Purpose

The purpose of this document is to define the conversion approach to create EAM Characteristics in S/4 HANA.

Legacy Plant Maintenance Characteristics is using a diverse range of formats across the different systems. There are instances where the same characteristics are duplicated within and across sources and with informal words. This results in data inconsistency. As per SyWay design, EAM Characteristics will be standardized.

Conversion Scope

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

Characteristics define a single custom field used to capture specific properties, attributes or values of an object. In SAP, Classes and Characteristics together form the “Classification System”.
For Syensqo, Characteristics will be used to record key attributes supporting reliability categorization and various analyses. It will be primarily used for information and reporting of attribute data across a large set of technical objects (e.g. Functional Location Structure). These Characteristics will be created centrally and assigned to relevant Classes.

From the current source systems’ perspective, Class and Characteristic concepts already exist (but in slightly different structure). Characteristic data and their allowed values are independently managed between PF2 and WP2. While these have been identified as source systems, a considerable amount of data construction will be required to support the production of data load sheets in the desired format.

While these systems serve as sources, extensive construction will be necessary to produce properly formatted data load sheets for S/4 HANA. 
The scope of this document covers the approach for converting active Characteristics from Legacy systems (PF2, WP2) and creation of New EAM Characteristics into S/4 HANA following the Characteristics Master Data Design Standard. 

The data from legacy system includes:

1. Characteristics assigned to Classes with below Class Type
   • 001-Material Class
   • 002-Equipment Class
   • 003-Functional Location
   • 017-Document Management
   • 018-Task List Class
   • 037-Measuring Point Class
   • 080-Maintenance Plans Class
2. Characteristics assigned to Active Legacy Measuring Points
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 

Additional Information

Multi-language Requirement

EAM Characteristic description will be made available in English.
Multi language is supported for EAM Characteristics. Login via a different language will have its description displayed in the logon language if the language key is maintained in the Characteristics.

Document Management

Not Applicable

Legal Requirement

Not Applicable

Special Requirements

Not Applicable

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.

1. Characteristics

2. Characteristic Descriptions

Note: Each Characteristic must have 1 entry for each language in scope: English, French, Italian, Mandarin, Brazilian, Portuguese, German and Spanish

3. Characteristic Restrictions to Class Types

Note: One Characteristic should have at least one Class Type Restriction assigned.

4. Characteristic Values

Note: Construct Data Selection Value is to be defined for the Characteristic.

5. Characteristic Value Descriptions

Note: Each Characteristic Value must have 1 entry for each language in scope: English, French, Italian, Mandarin, Brazilian, Portuguese, German and Spanish

Characteristics A2D Data strictly adheres to the Master Data Standard. The complete information of the key fields that hold the Characteristic information follows the Master Data Standard document that is located here.

Data Cleansing

No data cleansing is required for Characteristics in the legacy systems. If any cleansing is deemed necessary, it will be performed outside of the systems.

As a result, the cleansed Characteristics data will be populated directly in the Data Collection Template (DCT).

Conversion Process

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

Collection will be done manually in the Data Collection Template for the following scenarios:

• For sites not on SAP-PF2 or WP2 systems
• For new Characteristics that need to be created to support the to-be design

Data Privacy and Sensitivity

Extraction

1. 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)

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

1. The extracted report will be loaded into the required structure using the DCT.
2. Standardization activities (including deduplication, standardization and additions)  will be carried out within the DCT.

Delta Data Management: Initial collection will be done via the report and one-time load to the DCT will be performed. Any delta after the initial collection within the DCT will require business to take due diligence to ensure any subsequent delta cleansing is verified and aligned within the DCT.

1. Characteristics DCT Rules

2. Characteristic Description DCT Rules

 3. Characteristic Restrictions to Class Types DCT Rules

4. Characteristic Value DCT Rules

 5. Characteristic Value Description DCT Rules

Extraction Dependencies

List the steps that need to occur before extraction can commence

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

Transformation Rules

1. Characteristics

2. Characteristic Descriptions

3. Characteristic Descriptions

4. Characteristic Values

5. Characteristic Value Descriptions

List of Custom Target Reports for this object is maintained here: Conversion Specification - Custom Reports Register.

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

Pre-Cutover

Configuration

List the Configurations required before loading can commence

Conversion Objects

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

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.
• Data cleansing has met the required percentage threshold for the specified mock cycle and all preparation activities have been completed. (If applicable for Cleansing)
• Data entries in DCT are target-ready data unless a specific transformation rule is stated for that field in the transformation rules.
• Not all legacy Plant Maintenance (PM) Characteristics need to be mapped to S/4 HANA PM Characteristics. If any of the successor objects is dependent on a PM Characteristic field with no mapped values, this will be an enrichment activity or manual transformation for the successor object to derive the PM Characteristic.

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