Master Data Governance for Financials at a Glance:
- Master Data Governance for Financials (MDG-F) is an application to centrally govern the maintenance of financial master data.
- Master Data Governance for Financials provides central steering and control mechanisms independently of local or centralized execution.
- In Master Data Governance for Financials, master data records can be created, completed, or changed in the staging area, using a distributed step-by-step process before making the record available to connected business applications.
Central governance for financial data means - in analogy to the other master data domains covered by master data governance - that the data is centrally created and maintained and only once it has been fully checked and completed along the master data governance workflow, is it distributed to the subscribing business applications for operative use.
Master Data Governance for Financials Addresses Main Action Areas
SAP Master Data Governance centrally manages financial data:
- Ensures consistent financial master data across the entire organization
- Provides collaborative and traceable execution of changes
- Supports excellent financial processes
- Ensures high-quality master data and single version of the truth
Master data governance provides adjustable data models, the appropriate architecture, the processing environment, and the usability that enable end-to-end central governance from search to replication.
The preceding figure illustrates the process framework. It explains the objects, Work Center, Search, Workflow/Business Rules and Roles, and how they are assigned.
Editions
Editions control the validity of a change. In the edition, planned change requests for the creation of new data or for changes to existing data are collected and released collectively at a certain date. Time-dependent objects (profit or cost center) automatically inherit the valid-from date from the edition's valid-from date.
Intuitive - Integrated Maintenance
SAP Master Data Governance for Financials offers an intuitive interface to efficiently maintain financial master data in an integrated fashion. Instead of navigating through multiple tabs and switching between organizational structures, the key users work with a browser-based interface. For less frequent users, SAP Fiori-based applications are offered.
Work with Changeable Keys
When a user requests a new financial master data item, they frequently do not yet know the number to be used in the consuming applications. To provide flexibility to the requestor and meet corporate numbering standards, the single-object maintenance in SAP Master Data Governance for Financials offers the feature to use a generated key first then change it to the desired final number in a later step of the creation process.
Hierarchy Assignment in Single-Object Processing
The figure shows master data and hierarchy assignment in the same Financial Objects user interface; it illustrates the following fields:
Cost Center
Profit Center
Cost Element
Cost Center Group
Profit Center Group
Cost Element Group
And also:
G/L Account
Financial Reporting Structure Item
In addition to ERP:
Overview of all assignments in all hierarchies
Displaying and maintaining not only standard group, but also alternative hierarchies on master data screen
Integrated Change Request
A change request can be generated from various processing applications in master data governance: these include hierarchy processing, file upload, mass change.
Process Efficiency Features
The figure illustrates the settings for process efficiency features.
Further Details:
- Copy multiple company codes
Create multiple company code-specific G/L accounts through the copy function.
- One-step creation of cost element
Automatically create the primary cost element connected to a new account in the same maintenance step. This is standard for primary cost elements and optional with SAP S/4HANA 1809 for secondary cost elements.
Central Governance for Internal Order Master Data
The figure shows a screenshot of an internal order, displaying master data. Central governance for internal order master data is available as of SAP Master Data Governance 9.2 / SAP Master Data Governance on SAP S/4HANA 1809. It provides:
- Innovations
- Central maintenance and governance of internal order master data
- Replicating internal orders using IDOC from the master data governance system to SAP S/4HANA or SAP ERP
- Initial load of internal orders into master data governance, for example, from SAP ERP or SAP S/4HANA
- Business Value
- Centralized governance, compliance, and transparency of master data during creation and change through integrated staging, approval, and central audit trail
- Consistent definition, authorization, and replication of internal order master data. This keeps data consistent across systems.
- Elimination of error-prone manual maintenance processes for internal order master data in multiple systems
Merge Cost Element into G/L Account
The figure illustrates the merge of a cost element into a G/L account.
The merge of a cost element into a G/L account has come with SAP Master Data Governance on SAP S/4HANA 1809.
Further Details:
- Innovations
SAP Master Data Governance on SAP S/4HANA 1809 covers:
- Central maintenance of controlling data (cost element) integrated into the G/L Account user interface
- Replication of cost element data to SAP S/4HANA can be done using the G/L Account IDOC and SOA service
- Business value
- Simplified maintenance of financial master data
- Harmonized behavior with SAP S/4HANA
- Simplified replication channel lowers TCO
The figure illustrates some usability features in single-object maintenance UI.
Further details:
- Side panel: Business Context Viewer (BCV)
Context information can be displayed in the side panel (BCV) to provide further related information about the current data record, for example, the change history.
- Highlight changes
Fields that were changed in the previous step are highlighted in color.
Usability Features in Hierarchy Processing
The following figure shows some of the usability features in Hierarchy Processing.
Usability Features in Hierarchy Processing include:
Easy actions supported for multiple objects:
- Drag and drop
- Move up and down
- Rank higher and rank lower
- Copy and paste or paste at lower level
- Cut and paste or paste at lower level
Easy to use:
Select multiple subnodes of one node and carry out any of the actions above.
Usability features in Hierarchy Processing also include direct access/insight to Hierarchy Change by clicking icons:
Pending Change Request
- Change Document
Display of Current Hierarchy Assignment
As a data specialist, you want to see the hierarchy assignments for cost centers and profit centers which are valid today.
The figure shows the UIBB list that provides a dropdown to select the edition for which the hierarchy assignments are displayed. By default, assignments for the edition valid today are displayed.
Hierarchy Interlocking
The settings can be found in the implementation guide: Master Data Governance, Central Governance→General Settings→Process Modeling→Hierarchies→Define Scope for Changes
Explanations about "Interlocked":
- Interlocked: You must use the pending change request to add, delete, move, or change the attributes of this node.
- Not Interlocked: You can add, delete, move, or change the attributes of this node in a separate change request.
Flexible Edition Management
The Business Value of the Flexible Edition Management is as follows:
- Easy and flexible scheduling of changes
- Using and combining as many editions as you need
- Rescheduling changes across editions
- Intuitive access to business objects across validity time frames
- Access to master data through time frames
- Transparency for previous and upcoming changes
- Full transparency across all time frames
- Granular control over replication timing
- Possibility for the end user to decide when to replicate changes
Flexible Scheduling
Edition management in central governance of financial data is about scheduling the validity of changes. You can use and combine as many editions as you need. In the example in the figure, you can see that Account B has been added within E1 with unlimited validity as there is no change in E2. It is also possible to reschedule changes across editions. In the example, you can see that a pending change of Account D in E1 can be moved to E2.
This detailed end-to-end example focuses on two accounts. Each of the accounts was changed at different points in time. Each change was associated with an edition. As shown at the top of the figure, the time frames are for the account we are focusing on - account 20000, which for simplicity, we refer to as account A.
We give account A a variant name for each instance. So, when it is created in edition E1, we call it account A1. When it is changed in edition E2, we call it account A2, and so on. You may notice that account A2 has the same time frame as account A6. This is because the accountant needed to change data for the relevant time frame after the release of edition E2. So the master data steward had to create a new edition, E6, in which the accountant could make the change. We call the instance of the account changed in Edition E6, A6.
The following events occurred before today:
- In edition E1, accounts 20000 and 90000 are created (we call them A1 and B1). When the accounts are created, they are both valid from Q2.2023 until Q4.9999.
- In edition E2, account 20000 is changed and approved (now called A2). This change creates two new time frames for the account. A1 is valid only during Q2.2023. A2, at the time of the change, is valid from Q3.2023 until Q4.9999. Account 90000 (B1) remains unchanged.
Color-coding of time frames is used to enable the reader to quickly relate between the screenshot and the timescale.
Type of Edition: Currently it is not recommended to create new Edition Types for Master Data Governance for Financials. Use the pre-delivered one (description can be changed).
The example in the figure of the flexible scheduling shows how a user accesses account 20000 in order to change it starting in Q3 or Q4 2023. The user accesses it through time frame T2, and by assigning the editions E6 or E3, the change is requested either by Q3 2023 (E6) or Q4 2023 (E3). If the change was supposed to become effective in Q1 2024, an edition for this would have to be created (in a realistic example, there would already be one).
More explanations about functions:
- New
- Creates a new account (not a new time frame)
- Copy
Enables an account to be used as a template for a new account
Additionally, a new search parameter (Valid On) enables a convenient way to display the values of one or more accounts at a specific point in time (or within a defined time frame). Refer to the previous figures.
Transparency About Changes in All Time Frames
The example in the figure shows the transparency of the changes in a scenario with an open change request in time frame T3. The instance of the account in T1 shows the Next Change in T2 (a change that has already been approved and where the data is "active"), and the Pending Change in T3 (there can always only be one pending change across all editions).
For the account instance in T2, the Next Change is the change in T3, and the Pending Change refers to the change request holding the change to "A4*". This change might be unrelated to the earlier change in T2, or it might be required because of this change.
In this example, a change planned for T3 is rescheduled to T4. Rescheduling is possible for each edition within the time frame between the "Last Change" (the last approved change in an earlier edition) and the "Next Change" (the next approved change in a later edition).
Rescheduling to editions beyond this is not possible as this would "skip" changes that might be relevant. In these cases, the changes have to be entered manually.
Characteristics of Controlled Data Replication are:
Replication Timing
- Edition-Based: Manually started after the edition's release
- Change Request-Based: Automatically after approval of a change request or selected in each change request
Object-Based Replication
Manual replication (for example, from Search): independent from Replication Timing defined in the edition
Time-Dependent and Non-Time-Dependent client systems and objects supported
Replication is placed on hold if needed and started when possible (scheduled report).
Refer to the report USMD_EDITION_REPLICATE for scheduling replications. Refer to the Master Data Governance for Financials Configuration Guide for details.
Standard Objects in Data Model
Data objects can be extended or modified flexibly to specific needs, according to the back-end and target systems.
For the SAP S/4HANA 1809 and SAP Master Data Governance 9.2 releases, the new entity type, Internal Order, has been added.
Replication
Master Data Governance for Financials replicates the data according to the needs of the connected business systems. This is independent of the deployment option, if master data governance is used on top of one of the operational SAP ERP systems, or as a standalone Master Data Governance hub.
Integration Technology (Elective)
Master Data Governance for Financial Data supports various replication technologies. These include, for example, SOA and ALE / IDoc.
Request Cost Center or Profit Center with SAP Fiori App
You can also use SAP Fiori apps to request a new cost center or a new profit center.
These apps can be flexibly used on a variety of devices, including tablets and smartphones.
Approve Cost Center, Profit Center, or G/L Account
The examples show SAP Fiori screens for the approval of Cost Center, Profit Center, or G/L Account. Only the relevant fields for the approval (newly created or changed) are displayed.
Especially in the case of mergers and acquisitions, when you're adding new local systems, you can use master data governance to maintain mappings in your local and corporate systems. SAP Master Data Governance consolidation identifies common content in different repositories and writes related mapping information into the mapping tables.
Benefits of SAP Master Data Governance for Financials
The benefits of applying central governance for financial data range from increased process efficiency (for example, faster financial close, increased trust in reporting data)...
... and compliance support (that is, for example, transparency and traceability for full audit trail that helps to avoid non-compliance penalties) ...
... to increased data quality and consistency, for example, to minimize the need for restatements and enable improved planning and analysis.
