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lukemarson
Active Contributor


*UPDATE July 19th 2018: SAP have retired this package*

 

On the many Employee Central implementations that I have worked on, data migration has always been a huge undertaking for customers and for the implementation team. Extracting large volumes of data from any system – SAP ERP HCM or otherwise – and transforming that data from the source format into the format required by Employee Central is a mammoth activity, whether you have a few hundred employees or tens of thousands. I always like to be totally transparent with customers and warn them before a project kicks off to the magnitude of the effort required. This is why I was delighted to hear about the release of the Rapid-Deployment Solution (RDS) for migrating SAP ERP HCM data to SuccessFactors Employee Central some months ago. In this blog I will give the lowdown on the RDS package and discuss how this solution can help you migrate your SAP ERP HCM data to Employee Central.


Overview


The RDS provides a full solution to analyze, extract, clean, transform and validate data from SAP ERP HCM and then load and reconcile that data directly into Employee Central. The RDS runs on SAP Data Services and the out-of-the-box solution comes with full mappings between SAP ERP HCM infotypes and Employee Central HRIS elements and fields (which can be modified as required by the customer and means that custom fields on both sides can be mapped), project methodology, Business Process Documents, and test plans per object. The RDS is available at no cost to SAP customers, although customers who do not use SAP Data Services would need to license SAP Data Services.


The solution is built on SAP Data Services, which is the same solution used to replicate data from SuccessFactors HCM suite to SAP Business Warehouse (BW). Without wanting to cover the core capabilities of SAP Data Services too much, it is important to point out that the solution provides a number of Extract, Transfer, and Load (ETL) functions:




  • Importation of metadata from the target system

  • Data field mappings between systems

  • Profiling

  • Transformation

  • Validations (e.g. address validations)

  • Cleansing

  • Extraction

  • Upload

  • Reconciliation

  • Source from multiple systems (e.g. SAP ERP, database, legacy system, etc.) and file types (e.g. CSV, TXT, XML etc.)


Because this solution is built on SAP Data Services, it does not even require SAP ERP to be the data source. In fact, the solution supports multiple different data sources and so data can come from any and multiple databases, SAP systems, non-SAP systems, or flat-files (e.g.CSV, XML, etc.). Below is a screenshot of SAP Data Services:



For more information on SAP Data Services, I highly recommend checking out the SAP Help page for SAP Data Services or the SCN document SAP Data Services Product Tutorials by ina.mutschelknaus.


How it works


The RDS is designed with a six-step process flow, as illustrated in the diagram below:



The below diagram illustrates the process architecture for each of these six steps:



Now let’s discuss each of these steps in a little more detail.


Analysis


In this step of the process the source and target systems are analyzed and the SAP Data Services environment is prepared. During this analysis step, the data can be profiled on the source side to learn more about the source structure and understand the legacy data model. For example, the patterns of the postal codes are analyzed and different unique values for states and country are identified. This will help with both the field and value mapping.


Extract


In this step the data is extracted from the source system (e.g. SAP ERP HCM) into the SAP Data Services staging area where it is profiled and is prepared for the next step. Here the data can be analyzed and dissected to ensure consistency. Examples stated by frank.densborn in his blog A better way to migrate your SAP data with Rapid Deployment Solutions might be checking the US 5-digit zip code (and optional 4-digit ZIP+4) or Germany being referred to as Germany, DE, or Deutschland.


Clean


In this step the extracted data is cleaned, parsed, and transformed. This means ensuring that things like names, addresses, cost centers, etc. are in the correct format, that target data types are matched, and that data integrity is validated. It also means ensuring that the data meets specific formats, patterns, and is reformatting as necessary (e.g. concatenating fields, or breaking them into two or more fields as required). Additionally, here you have the opportunity to do a “search and replace” on certain values to update them as necessary. Overall, this step gives you the opportunity to review and correct data and ensure that any data is accurate.


Transform


In this step (not shown in 6-step diagram, but shown in the architecture diagram) the clean data is transformed into the target Employee Central format using the mappings. Prior to the transformation, if necessary, the delivered mappings can be modified based on customer-specific requirements. The screenshot below shows a mapping process flow in SAP Data Services:



Below we can see a mapping process definition for SAP infotype 0006 to Employee Central HRIS element homeAddress:



And finally we can see a mapping between field ORT01 and field city:



Validate


In this step the Employee Central metadata (object structures, HRIS elements configuration, countries, languages, lookup values etc. for validations) is extracted into SAP Data Services and the transformed data is validated using business rules defined by the metadata. This ensures the data will match the target Employee Central system.


Load


Once the data is validated and ready then the load process can commence. The majority of the data – all but some of the Time Off data – is loaded into Employee Central using the OData API. However, it is possible to output the data as CSV files to upload manually. This is lift off!


Reconcile


Once the data is loaded then the reconciliation can take place. This is essentially a comparison of what was actually loaded against what you expected to be loaded. This is done via dashboards and WebI (Web Intelligence) reports in SAP BusinessObjects BI Platform.


What’s in scope?


There is a fairly comprehensive scope for the RDS, which includes all data required. The only exception are workflow objects, which are not replicated as part of the RDS. The following list indicates all items that are in the scope of the RDS:




  • Foundation Objects:

    • Legal Entity

    • Legal Entity Local

    • Business Unit

    • Division

    • Department

    • Location

    • Location Group

    • Cost Center

    • Job Classification

    • Job Class Local

    • Job Function

    • Pay Component

    • Pay Component Group

    • Pay Grade

    • Pay Group

    • Pay Range

    • Geozone

    • Frequency

    • Event Reason

    • Dynamic Role



  • Positions:

    • Position data



  • Employee Data:

    • Profiles and User accounts

    • Biographical information

    • Personal information

    • Personal Global Information

    • Direct Deposit information

    • Email information

    • Emergency Contact Information

    • Address Information

    • Phone information

    • Social Account information

    • National ID Information

    • Employment information

    • Job Information

    • Job Relationships

    • Compensation Information

    • Recurring and Non-Recurring Pay Components

    • Termination Information



  • Time Off data:

    • Employee Time

    • Employee Time Calendar

    • Time Account

    • Time Account Change Calendar

    • Time Account Detail

    • Time Account Eligibility Status

    • Time Account Type

    • Time Account Type Rule Group

    • Time And Labor Configuration

    • Time Type

    • Time Type Profile




In addition to Employee Central, there is also predefined scope for migrating data to Employee Central Payroll. The following infotypes are in scope:




  • Residence Tax Area (IT0207)

  • Work Tax Area (IT0208)

  • Unemployment State (IT0209)

  • Withholding Information W4/W5 US (IT0210)

  • Additional Withholding Information (IT0234)

  • Other Taxes US (IT0235)

  • Payroll Results (T558B)

  • Payroll Results (T558C)

  • Payroll Results (T5U8C)

  • Garnishment Document (IT0194)

  • Garnishment Order (IT0195)

  • Contract Elements (IT0016)

  • Loans (IT0045)

  • Loan Repayments (IT0078)


Practicalities


SAP customers can download the RDS at no cost and can get the RDS up-and-running in SAP Data Services in less than one day. If you don’t use SAP Data Services then you may need to set aside approximately 2 to 3 days to install and test SAP Data Services in a server environment. A partner is not required to implement the RDS if you have SAP Data Services skills in-house. Deployment information and prerequisites for SAP Data Services can be found in the Master Guide on SAP Help page for SAP Data Services.


The only prerequisite of the solution is SAP Data Services version 4.2. Please note that documentation is only provided in English at this stage.


You can view details and scope of the package on SAP Service Marketplace using this link (expand Data Migration to SuccessFactors Employee Central) and download the package from the Software Download Center (SWDC) using this link.


More Information & Additional Resources


There are a number of resources you can view to get more information:




Questions on data migration – including this RDS – can be raised on the Data Migration space on SCN.


Summary


The value of this RDS cannot be argued; it removes the huge headache of extracting, transforming, and uploading data into Employee Central from a number of data sources, including SAP ERP HCM. Additionally, the RDS mitigates the risk with this process and helps you get your system live with trusted data. The package is available at no cost to SAP customers, although it does require the SAP Data Services solution that you might not be using right now. This RDS will drastically reduce the time and effort needed to get your data from SAP ERP HCM to Employee Central and ensures that you can avoid a Garbage In, Garbage Out (GIGO) scenario once you go live with your new Employee Central system.



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