Status
Owner	THANGARAJAN-ext, Ganesan
Stakeholders	The business stakeholders involved in making, reviewing, and endorsing this decision. Type @ to mention people by name

Purpose

The purpose of this document is to define the data conversion approach for creating Tax Condition Records in the SAP S/4HANA target system, as part of a Greenfield implementation.

In SAP ECC, sales tax condition records for pricing condition types that exist as part of the pricing procedure configuration and are stored in condition tables such as A*, KONV, and related master and transactional tables. These records are used to define tax elements such as sales tax, VAT, GST,  etc., across sales documents.
 
In SAP S/4HANA, the structure and usage of sales condition records remain largely consistent; however, data models may be simplified, and dependencies on country of sales,  receiver's country, business partners (replacing customer/vendor master records) become critical in ensuring consistency across sales functions.
 
This conversion aims to migrate active and relevant tax pricing condition records from existing ECC systems into S/4HANA by applying required transformation logic using Syniti as the data migration and transformation platform. The converted records will be loaded into the target S/4HANA system using standard SAP mechanisms such as IDOCs, BAPIs, or direct table loads where applicable.

Conversion Scope

The scope of this document includes the end-to-end approach for:

• Extracting existing Tax Condition Records from SAP ECC systems WP2 and PF2.
• Applying transformation and cleansing logic via Syniti to conform with the S/4HANA data model and business partner framework.
• Loading the transformed condition records into SAP S/4HANA while ensuring data integrity, correct assignment to condition types, condition tables, access sequences, and pricing procedures.

This process will support the migration of condition records such as:

• Output Tax (e.g., MWST)
• US Tax per document (e.g., UTXD)
• India GST ( e.g., JOCG )

The data from legacy system includes:

1. Tax condition records relevant for sales transactions, maintained across applicable tax codes and jurisdiction codes

2. Tax rates for output tax determination (e.g., VAT, GST, sales tax)

3. Tax exemption indicators or reduced rates as per customer-specific agreements

4. Effective and expiration dates for tax condition records

The data from legacy system excludes:

1. Pricing condition records (covered in CONV-1034 Pricing Condition Records Specification)

2. Rebate condition records (managed via Condition Contracts setup)

3. Withholding tax configurations (handled separately in the Master Data Migration scope)

List of source systems and approximate number of records

Source	Scope	Source Approx No. of Records	Target System	Target Approx No. of Records
WP2	Tax Condition Records		S/4HANA System
PF2	Tax Condition Records		S/4HANA System

Additional Information

Multi-language Requirement

Not Applicable

Document Management

None identified. The conversion scope is limited to the migration of tax condition data records. No document attachments, images, or supporting files are included.

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

With Functional input, document the technical design of the target fields that are in the scope of this document.

The technical design of the target for this conversion approach.

Table	Field	Data Element	Field Description	Data Type	Length	Requirement
KONH	KNUMH	KNUMH	Condition Record Number	CHAR	10	Mandatory (Key)
KONH	ERDAT	ERDAT	Created On	DATS	8	Optional
KONH	DATAB	DATAB	Valid From	DATS	8	Mandatory
KONH	DATBI	DATBI	Valid To	DATS	8	Mandatory
KONP	KSCHL	KSCHL	Condition Type (Tax Code)	CHAR	4	Mandatory
KONP	KBETR	KBETR	Tax Rate	CURR	11	Mandatory
KONP	KONWA	KONWA	Condition Unit (Currency or Percentage)	CUKY	5	Mandatory

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.

ID	Criticality	Error Message/Report Description	Rule	Output	Source System
1035-001	C1	Remove obsolete condition records	Eliminate pricing condition records where the material, customer, or condition type is blocked or discontinued.	List of obsolete records	WP2/PF2
1035-002	C1	Validate Customer-Material master data	Ensure pricing condition records refer to valid and active Customer and Material master records.	List of invalid Customer Material combinations	WP2/PF2
1035-003	C1	Remove expired condition records	Delete condition records where validity end date has already passed. Exception the condition records required for open sales orders under migration scope	List of expired records	WP2/PF2
1035-004	C1	Validate mandatory fields	Check for missing mandatory fields (e.g. Condition Value, Currency, UoM, Scale data, Validity dates).	List of incomplete records	WP2/PF2
1035-005	C2	Detect duplicate condition records	Identify and flag duplicate pricing condition records for the same condition type, key combination, and validity period. This is possible as the source is from multiple systems WP2 and PF2	List of duplicate records	WP2/PF2
1035-006	C1	Validate currency consistency	Validate that the currency used in pricing conditions matches the currency allowed for the corresponding sales organization or customer master data.	List of inconsistent currency	WP2/PF2
1035-007	C2	Validate scale data	Identify and correct scale records with inconsistent or overlapping ranges (quantity/value).	List of scale issues	WP2/PF2
1035-008	C1	Validate unit of measure consistency	Validate unit of measure used in pricing conditions aligns with material master base UoM and allowed UoMs.	List of inconsistent UoM records	WP2/PF2

Conversion Process

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

Summarize High-Level Process. Include diagrams, where applicable. Include information supporting details of Extract, Transform and Load specific to the Data Object

Data Privacy and Sensitivity

Summarize Data Privacy and Sensitivity Requirements, if any

Extraction

Extract data from a source into Syniti Migrate. There are 2 possibilities:

1. The data exists. Syniti Migrate connects to the source and loads the data into Syniti Migrate. There are 3 methods:
   1. Perform full data extraction from relevant tables in the source system(s).
   2. Perform extraction through the application layer.
   3. Only if Syniti Migrate; cannot connect to the source, data is loaded to the repository from the provided source system extract/report.
2. The data does not exist (or cannot be converted from its current state). The data is manually collected by the business directly in Syniti Migrate. This is to be conducted using DCT (Data Collection Template) in Syniti Migrate

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

Extraction Run Sheet

Req #	Requirement Description	Team Responsible

Selection Screen

If applicable, this section will give the details on any selection screen parameters, including the parameter type, that are required to be entered to ensure consistent data extracts.

Selection Ref Screen	Parameter Name	Selection Type	Requirement	Value to be entered/set

Data Collection Template (DCT)

Target Ready Data Collection Template will be created for Data Object data with exception of some fields which require transformation as mentioned in the transformation rule.

<Object> DCT Rules

Field Name	Field Description	Rule

Extraction Dependencies

List the steps that need to occur before extraction can commence

Item #	Step Description	Team Responsible

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

Item #	Step Description	Team Responsible

Transformation Rules

Rule #	Source system	Source Table	Source Field	Source Description	Target System	Target Table	Target Field	Target Description	Transformation Logic

Transformation Mapping

Use the exact name and reference this section in the “Transformation rules” above

Mapping Table Name	Mapping Table Description

Transformation Dependencies

List the steps that need to occur before transformation can commence

Item #	Step Description	Team Responsible

Pre-Load Validation

Project Team

The following pre-load validations will be performed by the Project Team.

Completeness

Task	Action
title	specific details of what and how the task needs to be performed e.g. which reports are being used etc.

Accuracy

Task	Action
title	specific details of what and how the task needs to be performed e.g. which reports are being used etc.

Business

The following pre-load validations will be performed by the business.

Completeness

Task	Action
title	specific details of what and how the task needs to be performed e.g. which reports are being used etc.

Accuracy

Task	Action
title	specific details of what and how the task needs to be performed e.g. which reports are being used etc.

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

Item #	Step Description	Team Responsible

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

Item #	Configuration Item

Conversion Objects

Object #	Preceding Object Conversion Approach
	list the exact title of the conversion object of only the immediate predecessor – this will then confirm the DDD (Data Dependency Diagram)

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

Error Type	Error Description	Action Taken

Post-Load Validation

Project Team

The following post-load validations will be performed by the Project Team.

Completeness

Task	Action
title	specific details of what and how the task needs to be performed e.g. which reports are being used etc.

Accuracy

Task	Action
title	specific details of what and how the task needs to be performed e.g. which reports are being used etc.

Business

The following post-load validations will be performed by the business.

Completeness

Task	Action
title	specific details of what and how the task needs to be performed e.g. which reports are being used etc.

Accuracy

Task	Action
title	specific details of what and how the task needs to be performed e.g. which reports are being used etc.

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

Workflow history