Status
Owner	OMER-ext, Mohammed
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 TM-Locations in S/4 HANA TM (Transportation management).

In SAP Transportation Management (TM), a location represents a physical or logical place where goods or resources are handled or stored. These locations are fundamental to transportation planning, serving as source, destination, or intermediate stops within the transportation network. 

Locations are the most granular objects in the transportation network. They are used for further definitions, such as transportation lanes, and so on. They are classified using a location type.

<Assumption> The data for TM Locations in S/4 would need to be constructed in data collection template (DCT).

Conversion Scope

The scope of this document covers the approach for creating TM Locations in S/4HANA following the TM-Locations Master Data Design Standard. This includes:

• Capturing and using the TM Locations data in data collection template (DCT).
• Applying transformation logic via Syniti to conform with the S/4 HANA data model.
• Loading the transformed data into SAP S/4 HANA while ensuring data integrity.

The data from legacy system includes:

1. N/A (Manual data collection)

The data from legacy system excludes:

1. N/A (Manual data collection)

List of source systems and approximate number of records

Source	Scope	Source Approx No. of Records	Target System	Target Approx No. of Records
DCT	Creation of TM Locations	TBD	S/4 HANA (TM)	TBD

Additional Information

Multi-language Requirement

TBD

Document Management

Not Applicable

Legal Requirement

Not Applicable

Special Requirements

Not Applicable

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

The complete information of the key fields that hold the TM Location information follows the Master Data Standard document.

The technical design of the target for this conversion approach.

Table	Field	Data Element	Field Description	Data Type	Length	Requirement
/SAPAPO/LOC	LOCNO	MATNR	Location Location no would be input by user	CHAR	20	Mandatory
/SAPAPO/LOC	LOCTYPE		Location Type	CHAR	4	Mandatory
/SAPAPO/LOCT	SPRAS		Language Key 8 languages in scope: English, French, Italian and Mandarin and Brazilian Portuguese, German, Spanish and Thai, as per KDD055	CHAR	1	Mandatory
/SAPAPO/LOCT	DESCR40		Location Description	CHAR	40	Mandatory
/SAPAPO/LOC	TZONE		Timezone	CHAR	6	Optional
/SAPAPO/LOC	UNLOCODE		UN/LOCODE	CHAR	5	Optional
/SAPAPO/LOC	IATACODE		IATA Code	CHAR	3	Optional
/SAPAPO/LOC	PARTNER_GUID		BusinessPartner	CHAR	16	Optional
/SAPAPO/LOC	ADV_SHP_RECV_RLV		Advanced Shipping and Receiving Relevance Values: 1 or empty Syensqo Locations with EWM we put 1, rest "empty"	CHAR	1	Optional
ADRC	TITLE		Title	CHAR	4	Optional
ADRC	NAME1		Name 1	CHAR	40	Optional
ADRC	HOUSE_NUM1		House Number	CHAR	10	Optional
ADRC	STREET		STREET	CHAR	60	Optional
ADRC	CITY1		City	CHAR	40	Optional
ADRC	POST_CODE1		City postal code	CHAR	10	Optional
ADRC	COUNTRY		COUNTRY	CHAR	2	Optional
ADRC	REGION		REGION	CHAR	3	Optional
ADRC	SORT1		Search Term 1	CHAR	20	Optional
ADRC	LANGU		Language	CHAR	1	Optional
ADRC	TEL_NUMBER		Telephone	CHAR	30	Optional
ADRC	SMTP_ADDR		Email	CHAR	241	Optional

Data Cleansing

TM Location data will be populated directly in the Data Collection Template (DCT).

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

Conversion Process

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

Please note that the data may have to be loaded in multiple target systems (US instance, China instance and RoW).

Data Privacy and Sensitivity

Summarize Data Privacy and Sensitivity Requirements, if any

Extraction

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.

Extraction Run Sheet

Req #	Requirement Description	Team Responsible
1	Data is populated in the DCT or uploaded from downloaded Excel template	Data owner (Business)
2	If the data is uploaded to DCT in bulk via excel template, any upload errors need to be reviewed and corrected	Data owner (Business), Syniti/ Data Team
3	The data which has passed validation checks in DCT will be used for transformation/further processing	Syniti

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