Status

OwnerTHANGARAJAN-ext, Ganesan 
StakeholdersThe 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 Pricing Condition Records in the SAP S/4HANA target system, as part of a Greenfield implementation.

In SAP ECC, sales pricing condition records exist as part of the pricing procedure configuration and are stored in condition tables such as KONV, A*, and related master and transactional tables. These records are used to define pricing elements such as base price, discounts, freight, and surcharges across sales documents.
 
In SAP S/4HANA, the structure and usage of pricing condition records remain largely consistent; however, data models may be simplified, and dependencies on business partners (replacing customer/vendor master records) become critical in ensuring consistency across sales and purchasing functions.
 
This conversion aims to migrate active and relevant sales 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 Pricing 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:

  • Base Price (e.g., PR00)
  • Discounts (e.g., K007, K004)
  • Freight and surcharges

The conversion will ensure all condition records are aligned to the new Pricing Key combinations defined for example, based on Business Partner, Material Masters and relevant Organizational Units (Sales Org, Distribution Channel, Division) as designed for the target S/4HANA landscape.

The data from legacy system includes:

  1. List price at various key combinations including scale-based pricing as applicable
  2. Discounts and surcharges at various key combinations
  3. Freight condition records at various key combinations

The data from legacy system excludes:

  1. Tax condition records that will be covered in CONV-1034 Tax condition records spec.
  2. Rebate condition records that will be managed via Condition contracts set up


List of source systems and approximate number of records
SourceScope

Source Approx No. of Records

Target SystemTarget Approx

No. of Records

WP2

Pricing Condition Records

 

S/4HANA System

 

PF2

Pricing Condition Records

 

S/4HANA System

 











Additional Information

Multi-language Requirement

International Version

Description

C

Simplified Chinese

R

Cyrillic

K

Kanji (Japanese)

A

Arabic

3

Korean

T

Thai

H

Hangul

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

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.

TableFieldData ElementField DescriptionData TypeLengthRequirement

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

CHAR

4

Mandatory

KONP

KBETR

KBETR

Rate

CURR

11

Mandatory

KONP

KPEIN

KPEIN

Pricing Unit

DEC

5

Mandatory if UoM

KONP

KMEIN

KMEIN

Unit of Measure

UNIT

3

Optional

KONP

WAERS

WAERS

Currency

CUKY

5

Mandatory

KONP

KZBZG

KZBZG

Calculation Type

CHAR

1

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.

IDCriticalityError Message/Report DescriptionRuleOutputSource System


























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 DescriptionTeam 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 ScreenParameter NameSelection TypeRequirementValue 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 NameField DescriptionRule












Extraction Dependencies

List the steps that need to occur before extraction can commence

Item #Step DescriptionTeam 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 DescriptionTeam Responsible













Transformation Rules

Rule #Source systemSource TableSource FieldSource DescriptionTarget SystemTarget TableTarget FieldTarget DescriptionTransformation Logic









































Transformation Mapping

Use the exact name and reference this section in the “Transformation rules” above
Mapping Table NameMapping Table Description








Transformation Dependencies

List the steps that need to occur before transformation can commence
Item #Step DescriptionTeam Responsible













Pre-Load Validation

Project Team

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

Completeness

TaskAction
titlespecific details of what and how the task needs to be performed e.g. which reports are being used etc.





Accuracy

TaskAction
titlespecific 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

TaskAction
titlespecific details of what and how the task needs to be performed e.g. which reports are being used etc.





Accuracy

TaskAction
titlespecific 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 DescriptionTeam 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 TypeError DescriptionAction Taken










Post-Load Validation

Project Team

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

Completeness

TaskAction
titlespecific details of what and how the task needs to be performed e.g. which reports are being used etc.





Accuracy

TaskAction
titlespecific 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

TaskAction
titlespecific details of what and how the task needs to be performed e.g. which reports are being used etc.





Accuracy

TaskAction
titlespecific 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