Exploring SAP Analytics Cloud Reports

To better understand how margin analysis works, let's use an example.

Suppose that a company sells customer-configured forklifts and related services. The company can use margin analysis to determine the profitability of each forklift and service type (for example, maintenance or repairs) sold. Direct costs (such as raw materials and labor) and indirect costs (such as overhead expenses) associated with production are considered. This information helps logistics companies to make informed decisions about pricing and resource allocation for each forklift configuration and service type.

In SAP S/4HANA, margin analysis enables us to measure profit margins across various market segments, such as product types, customer groups, and sales regions.

Financial data is stored in real time, on a detailed, line item basis, in a universal journal. All actual data relating to the profitability segments of margin analysis is stored in the same universal journal (ACDOCA), which is used across all of finance. Therefore, you can always trust the data to be true to its source and skip complex, time-consuming data reconciliations. In margin analysis, costs and revenues are grouped using cost and revenue general ledger accounts. Anyone can expand a report and drill-down to the detailed line items that make up a figure.

Let’s look at an example of how margin analysis is updated across the steps of an order-to-cash business process for a make-to-order scenario. Business scenarios with manufacturing or with services (without manufacturing) can be distinguished. In a business scenario with services, there is no delivery or goods issue.

The following video explains SAP S/4HANA's configure-to-order process, using a custom forklift order to showcase how the system manages complex manufacturing requests from initial order to final delivery.

Upon sales order entry, the system posts line items to an extension ledger that is used for predictive accounting (which doesn't show up in your external financial statements). Moving to delivery and billing, the system deletes the statistical entries and creates actual line items in the standard ledgers. The entries, either statistical or actual, carry the full detail for the relevant profitability segments you have defined.

SAP Analytics Cloud is a software as a service (SaaS) for analytics, planning, and smart prediction. Currently, SAP provides two types of SAP Analytics Cloud platform options: embedded SAP Analytics Cloud and standalone SAP Analytics Cloud. SAP S/4HANA Cloud fully manages the embedded SAP Analytics Cloud and exposes the embedded SAP Analytics Cloud functionality through SAP Fiori apps. It is offered with no additional license fee. In the standalone option, each tenant has a dedicated SAP Analytics Cloud tenancy. In both options, each tenant’s data is isolated and remains invisible to other tenants. In terms of architecture, SAP Analytics Cloud accesses the ABAP core data services (CDS) views live, using the transient analytical queries generated automatically for the CDS views.

CDS Views

The virtual data model (VDM) forms the basis for analytical (and other) applications to access data in SAP S/4HANA. It is represented by CDS views. The CDS views expose business data (stored in database tables) in a format that is based on business semantics and therefore easier to consume.

Semantic Tags

Semantic tags are financial data objects aiming to simplify and enhance the use of the financial statement (FS) item, general ledger account, and functional area in analytical applications. Semantic tags are short text IDs that you define centrally for an organization, meaning they can be reused across many analytical applications. They can be used flexibly in report columns and rows, and for calculating key performance indicators (KPIs).

SAP delivers standard semantic tags that are used in analytical apps. These tags are assigned to the general ledger accounts for the delivered chart of accounts and financial statement versions (FSVs). Many analytical apps use these standard semantic tags so it is important not to change them. Instead, it is recommended to define new organization-specific semantic tags as needed and use them in the organization-specific custom analytical applications and custom queries.

You can define financial reporting items, such as revenue, COGS, labor, sales deductions, recognized margin, as semantic tags. You can then use them directly in reports, instead of defining them each time a new query is built. When you must adjust the definition of a semantic tag, for example, if you introduce a new functional area, you update the semantic tags centrally. This way, all relevant queries and apps using the same semantic tags are automatically updated.

To see an introduction to SAP Analytics Cloud, watch this video.

The main benefits of SAP Analytics Cloud include:

• Ease of viewing content.
• Connectivity to trusted data.
• Access to various visualization tools.
• Augmented analytic capabilities.
• Financial planning features.
• In a single cloud system, you can analyze, ask, predict, plan, and report.

The technical basis for analytics in SAP systems is CDS views and semantic tags. Core Data Service (CDS) views are virtual data models of SAP HANA which allows direct access to the underlying tables of the HANA database. Semantic tags are short text identifiers that you use to represent key figures. They are assigned to calculate key performance indicators (KPIs) for analytical reports.