Status
Owner	RAYUDU-ext, Narasimha Kumar
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 conversion approach to create Batch Characteristics in S/4 HANA.

In both legacy systems, batch characteristics (class type 023) are used to hold key information related to Logistics & Quality information. Currently, there are more than 1,000 characteristics where these are duplicated with identical descriptions and assigned to different classes. To enable effective global utilization and reporting purposes, these characteristics need to be standardized. SyWay program to harmonize and standardize these characteristics across the organization.

Conversion Scope

The scope of this document covers the approach for converting active Batch Characteristics from Legacy Source Systems into S/4HANA following the Batch Characteristics Master Data Design Standard.

SAP Batch Characteristics are specific data fields used within the SAP system to describe and manage the properties of a batch of materials. They are part of the SAP Classification System and are typically associated with class type 023 (Batch Class).

Material Batches capture detailed information about each batch, such as production date, quality parameters, supplier details, or any other relevant property and enable traceability; allow track and trace batches throughout the supply chain with structured data for analysis and reporting.

The data from legacy system includes:

1. Characteristics assigned to Classes with below Class Type
• 023 – Batch Class (PF2, WP2)
2. Batch Characteristics assigned to Active Classes of 023.
3. Valid from [Current Date]
4. Status = 1 (Released)

The data from legacy system excludes:

1. Characteristics for Deletion (Deletion Indicator = X)

List of source systems and approximate number of records

Source	Scope	Source Approx No. of Records	Target System	Target Approx No. of Records
PF2	Batch Characteristics will be collected via DCT. An extract of the relevant Characteristics will be provided to assist business in standardizing the Characteristics from PF2 and WP2. If Any additional Characteristics that need to be created to support the new design may be added in the DCT.	4285
WP2	Batch Characteristics will be collected via DCT. An extract of the relevant Characteristics will be provided to assist business in standardizing the Characteristics from PF2 and WP2. If Any additional Characteristics that need to be created to support the new design may be added in the DCT.	1179

Additional Information

Multi-language Requirement

Characteristics descriptions are maintained in different languages.

Document Management

NA

Legal Requirement

NA

Special Requirements

NA

Target Design

The technical design of the target for this conversion approach.

Table	Field	Data Element	Field Description	Data Type	Length	Requirement
CABN	ATNAM	ATNAM	Characteristic	CHAR	30	Mandatory
CABN	AENNR	AENNR	Change Number	CHAR	12	Optional
CABN	DATUV	DATUV	Valid From	DATS	8	Mandatory
CABNT	ATBEZ	TEXT30	Description	CHAR	30	Mandatory
CABN	ATKLA	ATKLA	Characteristic Group	CHAR	10	Conditional
CABN	ATMST	ATMST	Status	CHAR	1	Mandatory
CABN	ATAUTH	ATAUTH	Authorization Group	CHAR	3	Optional
CABN	ATFOR	ATFOR	Data Type	CHAR	4	Mandatory
CABN	ANZST	ANZST	Number of Characters	INT2	5	Mandatory
CABN	ATKLE	ATKLE	Case Sensitive	CHAR	1	Optional
CABN	ATSCH	ATSCH	Template	CHAR	30	Optional
CABN	ANZDZ	ANZDZ	Decimal places	INT2	5	Mandatory
CABN	CURRENCY	WAERS_CURC	Currency	CUKY	1	Mandatory (For Currency related Characteristics) / Optional
CABN	ATEIN	ATEIN	Value Assignment	CHAR	1	Mandatory
CABN	MSEHI	MSEHI	Unit of Measure	UNIT	3	Mandatory
CABN	ATDIM	ATDIM	Exponent display	INT2	5	Mandatory
CABN	ATINT	ATINT	Interval values allowed	CHAR	1	Optional
CABN	ATVOR	ATVOR	Negative values allowed	CHAR	1	Optional
CABN	ATGLA	ATGLA	Restrictable	CHAR	1	Optional
CABN	ATERF	ATERF	Entry Required	CHAR	1	Optional
CABNT	SPRAS	SPRAS	Language	LANG	1	Mandatory
CABN	ATSON	ATSON	Additional Values	CHAR	1	Optional
CABN	ATTAB	ATTAB	Reference Table	CHAR	30	Optional
CABN	ATFEL	ATFEL	Reference Field	CHAR	30	Optional
CABN	DOKNR	DOKNR	Document	CHAR	25	Optional
CABN	DOKAR	DOKAR	Document Type	CHAR	3	Optional
CABN	DOKTL	DOKTL	Document Part	CHAR	2	Optional
CABN	DOKVR	DOKVR	Document Version	CHAR	3	Optional
CABN	ATINP	ATINP	Not ready for input	CHAR	1	Optional
CABN	ATVIE	ATVIE	No display	CHAR	1	Optional
CABN	ATWRD	ATWRD	Display Allowed Values	CHAR	1	Optional
CABN	ATFOD	ATFOD	Unformatted Entry	CHAR	1	Optional
CABN	ATVSC	ATVSC	Propose Template	CHAR	1	Optional

Data Cleansing

No data cleansing is required within the source systems. Standardization and cleansing activities will be carried out outside of the Syniti tool, and the finalized characteristics will be populated in the DCT.

ID	Criticality	Error Message/Report Description	Rule	Output	Source System
	NA	NA	NA	NA	NA

Conversion Process

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

Data Privacy and Sensitivity

NA

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
1	Legacy System Extraction (PF2 & WP2) based on the Relevancy Rules	SyWay Data Team

Selection Screen

NA

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

Data Collection Template (DCT)

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

Batch Characteristics DCT Rules

Field Name	Field Description	Rule
ATNAM	Characteristic	TBD Need to follow the naming Convention
AENNR	Change Number
DATUV	Valid From
ATBEZ	Description
ATKLA	Characteristic Group
ATMST	Status
ATAUTH	Authorisation Group
ATFOR	Data Type
ANZST	Number of Characters
ATKLE	Case Sensitive
ATSCH	Template
ANZDZ	Decimal places
CURRENCY	Currency
ATEIN	Value Assignment
MSEHI	Unit of Measure
ATDIM	Exponent display
ATINT	Interval values allowed
ATVOR	Negative values allowed
ATGLA	Restrictable
ATERF	Entry Required
SPRAS	Language
ATSON	Additional Values
ATTAB	Reference Table
ATFEL	Reference Field
DOKNR	Document
DOKAR	Document Type
DOKTL	Document Part
DOKVR	Document Version
ATINP	Not ready for input
ATVIE	No display
ATWRD	Display Allowed Values
ATFOD	Unformatted Entry
ATVSC	Propose Template

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
Verify DCT & Load File Count	SCM Data Team to verify that the total number of relevant records from the  DCT is equal to the total number of records in the Preload and Load Sheets.
Verify Consent	Verify the appropriate consents for the records have been obtained by the business/Data Owners and properly recorded

Accuracy

Task	Action
Conversion Accuracy	SCM Data team to verify that all the data in the load table/file is accurate as per signed-off DCT contents and transformation rules with below checks:  Mandatory Fields Field and Value Mapping Correctness Null Checks
Review Error Reports	Review and correct the errors.  Achieve a zero-error record count as much as possible. Raise defects for data remediated and requiring a correction in the source data.

Business

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

Completeness

Task	Action
Verify Record Count	Business Data Owner/s to verify that the total number of relevant records from the the DCT is equal to the total number of records in the Preload and Load Sheets.
Verify Consent	Verify that the appropriate consents for the records have been obtained by the business and properly recorded

Accuracy

Task	Action
Conversion Accuracy	Business Data Owner/s to verify that all the data in the load table/file is accurate as per endorsed transformation/mapping rules (and signed-off DCT data).

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
1	Ensure Pre-load sign-offs are obtained.	SCM Data team
2	Go to the load tool and select the correct load Program.	SCM Data team
3	Proceed with Data load.	SCM Data team
4	Validate few records loaded by accessing standard transactions.	SCM Data team
5	Generate the post load reports in the tool.	SCM Data team
6	Log errors as defects, if any and address resolutions. Close defects.	SCM Data team
7	Resolve defects by re-upload and re-generate post load reports if necessary.	SCM Data team
8	Business to validate the post load files as part of post-load validation, raise data defects or provide the post-load sign-off.	Business
9	Repeat steps 5 to 7 if necessary.	SCM Data team

Load Phase and Dependencies

Pre Cutover

Configuration

Item #	Configuration Item
1	V_CMG - Characteristics Group
2	T002 - Language Keys

Conversion Objects

Object #	Preceding Object Conversion Approach
NA	NA

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
Configuration	<configuration> is not valid/missing	If it is a missing configuration item, then engage Functional team to expedite and fix the error in the system.
Invalid Data	<parameter> is not valid.	The parameter entry needs to be reviewed If it is an invalid data, business needs to review and correct the source of the data either in PE1 or if it’s mapped in DCT.
Technical Setup	Interface / Connection issue within target system’s landscape	N/A – the data will be loaded directly to S/4HANA environment

Post-Load Validation

Project Team

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

Completeness

Task	Action
Verify the count	Verify that the record count in the post-load file is the same as the record count based on the relevancy (including any deduplication) results

Accuracy

Task	Action
Data Accuracy	SCM Data team to verify that all the data in the post load table/file is accurate as per signed-off transformation rules and DCT contents
Error Reports	Verify that all necessary error reports have been validated, and that errors have been addressed.
Data Consistency	Verify that the data loaded is correctly reflected in SAP S4 HANA

Business

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

Completeness

Task	Action
Verify Count	Verify that the record count in the post load file is the same as the record count based on the relevancy (including deduplication) results
Validate Loaded Data	Validate, as per the load files signed-off, that all records were created

Accuracy

Task	Action
Data Accuracy	Verify that all the data in the S/4HANA table is accurate as per signed-off DCT contents and transformation rules For mock loads, the post load data validation will be as per scrambled data, thus data accuracy is not to be checked against DCT which holds the actual data. Post-load data to be validated against the pre-load report (scrambled data).
Verify Relationships	Verify that each Vendor have been assigned to the appropriate Business Partner correctly

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