Purpose

The purpose of this document is to define the conversion approach to create the WBS - CAPEX, OPEX, Statistical

in S/4 HANA.

In SAP, a WBS element (Work Breakdown Structure element) is a key component in project structure. WBS elements are organized hierarchically and facilitates planning, execution, and control.

Conversion Scope

The scope of this document covers the approach for converting active WBS - CAPEX, OPEX, Statistical from Legacy Source Systems into S/4HANA following the WBS - CAPEX, OPEX, Statistical Master Data Design Standard. tems into S/4HANA: 

The guiding principle is that we should only migrate data necessary to support ongoing business operations. This may also involve cleansing activities within the source systems to align with the migration criteria.

In terms of Historical Data, it will not be migrated except where specific records are required to support application functionality, meet legislative obligations or ensure regulatory compliance.

WBS from the legacy system to be used for the basis of the system include projects from PF2 and WP2.

The data from legacy system includes:

1. WBS elements not in closed status
2. Closed CAPEX WBS elements which has current year postings - require postings according to CNV-9031.
3. The parent WBS elements included in the above.
4. New projects to be created to replace Internal orders with current year postings – require postings according to CNV-9032

The data from legacy system excludes:

1. WBS elements for company codes out of scope

Logic:

1. WBS elements not in closed status
2. Table PRPS

Key in field "Company Code" in scope.

Result: Object numbers of WBS that are in company codes in scope.

1. Table JEST:

Field "Object number" = Key in the object numbers of WBS (from Step A)

Field "Status Inactive" = blank

Then filter object number that do not have status I0046 (Closed) or IFO07 (Closed) 

These WBS need to be migrated.

1. Closed CAPEX WBS element that have cost in current year must also be migrated.

Logic:

1. Table PRPS

Key in field "Company Code" in scope.

Result: Object numbers of WBS that are in company codes in scope.

1. Table JEST:

Field "Object number" = Key in the object numbers of WBS (from Step A)

Field "Status Inactive" = blank

Then filter object number that has status I0046 (Closed) or IFO07 (Closed).

Result: Object number with status I0046 (Closed) or IFO07 (Closed).

1. Table RPSCO:

Field "Object number" = Key in the object numbers of WBS (from Step B) 

Field "Fiscal Year" = Current year

Field "Value Type" = 4

Result = Object numbers that have cost in current year.

These WBS needs to be migrated.

1. Parent WBS elements

For each WBS element with closed status include all superior level WBS elements.  If status of element is not closed superior WBS elements will also be not closed.

1. Table PRHI:

Field “WBS elements” (All PS_POSNR from PRPS)

IF “UP” is Null no superior objects

Result = Field “UP” additional WBS to be migrated

Repeat until “UP” is Null.

Predecessor Objects

CNV-1024 Project Definition

Additional Information

Multi-language Requirement

Document Management

Legal Requirement

Special Requirements

Target Design

The technical design of the target for this conversion approach.

Data Cleansing

Data cleansing tasks are set out in CNV-1024 which deals with projects and also by definition includes the closing of WBS elements in those projects.

Conversion Process

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

Data Privacy and Sensitivity

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

Selection Screen

Data Collection Template (DCT)

DCT Rules

Extraction Dependencies

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 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
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

Configuration

Conversion Objects

Error Handling

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.
• is in scope based on data design and any exception requested by business.

See also

Change log