Purpose

The purpose of this document is to define the functional requirements, methodology, and approach for the initial data loading and subsequent synchronization of Business Rule Framework Plus (BRF+) Output Management data in SAP S/4HANA.

This process will establish and maintain output determination records (e.g., email recipients, output channels, and conditions related to BP) in BRF+ based on the configuration and master data currently maintained in Classic Output Management (NAST framework) within the legacies from SAP ECC.

Conversion Scope

The conversion scope covers the extraction, transformation, and loading of output determination data from Classic Output Management (NAST-based framework) into BRF+ Output Parameter Determination (OPD) in S/4HANA, ensuring both initial migration and interim synchronization until full adoption of BRF+ is achieved.

The scope includes:

• Extraction of customer-related output condition records (e.g., for Sales Orders,  Quotations, Contracts, Scheduling Agreements, Invoice and Credit and Debit memos) from Classic Output Management, including associated communication details such as email addresses, language, and output channels;
• Cleansing and Harmonization of extracted data to remove obsolete, incomplete, or duplicated entries, ensuring only valid and active output records are migrated;
• Mapping of Classic condition record keys (application, condition type, key combination) to BRF+ OPD parameters (e.g., Customer, Sales Organization, Document Type, Output Type);
• Transformation of medium and dispatch settings from Classic (e.g., NAST medium codes) to BRF+ equivalent channels (e.g., Email, Print, EDI), ensuring compatibility with S/4HANA Output Management settings;
• Initial Load of the transformed dataset into BRF+ Output Parameter Determination using the OPD framework and/or BRF+ application data load methods;
• Ongoing Synchronization process to detect and apply changes made in Classic Output Management to BRF+, allowing a parallel run period until Classic Output Management is fully decommissioned;
• Validation to ensure that migrated BRF+ records produce identical output results as their Classic counterparts for equivalent sales scenarios.

Out of Scope:

• Migration of output determination for applications outside of sales (e.g., MM Purchasing outputs);
• Modifications to customer master data beyond the email and communication fields required for BRF+;
• Changes to output form templates (Smartforms/Adobe Forms) beyond what is required for enabling BRF+.

The data from legacy system includes:

1. Active output condition records for Sales (Application V1 and V3) linked to customers (Partner Function SP, BP,PY, CONTACTS) with maintained communication details (email address, fax, etc.)
   1. Output types relevant for Sales Orders, Quotations, Contracts, Invoices and memos and Scheduling Agreements that are in active use in the business process
2. Records with valid medium settings (e.g., Email, Print, EDI) compatible with S/4HANA BRF+ output channels
3. Language assignments that are valid in the target system

The data from legacy system excludes:

1. Obsolete, expired, or logically deleted output condition records
2. Condition records for customers that are blocked for sales or flagged for deletion in the customer master
3. Output types not used in the current or target S/4HANA sales processes
4. Records with incomplete or invalid communication data (e.g., missing email for email output medium)
5. Condition records belonging to applications other than sales (e.g., MM, FI outputs)

PROFILE

List of source systems and approximate number of records for tables for

• Usage = B

• Application: = V1 V3

• transmission mediums 5,6,7,8:

Additional Information

Multi-language Requirement

Summarize Multi-language Requirement/s, if any

Document Management

Summarize Document Management requirement, if any

Legal Requirement

Summarize Legal Requirement/s, if any

Special Requirements

Specify any special requirements or considerations that may impact the data conversion process based on specific locations, regulatory compliance or system limitations. Clearly outline any regional or localization requirements such as country-specific data formats, legal reporting obligations or industry standards that must be adhered to (e.g., localization rules for countries like China).

If the data conversion involves third-party systems or external data sources, such as Icertis, describe any additional requirements related to data mapping, transformation logic, validation rules or security measures that must be followed.

Target Design

In S/4HANA Output Management (via BRF+), decision tables replace the condition technique. Each BRF+ decision table acts like a flexible rule set:

Input parameters → Decision Logic → Output Parameters

They determine:

1. Output Type (e.g., ORDER_CONFIRMATION, BILLING_OUTPUT)
2. Output Channel (e.g., Email, Print, EDI)
3. Form Template (Adobe Form)
4. Receiver (Partner Function)
5. Language

Following Decision tables have been identified so far:

ECC → BRF+ Field Mapping Table

if the Business partner output requirement are maintained in the business partner, the entries depending on the BP no will disappear

Data Cleansing

All data cleansing should take place in the data source system as defined in this document, unless system limitations prevent it.

If data cleansing is managed outside of the source system (e.g. Syniti Migrate, 3rd Party Vendor, DCT), the necessary documentation must be produced and appended to this deliverable for sign-off.

Conversion Process

The high-level process is represented by the diagram below:

Data Privacy and Sensitivity

All data extracted must be anonymized and handled according to data protection policies.

Extraction

Data will be extracted from ECC using SQL-based queries executed on the source database. The extraction will include relevant tables such as NACH, TNAPR, The extraction methods are as follows:

• Full extraction from relevant tables in ECC (preferred).
• Extraction through the application layer when database access is restricted.
• Manual extraction via reports or DCT if system access is not possible.

Relevancy criteria will be applied to include only active, valid, and in-scope records.

Extraction Run Sheet: To be provided after the first mock cycle.

Source Table to be extracted: NACH Table

The agreed Relevancy criteria is applied to the extracted records to identify the records that are applicable for the Target loads

Extraction Run Sheet

Selection Screen

Data Collection Template (DCT)

<Object> DCT Rules

Extraction Dependencies

List the steps that need to occur before extraction can commence

Transformation

The Target fields are mapped to the applicable Legacy field that will be its source, this is a 3-way activity involving the Business, Functional team and Data team. This identifies the transformation activity required to allow Syniti Migrate to make the data Target ready:

1. Perform value mapping and data transformation rules.
   1. Legacy values are mapped to the to-be values (this could include a default value)
   2. Values are transformed according to the rules defined in Syniti Migrate
2. Prepare target-ready data in the structure and format that is required for loading via prescribed Load Tool. This step also produces the load data ready for business to perform Pre-load Data Validation

Transformation Run Sheet

Transformation Rules

Transformation Mapping

Transformation Dependencies

Pre-Load Validation

Project Team

Completeness

Accuracy

Business

Completeness

Accuracy

Load

The load process includes:

1. Execute the automated data load into target system using load tool or product the load file if the load must be done manually
2. Once the data is loaded to the target system, it will be extracted and prepared for Post Load Data Validation

Load Run Sheet

Load Phase and Dependencies

Identify the phase as to “when” the load for this object will occur. <Pre-Cutover, Cutover, Post Cutover> and list the steps that need to occur before the load can commence

Configuration

List the Configurations required before loading can commence

Conversion Objects

Error Handling

The table below depicts some possible system errors for this data object during data load. All data load error is to be logged as defect and managed within the Defect Management

Post-Load Validation

Project Team

Completeness

Accuracy

Business

Completeness

Accuracy

Key Assumptions

• Master Data Standard is up to date as on the date of documenting this conversion approach and data load.
• Data Object is in scope based on data design and any exception requested by business.

Any additional key assumptions.

See also

Insert links and references to other documents which are relevant when trying to understand this decision and its implications. Other decisions are often impacted, so it's good to list them here with links. Attachments are also possible but dangerous as they are static documents and not updated by their authors.

Change log