be aggregated by means of a crosstab query (or pivot table ). OLAP systems are often used for this in ERP systems with a correspondingly larger data volume .