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Master Data Assessment

Now a days, all the SAP implemented organizations are looking forward for assessment of their Master Data as a part of Data Management Initiative, which would help to identify the areas of unclean data as well as the need to switch on to SAP-Master Data Management Module for better data quality.

This blog gives an overview of the procedure for assessment of Master Data such as Material Master, Vendor Master, Customer master & so on. Vendor master data is consisered here for the discussion.

Basically, every master data is created abiding to the specific business rules of the Industry. Out of which, if there is any deviation, it’ll be considered as an unclean data. The assessment for the master data can be carried out against various criterions such as completeness, conformance, duplicates and consistency.

Initially, we need to download all the Master data key fields from the system into an excel or note pad (can be exported to MS access in case of large data).  For example, the key fields such as NAME1, NAME2, Street, City, PO Box No, Address fields, Deletion indicator, Tax fields etc. from General Data view, PO Order currency, Terms of Payment, Reconciliation account, Double invoice validation, Deletion indicators etc. from Purchasing and Company code data. LFA1, LFB1, LFM1, ADRC tables are used for dowloading the Vendor Master Data.

For the data downloaded, the following assessment can be done by checking against the below criterions.

            1.Completeness: All the required fields filled

Case study: The business rule of the client mentions Name1, Name2, Tax1 and Tax2 fields are to be maintained for the Vendor Master. Although this can be maintained as required in the configuration, however in some cases, the settings are exceptional depending upon requirements related to region wise, account group wise etc.,

In this case, all the entries for the fields to be maintained are to be checked whether there is an input in the field or not (empty). The percentage of the required fields not maintained out of the total valid entries indicate the incompleteness.


 2.Conformance: Standards that need to be adopted

Case study:  The business rule of the client mentions all the Name fields are to be entered in capital letters (Ex: Should be CHARLES instead of Charles) or the contact numbers are to be maintained in a specific format (Ex: Should be 123-456-7890 instead of 1234567890) & so on.

In this case, the conformance is to be checked for all the entries whether if they are maintained as per the standards or not.


            3.Duplicates: Multiple records referring to the same vendor

In most cases, the same vendor is created with multiple vendor master records in SAP due to various reasons.

The duplicates can be checked for various combination of fields such as Name1-Adress fields combinations, NAME1-Tax id Field combination etc. The address fields which can be considered for checking duplicates are Street, Postal code, City, PO Box no, Tel no, Fax no etc.


            4.Consistency: Sanctity of data

Case study: The business rule of the client mentions that some fields shouldn’t contain specific words or a special character is not allowed etc.

For example, NAME1 field should not contain any special characters except ‘&’ or spaces are not allowed in between letters of the abbreviations (Ex: Should be AT&T instead of A T & T). In these cases, inconsistency represents the total entries having special characters except ‘&’ sign for NAME1 or space in abbreviations out of all the entries checked.


The following conclusions can be derived with the assessment:

-Cleanliness of the data can be assessed, which will be useful to redesign the master data creation or upload process meeting business requirements.

-Standard template usage for assessment of the input master data can be done before it is created in SAP

-Identifying the need for implementing SAP MDM (Master data management) as an alternative for maintaining clean master data. 

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